The present disclosure provides systems and methods useful for optimally steering a wellbore into one or multiple geological target formations when one or multiple wells have already been drilled in the vicinity. The method can be executed with a programmed computer system in fully automated, semi-automated and manual modes.
Drilling a borehole for the extraction of minerals has become an increasingly complicated operation due to the increased depth and complexity of many boreholes, including the complexity added by directional drilling. Drilling is an expensive operation and errors in drilling add to the cost and, in some cases, drilling errors may permanently lower the output of a well for years into the future. Conventional technologies and methods may not adequately address the complicated nature of drilling and may not be capable of gathering and processing various information from downhole sensors and surface control systems in a timely manner, in order to improve drilling operations and minimize drilling errors.
The determination of the well trajectory from a downhole survey may involve various calculations that depend upon reference values and measured values. However, various internal and external factors may adversely affect the downhole survey and, in turn, the determination of the well trajectory.
In some aspects, a system for drilling a well includes: a processor; a memory coupled to the processor, wherein the memory comprises instructions executable by the processor for: receiving first information related to a location of a bottom hole assembly (BHA) in a wellbore being drilled; receiving second information related to a geological formation associated with the wellbore; receiving updated information related to an updated location of the BHA in the wellbore; responsive to the first information, the second information, and the updated information, generating a probability matrix comprising a plurality of probabilities, each of the probabilities corresponding to a probability that the updated location corresponds to a location relative to a geological formation; responsive to the probability matrix, determining a most likely probability of the updated location of the BHA; responsive to the most likely probability, determining if one or more drilling parameters are to be adjusted; and sending one or more control signals to adjust the one or more drilling parameters determined to be adjusted.
In some aspects, the first information comprises measured depth, true vertical depth, or measurement while drilling information.
In some aspects, the second information comprises gamma log, resistivity log, neutron density log, or mechanical specific energy information.
In some aspects, the updated information comprises measured depth, true vertical depth, measurement while drilling information, gamma log, resistivity log, neutron density log, or mechanical specific energy information.
In some aspects, the second information comprises information from an offset well or from a portion of the wellbore that has already been drilled.
In some aspects, the instructions for generating a probability matrix comprise instructions for: assigning a probability that the updated information corresponds to each of a plurality of states.
In some aspects, the instructions further comprise instructions for: applying a Viterbi algorithm to the probability matrix to determine a likelihood of each of a plurality of states; and generating a state likelihood matrix that comprises a likelihood of each of the plurality of states; and wherein the step of determining the most likely probability of the updated location of the BHA comprises determining which of a plurality of states has a highest likelihood.
In some aspects, the updated information comprises information related to the location of the BHA and information related to a geological formation in which the BHA is located.
In some aspects, each of the plurality of states corresponds to a location of the BHA relative to the geological formation in which the BHA is located.
In some aspects, the probability matrix comprises a Bayesian state space matrix or an emission matrix.
In some aspects, the instructions for generating a state likelihood matrix further comprise instructions for applying a transition function to the probability matrix, and the state likelihood matrix comprises a plurality of transition probabilities, each corresponding to a probability that the BHA has transitioned from one state to another.
In some aspects, instructions for controlling drilling by a drilling rig in accordance with the one or more control signals.
In some aspects, a method for geosteering a well includes; obtaining first information relating to a location of a bottom hole assembly (BHA) in a wellbore; receiving second information related to a geological formation associated with the wellbore; generating a probability matrix responsive to the first information and the second information, wherein the probability matrix comprises a plurality of probabilities each of which corresponds to a probability of the BHA's location relative to a geological formation; and determining, responsive to the probability matrix, a BHA location that has a highest probability.
In some aspects, the step of generating a probability matrix comprises assigning a probability to each of a plurality of possible states, each of the plurality of possible states corresponds to a possible location of the BHA relative to the geological formation.
In some aspects, the probability matrix comprises a Bayesian state space matrix or an emission matrix.
In some aspects, generating a probability matrix further comprises assigning a probability to each of a plurality of possible states responsive to the obtained information relating to the location of the BHA and to information relating to the geological formation.
In some aspects, the method includes advancing the wellbore by a drilling rig responsive to the determining of the BHA location having the highest probability.
In some aspects, advancing the wellbore further comprises adjusting a direction of drilling or one or more drilling parameters responsive to the determined location of the BHA.
