DRILLING OPERATIONS EMISSIONS FRAMEWORK

Abstract

A method may include receiving drilling operations data with respect to time as acquired during drilling operations at a rig site; receiving contextual information associated with the drilling operations at the rig site; and determining emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information.

Description

BACKGROUND

A reservoir may be a subsurface formation that may be characterized at least in part by its porosity and fluid permeability. As an example, a reservoir may be part of a basin such as a sedimentary basin. A basin may be a depression (e.g., caused by plate tectonic activity, subsidence, etc.) in which sediments accumulate. As an example, where hydrocarbon source rocks occur in combination with appropriate depth and duration of burial, a petroleum system may develop within a basin, which may form a reservoir that includes hydrocarbon fluids (e.g., oil, gas, etc.).

As an example, one or more workflows may be performed using one or more computational frameworks and/or one or more pieces of equipment that include features for one or more of analysis, acquisition, model building, control, etc., for exploration, interpretation, drilling, fracturing, production, etc.

SUMMARY

A method may include receiving drilling operations data with respect to time as acquired during drilling operations at a rig site; receiving contextual information associated with the drilling operations at the rig site; and determining emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information. A system may include one or more processors; memory accessible to at least one of the one or more processors; processor-executable instructions stored in the memory and executable to instruct the system to: receive drilling operations data with respect to time as acquired during drilling operations at a rig site; receive contextual information associated with the drilling operations at the rig site; and determine emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information. One or more computer-readable storage media may include processor-executable instructions to instruct a computing system to: receive drilling operations data with respect to time as acquired during drilling operations at a rig site; receive contextual information associated with the drilling operations at the rig site; and determine emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information. Various other apparatuses, systems, methods, etc., are also disclosed.

This summary is provided to introduce a selection of concepts that are further described below in the detailed description. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used as an aid in limiting the scope of the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

The following detailed description refers to the accompanying drawings. Wherever convenient Features and advantages of the described implementations may be more readily understood by reference to the following description taken in conjunction with the accompanying drawings.

FIG. 1 shows an example of a system;

FIG. 2 shows an example of a system;

FIG. 3 shows an example of a system;

FIG. 4 shows an example of a system;

FIG. 5 shows an example of a system;

FIG. 6 shows an example of a workflow;

FIG. 7 shows an example of a method;

FIG. 8 shows an example of a method;

FIG. 9 shows an example of a method;

FIG. 10 shows an example of a graphical user interface;

FIG. 11 shows an example of a graphical user interface;

FIG. 12 shows an example of a graphical user interface;

FIG. 13 shows an example of a graphical user interface;

FIG. 14 shows an example of a graphical user interface;

FIG. 15 shows an example of a method and an example of a system; and

FIG. 16 shows an example of a system.

DETAILED DESCRIPTION

This description is not to be taken in a limiting sense, but rather is made merely for the purpose of describing the general principles of the implementations. The scope of the described implementations should be ascertained with reference to the issued claims.

FIG. 1 shows an example of a system 100 that includes a workspace framework 110 that may provide for instantiation of, rendering of, interactions with, etc., a graphical user interface (GUI) 120. In the example of FIG. 1, the GUI 120 may include graphical controls for computational frameworks (e.g., applications, etc.) 121, projects 122, visualization 123, one or more other features 124, data access 125, and data storage 126.

In the example of FIG. 1, the workspace framework 110 may be tailored to a particular geologic environment such as an example geologic environment 150. For example, the geologic environment 150 may include layers (e.g., stratification) that include a reservoir 151 and that may be intersected by a fault 153. As an example, the geologic environment 150 may be outfitted with a variety of sensors, detectors, actuators, etc. For example, equipment 152 may include communication circuitry to receive and to transmit information with respect to one or more networks 155. Such information may include information associated with downhole equipment 154, which may be equipment to acquire information, to assist with resource recovery, etc. Other equipment 156 may be located remote from a wellsite and include sensing, detecting, emitting or other circuitry. Such equipment may include storage and communication circuitry to store and to communicate data, instructions, etc. As an example, one or more satellites may be provided for purposes of communications, data acquisition, etc. For example, FIG. 1 shows a satellite in communication with the network 155 that may be configured for communications, noting that the satellite may additionally or alternatively include circuitry for imagery (e.g., spatial, spectral, temporal, radiometric, etc.).

FIG. 1 also shows the geologic environment 150 as optionally including equipment 157 and 158 associated with a well that includes a substantially horizontal portion that may intersect with one or more fractures 159. For example, consider a well in a shale formation that may include natural fractures, artificial fractures (e.g., hydraulic fractures) or a combination of natural and artificial fractures. As an example, a well may be drilled for a reservoir that is laterally extensive. In such an example, lateral variations in properties, stresses, etc. may exist where an assessment of such variations may assist with planning, operations, etc. to develop a laterally extensive reservoir (e.g., via fracturing, injecting, extracting, etc.). As an example, the equipment 157 and/or 158 may include components, a system, systems, etc. for fracturing, seismic sensing, analysis of seismic data, assessment of one or more fractures, etc.

In the example of FIG. 1, the GUI 120 shows some examples of computational frameworks, including the DRILLPLAN, DRILLOPS, PETREL, TECHLOG, PETROMOD, ECLIPSE, PIPESIM, and INTERSECT frameworks (SLB, Houston, Texas).

The DRILLPLAN framework provides for digital well construction planning and includes features for automation of repetitive tasks and validation workflows, enabling improved quality drilling programs (e.g., digital drilling plans, etc.) to be produced quickly with assured coherency.

The DRILLOPS framework may execute a digital drilling plan and ensures plan adherence, while delivering goal-based automation. The DRILLOPS framework may generate activity plans automatically individual operations, whether they are monitored and/or controlled on the rig or in town. Automation may utilize data analysis and learning systems to assist and optimize tasks, such as, for example, setting ROP to drilling a stand. A preset menu of automatable drilling tasks may be rendered, and, using data analysis and models, a plan may be executed in a manner to achieve a specified goal, where, for example, measurements may be utilized for calibration. The DRILLOPS framework provides flexibility to modify and replan activities dynamically, for example, based on a live appraisal of various factors (e.g., equipment, personnel, and supplies). Well construction activities (e.g., tripping, drilling, cementing, etc.) may be continually monitored and dynamically updated using feedback from operational activities. The DRILLOPS framework may provide for various levels of automation based on planning and/or re-planning (e.g., via the DRILLPLAN framework), feedback, etc.

The PETREL framework may be part of the DELFI environment for utilization in geosciences and geoengineering, for example, to analyze subsurface data from exploration to production of fluid from a reservoir. The DELFI cognitive exploration and production (E&P) environment (SLB, Houston, Texas), referred to herein as the DELFI environment or DELFI framework, is a secure, cognitive, cloud-based collaborative environment that integrates data and workflows with digital technologies, such as artificial intelligence and machine learning.

The PETREL framework provides components that allow for optimization of various exploration, development and production operations. The PETREL framework includes seismic to simulation software components that may output information for use in increasing reservoir performance, for example, by improving asset team productivity. Through use of such a framework, various professionals (e.g., geophysicists, geologists, and reservoir engineers) may develop collaborative workflows and integrate operations to streamline processes (e.g., with respect to one or more geologic environments, etc.). Such a framework may be considered an application (e.g., executable using one or more devices) and may be considered a data-driven application (e.g., where data is input for purposes of modeling, simulating, etc.).

The TECHLOG framework may handle and process field and laboratory data for a variety of geologic environments (e.g., deepwater exploration, shale, etc.). The TECHLOG framework may structure wellbore data for analyses, planning, etc.

The PETROMOD framework provides petroleum systems modeling capabilities that may combine one or more of seismic, well, and geological information to model the evolution of a sedimentary basin. The PETROMOD framework may predict if, and how, a reservoir has been charged with hydrocarbons, including the source and timing of hydrocarbon generation, migration routes, quantities, and hydrocarbon type in the subsurface or at surface conditions.

The ECLIPSE framework provides a reservoir simulator (e.g., as a computational framework) with numerical solutions for fast and accurate prediction of dynamic behavior for various types of reservoirs and development schemes.

The INTERSECT framework provides a high-resolution reservoir simulator for simulation of detailed geological features and quantification of uncertainties, for example, by creating accurate production scenarios and, with the integration of precise models of the surface facilities and field operations, the INTERSECT framework may produce reliable results, which may be continuously updated by real-time data exchanges (e.g., from one or more types of data acquisition equipment in the field that may acquire data during one or more types of field operations, etc.). The INTERSECT framework may provide completion configurations for complex wells where such configurations may be built in the field, may provide detailed enhanced-oil-recovery (EOR) formulations where such formulations may be implemented in the field, may analyze application of steam injection and other thermal EOR techniques for implementation in the field, advanced production controls in terms of reservoir coupling and flexible field management, and flexibility to script customized solutions for improved modeling and field management control. The INTERSECT framework, as with the other example frameworks, may be utilized as part of the DELFI environment, for example, for rapid simulation of multiple concurrent cases. For example, a workflow may utilize one or more of the DELFI environment on demand reservoir simulation features.

The aforementioned DELFI environment provides various features for workflows as to subsurface analysis, planning, construction and production, for example, as illustrated in the workspace framework 110. As shown in FIG. 1, outputs from the workspace framework 110 may be utilized for directing, controlling, etc., one or more processes in the geologic environment 150 and, feedback 160, may be received via one or more interfaces in one or more forms (e.g., acquired data as to operational conditions, equipment conditions, environment conditions, etc.).

As an example, a workflow may progress to a geology and geophysics (“G&G”) service provider, which may generate a well trajectory, which may involve execution of one or more G&G frameworks (e.g., consider the PETREL framework, etc.).

In the example of FIG. 1, the visualization features 123 may be implemented via the workspace framework 110, for example, to perform tasks as associated with one or more of subsurface regions, planning operations, constructing wells and/or surface fluid networks, and producing from a reservoir.

As an example, a visualization process may implement one or more of various features that may be suitable for one or more web applications. For example, a template may involve use of the JAVASCRIPT object notation format (JSON) and/or one or more other languages/formats. As an example, a framework may include one or more converters. For example, consider a JSON to PYTHON converter and/or a PYTHON to JSON converter. Such an approach may provide for compatibility of devices, frameworks, etc., with respect to one or more sets of instructions.

As an example, visualization features may provide for visualization of various earth models, properties, etc., in one or more dimensions. As an example, visualization features may provide for rendering of information in multiple dimensions, which may optionally include multiple resolution rendering. In such an example, information being rendered may be associated with one or more frameworks and/or one or more data stores. As an example, visualization features may include one or more control features for control of equipment, which may include, for example, field equipment that may perform one or more field operations. As an example, a workflow may utilize one or more frameworks to generate information that may be utilized to control one or more types of field equipment (e.g., drilling equipment, wireline equipment, fracturing equipment, etc.).

As to a reservoir model that may be suitable for utilization by a simulator, consider acquisition of seismic data as acquired via reflection seismology, which finds use in geophysics, for example, to estimate properties of subsurface formations. As an example, reflection seismology may provide seismic data representing waves of elastic energy (e.g., as transmitted by P-waves and S-waves, in a frequency range of approximately 1 Hz to approximately 100 Hz). Seismic data may be processed and interpreted, for example, to understand better composition, fluid content, extent and geometry of subsurface rocks. Such interpretation results may be utilized to plan, simulate, perform, etc., one or more operations for production of fluid from a reservoir (e.g., reservoir rock, etc.).

Field acquisition equipment may be utilized to acquire seismic data, which may be in the form of traces where a trace may include values organized with respect to time and/or depth (e.g., consider 1D, 2D, 3D or 4D seismic data). For example, consider acquisition equipment that acquires digital samples at a rate of one sample per approximately 4 ms. Given a speed of sound in a medium or media, a sample rate may be converted to an approximate distance. For example, the speed of sound in rock may be on the order of around 5 km per second. Thus, a sample time spacing of approximately 4 ms would correspond to a sample “depth” spacing of about 10 meters (e.g., assuming a path length from source to boundary and boundary to sensor). As an example, a trace may be about 4 seconds in duration; thus, for a sampling rate of one sample at about 4 ms intervals, such a trace would include about 1000 samples where latter acquired samples correspond to deeper reflection boundaries. If the 4 second trace duration of the foregoing example is divided by two (e.g., to account for reflection), for a vertically aligned source and sensor, a deepest boundary depth may be estimated to be about 10 km (e.g., assuming a speed of sound of about 5 km per second).