For a more complete understanding of the present invention and its features and advantages, reference is now made to the following description, taken in conjunction with the accompanying drawings, in which:
In the following description, details are set forth by way of example to facilitate discussion of the disclosed subject matter. It should be apparent to a person of ordinary skill in the field, however, that the disclosed embodiments are exemplary and not exhaustive of all possible embodiments.
Throughout this disclosure, a hyphenated form of a reference numeral refers to a specific instance of an element and the un-hyphenated form of the reference numeral refers to the element generically or collectively. Thus, as an example (not shown in the drawings), device “12-1” refers to an instance of a device class, which may be referred to collectively as devices “12” and any one of which may be referred to generically as a device “12”. In the figures and the description, like numerals are intended to represent like elements.
Drilling a well typically involves a substantial amount of human decision-making during the drilling process. For example, geologists and drilling engineers use their knowledge, experience, and the available information to make decisions on how to plan the drilling operation, how to accomplish the drilling plan, and how to handle issues that arise during drilling. However, even the best geologists and drilling engineers perform some guesswork due to the unique nature of each borehole. Furthermore, a directional human driller performing the drilling may have drilled other boreholes in the same region and so may have some similar experience. However, during drilling operations, a multitude of input information and other factors may affect a drilling decision being made by a human operator or specialist, such that the amount of information may overwhelm the cognitive ability of the human to properly consider and factor into the drilling decision. Furthermore, the quality or the error involved with the drilling decision may improve with larger amounts of input data being considered, for example, such as formation data from a large number of offset wells. For these reasons, human specialists may be unable to achieve optimal drilling decisions, particularly when such drilling decisions are made under time constraints, such as during drilling operations when continuation of drilling is dependent on the drilling decision and, thus, the entire drilling rig waits idly for the next drilling decision. Furthermore, human decision-making for drilling decisions can result in expensive mistakes because drilling errors can add significant cost to drilling operations. In some cases, drilling errors may permanently lower the output of a well, resulting in substantial long term economic losses due to the lost output of the well.
Referring now to the drawings, Referring to
In
A mud pump 152 may direct a fluid mixture 153 (e.g., a mud mixture) from a mud pit 154 into drill string 146. Mud pit 154 is shown schematically as a container, but it is noted that various receptacles, tanks, pits, or other containers may be used. Mud 153 may flow from mud pump 152 into a discharge line 156 that is coupled to a rotary hose 158 by a standpipe 160. Rotary hose 158 may then be coupled to top drive 140, which includes a passage for mud 153 to flow into borehole 106 via drill string 146 from where mud 153 may emerge at drill bit 148. Mud 153 may lubricate drill bit 148 during drilling and, due to the pressure supplied by mud pump 152, mud 153 may return via borehole 106 to surface 104.
In drilling system 100, drilling equipment (see also
Sensing, detection, measurement, evaluation, storage, alarm, and other functionality may be incorporated into a downhole tool 166 or BHA 149 or elsewhere along drill string 146 to provide downhole surveys of borehole 106. Accordingly, downhole tool 166 may be an MWD tool or a LWD tool or both, and may accordingly utilize connectivity to the surface 104, local storage, or both. In different implementations, gamma radiation sensors, magnetometers, accelerometers, and other types of sensors may be used for the downhole surveys. Although downhole tool 166 is shown in singular in drilling system 100, it is noted that multiple instances (not shown) of downhole tool 166 may be located at one or more locations along drill string 146.
In some embodiments, formation detection and evaluation functionality may be provided via a steering control system 168 on the surface 104. Steering control system 168 may be located in proximity to derrick 132 or may be included with drilling system 100. In other embodiments, steering control system 168 may be remote from the actual location of borehole 106 (see also
In operation, steering control system 168 may be accessible via a communication network (see also
In particular embodiments, at least a portion of steering control system 168 may be located in downhole tool 166 (not shown). In some embodiments, steering control system 168 may communicate with a separate controller (not shown) located in downhole tool 166. In particular steering control system 168 may receive and process measurements received from downhole surveys and may perform the calculations described herein for surface steering using the downhole surveys and other information referenced herein.
In drilling system 100, to aid in the drilling process, data is collected from borehole 106, such as from sensors in BHA 149, downhole tool 166, or both. The collected data may include the geological characteristics of formation 102 in which borehole 106 was formed, the attributes of drilling system 100, including BHA 149, and drilling information such as weight-on-bit (WOB), drilling speed, and other information pertinent to the formation of borehole 106. The drilling information may be associated with a particular depth or another identifiable marker to index collected data. For example, the collected data for borehole 106 may capture drilling information indicating that drilling of the well from 1,000 feet to 1,200 feet occurred at a first rate of penetration (ROP) through a first rock layer with a first WOB, while drilling from 1,200 feet to 1,500 feet occurred at a second ROP through a second rock layer with a second WOB (see also
The collected data may be stored in a database that is accessible via a communication network for example. In some embodiments, the database storing the collected data for borehole 106 may be located locally at drilling system 100, at a drilling hub that supports a plurality of drilling systems 100 in a region, or at a database server accessible over the communication network that provides access to the database (see also
In
Steering control system 168 may further be used as a surface steerable system, along with the database, as described above. The surface steerable system may enable an operator to plan and control drilling operations while drilling is being performed. The surface steerable system may itself also be used to perform certain drilling operations, such as controlling certain control systems that, in turn, control the actual equipment in drilling system 100 (see also
Manual control may involve direct control of the drilling rig equipment, albeit with certain safety limits to prevent unsafe or undesired actions or collisions of different equipment. To enable manual-assisted control, steering control system 168 may present various information, such as using a graphical user interface (GUI) displayed on a display device (see
To implement semi-automatic control, steering control system 168 may itself propose or indicate to the user, such as via the GUI, that a certain control operation, or a sequence of control operations, should be performed at a given time. Then, steering control system 168 may enable the user to imitate the indicated control operation or sequence of control operations, such that once manually started, the indicated control operation or sequence of control operations is automatically completed. The limits and safety features mentioned above for manual control would still apply for semi-automatic control. It is noted that steering control system 168 may execute semi-automatic control using a secondary processor, such as an embedded controller that executes under a real-time operating system (RTOS), that is under the control and command of steering control system 168. To implement automatic control, the step of manual starting the indicated control operation or sequence of operations is eliminated, and steering control system 168 may proceed with only a passive notification to the user of the actions taken.
In order to implement various control operations, steering control system 168 may perform (or may cause to be performed) various input operations, processing operations, and output operations. The input operations performed by steering control system 168 may result in measurements or other input information being made available for use in any subsequent operations, such as processing or output operations. The input operations may accordingly provide the input information, including feedback from the drilling process itself, to steering control system 168. The processing operations performed by steering control system 168 may be any processing operation associated with surface steering, as disclosed herein. The output operations performed by steering control system 168 may involve generating output information for use by external entities, or for output to a user, such as in the form of updated elements in the GUI, for example. The output information may include at least some of the input information, enabling steering control system 168 to distribute information among various entities and processors.
In particular, the operations performed by steering control system 168 may include operations such as receiving drilling data representing a drill path, receiving other drilling parameters, calculating a drilling solution for the drill path based on the received data and other available data (e.g., rig characteristics), implementing the drilling solution at the drilling rig, monitoring the drilling process to gauge whether the drilling process is within a defined margin of error of the drill path, and calculating corrections for the drilling process if the drilling process is outside of the margin of error.
Accordingly, steering control system 168 may receive input information either before drilling, during drilling, or after drilling of borehole 106. The input information may comprise measurements from one or more sensors, as well as survey information collected while drilling borehole 106. The input information may also include a well plan, a regional formation history, drilling engineer parameters, downhole tool face/inclination information, downhole tool gamma/resistivity information, economic parameters, reliability parameters, among various other parameters. Some of the input information, such as the regional formation history, may be available from a drilling hub 410, which may have respective access to a regional drilling database (DB) 412 (see
As noted, the input information may be provided to steering control system 168. After processing by steering control system 168, steering control system 168 may generate control information that may be output to drilling rig 210 (e.g., to rig controls 520 that control drilling equipment 530, see also
Referring now to
In drilling environment 200, it may be assumed that a drilling plan (also referred to as a well plan) has been formulated to drill borehole 106 extending into the ground to a true vertical depth (TVD) 266 and penetrating several subterranean strata layers. Borehole 106 is shown in
Also visible in
Current drilling operations frequently include directional drilling to reach a target, such as target area 280. The use of directional drilling has been found to generally increase an overall amount of production volume per well, but also may lead to significantly higher production rates per well, which are both economically desirable. As shown in
Referring now to
The build rate used for any given build up section may depend on various factors, such as properties of the formation (i.e., strata layers) through which borehole 106 is to be drilled, the trajectory of borehole 106, the particular pipe and drill collars/BHA components used (e.g., length, diameter, flexibility, strength, mud motor bend setting, and drill bit), the mud type and flow rate, the specified horizontal displacement, stabilization, and inclination, among other factors. An overly aggressive built rate can cause problems such as severe doglegs (e.g., sharp changes in direction in the borehole) that may make it difficult or impossible to run casing or perform other operations in borehole 106. Depending on the severity of any mistakes made during directional drilling, borehole 106 may be enlarged or drill bit 146 may be backed out of a portion of borehole 106 and re-drilled along a different path. Such mistakes may be undesirable due to the additional time and expense involved. However, if the built rate is too cautious, additional overall time may be added to the drilling process because directional drilling generally involves a lower ROP than straight drilling. Furthermore, directional drilling for a curve is more complicated than vertical drilling and the possibility of drilling errors increases with directional drilling (e.g., overshoot and undershoot that may occur while trying to keep drill bit 148 on the planned trajectory).