As an example, a model may be a simulated version of a geologic environment. As an example, a simulator may include features for simulating physical phenomena in a geologic environment based at least in part on a model or models. A simulator, such as a reservoir simulator, may simulate fluid flow in a geologic environment based at least in part on a model that may be generated via a framework that receives seismic data. A simulator may be a computerized system (e.g., a computing system) that may execute instructions using one or more processors to solve a system of equations that describe physical phenomena subject to various constraints. In such an example, the system of equations may be spatially defined (e.g., numerically discretized) according to a spatial model that that includes layers of rock, geobodies, etc., that have corresponding positions that may be based on interpretation of seismic and/or other data. A spatial model may be a cell-based model where cells are defined by a grid (e.g., a mesh). A cell in a cell-based model may represent a physical area or volume in a geologic environment where the cell may be assigned physical properties (e.g., permeability, fluid properties, etc.) that may be germane to one or more physical phenomena (e.g., fluid volume, fluid flow, pressure, etc.). A reservoir simulation model may be a spatial model that may be cell-based.

A simulator may be utilized to simulate the exploitation of a real reservoir, for example, to examine different productions scenarios to find an optimal one before production or further production occurs. A reservoir simulator does not provide an exact replica of flow in and production from a reservoir at least in part because the description of the reservoir and the boundary conditions for the equations for flow in a porous rock are generally known with an amount of uncertainty. Certain types of physical phenomena occur at a spatial scale that may be relatively small compared to size of a field. A balance may be struck between model scale and computational resources that results in model cell sizes being of the order of meters; rather than a lesser size (e.g., a level of detail of pores). A modeling and simulation workflow for multiphase flow in porous media (e.g., reservoir rock, etc.) may include generalizing real micro-scale data from macro scale observations (e.g., seismic data and well data) and upscaling to a manageable scale and problem size. Uncertainties may exist in input data and solution procedure such that simulation results too are to some extent uncertain. A process known as history matching may involve comparing simulation results to actual field data acquired during production of fluid from a field. Information gleaned from history matching, may provide for adjustments to a model, data, etc., which may help to increase accuracy of simulation.

As an example, a simulator may utilize various types of constructs, which may be referred to as entities. Entities may include earth entities or geological objects such as wells, surfaces, reservoirs, etc. Entities may include virtual representations of actual physical entities that may be reconstructed for purposes of simulation. Entities may include entities based on data acquired via sensing, observation, etc. (e.g., consider entities based at least in part on seismic data and/or other information). As an example, an entity may be characterized by one or more properties (e.g., a geometrical pillar grid entity of an earth model may be characterized by a porosity property, etc.). Such properties may represent one or more measurements (e.g., acquired data), calculations, etc.

As an example, a simulator may utilize an object-based software framework, which may include entities based on pre-defined classes to facilitate modeling and simulation. As an example, an object class may encapsulate reusable code and associated data structures. Object classes may be used to instantiate object instances for use by a program, script, etc. For example, borehole classes may define objects for representing boreholes based on well data. A model of a basin, a reservoir, etc. may include one or more boreholes where a borehole may be, for example, for measurements, injection, production, etc. As an example, a borehole may be a wellbore of a well, which may be a completed well (e.g., for production of a resource from a reservoir, for injection of material, etc.).

While several simulators are illustrated in the example of FIG. 1, one or more other simulators may be utilized, additionally or alternatively. For example, consider the VISAGE geomechanics simulator (SLB, Houston Texas) or the PIPESIM network simulator (SLB, Houston Texas), etc. The VISAGE simulator includes finite element numerical solvers that may provide simulation results such as, for example, results as to compaction and subsidence of a geologic environment, well and completion integrity in a geologic environment, cap-rock and fault-seal integrity in a geologic environment, fracture behavior in a geologic environment, thermal recovery in a geologic environment, CO2 disposal, etc. The PIPESIM simulator includes solvers that may provide simulation results such as, for example, multiphase flow results (e.g., from a reservoir to a wellhead and beyond, etc.), flowline and surface facility performance, etc. The PIPESIM simulator may be integrated, for example, with the AVOCET production operations framework (SLB, Houston Texas). As an example, a reservoir or reservoirs may be simulated with respect to one or more enhanced recovery techniques (e.g., consider a thermal process such as steam-assisted gravity drainage (SAGD), etc.). As an example, the PIPESIM simulator may be an optimizer that may optimize one or more operational scenarios at least in part via simulation of physical phenomena. The MANGROVE simulator (SLB, Houston, Texas) provides for optimization of stimulation design (e.g., stimulation treatment operations such as hydraulic fracturing) in a reservoir-centric environment. The MANGROVE framework may combine scientific and experimental work to predict geomechanical propagation of hydraulic fractures, reactivation of natural fractures, etc., along with production forecasts within 3D reservoir models (e.g., production from a drainage area of a reservoir where fluid moves via one or more types of fractures to a well and/or from a well). The MANGROVE framework may provide results pertaining to heterogeneous interactions between hydraulic and natural fracture networks, which may assist with optimization of the number and location of fracture treatment stages (e.g., stimulation treatment(s)), for example, to increased perforation efficiency and recovery.

As an example, data may include geochemical data. For example, consider data acquired using X-ray fluorescence (XRF) technology, Fourier transform infrared spectroscopy (FTIR) technology and/or wireline geochemical technology.

As an example, one or more probes may be deployed in a bore via a wireline or wirelines. As an example, a probe may emit energy and receive energy where such energy may be analyzed to help determine mineral composition of rock surrounding a bore. As an example, nuclear magnetic resonance may be implemented (e.g., via a wireline, downhole NMR probe, etc.), for example, to acquire data as to nuclear magnetic properties of elements in a formation (e.g., hydrogen, carbon, phosphorous, etc.).

As an example, lithology scanning technology may be employed to acquire and analyze data. For example, consider the LITHO SCANNER technology (SLB, Houston, Texas). As an example, a LITHO SCANNER tool may be or include a gamma ray spectroscopy tool.

As an example, a tool may be positioned to acquire information in a portion of a borehole. Analysis of such information may reveal vugs, dissolution planes (e.g., dissolution along bedding planes), stress-related features, dip events, etc. As an example, a tool may acquire information that may help to characterize a fractured reservoir, optionally where fractures may be natural and/or artificial (e.g., hydraulic fractures). Such information may assist with completions, stimulation treatment, etc. As an example, information acquired by a tool may be analyzed using a framework such as the aforementioned TECHLOG framework.

As an example, a workflow may utilize one or more types of data for one or more processes (e.g., stratigraphic modeling, basin modeling, completion designs, drilling, production, injection, etc.). As an example, one or more tools may provide data that may be used in a workflow or workflows that may implement one or more frameworks (e.g., PETREL, TECHLOG, PETROMOD, ECLIPSE, etc.).

In the example of FIG. 1, drilling may be performed in the geologic environment 150, for example, to access the reservoir 151, which may be accessed from land or offshore. In FIG. 1, the downhole equipment 154 may be, for example, part of a bottom hole assembly (BHA). The BHA may be used to drill a well. The downhole equipment 154 may communicate information to equipment at the surface, and may receive instructions and information from the equipment at the surface. During a well construction process, a variety of operations (such as cementing, wireline evaluation, testing, etc.) may be conducted. In such embodiments, data collected by tools and sensors and used for reasons such as reservoir characterization may be collected and transmitted.

A well may include a substantially horizontal portion (e.g., lateral portion) that may intersect with one or more fractures. For example, a well in a shale formation may pass through natural fractures, artificial fractures (e.g., hydraulic fractures), or a combination thereof. Such a well may be constructed using directional drilling techniques as described herein. However, these same techniques may be used in connection with other types of directional wells (such as slant wells, S-shaped wells, deep inclined wells, and others) and are not limited to horizontal wells.

FIG. 2 shows an example of a wellsite system 200 (e.g., at a wellsite that may be onshore or offshore). As shown, the wellsite system 200 may include a mud tank 201 for holding mud and other material (e.g., where mud may be a drilling fluid), a suction line 203 that serves as an inlet to a mud pump 204 for pumping mud from the mud tank 201 such that mud flows to a vibrating hose 206, a drawworks 207 for winching drill line or drill lines 212, a standpipe 208 that receives mud from the vibrating hose 206, a kelly hose 209 that receives mud from the standpipe 208, a gooseneck or goosenecks 210, a traveling block 211, a crown block 213 for carrying the traveling block 211 via the drill line or drill lines 212, a derrick 214, a kelly 218 or a top drive 240, a kelly drive bushing 219, a rotary table 220, a drill floor 221, a bell nipple 222, one or more blowout preventors (BOPs) 223, a drillstring 225, a drill bit 226, a casing head 227 and a flow pipe 228 that carries mud and other material to, for example, the mud tank 201.

In the example system of FIG. 2, a borehole 232 is formed in subsurface formations 230 by rotary drilling; noting that various example embodiments may also use one or more directional drilling techniques, equipment, etc.

As shown in the example of FIG. 2, the drillstring 225 is suspended within the borehole 232 and has a drillstring assembly 250 that includes the drill bit 226 at its lower end. As an example, the drillstring assembly 250 may be a bottom hole assembly (BHA).

The wellsite system 200 may provide for operation of the drillstring 225 and other operations. As shown, the wellsite system 200 includes the traveling block 211 and the derrick 214 positioned over the borehole 232. As mentioned, the wellsite system 200 may include the rotary table 220 where the drillstring 225 pass through an opening in the rotary table 220.

As shown in the example of FIG. 2, the wellsite system 200 may include the kelly 218 and associated components, etc., or a top drive 240 and associated components. As to a kelly example, the kelly 218 may be a square or hexagonal metal/alloy bar with a hole drilled therein that serves as a mud flow path. The kelly 218 may be used to transmit rotary motion from the rotary table 220 via the kelly drive bushing 219 to the drillstring 225, while allowing the drillstring 225 to be lowered or raised during rotation. The kelly 218 may pass through the kelly drive bushing 219, which may be driven by the rotary table 220. As an example, the rotary table 220 may include a master bushing that operatively couples to the kelly drive bushing 219 such that rotation of the rotary table 220 may turn the kelly drive bushing 219 and hence the kelly 218. The kelly drive bushing 219 may include an inside profile matching an outside profile (e.g., square, hexagonal, etc.) of the kelly 218; however, with slightly larger dimensions so that the kelly 218 may freely move up and down inside the kelly drive bushing 219.

As to a top drive example, the top drive 240 may provide functions performed by a kelly and a rotary table. The top drive 240 may turn the drillstring 225. As an example, the top drive 240 may include one or more motors (e.g., electric and/or hydraulic) connected with appropriate gearing to a short section of pipe called a quill, that in turn may be screwed into a saver sub or the drillstring 225 itself. The top drive 240 may be suspended from the traveling block 211, so the rotary mechanism is free to travel up and down the derrick 214. As an example, a top drive 240 may allow for drilling to be performed with more joint stands than a kelly/rotary table approach.

As an example, a stand may be two or three single joints of drillpipe or drill collars that remain screwed together during tripping operations. Various drilling rigs may handle three-joint stands, called trebles or triples. In each case, the drillpipe or drill collars are stood back upright in the derrick and placed into fingerboards to keep them orderly. This is a relatively efficient way to remove the drillstring from the well when changing the bit or making adjustments to the bottomhole assembly, rather than unscrewing every threaded connection and laying the pipe down to a horizontal position. As an example, a joint may be approximately 31.6 ft or 9.6 m in length such that a stand may be approximately 63.2 ft or 19.2 m (double) or approximately 94.8 ft or 28.8 m (triple). If a rate of penetration (ROP) is 94.8 ft/h, then drilling a stand (triple) to deepen a borehole by 94.8 ft may be performed in one hour.