Two modes of drilling, referred to herein as “rotating” and “sliding,” are commonly used to form borehole 106. Rotating, also called “rotary drilling,” uses top drive 140 or rotary table 162 to rotate drill string 146. Rotating may be used when drilling occurs along a straight trajectory, such as for vertical portion 310 of borehole 106. Sliding, also called “steering” or “directional drilling” as noted above, typically uses a mud motor located downhole at BHA 149. The mud motor may have an adjustable bent housing and is not powered by rotation of the drill string. Instead, the mud motor uses hydraulic power derived from the pressurized drilling mud that circulates along borehole 106 to and from the surface 104 to directionally drill borehole 106 in buildup section 316.
Thus, sliding is used in order to control the direction of the well trajectory during directional drilling. A method to perform a slide may include the following operations. First, during vertical or straight drilling, the rotation of drill string 146 is stopped. Based on feedback from measuring equipment, such as from downhole tool 166, adjustments may be made to drill string 146, such as using top drive 140 to apply various combinations of torque, WOB, and vibration, among other adjustments. The adjustments may continue until a tool face is confirmed that indicates a direction of the bend of the mud motor is oriented to a direction of a desired deviation (i.e., build rate) of borehole 106. Once the desired orientation of the mud motor is attained, WOB to the drill bit is increased, which causes the drill bit to move in the desired direction of deviation. Once sufficient distance and angle have been built up in the curved trajectory, a transition back to rotating mode can be accomplished by rotating the drill string again. The rotation of the drill string after sliding may neutralize the directional deviation caused by the bend in the mud motor due to the continuous rotation around a centerline of borehole 106.
Referring now to
Specifically, in a region 401-1, a drilling hub 410-1 may serve as a remote processing resource for drilling rigs 210 located in region 401-1, which may vary in number and are not limited to the exemplary schematic illustration of
In
Also shown in
In
In some embodiments, the formulation of a drilling plan for drilling rig 210 may include processing and analyzing the collected data in regional drilling DB 412 to create a more effective drilling plan. Furthermore, once the drilling has begun, the collected data may be used in conjunction with current data from drilling rig 210 to improve drilling decisions. As noted, the functionality of steering control system 168 may be provided at drilling rig 210, or may be provided, at least in part, at a remote processing resource, such as drilling hub 410 or central command 414.
As noted, steering control system 168 may provide functionality as a surface steerable system for controlling drilling rig 210. Steering control system 168 may have access to regional drilling DB 412 and central drilling DB 416 to provide the surface steerable system functionality. As will be described in greater detail below, steering control system 168 may be used to plan and control drilling operations based on input information, including feedback from the drilling process itself. Steering control system 168 may be used to perform operations such as receiving drilling data representing a drill trajectory and other drilling parameters, calculating a drilling solution for the drill trajectory based on the received data and other available data (e.g., rig characteristics), implementing the drilling solution at drilling rig 210, monitoring the drilling process to gauge whether the drilling process is within a margin of error that is defined for the drill trajectory, or calculating corrections for the drilling process if the drilling process is outside of the margin of error.
Referring now to
Steering control system 168 represent an instance of a processor having an accessible memory storing instructions executable by the processor, such as an instance of controller 1000 shown in
In rig control systems 500 of
In rig control systems 500, autodriller 510 may represent an automated rotary drilling system and may be used for controlling rotary drilling. Accordingly, autodriller 510 may enable automate operation of rig controls 520 during rotary drilling, as indicated in the well plan. Bit guidance 512 may represent an automated control system to monitor and control performance and operation drilling bit 148.
In rig control systems 500, autoslide 514 may represent an automated slide drilling system and may be used for controlling slide drilling. Accordingly, autoslide 514 may enable automate operation of rig controls 520 during a slide and may return control to steering control system 168 for rotary drilling at an appropriate time, as indicated in the well plan. In particular implementations, autoslide 514 may be enabled to provide a user interface during slide drilling to specifically monitor and control the slide. For example, autoslide 514 may rely on bit guidance 512 for orienting a tool face and on autodriller 510 to set WOB or control rotation or vibration of drill string 146.
Steering control process 700 in
It is noted that in some implementations, at least certain portions of steering control process 700 may be automated or performed without user intervention, such as using rig control systems 700 (see
Referring to
As shown in
In
In
In
In user interface 850, circular chart 886 may also be color coded, with the color coding existing in a band 890 around circular chart 886 or positioned or represented in other ways. The color coding may use colors to indicate activity in a certain direction. For example, the color red may indicate the highest level of activity, while the color blue may indicate the lowest level of activity. Furthermore, the arc range in degrees of a color may indicate the amount of deviation. Accordingly, a relatively narrow (e.g., thirty degrees) arc of red with a relatively broad (e.g., three hundred degrees) arc of blue may indicate that most activity is occurring in a particular tool face orientation with little deviation. As shown in user interface 850, the color blue may extend from approximately 22-337 degrees, the color green may extend from approximately 15-22 degrees and 337-345 degrees, the color yellow may extend a few degrees around the 13 and 345 degree marks, while the color red may extend from approximately 347-10 degrees. Transition colors or shades may be used with, for example, the color orange marking the transition between red and yellow or a light blue marking the transition between blue and green. This color coding may enable user interface 850 to provide an intuitive summary of how narrow the standard deviation is and how much of the energy intensity is being expended in the proper direction. Furthermore, the center of energy may be viewed relative to the target. For example, user interface 850 may clearly show that the target is at 90 degrees but the center of energy is at 45 degrees.
In user interface 850, other indicators, such as a slide indicator 892, may indicate how much time remains until a slide occurs or how much time remains for a current slide. For example, slide indicator 892 may represent a time, a percentage (e.g., as shown, a current slide may be 56% complete), a distance completed, or a distance remaining. Slide indicator 892 may graphically display information using, for example, a colored bar 893 that increases or decreases with slide progress. In some embodiments, slide indicator 892 may be built into circular chart 886 (e.g., around the outer edge with an increasing/decreasing band), while in other embodiments slide indicator 892 may be a separate indicator such as a meter, a bar, a gauge, or another indicator type. In various implementations, slide indicator 892 may be refreshed by autoslide 514.
In user interface 850, an error indicator 894 may indicate a magnitude and a direction of error. For example, error indicator 894 may indicate that an estimated drill bit position is a certain distance from the planned trajectory, with a location of error indicator 894 around the circular chart 886 representing the heading. For example,
It is noted that user interface 850 may be arranged in many different ways. For example, colors may be used to indicate normal operation, warnings, and problems. In such cases, the numerical indicators may display numbers in one color (e.g., green) for normal operation, may use another color (e.g., yellow) for warnings, and may use yet another color (e.g., red) when a serious problem occurs. The indicators may also flash or otherwise indicate an alert. The gauge indicators may include colors (e.g., green, yellow, and red) to indicate operational conditions and may also indicate the target value (e.g., an ROP of 100 feet/hour). For example, ROP indicator 868 may have a green bar to indicate a normal level of operation (e.g., from 10-300 feet/hour), a yellow bar to indicate a warning level of operation (e.g., from 300-360 feet/hour), and a red bar to indicate a dangerous or otherwise out of parameter level of operation (e.g., from 360-390 feet/hour). ROP indicator 868 may also display a marker at 100 feet/hour to indicate the desired target ROP.
Furthermore, the use of numeric indicators, gauges, and similar visual display indicators may be varied based on factors such as the information to be conveyed and the personal preference of the viewer. Accordingly, user interface 850 may provide a customizable view of various drilling processes and information for a particular individual involved in the drilling process. For example, steering control system 168 may enable a user to customize the user interface 850 as desired, although certain features (e.g., standpipe pressure) may be locked to prevent a user from intentionally or accidentally removing important drilling information from user interface 850. Other features and attributes of user interface 850 may be set by user preference. Accordingly, the level of customization and the information shown by the user interface 850 may be controlled based on who is viewing user interface 850 and their role in the drilling process.