In the example of FIG. 2, the mud tank 201 may hold mud, which may be one or more types of drilling fluids. As an example, a wellbore may be drilled to produce fluid, inject fluid or both (e.g., hydrocarbons, minerals, water, etc.).

In the example of FIG. 2, the drillstring 225 (e.g., including one or more downhole tools) may be composed of a series of pipes threadably connected together to form a long tube with the drill bit 226 at the lower end thereof. As the drillstring 225 is advanced into a wellbore for drilling, at some point in time prior to or coincident with drilling, the mud may be pumped by the pump 204 from the mud tank 201 (e.g., or other source) via the lines 206, 208 and 209 to a port of the kelly 218 or, for example, to a port of the top drive 240. The mud may then flow via a passage (e.g., or passages) in the drillstring 225 and out of ports located on the drill bit 226 (see, e.g., a directional arrow). As the mud exits the drillstring 225 via ports in the drill bit 226, it may then circulate upwardly through an annular region between an outer surface(s) of the drillstring 225 and surrounding wall(s) (e.g., open borehole, casing, etc.), as indicated by directional arrows. In such a manner, the mud lubricates the drill bit 226 and carries heat energy (e.g., frictional or other energy) and formation cuttings to the surface where the mud (e.g., and cuttings) may be returned to the mud tank 201, for example, for recirculation (e.g., with processing to remove cuttings, etc.).

The mud pumped by the pump 204 into the drillstring 225 may, after exiting the drillstring 225, form a mudcake that lines the wellbore which, among other functions, may reduce friction between the drillstring 225 and surrounding wall(s) (e.g., borehole, casing, etc.). A reduction in friction may facilitate advancing or retracting the drillstring 225. During a drilling operation, the entire drillstring 225 may be pulled from a wellbore and optionally replaced, for example, with a new or sharpened drill bit, a smaller diameter drillstring, etc. As mentioned, the act of pulling a drillstring out of a hole or replacing it in a hole is referred to as tripping. A trip may be referred to as an upward trip or an outward trip or as a downward trip or an inward trip depending on trip direction.

As an example, consider a downward trip where upon arrival of the drill bit 226 of the drillstring 225 at a bottom of a wellbore, pumping of the mud commences to lubricate the drill bit 226 for purposes of drilling to enlarge the wellbore. As mentioned, the mud may be pumped by the pump 204 into a passage of the drillstring 225 and, upon filling of the passage, the mud may be used as a transmission medium to transmit energy, for example, energy that may encode information as in mud-pulse telemetry.

As an example, mud-pulse telemetry equipment may include a downhole device configured to effect changes in pressure in the mud to create an acoustic wave or waves upon which information may modulated. In such an example, information from downhole equipment (e.g., one or more modules of the drillstring 225) may be transmitted uphole to an uphole device, which may relay such information to other equipment for processing, control, etc.

As an example, telemetry equipment may operate via transmission of energy via the drillstring 225 itself. For example, consider a signal generator that imparts coded energy signals to the drillstring 225 and repeaters that may receive such energy and repeat it to further transmit the coded energy signals (e.g., information, etc.).

As an example, the drillstring 225 may be fitted with telemetry equipment 252 that includes a rotatable drive shaft, a turbine impeller mechanically coupled to the drive shaft such that the mud may cause the turbine impeller to rotate, a modulator rotor mechanically coupled to the drive shaft such that rotation of the turbine impeller causes said modulator rotor to rotate, a modulator stator mounted adjacent to or proximate to the modulator rotor such that rotation of the modulator rotor relative to the modulator stator creates pressure pulses in the mud, and a controllable brake for selectively braking rotation of the modulator rotor to modulate pressure pulses. In such example, an alternator may be coupled to the aforementioned drive shaft where the alternator includes at least one stator winding electrically coupled to a control circuit to selectively short the at least one stator winding to electromagnetically brake the alternator and thereby selectively brake rotation of the modulator rotor to modulate the pressure pulses in the mud.

In the example of FIG. 2, an uphole control and/or data acquisition system 262 may include circuitry to sense pressure pulses generated by telemetry equipment 252 and, for example, communicate sensed pressure pulses or information derived therefrom for process, control, etc.

The assembly 250 of the illustrated example includes a logging-while-drilling (LWD) module 254, a measurement-while-drilling (MWD) module 256, an optional module 258, a rotary-steerable system (RSS) and/or motor 260, and the drill bit 226. Such components or modules may be referred to as tools where a drillstring may include a plurality of tools.

As to an RSS, it involves technology utilized for directional drilling. Directional drilling involves drilling into the Earth to form a deviated bore such that the trajectory of the bore is not vertical; rather, the trajectory deviates from vertical along one or more portions of the bore. As an example, consider a target that is located at a lateral distance from a surface location where a rig may be stationed. In such an example, drilling may commence with a vertical portion and then deviate from vertical such that the bore is aimed at the target and, eventually, reaches the target. Directional drilling may be implemented where a target may be inaccessible from a vertical location at the surface of the Earth, where material exists in the Earth that may impede drilling or otherwise be detrimental (e.g., consider a salt dome, etc.), where a formation is laterally extensive (e.g., consider a relatively thin yet laterally extensive reservoir), where multiple bores are to be drilled from a single surface bore, where a relief well is desired, etc.

One approach to directional drilling involves a mud motor; however, a mud motor may present some challenges depending on factors such as rate of penetration (ROP), transferring weight to a bit (e.g., weight on bit, WOB) due to friction, etc. A mud motor may be a positive displacement motor (PDM) that operates to drive a bit (e.g., during directional drilling, etc.). A PDM operates as drilling fluid is pumped through it where the PDM converts hydraulic power of the drilling fluid into mechanical power to cause the bit to rotate.

As an example, a mud motor (e.g., PDM) may be operated in different modes, which may include a rotating mode and a sliding mode. A sliding mode involves drilling with a mud motor rotating the bit downhole without rotating the drillstring from the surface. Such an operation may be conducted when a BHA has been fitted with a bent sub or a bent housing mud motor, or both, for directional drilling. Sliding may be used in building and controlling or adjusting hole angle. In directional drilling, pointing of a bit may be accomplished through a bent sub, which may have a relatively small angle offset from the axis of a drillstring, and a measurement device to determine the direction of offset. Without turning the drillstring, the bit may be rotated with mud flow through the mud motor to drill in the direction it is pointed. With steerable motors, when a desired wellbore direction is attained, the entire drillstring may be rotated to drill straight rather than at an angle. By controlling the amount of hole drilled in the sliding mode versus the rotating mode, a wellbore trajectory may be controlled rather precisely.

As an example, a PDM may operate in a combined rotating mode where surface equipment is utilized to rotate a bit of a drillstring (e.g., a rotary table, a top drive, etc.) by rotating the entire drillstring and where drilling fluid is utilized to rotate the bit of the drillstring. In such an example, a surface RPM (SRPM) may be determined by use of the surface equipment and a downhole RPM of the mud motor may be determined using various factors related to flow of drilling fluid, mud motor type, etc. As an example, in the combined rotating mode, bit RPM may be determined or estimated as a sum of the SRPM and the mud motor RPM, assuming the SRPM and the mud motor RPM are in the same direction.

As an example, a PDM mud motor may operate in a so-called sliding mode, when the drillstring is not rotated from the surface. In such an example, a bit RPM may be determined or estimated based on the RPM of the mud motor.

An RSS may drill directionally where there is continuous rotation from surface equipment, which may alleviate the sliding of a steerable motor (e.g., a PDM). An RSS may be deployed when drilling directionally (e.g., deviated, horizontal, or extended-reach wells). An RSS may aim to minimize interaction with a borehole wall, which may help to preserve borehole quality. An RSS may aim to exert a relatively consistent side force akin to stabilizers that rotate with the drillstring or orient the bit in the desired direction while continuously rotating at the same number of rotations per minute as the drillstring.

The LWD module 254 may be housed in a suitable type of drill collar and may contain one or a plurality of selected types of logging tools. It will also be understood that more than one LWD and/or MWD module may be employed. Where the position of an LWD module is mentioned, as an example, it may refer to a module at the position of the LWD module 254, the MWD module 256, etc. An LWD module may include capabilities for measuring, processing, and storing information, as well as for communicating with the surface equipment. In the illustrated example, the LWD module 254 may include a seismic measuring device.

The MWD module 256 may be housed in a suitable type of drill collar and may contain one or more devices for measuring characteristics of the drillstring 225 and the drill bit 226. As an example, the MWD module 256 may include equipment for generating electrical power, for example, to power various components of the drillstring 225. As an example, the MWD module 256 may include the telemetry equipment 252, for example, where the turbine impeller may generate power by flow of the mud; it being understood that other power and/or battery systems may be employed for purposes of powering various components. As an example, the MWD module 256 may include one or more of the following types of measuring devices: a weight-on-bit measuring device, a torque measuring device, a vibration measuring device, a shock measuring device, a stick slip measuring device, a direction measuring device, and an inclination measuring device.

FIG. 2 also shows some examples of types of holes that may be drilled. For example, consider a slant hole 272, an S-shaped hole 274, a deep inclined hole 276 and a horizontal hole 278.

As an example, a drilling operation may include directional drilling where, for example, at least a portion of a well includes a curved axis. For example, consider a radius that defines curvature where an inclination with regard to the vertical may vary until reaching an angle between about 30 degrees and about 60 degrees or, for example, an angle to about 90 degrees or possibly greater than about 90 degrees.

As an example, a directional well may include several shapes where each of the shapes may aim to meet particular operational demands. As an example, a drilling process may be performed on the basis of information as and when it is relayed to a drilling engineer. As an example, inclination and/or direction may be modified based on information received during a drilling process.

As an example, deviation of a bore may be accomplished in part by use of a downhole motor and/or a turbine. As to a motor, for example, a drillstring may include a positive displacement motor (PDM).

As an example, a system may be a steerable system and include equipment to perform method such as geosteering. As mentioned, a steerable system may be or include an RSS. As an example, a steerable system may include a PDM or of a turbine on a lower part of a drillstring which, just above a drill bit, a bent sub may be mounted. As an example, above a PDM, MWD equipment that provides real time or near real time data of interest (e.g., inclination, direction, pressure, temperature, real weight on the drill bit, torque stress, etc.) and/or LWD equipment may be installed. As to the latter, LWD equipment may make it possible to send to the surface various types of data of interest, including for example, geological data (e.g., gamma ray log, resistivity, density and sonic logs, etc.).

The coupling of sensors providing information on the course of a well trajectory, in real time or near real time, with, for example, one or more logs characterizing the formations from a geological viewpoint, may allow for implementing a geosteering method. Such a method may include navigating a subsurface environment, for example, to follow a desired route to reach a desired target or targets.

As an example, a drillstring may include an azimuthal density neutron (ADN) tool for measuring density and porosity; a MWD tool for measuring inclination, azimuth and shocks; a compensated dual resistivity (CDR) tool for measuring resistivity and gamma ray related phenomena; one or more variable gauge stabilizers; one or more bend joints; and a geosteering tool, which may include a motor and optionally equipment for measuring and/or responding to one or more of inclination, resistivity and gamma ray related phenomena.

As an example, geosteering may include intentional directional control of a wellbore based on results of downhole geological logging measurements in a manner that aims to keep a directional wellbore within a desired region, zone (e.g., a pay zone), etc. As an example, geosteering may include directing a wellbore to keep the wellbore in a particular section of a reservoir, for example, to minimize gas and/or water breakthrough and, for example, to maximize economic production from a well that includes the wellbore.

Referring again to FIG. 2, the wellsite system 200 may include one or more sensors 264 that are operatively coupled to the control and/or data acquisition system 262. As an example, a sensor or sensors may be at surface locations. As an example, a sensor or sensors may be at downhole locations. As an example, a sensor or sensors may be at one or more remote locations that are not within a distance of the order of about one hundred meters from the wellsite system 200. As an example, a sensor or sensor may be at an offset wellsite where the wellsite system 200 and the offset wellsite are in a common field (e.g., oil and/or gas field).

As an example, one or more of the sensors 264 may be provided for tracking pipe, tracking movement of at least a portion of a drillstring, etc.

As an example, the system 200 may include one or more sensors 266 that may sense and/or transmit signals to a fluid conduit such as a drilling fluid conduit (e.g., a drilling mud conduit). For example, in the system 200, the one or more sensors 266 may be operatively coupled to portions of the standpipe 208 through which mud flows. As an example, a downhole tool may generate pulses that may travel through the mud and be sensed by one or more of the one or more sensors 266. In such an example, the downhole tool may include associated circuitry such as, for example, encoding circuitry that may encode signals, for example, to reduce demands as to transmission. As an example, circuitry at the surface may include decoding circuitry to decode encoded information transmitted at least in part via mud-pulse telemetry. As an example, circuitry at the surface may include encoder circuitry and/or decoder circuitry and circuitry downhole may include encoder circuitry and/or decoder circuitry. As an example, the system 200 may include a transmitter that may generate signals that may be transmitted downhole via mud (e.g., drilling fluid) as a transmission medium.

As an example, one or more portions of a drillstring may become stuck. The term stuck may refer to one or more of varying degrees of inability to move or remove a drillstring from a bore. As an example, in a stuck condition, it might be possible to rotate pipe or lower it back into a bore or, for example, in a stuck condition, there may be an inability to move the drillstring axially in the bore, though some amount of rotation may be possible. As an example, in a stuck condition, there may be an inability to move at least a portion of the drillstring axially and rotationally.

As to the term “stuck pipe”, this may refer to a portion of a drillstring that cannot be rotated or moved axially. As an example, a condition referred to as “differential sticking” may be a condition whereby the drillstring cannot be moved (e.g., rotated or reciprocated) along the axis of the bore. Differential sticking may occur when high-contact forces caused by low reservoir pressures, high wellbore pressures, or both, are exerted over a sufficiently large area of the drillstring. Differential sticking may have time and financial cost.

As an example, a sticking force may be a product of the differential pressure between the wellbore and the reservoir and the area that the differential pressure is acting upon. This means that a relatively low differential pressure (delta p) applied over a large working area may be just as effective in sticking pipe as may a high differential pressure applied over a small area.

As an example, a condition referred to as “mechanical sticking” may be a condition where limiting or prevention of motion of the drillstring by a mechanism other than differential pressure sticking occurs. Mechanical sticking may be caused, for example, by one or more of junk in the hole, wellbore geometry anomalies, cement, keyseats or a buildup of cuttings in the annulus.

FIG. 3 shows an example of a wellsite system 300, specifically, FIG. 3 shows the wellsite system 300 in an approximate side view and an approximate plan view along with a block diagram of a system 370.

In the example of FIG. 3, the wellsite system 300 may include a cabin 310, a rotary table 322, drawworks 324, a mast 326 (e.g., optionally carrying a top drive, etc.), mud tanks 330 (e.g., with one or more pumps, one or more shakers, etc.), one or more pump buildings 340, a boiler building 342, an HPU building 344 (e.g., with a rig fuel tank, etc.), a combination building 348 (e.g., with one or more generators, etc.), pipe tubs 362, a catwalk 364, a flare 368, etc. Such equipment may include one or more associated functions and/or one or more associated operational risks, which may be risks as to time, resources, and/or humans.

As shown in the example of FIG. 3, the wellsite system 300 may include a system 370 that includes one or more processors 372, memory 374 operatively coupled to at least one of the one or more processors 372, instructions 376 that may be, for example, stored in the memory 374, and one or more interfaces 378. As an example, the system 370 may include one or more processor-readable media that include processor-executable instructions executable by at least one of the one or more processors 372 to cause the system 370 to control one or more aspects of the wellsite system 300. In such an example, the memory 374 may be or include the one or more processor-readable media where the processor-executable instructions may be or include instructions. As an example, a processor-readable medium may be a computer-readable storage medium that is not a signal and that is not a carrier wave.

FIG. 3 also shows a battery 380 that may be operatively coupled to the system 370, for example, to power the system 370. As an example, the battery 380 may be a back-up battery that operates when another power supply is unavailable for powering the system 370. As an example, the battery 380 may be operatively coupled to a network, which may be a cloud network. As an example, the battery 380 may include smart battery circuitry and may be operatively coupled to one or more pieces of equipment via a SMBus or other type of bus.

In the example of FIG. 3, services 390 are shown as being available, for example, via a cloud platform. Such services may include data services 392, query services 394 and drilling services 396. As an example, the services 390 may be part of a system such as the system 100 of FIG. 1 (e.g., consider planning services and/or operational services). As an example, the services 390 may include one or more services for directional drilling (e.g., consider a computational framework that may provide for one or more services that utilize real-time data to estimate one or more parameters, etc.).

As an example, the system 370 may be utilized to generate one or more rate of penetration drilling parameter values, which may, for example, be utilized to control one or more drilling operations.

As an example, a method may include automating operations of one or more types of downhole tools. For example, consider automating operations of one or more of mud motors, rotary steerable systems (RSSs) and at-bit steerable systems (ABSSs). As an example, one or more of such types of equipment, systems, etc., may be implemented using one or more features of the system 200 of FIG. 2.

As an example, an ABSS may include an actuator with a pressure drop range, hold inclination and azimuth (HIA), and dual downlinking capabilities. As an example, an ABSS may include onboard near-bit sensors that may acquire continuous six-axis inclination and azimuth measurements with a 6-ft range, and optional natural gamma ray and azimuthal images with a 9-ft range. As an example, an ABSS may include one of more features of one or more of the NEOSTEER family of ABSSs (SLB, Houston, Texas).

FIG. 4 shows an example of a system 400 that includes offsite equipment 401 (e.g., remote) and onsite equipment 402 (e.g., local). As shown, the offsite equipment 401 may include a drill operations framework 410, a drill planning framework 420 and a database 430 and the onsite equipment 402 may include a controller 440 that may receive real-time data and output recommendations such as control instructions to control onsite equipment. In such an example, the drill operations framework 410 may provide for steering sheets, execution parameters, etc., and the drill planning framework 420 may provide for evaluation of steering responses and statistics. As shown, the controller 440 may output information to the drill operations framework 410 and receive information from the drill planning framework 420. The system 400 may include plan generation features for real-time plan generation during drilling operations execution phase and/or plan generation during a planning phase. The system 400 may be utilized for one or more types of drilling (e.g., rotary, mud motor, RSS, ABSS, etc.). The system 400 may operate loops, which may include at least one real-time loop that provides for control of equipment to perform drilling operations.

A system such as the system 400 may utilize various functions and penalties for generation of plans, which may provide for single or multiple target aiming. As explained, a plan may be generated that aims to provide for drilling operations that aim for multiple targets simultaneously. As an example, the system 400 may include and/or be operatively coupled to a drilling operations emissions framework (DOEF) that may generate emissions for drilling operations, which may be, for example, on a time basis, a stand-by-stand basis, a length basis, a piece or pieces of equipment basis, etc. In such an example, the system 400 may plan and/or control drilling operations based at least in part on output from a DOEF (e.g., emissions values, emissions comparisons, emissions averages, emissions sources, etc.).

Various types of data associated with field operations may be 1-D series data. For example, consider data as to one or more of a drilling system, downhole states, formation attributes, and surface mechanics being measured as single or multi-channel time series data. As an example, data may be drilling operations data that are associated with drilling operations. For example, consider rig data that may be indicative of one or more rig states, which may facilitate determining when a stand begins being drilled and when a stand ends being drilled. As an example, rig data may include data indicative of drilling mode (e.g., slide or rotate). As explained, a rig may include various types of equipment where equipment such as a top drive, a mud pump, a drawworks, etc., may consume energy and, depending on energy source, generate emissions.

FIG. 5 shows an example of various components of a hoisting system 500, which includes a cable 501, drawworks 510, a traveling block 511, a hook 512, a crown block 513, a top drive 514, a cable deadline tiedown anchor 520, a cable supply reel 530, one or more sensors 540 and circuitry 550 operatively coupled to the one or more sensors 540. In the example of FIG. 5, the hoisting system 500 may include various sensors, which may include one or more of load sensors, displacement sensors, accelerometers, etc. As an example, the cable deadline tiedown anchor 520 may be fit with a load cell (e.g., a load sensor).

The hoisting system 500 may be part of a wellsite system (see, e.g., FIG. 2 and FIG. 3). In such a system, a measurement channel may be a block position measurement channel, referred to as BPOS, which provides measurements of a height of a traveling block, which may be defined about a deadpoint (e.g., zero point) and may have deviations from that deadpoint in positive and/or negative directions. For example, consider a traveling block that may move in a range of approximately −5 meters to +45 meters, for a total excursion of approximately 50 meters. As an example, a null point or deadpoint may be defined to make a scale positive, negative or both positive and negative. In such an example, a rig height may be greater than approximately 50 meters (e.g., a crown block may be set at a height from the ground or rig floor in excess of approximately 50 meters). While various examples are given for land-based field operations (e.g., fixed, truck-based, etc.), various methods may apply for marine-based operations (e.g., vessel-based rigs, platform rigs, etc.).

BPOS is a type of real-time channel (e.g., data channel) that reflects surface mechanical properties of a rig. Another example of a channel is hook load, which may be referred to as HKLD. HKLD may be a 1-D series measurement of the load of a hook. As to a derivative, a first derivative may be a load velocity and a second derivative may be a load acceleration. Such data channels may be utilized to infer and monitor various operations and/or conditions. In some examples, a rig may be represented as being in one or more states, which may be referred to as rig states.

As to the HKLD channel, it may help to detect if a rig is “in slips”, while the BPOS channel may be a primary channel for depth tracking during drilling. For example, BPOS may be utilized to determine a measured depth in a geologic environment (e.g., a borehole being drilled, etc.). As to the condition or state “in slips”, HKLD is at a much lower value than in the condition or state “out of slips”.

The term slips refers to a device or assembly that may be used to grip a drillstring (e.g., drillcollar, drillpipe, etc.) in a relatively non-damaging manner and suspend it in a rotary table. Slips may include three or more steel wedges that are hinged together, forming a near circle around a drillpipe. On the drillpipe side (inside surface), the slips are fitted with replaceable, hardened tool steel teeth that embed slightly into the side of the pipe. The outsides of the slips are tapered to match the taper of the rotary table. After the rig crew places the slips around the drillpipe and in the rotary, a driller may control a rig to slowly lower the drillstring. As the teeth on the inside of the slips grip the pipe, the slips are pulled down. This downward force pulls the outer wedges down, providing a compressive force inward on the drillpipe and effectively locking components together. Then the rig crew may unscrew the upper portion of the drillstring (e.g., a kelly, saver sub, a joint or stand of pipe) while the lower part is suspended. After some other component is screwed onto the lower part of the drillstring, the driller raises the drillstring to unlock the gripping action of the slips, and a rig crew may remove the slips from the rotary.

A hook load sensor may be used to measure a weight of load on a drillstring and may be used to detect whether a drillstring is in-slips or out-of-slips. When the drillstring is in-slips, motion from the blocks or motion compensator do not have an effect on the depth of a drill bit at the end of the drillstring (e.g., it will tend to remain stationary). Where movement of a traveling block is via a drawworks encoder (DWE), which may be mounted on a shaft of the drawworks, acquired DWE information (e.g., BPOS) does not augment the recorded drill bit depth. When a drillstring is out-of-slips (e.g., drilling ahead), DWE information (e.g., BPOS) may augment the recorded bit depth. The difference in hook load weight (HKLD) between in-slips and out-of-slips tends to be distinguishable. As to marine operations, heave of a vessel may affect bit depth whether a drillstring is in-slips or out-of-slips. As an example, a vessel may include one or more heave sensors, which may sense data that may be recorded as 1-D series data.

As to marine operations, a vessel may experience various types of motion, such as, for example, one or more of heave, sway and surge. Heave is a linear vertical (up/down) motion, sway is linear lateral (side-to-side or port-starboard) motion, and surge is linear longitudinal (front/back or bow/stern) motion imparted by maritime conditions. As an example, a vessel may include one or more heave sensors, one or more sway sensors and/or one or more surge sensors, each of which may sense data that may be recorded as 1-D series data.

As an example, BPOS alone, or combined with one or more other channels, may be used to detect whether a rig is “on bottom” drilling or “tripping”, etc. An inferred state may be further consumed by one or more systems such as, for example, an automatic drilling control system, which may be a dynamic field operations system or a part thereof. In such an example, the conditions, operations, states, etc., as discerned from BPOS and/or other channel data may be predicates to making one or more drilling decisions, which may include one or more control decisions (e.g., of a controller that is operatively coupled to one or more pieces of field equipment, etc.).

A block may be a set of pulleys used to gain mechanical advantage in lifting or dragging heavy objects. There may be two blocks on a drilling rig, the crown block and the traveling block. Each may include several sheaves that are rigged with steel drilling cable or line such that the traveling block may be raised (or lowered) by reeling in (or out) a spool of drilling line on the drawworks. As such, block position may refer to the position of the traveling block, which may vary with respect to time. FIG. 5 shows the traveling block 511.

A hook may be high-capacity J-shaped equipment used to hang various equipment such as a swivel and kelly, elevator bails, or a top drive. FIG. 5 shows the hook 512 as operatively coupled to a top drive 514. As shown in FIG. 2, a hook may be attached to the bottom of the traveling block 211. A hook may provide a way to pick up heavy loads with a traveling block. The hook may be either locked (e.g., a normal condition) or free to rotate, so that it may be mated or decoupled with items positioned around the rig floor, etc.

Hook load may be the total force pulling down on a hook as carried by a traveling block. The total force includes the weight of the drillstring in air, the drill collars and ancillary equipment, reduced by forces that tend to reduce that weight. Some forces that might reduce the weight include friction along a bore wall (especially in deviated wells) and buoyant forces on a drillstring caused by its immersion in drilling fluid (e.g., and/or other fluid). If a blowout preventer (BOP) (e.g., or BOPs) is closed, pressure in a bore acting on cross-sectional area of a drillstring in the BOP may also exert an upward force.

A standpipe may be a rigid metal conduit that provides a high-pressure pathway for drilling fluid to travel approximately one-third of the way up the derrick, where it connects to a flexible high-pressure hose (e.g., kelly hose). A large rig may be fitted with more than one standpipe so that downtime is kept to a minimum if one standpipe demands repair. FIG. 2 shows the standpipe 208 as being a conduit for drilling fluid (e.g., drilling mud, etc.). Pressure of fluid within the standpipe 208 may be referred to as standpipe pressure.

As to surface torque, such a measurement may be provided by equipment at a rig site. As an example, one or more sensors may be utilized to measure surface torque, which may provide for direct and/or indirect measurement of surface torque associated with a drillstring. As an example, equipment may include a drill pipe torque measurement and controller system with one or more of analog frequency output and digital output. As an example, a torque sensor may be associated with a coupling that includes a resilient element operatively joining an input element and an output element where the resilient element allows the input and output elements to twist with respect to one another in response to torque being transmitted through the torque sensor where the twisting may be measured and used to determine the torque being transmitted. As an example, such a coupling may be located between a drive and drill pipe. As an example, torque may be determined via an inertia sensor or sensors. As an example, equipment at a rig site may include one or more sensors for measurement and/or determination of torque (e.g., in units of Nm, etc.).

As an example, equipment may include a real-time drilling service system that may provide data such as weight transfer information, torque transfer information, equivalent circulation density (ECD) information, downhole mechanical specific energy (DMSE) information, motion information (e.g., as to stall, stick-slip, etc.), bending information, vibrational amplitude information (e.g., axial, lateral and/or torsional), rate of penetration (ROP) information, pressure information, differential pressure information, flow information, etc. As an example, sensor information may include inclination, azimuth, total vertical depth, etc. As an example, a system may provide information as to whirl (e.g., backward whirl, etc.) and may optionally provide information such as one or more alerts (e.g., “severe backward whirl: stop and restart with lower surface RPM”, etc.).

As to mechanical specific energy (e.g., DMSE, etc.), it may be defined as the energy demand to remove a unit volume of rock. As an example, drilling may aim to drill more optimally according to one or more criteria. For example, drilling may aim to minimize or reduce MSE and/or to maximize or increase ROP. As to factors that may affect MSE, consider one or more of WOB, torque, ROP, and RPM. As explained, a controller may aim to drill more optimally according to one or more criteria, which may include one or more emissions criteria. For example, consider a controller that may aim to drill with reduced MSE, increased ROP and/or reduced emissions (e.g., reduced greenhouse gas (GHG) emissions, etc.).

As an example, a drillstring may include a tool or tools that include various sensors that may make various measurements. For example, consider the OPTIDRILL tool (SLB, Houston, Texas), which includes strain gauges, accelerometers, magnetometer(s), gyroscope(s), etc. For example, such a tool may acquire weight on bit (WOB) measurements using a strain gauge (e.g., 10 second moving window with bandwidth of 200 Hz), torque measurements using a strain gauge (e.g., 10 second moving window with bandwidth of 200 Hz), bending moment using a strain gauge (e.g., 10 second moving window with bandwidth of 200 Hz), vibration using one or more accelerometers (e.g., 30 second RMS with bandwidth of 0.2 to 150 Hz), rotational speed using a magnetometer and a gyroscope (e.g., 30 moving window with bandwidth of 4 Hz), annular and internal pressures using one or more strain gauges (e.g., 1 second average with bandwidth of 200 Hz), annular and internal temperatures using one or more temperature sensors (1 second average with bandwidth of 10 Hz), and continuous inclination using an accelerometer (30 second average with bandwidth of 10 Hz).

As mentioned, channels of real time drilling operation data may be received and characterized using generated synthetic data, which may be generated based at least in part on one or more operational parameters associated with the real time drilling operation. Such real time drilling operation data may include surface data and/or downhole data. As mentioned, data availability may differ temporally (e.g., frequency, gaps, etc.) and/or otherwise (e.g., resolution, etc.). Such data may differ as to noise level and/or noise characteristics. While various types of sensors are mentioned, equipment may be utilized that may not include one or more types of downhole sensors. In such instances, a method may be utilized that may determine one or more downhole values.

FIG. 6 shows an example of a method 600 that includes various blocks that may receive data, perform one or more analyses, perform one or more decisions, etc., to determine one or more states. In the example of FIG. 6, various examples of states may be illustrated with respect to hatching, color, etc. In FIG. 6, the example states include drilling, non-drilling, run-in-hole (RIH), pull-out-of-hole (POOH), pre-connection, connection, post-connection, and absent; noting that one or more other states may be included, additionally or alternatively.

Drilling may be drilling to increase the depth of a wellbore. Non-drilling activity may be determined to be occurring when no other activities are occurring (e.g., drilling, RIH, POOH, pre-connection, connection, post connection) and where the end of a current drill stand has not yet been reached. During non-drilling, the flow rate of fluid being pumped into a drillstring may increase and/or decrease, the rate of rotation of a drillstring may increase and/or decrease, a downhole tool (e.g., a drill bit) may move upwards and/or downwards, or a combination thereof. A non-drilling activity may be or include a time when a drill bit is idle (e.g., not drilling) and a slips assembly is not engaged with a drillstring.

Pre-connection may be where a downhole tool (e.g., a drill bit) has completed drilling operations for a current section of pipe, but the slips assembly has not begun to move (e.g., radially-inward) into engagement with the drillstring. During pre-connection, the flow rate of fluid being pumped into the drillstring may increase and/or decrease, the rate of rotation of the drillstring may increase and/or decrease, the downhole tool (e.g., the drill bit) may move upwards and/or downwards, or a combination thereof.

Connection may be where a slips assembly is engaged with, and supports, a drillstring (e.g., the drillstring is “in-slips”). When a connection is occurring, a segment (e.g., a pipe, a stand, etc.) may be added to the drillstring to increase the length of the drillstring, or a segment may be removed from the drillstring to reduce the length of the drillstring.

Post-connection may be where the drillstring is released by a slips assembly, and a downhole tool (e.g., the drill bit) are lowered to be on-bottom (e.g., bottom of hole or BOH). During post-connection, the flow rate of fluid being pumped into a drillstring may increase/and/or decrease, the rate of rotation of a drillstring may increase and/or decrease, a downhole tool (e.g., the drill bit) may move upwards and/or downwards, or a combination thereof.

As to an absent state, it may indicate a scenario where data are not being received (e.g., at least one of a plurality of inputs is missing).

As an example, a method may be utilized to determine a slips status. For example, slips status may include one or more of the following: In-slips where a slips assembly is engaged with, and supports, a drillstring (“in-slips”); out-of-slips where the slips assembly is not engaged with, and does not support, the drillstring; and absent where data are not received (e.g., at least one of the inputs is missing).

The method 600 of FIG. 6 may include various data acquisition or data reception blocks 602, 606, 608, etc., various decision block 605, 607, 609, 613, 615, 617, and 643, detection blocks 612 and 642 and state blocks. Measurements may include (1) a depth of a wellbore, (2) a depth of a drill bit, (3) a position of a travelling block, or a combination thereof. A set of measurements may or may not include weight on hook (e.g., HKLD), or weight on a drill bit (e.g., WOB). Each set of measurements may be captured/received a predetermined amount of time after a previous set of measurements is captured/received. A predetermined amount of time may be, for example, about three seconds; however, the predetermined amount of time may be shorter or longer.

A PCT publication WO 2017/221046 A1 of 28 Dec. 2017 is incorporated by reference herein and entitled “Automatic drilling activity detection” ('046 publication). The '046 publication describes a method of determining a drilling activity that includes receiving a set of measurements at different times. The set of measurements may include a depth of a wellbore, a depth of a drill bit, and a position of a travelling block. The method may also include identifying a connection by determining when the position of the travelling block changes but the depth of the drill bit does not change. The method may also include determining when the depth of the wellbore does not increase between two different connections. The method may also include determining a direction that the drill bit moves between the two connections.

A PCT publication WO 2022/246083 A1 of 24 Nov. 2022 is incorporated by reference herein and entitled “Measuring of Carbon Footprint in Offshore Drilling” ('083 publication). The '083 publication describes various types of emissions from various types of equipment. For example, a carbon footprint baseline may be established for a drilling unit. Power consumption may be calculated for drilling unit components. The power consumption of components may be converted to CO2 emissions according to a GHG standard. The power consumption may be transformed into real-time power consumption during drilling operations using power ratings, diversity factors, fuel usage, and specific fuel oil consumption. Real-time CO2 emissions may be computed based on the real-time power consumption. CO2 emissions computations and modelling of supply transport units may be performed based on previously collected power consumption data from supply transport units. In such an approach, real-time CO2 emissions of drilling operations may be determined, which may be stored, rendered, transmitted, etc.

As an example, a framework may provide for drilling operations emissions determinations, which may be utilized for one or more purposes, which may include, for example, control, equipment design, equipment selection, equipment configuration, power source selection, well operations planning, well design, well completions, etc.

As an example, consider a scenario where directional drilling utilizes a mud motor that may provide for slide drilling where a drill bit is rotated via flow of mud through the mud motor. In such an example, energy expended via mud pumps to drive the mud motor may be compared to energy expended to rotate the drill bit by a top drive (e.g., or rotary table). In such example, the energy expended may be utilized to determine emissions, which may depend on type of energy source utilized (e.g., wind, solar, diesel, natural gas turbine, etc.). Where a goal is to reduce emissions, decisions may be made as to slide and/or rotation modes of drilling, which may be, for example, based on a trajectory and a dog leg severity (DLS) of a borehole to be drilled. As an example, one source of energy may be utilized for a top drive and another source of energy may be utilized for a mud pump(s) to power a mud motor.

As another example, consider drill bit design where a new drill bit design may provide for a higher ROP. However, if the new drill bit design demands more mud flow, then there may be a tradeoff as to energy expended for a mud pump(s). Hence, while a higher ROP may be realized, there may possibly be a higher level of emissions (e.g., depending on source or sources of energy utilized to drive the mud pump(s). Similarly, the higher ROP drill bit design may demand higher energy input by a top drive. Further, the higher ROP drill bit design may perform differently depending on whether slide mode or rotation mode is utilized. In such examples, a drilling operations emissions framework (DOEF) may provide detailed emissions information to assess equipment decisions, operational decisions, planning decisions, etc., for example, in an effort to reduce emissions.

As an example, a DOEF may provide performance insights such as, for example, emissions per stand for various drilling operations, which may depend on type of drilling mode, type of equipment, team, service company, etc.

As an example, a DOEF may include components that may decompose and contextualize high frequency streams of emissions data and/or estimate emissions for various operations, which may include drilling operations. For example, consider detailed stand-by-stand emissions outputs. Such an approach allows for composition of emission performance indicators (e.g., “key performance indicators” or “KPIs”), which may be categorized and/or classified by operation, section, rig, operational codes, sections, stands, length, etc.

As an example, a DOEF may leverage rig state and stand decomposition to compute emissions per stand and/or per unit length. As an example, a rig state framework may be used to decompose time and contextualize with activities. Such a workflow may leverage the output of rig state and stand decomposition to decompose an emissions channel, integrating the emissions over a period of time of a stand and associating the emissions as one more attribute to the stand. Such a process may be agnostic of the source of data (actual, estimated or modeled) and allow for segmentation of these emissions based on actual operational data.

As an example, a DOEF may include a language processing component that may leverage comments that may be entered by personnel during actual drilling operations. In such an example, the comments may be subjected to quality control using, for example, rig states and/or underlying data streams (e.g., high frequency channels at 1 Hz, etc.). In such an approach, comments may be quality controlled and mined such that they may be related to emissions information. As an example, one or more emissions channels may be generated using comments, whether raw and/or processed (e.g., quality controlled, etc.).

As to an example of quality control using language processing and data channels, consider comparing measured depths, timings, etc., as may appear in comments to those appearing in one or more data channels. In such an approach, it may be assumed that the one or more data channels are accurate such that issues may be identified in comments and, for example, adjusted to match sensor-based realities. In turn, quality controlled and data harmonized comments may be utilized to establish a link between emissions and operations. For example, to link changes to a plan as determined by rig personnel to determine deviations from the plan and, for example, deviations in planned emissions versus actual emissions. In such an example, teams, service companies, rig personnel, etc., and their decision making may be linked to decisions that may impact emissions, whether positive or negative. Such an approach may improve decision making, which may inform planning, etc.

As an example, a DOEF may provide for decomposing time series in activities and stands to also decompose an emissions time channel or emissions time channels (e.g., rig basis, equipment basis, etc.).

As an example, a DOEF may provide context to emissions in an automated manner. As mentioned, one or more natural language processing techniques may be implemented along with, for example, one or more machine learning models. In such an example, contextual information from comments (e.g., rig personnel, etc.) may be leveraged to improve contextualization of emissions information. As an example, a DOEF may allow for time series streams of emissions data for one or more purposes such as, for example, to prepare emissions KPIs (customizable) to compare performance of technologies, processes and practices to select the option that generates less emissions. As an example, a DOEF may allow for comparisons of emissions from live operations versus historical operations (e.g., historical wells) and provide for decision making (e.g., control of equipment, etc.) for running operations or to integrate into one or more planning phases.

FIG. 7 shows an example of a method 700 for stand decomposition with integration of contextual information. As shown, the method 700 may include an acquisition block 710 for receiving one or more streams of drilling operations parameters (e.g., BPOS, RPM, flow, WOH, TRQ, SPP, etc.), an identification block 720 for identifying rig states and stands, an integration block 730 for integrating contextual information from one or more sources (e.g., rig, crew, bit, BHA, etc.), and a stand decomposition block 740 that provides output as to stands decomposed with contextual information. For example, stand information may include contextual information that may be quality controlled and optionally processed using one or more ML models. In such an example, sensor data and other data may be harmonized with improvements in integrity (e.g., accuracy) and trust.

FIG. 8 shows an example of a method 800 for generation of emissions information where the method 800 may include an integration block 810 for integrating emissions information for stand duration of one or more stands and a reporting block 820 for reporting emissions at a stand level. In such an example, the stand durations may be provided by a method such as, for example, the method 700 of FIG. 7. In the example of FIG. 8, as explained, emissions information may come from one or more sources, which may include sensor-based, model-based, historical data-based, etc. As to sensor-based, one or more pieces of equipment may be instrumented with one or more sensors as to energy input and/or output (e.g., work, emissions, etc.). As an example, one or more sensors may measure emissions as one or more types of GHG emissions (e.g., directly and/or indirectly). As an example, a model-based approach may utilize one or more metrics as to how equipment operates to generate an emissions estimate. For example, consider a known mass of a stand and a lift that may be used to lift a stand for connection to a top drive such that the stand may be connected to a drillstring. In such an example, a minimum amount of energy expended may be determined and related to emissions based on an energy source for the lift. While lifting for connection to a drillstring is mentioned, as another example, lifting for disconnecting may be performed, for example, when tripping a drillstring out of a borehole. As an example, historical information may exist in one or more databases for already drilled wells where an estimate as to energy consumed may be determined, optionally, for example, based on a statistical and/or probabilistic approach. For example, given particular inputs such as measured depth, ROP, mud flow rates, etc., a database may be searched for corresponding energy and/or emissions. In such an example, data may optionally be interpolated and/or a machine learning model may be used that may have been trained using the historical data, etc.

As to the reporting block 820, it may report emissions via one or more graphical user interfaces (GUIs), via transmission of information, etc. As explained, such reporting may be on a stand level such that a level of emissions generated for an individual stand or a group of stands may be reported. In such an example, reporting may include reporting an expected level versus an actual level. As an example, an expected level may be determined during planning, simulation, etc. For example, consider a drilling simulation framework that may be executed to generate emissions information on a stand-by-stand level. In such an example, drilling operations may be expected to generate emissions approximately equal to the results of the simulation. Where actual emissions differ, differences may be noted and stored to a database, which may be used for one or more purposes. For example, consider training a ML model, training personnel, etc., using the differences where, as explained, the differences may be contextualized (e.g., using comments, etc.).

FIG. 9 shows an example of a method 900 that may include various blocks 910, 920 and 930 for integration of emissions, for example, as in the integration block 810 of the method 800 of FIG. 8. In such an example, the block 910 may be a SCR model block (e.g., a silicon-controlled rectifier-based model, etc.), the block 920 may be a genset measurements block (e.g., measurements from a generator) and the block 930 may be a direct emissions block (e.g., direct measurements of emissions).

As to an SCR model, consider power utilized by a drawworks. A drawworks may be chain-driven capable of operation ranging from 3,000 to 4,500 input horsepower. As an example, hoisting power of a drawworks may be provided by a two-or three-motor drive system, which may be either a variable frequency AC drive or silicon-controlled rectifier (SCR) DC drive. A chain-driven drawworks may be equipped with a robust disc brake system featuring hydraulically applied service brake calipers as well as spring-actuated emergency and parking brake calipers for operational safety. A drawworks may be available for transport by being mounted on an oilfield-type skid with provisions for crane lifting and easy tailboard loading onto transport trucks or rig structures.

As to mud pumps, consider, for example, 1,600-and 2,000-horsepower mud pumps for land applications. As an example, single-acting reciprocating triplex mud pumps may provide for delivery of increased reliability and maintainability in a smaller, lighter footprint. Such pumps may use advanced materials and treatments to improve bearing life where carburized and hardened gears resist pitting and wear. As to offshore operations, consider, for example, a 2,200-horsepower mud pump that may be a single-acting reciprocating triplex mud pump designed for high fluid flow rates, even at low operating speeds, and with a long stroke design. Such features may reduce the number of load reversals in various components and increase life of fluid end parts. As to maintenance, a two-piece, quick-release piston rod may provide for piston removal without disturbing a liner, which may help to minimize downtime when replacing fluid parts.

As to a top drive, consider a single motor or a multi-motor top drive. As an example, a top drive may be specified according to tons such as, for example, a 500 tonUS, a 750 tonUS, a 1,000 tonUS, etc., top drive. As an example, a top drive may include one or more AC motors where torque may be rated as continuous maximum torque (e.g., consider 50,000 N.m, 70,000 N.m, 90,000 N.m torque, etc.). As to power ratings, consider 500 horsepower, 1,000 horsepower, 1,500 horsepower, etc., noting that equipment with a 1,500 horsepower rating or more may be provided.

As explained, equipment such as a drawworks, a mud pump or mud pumps, and a top drive may consume energy during drilling operations. As example, a DOEF may provide for reporting emissions for individual pieces of equipment, which may be reported on a stand-by-stand basis. As explained, during slide drilling, mud flow may drive a mud motor that causes a drill bit to rotate. During slide drilling a top drive may also be utilized, for example, to oscillate a drillstring to ease sliding (e.g., consider oscillations that may be less than a few rotations in either direction, etc., that may help to reduce frictional forces on a drillstring). As an example, a DOEF may determine and report emissions for stands on a stand-by-stand basis where an individual stand may be drilled using a slide mode and/or a rotation mode; noting that generally a single stand may be drilled using a single mode.

As to a slide mode, as an example, drilling may occur using a mud motor for rotating a drill bit downhole without rotating the drillstring from the surface (e.g., noting that oscillating may be utilized by a top drive). A slide mode of operation may be conducted when a BHA has been fitted with a bent sub or a bent housing mud motor, or both, for directional drilling. Sliding is a predominant method to build and control or correct hole angle in modern directional drilling operations. Directional drilling may involve pointing a drill bit in a desired direction. Such pointing may be accomplished through a bent sub, which has a small angle offset from the axis of the drillstring, and a measurement device to determine the direction of offset. Without turning the drillstring, the drill bit may be rotated with a mud motor such that drilling occurs in the direction it is pointed. With steerable motors, when a desired wellbore direction is attained, the entire drillstring may be rotated and drill straight rather than at an angle. By controlling the amount of hole drilled in the sliding versus the rotating mode, a wellbore trajectory may be controlled precisely.

FIG. 10 shows an example of a GUI 1000 that includes tracks of drilling operations data including depth, BPOS, HKLD, SPPA, rig state, torque (TQA), surface weight on bit (SWOB), and various other types of information, which may include non-productive time (NPT), operations, phases, codes, comments, etc. In the example of FIG. 10, examples of stands are labeled 1, 2 and 3, which may include start and end times and operations (e.g., drilling, tripping, equipment such as BHA related, etc.). As explained, a DOEF may integrate contextual information with various channels (e.g., tracks) of data to provide for quality-controlled context that may be integrated with emissions information. Such an approach may facilitate more accurate emissions reporting, which, in turn, may improve uses of emissions information. For example, if comments alone were utilized, an error in a comment may result in a large error in reported emissions for a stand. Similarly, channel data may, at times, not resolve to a particular state with a high probability. In such an example, a combination of comments and channel data may improve emissions reporting where, as explained, cross-checking may be employed along with adjustments as appropriate. In various examples, one or more data cleansing processes may be utilized, which may be part of a state determination workflow implemented by a state determination framework.

FIG. 11 shows an example of a table 1100 for various types of information, which may include borehole (well), crew, rig name, start and stop times and measured depths. As an example, a framework may provide for rendering such a table, which may include one or more graphical controls for interactive generation of visualizations, for example, consider emissions information being rendered with respect to information in one or more of the columns and/or rows of the table 1100.

FIG. 12 shows an example of a GUI 1200 that includes stand information that is integrated with emissions information such as, for example, start and end times for drilling of a stand, hole size, operation code and emissions (e.g., in kg). As shown, emissions may vary as the emissions information in the example GUI 1200 ranges from 32 kg to 200 kg. As such, emissions may vary substantially during operations for one or more reasons even when the same type of operation is being performed. In the example of FIG. 12, the GUI 1200 includes a rendering of BPOS and emissions. In such an example, a driller, a monitor, etc., may visually track emissions with respect to one or more types operations where equipment may be moving in a borehole and/or one or more other operations may be performed.

FIG. 13 shows an example of a GUI 1300 that includes GHG emissions for various operations. For example, the GUI 1300 includes panels for emissions by depth, tripping emissions, emissions per stand, etc. As shown, section direction (e.g., in-hole (RIH) or out-of-hole (POOH)), emissions per trip, emissions per stand average, planned emissions, etc., may be rendered using the GUI 1300. As an example, the GUI 1300 may render indications of efficiency, which may be with respect to planned operations emissions. For example, efficiency may range from less than 100 percent to greater than 100 percent. As shown in a panel of the GUI 1300 for emissions per stand, reporting may include average, lost time and equipment specific emissions such as emissions for top drive (TDS), mud pump(s), drawworks (hoist), etc. Such emissions may be color or otherwise coded for ease of review and, for example, rendered with respect to time, distance drilled, etc. For example, the GUI 1300 may be a dynamic GUI that may be updated in real-time or near real-time as field operations are performed, etc. As an example, the GUI 1300 may be interactive such that user may interact with the GUI 1300 to cause the GUI 1300 to render specific information, perform various comparisons, access other data, etc.

As an example, a GUI may render one or more metrics as to efficiency, which may, for example, be utilized in one or more control loops to improve field operations. As an example, a GUI may include one or more graphical controls for accessing offset well information, setting performance indicator (e.g., KPI) targets, etc. As an example, a performance indicator target may be dynamic and depend on one or more factors such as, for example, availability of emissions credits, availability of energy sources, activity at one or more other wellsites, etc. As an example, a target may depend on one or more emissions goals for one or more wells, which may include one or more wells with wellbores in the process of being drilled.

FIG. 14 shows an example of a GUI 1400 that includes emissions broken out for particular operations with respect to time where coding may indicate actual duration, saved versus actual emissions, lost versus actual time, performance gap, etc.

In the example of FIG. 14, various operations are listed for various sections. Such operations may include cementing, wiping, pre-casing runs, blowout protecter (BOP) testing, etc. As explained, various operations may include associated energy expenditures that may be related to emissions where sources of energy and/or how such operations are performed may determine emissions. In the example of FIG. 14, the GUI 1400 may provide for ranking various types of operations for improvements, where some operations may be focused upon to provide for greater reductions in emissions than other operations.

As explained, one or more bases may be utilized for assessing and/or controlling emissions. As an example, a framework may utilize rig state, stand-by-stand, pipe length, time intervals, etc., for emissions. As an example, emissions may depend on various factors and may be characterized, for example, in terms of mechanical energy to electric energy or vice versa (e.g., consider utilization of SME, etc.). As an example, a framework may provide for assessing emissions with respect to a top drive and/or one or more other pieces of equipment. As an example, emissions may be associated with hook weight, block position velocity, POOH, RIH, etc. As an example, consider an approach that may optimally accelerate a block whether loaded or unloaded to provide for improved emissions. In such an example, a velocity profile may follow an optimal acceleration profile. As mentioned, in various types of drilling, a top drive may be utilized differently. For example, for rotary drilling a top drive may be used to rotate an entire drillstring to rotate a bit to extend a borehole while in slide drilling, a top drive may provide for oscillating a drillstring for purposes of reducing frictional forces. As an example, a framework may provide for improving top drive operation for one or more types of drilling (e.g., drilling modes, etc.) to reduce emissions or otherwise to help meet one or more emissions goals. As an example, a framework may provide for improving control of a drawworks during one or more types of operations (e.g., drilling, tripping, etc.) to reduce emissions. As an example, a framework may provide for control of one or more fluids such as drilling fluid to reduce emissions (e.g., pump control as to flow rate, standpipe pressure, mud motor, etc.).

As an example, one or more sensor-based measurements of emissions may provide for indications as to rig state, equipment state, operational state, etc., at a wellsite. For example, consider a machine learning model that may be trained on a combination of data types where such data types may include emissions data. In such an example, a trained machine learning model may be part of a framework and may help provide for rig state detection in manner associated with emissions.

As an example, a framework may provide for improved planning where, for example, planning may be performed in a manner that may tailor emissions (e.g., to meet one or more goals). As an example, a framework may provide for improving well design, for example, in a manner that may compare different wells, rigs, sections, drilling modes (e.g., sliding and rotating), etc., which may provide for improving operations for a borehole to be drilled, a borehole to be completed, etc.

As an example, a framework may operate to improve control of field operations. For example, consider a framework that may be operatively coupled to an autodriller that provides one or more levels of automation for drilling operations. As an example, an autodriller may provide for controlling one or more drilling operations in a manner that may provide for reduced emissions. As an example, an autodriller may include one or more machine learning models that may be trained at least in part using emissions such that a trained machine learning model may provide for automated control of drilling operations in a manner that may reduce emissions.

As an example, a framework may provide for tailoring one or more fluids to reduce emissions during drilling operations. For example, consider a framework that may recommend utilization of one or more types of mud (e.g., water-based, oil-based, synthetic, etc.), additives, etc., that may provide for viscosity, density, etc., that may reduce emissions.

As an example, a framework may provide for energy source decision-making, which may include, for example, switching from one source to another source. In such an example, a framework may provide for control of one or more switches that may control how equipment is powered (e.g., wind, electric, diesel, grid, etc.).

As explained, emissions may be reported and utilized for one or more purposes. In various examples, drilling operations may be intended to meet well integrity constraints, efficiency and cost constraints and emissions constraints. The introduction of GHG emissions constraints may impact efficiency and cost. As an example, a Pareto approach may be taken when planning drilling operations and/or during drilling operations such that constraints may be met. In various instances, GHG emissions may be a compliance issue or, for example, a GHG credit/cost type of issue. An ability to report GHG emissions on a stand-by-stand or other operational level facilitates an ability to quantify and meet GHG emissions constraints. And, as mentioned, GHG emissions information may be utilized for one or more purposes, which may include planning, design, control, etc.

FIG. 15 shows an example of a method 1500 and an example of a system 1590. As shown, the method 1500 may include a reception block 1510 for receiving drilling operations data with respect to time as acquired during drilling operations at a rig site; a reception block 1520 for receiving contextual information associated with the drilling operations at the rig site; and a determination block 1530 for determining emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information. As an example, the method 1500 may include an issuance block 1540 for issuing a control signal based on the emissions.

FIG. 15 also shows various computer-readable media (CRM) blocks 1511, 1521, 1531, and 1541. Such blocks may include instructions that are executable by one or more processors, which may be one or more processors of a computational framework, a system, a computer, etc. A computer-readable medium may be a computer-readable storage medium that is not a signal, not a carrier wave and that is non-transitory. For example, a computer-readable medium may be a physical memory component that may store information in a digital format.

In the example of FIG. 15, a system 1590 includes one or more information storage devices 1591, one or more computers 1592, one or more networks 1595 and instructions 1596. As to the one or more computers 1592, each computer may include one or more processors (e.g., or processing cores) 1593 and memory 1594 for storing the instructions 1596, for example, executable by at least one of the one or more processors. As an example, a computer may include one or more network interfaces (e.g., wired or wireless), one or more graphics cards, a display interface (e.g., wired or wireless), etc. The system 1590 may be specially configured to perform one or more portions of the method 1500 of FIG. 15.

As an example, various systems, frameworks, methods, etc., may implement one or more ML models. As to types of ML models, consider one or more of a support vector machine (SVM) model, a k-nearest neighbors (KNN) model, an ensemble classifier model, a neural network (NN) model, etc. As an example, a machine learning model may be a deep learning model (e.g., deep Boltzmann machine, deep belief network, convolutional neural network, stacked auto-encoder, etc.), an ensemble model (e.g., random forest, gradient boosting machine, bootstrapped aggregation, AdaBoost, stacked generalization, gradient boosted regression tree, etc.), a neural network model (e.g., radial basis function network, perceptron, back-propagation, Hopfield network, etc.), a regularization model (e.g., ridge regression, least absolute shrinkage and selection operator, elastic net, least angle regression), a rule system model (e.g., cubist, one rule, zero rule, repeated incremental pruning to produce error reduction), a regression model (e.g., linear regression, ordinary least squares regression, stepwise regression, multivariate adaptive regression splines, locally estimated scatterplot smoothing, logistic regression, etc.), a Bayesian model (e.g., naïve Bayes, average on-dependence estimators, Bayesian belief network, Gaussian naïve Bayes, multinomial naïve Bayes, Bayesian network), a decision tree model (e.g., classification and regression tree, iterative dichotomiser 3, C4.5, C5.0, chi-squared automatic interaction detection, decision stump, conditional decision tree, M5), a dimensionality reduction model (e.g., principal component analysis, partial least squares regression, Sammon mapping, multidimensional scaling, projection pursuit, principal component regression, partial least squares discriminant analysis, mixture discriminant analysis, quadratic discriminant analysis, regularized discriminant analysis, flexible discriminant analysis, linear discriminant analysis, etc.), an instance model (e.g., k-nearest neighbor, learning vector quantization, self-organizing map, locally weighted learning, etc.), a clustering model (e.g., k-means, k-medians, expectation maximization, hierarchical clustering, etc.), etc.

As an example, a system may utilize one or more recurrent neural networks (RNNs). One type of RNN is referred to as long short-term memory (LSTM), which may be a unit or component (e.g., of one or more units) that may be in a layer or layers. A LSTM component may be a type of artificial neural network (ANN) designed to recognize patterns in sequences of data, such as time series data. When provided with time series data, LSTMs take time and sequence into account such that an LSTM may include a temporal dimension. For example, consider utilization of one or more RNNs for processing temporal data from one or more sources, optionally in combination with spatial data. Such an approach may recognize temporal patterns, which may be utilized for making predictions (e.g., as to a pattern or patterns for future times, etc.).

As an example, the TENSORFLOW framework (Google LLC, Mountain View, California) may be implemented, which is an open-source software library for dataflow programming that includes a symbolic math library, which may be implemented for machine learning applications that may include neural networks. As an example, the CAFFE framework may be implemented, which is a DL framework developed by Berkeley Al Research (BAIR) (University of California, Berkeley, California). As another example, consider the SCIKIT platform (e.g., scikit-learn), which utilizes the PYTHON programming language. As an example, a framework such as the APOLLO AI framework may be utilized (APOLLO.AI GmbH, Germany). As mentioned, a framework such as the PYTORCH framework may be utilized.

As an example, a training method may include various actions that may operate on a dataset to train a ML model. As an example, a dataset may be split into training data and test data where test data may provide for evaluation. A method may include cross-validation of parameters and best parameters, which may be provided for model training.

The TENSORFLOW framework may run on multiple CPUs and GPUs (with optional CUDA (NVIDIA Corp., Santa Clara, California) and SYCL (The Khronos Group Inc., Beaverton, Oregon) extensions for general-purpose computing on graphics processing units (GPUs)). TENSORFLOW is available on 64-bit LINUX, MACOS (Apple Inc., Cupertino, California), WINDOWS (Microsoft Corp., Redmond, Washington), and mobile computing platforms including ANDROID (Google LLC, Mountain View, California) and IOS (Apple Inc.) operating system-based platforms.

TENSORFLOW computations may be expressed as stateful dataflow graphs; noting that the name TENSORFLOW derives from the operations that such neural networks perform on multidimensional data arrays. Such arrays may be referred to as “tensors”.

As an example, a device may utilize TENSORFLOW LITE (TFL) or another type of lightweight framework. TFL is a set of tools that enables on-device machine learning where models may run on mobile, embedded, and loT devices. TFL is optimized for on-device machine learning, by addressing latency (no round-trip to a server), privacy (no personal data leaves the device), connectivity (Internet connectivity is demanded), size (reduced model and binary size) and power consumption (e.g., efficient inference and a lack of network connections). TFL offers multiple platform support, covering ANDROID and iOS devices, embedded LINUX, and microcontrollers. TFL offers diverse language support, which includes JAVA, SWIFT, Objective-C, C++, and PYTHON. TFL offers high performance, with hardware acceleration and model optimization.

As an example, a method may include receiving drilling operations data with respect to time as acquired during drilling operations at a rig site; receiving contextual information associated with the drilling operations at the rig site; and determining emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information. In such an example, determining emissions may include using one or more of a model, emissions measurements and historical data.

As an example, drilling operations may include operations performed on a stand-by-stand basis and where emissions of the drilling operations include stand-by-stand emissions. For example, consider determining rig states based at least in part on drilling operations data where determining emissions of the drill operations is based at least in part on the rig states. In such an example, stand-by-stand emissions values may be reported.

As an example, a method may include integrating contextual information and drilling operations data prior to determining the emissions of the drilling operations. In such an example, integrating may include performing one or more quality control procedures using the contextual information and the drilling operations data to improve quality of one or more of the contextual information and the drilling operations data. In such an example, integrating may generate harmonized information that improves accuracy of the determining of emissions of the drilling operations.

As an example, a method may include controlling equipment at rig site based at least in part on determined emissions of the drilling operations. For example, consider controlling equipment to perform a mode of drilling. In such an example, the mode of drilling may be selected from a slide mode and a rotation mode. For example, consider powering a mud motor of a drillstring via mud pumped by one or more mud pumps to rotate a drill bit while oscillating the drillstring (e.g., clockwise and counter-clockwise) using a top drive or rotating a drill bit by rotating the drillstring using the top drive. Such different modes of drilling may generate different levels of emissions where, for example, an energy source may be a common energy source (e.g., diesel, natural gas turbine, etc.). As explained, different equipment may utilize different energy sources (e.g., diesel, natural gas turbine, grid, renewable, etc.).

As an example, a method may include determining emissions of drilling operations by determining emissions of pieces of equipment at the rig site. In such an example, the pieces of equipment may include, for example, one or more of a top drive, a rotary table, a mud pump and a drawworks.

As an example, emissions may include greenhouse gas (GHG) emissions. As an example, emissions may include at least carbon dioxide emissions.

As an example, a method may include receiving energy source

information for pieces of equipment where the energy source information specifies one or more energy sources for each of the pieces of equipment. For example, consider energy source information that specifies one or more of diesel fuel, natural gas turbine, grid and renewable.

As an example, drilling operations data may be received at a first frequency, where contextual information is received at a second frequency, where the first frequency is more frequent than the second frequency, and where emissions of drilling operations is reported at a frequency that is less frequent than the first frequency.

As an example, a rig state generator may generate rig states at a frequency that is less frequent than a frequency of drilling operations data and determining emissions of the drilling operations may utilize such generated rig states. For example, rig states may facilitate distinguishing stand-by-stand operations such that emissions may be reported on a stand-by-stand basis. As an example, a stand may be a triple with a length of approximately 100 ft or approximately 30 m. In such an example, if a ROP is 100 ft/h or 30 m/h, then drilling a stand (triple) to deepen a borehole by 100 ft or 30 m may be performed in one hour. During that one-hour period of time, various types of equipment may be operating such as, for example, a top drive, one or more mud pumps and a drawworks. Where a ROP is greater, then emissions may be less per stand, but not necessarily less per stand. For example, if more fuel is expended and more emissions generated per unit time for drilling at the greater ROP, the emissions may be the same or even greater. In various examples, output of a DOEF may be utilized to tailor a plan, drilling operations, etc., to meet various constraints, which may include emissions constraints that may be intertwined with borehole integrity constraints and/or efficiency and cost constraints.

As an example, a system may include one or more processors; memory accessible to at least one of the one or more processors; processor-executable instructions stored in the memory and executable to instruct the system to: receive drilling operations data with respect to time as acquired during drilling operations at a rig site; receive contextual information associated with the drilling operations at the rig site; and determine emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information.

As an example, one or more computer-readable storage media may include processor-executable instructions to instruct a computing system to: receive drilling operations data with respect to time as acquired during drilling operations at a rig site; receive contextual information associated with the drilling operations at the rig site; and determine emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information.

As an example, a computer program product that may include computer-executable instructions to instruct a computing system to perform one or more methods such as one or more of the methods described herein (e.g., in part, in whole and/or in various combinations).

In some embodiments, a method or methods may be executed by a computing system. FIG. 16 shows an example of a system 1600 that may include one or more computing systems 1601-1, 1601-2, 1601-3 and 1601-4, which may be operatively coupled via one or more networks 1609, which may include wired and/or wireless networks.

As an example, a system may include an individual computer system or an arrangement of distributed computer systems. In the example of FIG. 16, the computer system 1601-1 may include one or more modules 1602, which may be or include processor-executable instructions, for example, executable to perform various tasks (e.g., receiving information, requesting information, processing information, simulation, outputting information, etc.).

As an example, a module may be executed independently, or in coordination with, one or more processors 1604, which is (or are) operatively coupled to one or more storage media 1606 (e.g., via wire, wirelessly, etc.). As an example, one or more of the one or more processors 1604 may be operatively coupled to at least one of one or more network interface 1607. In such an example, the computer system 1601-1 may transmit and/or receive information, for example, via the one or more networks 1609 (e.g., consider one or more of the Internet, a private network, a cellular network, a satellite network, etc.). As shown, one or more other components 1608 may be included in the computer system 1601-1.

As an example, the computer system 1601-1 may receive from and/or transmit information to one or more other devices, which may be or include, for example, one or more of the computer systems 1601-2, etc. A device may be located in a physical location that differs from that of the computer system 1601-1. As an example, a location may be, for example, a processing facility location, a data center location (e.g., server farm, etc.), a rig location, a wellsite location, a downhole location, etc.

As an example, a processor may be or include a microprocessor, microcontroller, processor module or subsystem, programmable integrated circuit, programmable gate array, or another control or computing device.

As an example, the storage media 1606 may be implemented as one or more computer-readable or machine-readable storage media. As an example, storage may be distributed within and/or across multiple internal and/or external enclosures of a computing system and/or additional computing systems.

As an example, a storage medium or storage media may include one or more different forms of memory including semiconductor memory devices such as dynamic or static random access memories (DRAMs or SRAMs), erasable and programmable read-only memories (EPROMs), electrically erasable and programmable read-only memories (EEPROMs) and flash memories, magnetic disks such as fixed, floppy and removable disks, other magnetic media including tape, optical media such as compact disks (CDs) or digital video disks (DVDs), BLUERAY disks, or other types of optical storage, or other types of storage devices.

As an example, a storage medium or media may be located in a machine running machine-readable instructions, or located at a remote site from which machine-readable instructions may be downloaded over a network for execution.

As an example, various components of a system such as, for example, a computer system, may be implemented in hardware, software, or a combination of both hardware and software (e.g., including firmware), including one or more signal processing and/or application specific integrated circuits.

As an example, a system may include a processing apparatus that may be or include a general purpose processors or application specific chips (e.g., or chipsets), such as ASICs, FPGAs, PLDs, or other appropriate devices.

As an example, a device may be a mobile device that includes one or more network interfaces for communication of information. For example, a mobile device may include a wireless network interface (e.g., operable via IEEE 802.11, ETSI GSM, BLUETOOTH, satellite, etc.). As an example, a mobile device may include components such as a main processor, memory, a display, display graphics circuitry (e.g., optionally including touch and gesture circuitry), a SIM slot, audio/video circuitry, motion processing circuitry (e.g., accelerometer, gyroscope), wireless LAN circuitry, smart card circuitry, transmitter circuitry, GPS circuitry, and a battery. As an example, a mobile device may be configured as a cell phone, a tablet, etc. As an example, a method may be implemented (e.g., wholly or in part) using a mobile device. As an example, a system may include one or more mobile devices.

As an example, a system may be a distributed environment, for example, a so-called “cloud” environment where various devices, components, etc. interact for purposes of data storage, communications, computing, etc. As an example, a device or a system may include one or more components for communication of information via one or more of the Internet (e.g., where communication occurs via one or more Internet protocols), a cellular network, a satellite network, etc. As an example, a method may be implemented in a distributed environment (e.g., wholly or in part as a cloud-based service).

As an example, information may be input from a display (e.g., consider a touchscreen), output to a display or both. As an example, information may be output to a projector, a laser device, a printer, etc. such that the information may be viewed. As an example, information may be output stereographically or holographically. As to a printer, consider a 2D or a 3D printer. As an example, a 3D printer may include one or more substances that may be output to construct a 3D object. For example, data may be provided to a 3D printer to construct a 3D representation of a subterranean formation. As an example, layers may be constructed in 3D (e.g., horizons, etc.), geobodies constructed in 3D, etc. As an example, holes, fractures, etc., may be constructed in 3D (e.g., as positive structures, as negative structures, etc.).

Although only a few examples have been described in detail above, those skilled in the art will readily appreciate that many modifications are possible in the examples. Accordingly, all such modifications are intended to be included within the scope of this disclosure as defined in the following claims. In the claims, means-plus-function clauses are intended to cover the structures described herein as performing the recited function and not only structural equivalents, but also equivalent structures. Thus, although a nail and a screw may not be structural equivalents in that a nail employs a cylindrical surface to secure wooden parts together, whereas a screw employs a helical surface, in the environment of fastening wooden parts, a nail and a screw may be equivalent structures.

Claims

1. A method comprising: receiving drilling operations data with respect to time as acquired during drilling operations at a rig site;receiving contextual information associated with the drilling operations at the rig site; anddetermining emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information.

2. The method of claim 1, wherein the determining emissions comprises using one or more of a model, emissions measurements and historical data.

3. The method of claim 1, wherein the drilling operations comprise operations performed on a stand-by-stand basis and wherein the emissions of the drilling operations comprise stand-by-stand emissions.

4. The method of claim 3, comprising determining rig states based at least in part on the drilling operations data wherein the determining emissions of the drill operations is based at least in part on the rig states.

5. The method of claim 1, comprising integrating the contextual information and the drilling operations data prior to the determining the emissions of the drilling operations.

6. The method of claim 5, wherein the integrating comprises performing one or more quality control procedures using the contextual information and the drilling operations data to improve quality of one or more of the contextual information and the drilling operations data.

7. The method of claim 6, wherein the integrating generates harmonized information that improves accuracy of the determining of emissions of the drilling operations.

8. The method of claim 1, comprising controlling equipment at the rig site based at least in part on the emissions of the drilling operations.

9. The method of claim 8, wherein the controlling comprises controlling equipment to perform a mode of drilling.

10. The method of claim 9, wherein the mode of drilling is selected from a slide mode and a rotation mode.

11. The method of claim 1, wherein the determining emissions of the drilling operations comprises determining emissions of pieces of equipment at the rig site.

12. The method of claim 11, wherein the pieces of equipment comprise one or more of a top drive, a rotary table, a mud pump and a drawworks.

13. The method of claim 1, wherein the emissions comprise greenhouse gas (GHG) emissions.

14. The method of claim 1, wherein the emissions comprise at least carbon dioxide emissions.

15. The method of claim 1, comprising receiving energy source information for pieces of equipment wherein the energy source information specifies one or more energy sources for each of the pieces of equipment.

16. The method of claim 15, wherein the energy source information specifies one or more of diesel fuel, natural gas turbine, grid and renewable.

17. The method of claim 1, wherein the drilling operations data are received at a first frequency, wherein the contextual information is received at a second frequency, wherein the first frequency is more frequent than the second frequency, and wherein the emissions of the drilling operations is reported at a frequency that is less frequent than the first frequency.

18. The method of claim 1, wherein a rig state generator generates rig states at a frequency that is less frequent than a frequency of the drilling operations data and wherein the determining the emissions of the drilling operations utilizes the generated rig states.

19. A system comprising: one or more processors;memory accessible to at least one of the one or more processors;processor-executable instructions stored in the memory and executable to instruct the system to: receive drilling operations data with respect to time as acquired during drilling operations at a rig site;receive contextual information associated with the drilling operations at the rig site; anddetermine emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information.

20. One or more computer-readable storage media comprising processor-executable instructions to instruct a computing system to: receive drilling operations data with respect to time as acquired during drilling operations at a rig site;receive contextual information associated with the drilling operations at the rig site; anddetermine emissions of the drilling operations at the rig site based at least in part on the drilling operations data and the contextual information.