Referring to
In
In
In
In
In
Traditionally, deviation from the slide would be predicted by a human operator based on experience. The operator would, for example, use a long slide cycle to assess what likely was accomplished during the last slide. However, the results are generally not confirmed until the downhole survey sensor point passes the slide portion of the borehole, often resulting in a response lag defined by a distance of the sensor point from the drill bit tip (e.g., approximately 50 feet). Such a response lag may introduce inefficiencies in the slide cycles due to over/under correction of the actual trajectory relative to the planned trajectory.
In GCL 900, using slide estimator 908, each tool face update may be algorithmically merged with the average differential pressure of the period between the previous and current tool face readings, as well as the MD change during this period to predict the direction, angular deviation, and MD progress during the period. As an example, the periodic rate may be between 10 and 60 seconds per cycle depending on the tool face update rate of downhole tool 166. With a more accurate estimation of the slide effectiveness, the sliding efficiency can be improved. The output of slide estimator 908 may accordingly be periodically provided to borehole estimator 906 for accumulation of well deviation information, as well to geo modified well planner 904. Some or all of the output of the slide estimator 908 may be output to an operator, such as shown in the user interface 850 of
In
In
In
In
In
In
Other functionality may be provided by GCL 900 in additional modules or added to an existing module. For example, there is a relationship between the rotational position of the drill pipe on the surface and the orientation of the downhole tool face. Accordingly, GCL 900 may receive information corresponding to the rotational position of the drill pipe on the surface. GCL 900 may use this surface positional information to calculate current and desired tool face orientations. These calculations may then be used to define control parameters for adjusting the top drive 140 to accomplish adjustments to the downhole tool face in order to steer the trajectory of borehole 106.
For purposes of example, an object-oriented software approach may be utilized to provide a class-based structure that may be used with GCL 900 or other functionality provided by steering control system 168. In GCL 900, a drilling model class may be defined to capture and define the drilling state throughout the drilling process. The drilling model class may include information obtained without delay. The drilling model class may be based on the following components and sub-models: a drill bit model, a borehole model, a rig surface gear model, a mud pump model, a WOB/differential pressure model, a positional/rotary model, an MSE model, an active well plan, and control limits. The drilling model class may produce a control output solution and may be executed via a main processing loop that rotates through the various modules of GCL 900. The drill bit model may represent the current position and state of drill bit 148. The drill bit model may include a three dimensional (3D) position, a drill bit trajectory, BHA information, bit speed, and tool face (e.g., orientation information). The 3D position may be specified in north-south (NS), east-west (EW), and true vertical depth (TVD). The drill bit trajectory may be specified as an inclination angle and an azimuth angle. The BHA information may be a set of dimensions defining the active BHA. The borehole model may represent the current path and size of the active borehole. The borehole model may include hole depth information, an array of survey points collected along the borehole path, a gamma log, and borehole diameters. The hole depth information is for current drilling of borehole 106. The borehole diameters may represent the diameters of borehole 106 as drilled over current drilling. The rig surface gear model may represent pipe length, block height, and other models, such as the mud pump model, WOB/differential pressure model, positional/rotary model, and MSE model. The mud pump model represents mud pump equipment and includes flow rate, standpipe pressure, and differential pressure. The WOB/differential pressure model represents draw works or other WOB/differential pressure controls and parameters, including WOB. The positional/rotary model represents top drive or other positional/rotary controls and parameters including rotary RPM and spindle position. The active well plan represents the target borehole path and may include an external well plan and a modified well plan. The control limits represent defined parameters that may be set as maximums and/or minimums. For example, control limits may be set for the rotary RPM in the top drive model to limit the maximum RPMs to the defined level. The control output solution may represent the control parameters for drilling rig 210.
Each functional module of GCL 900 may have behavior encapsulated within a respective class definition. During a processing window, the individual functional modules may have an exclusive portion in time to execute and update the drilling model. For purposes of example, the processing order for the functional modules may be in the sequence of geo modified well planner 904, build rate predictor 902, slide estimator 908, borehole estimator 906, error vector calculator 910, slide planner 914, convergence planner 916, geological drift estimator 912, and tactical solution planner 918. It is noted that other sequences may be used in different implementations.
In
Referring now to
In the embodiment depicted in
Controller 1000, as depicted in
Controller 1000 is shown in
In
In various embodiments, stratigraphic information may also be used to steer a wellbore into one or multiple geological target formations, or to stay within a target formation, or even to stay within a particular location or zone within a formation. Reference information correlating geologic information to depth location from previously drilled offset wells is often helpful for this purpose.
Finding the most likely stratigraphic depth of the subject wellbore can be done with a statistical model. We can characterize the measurement uncertainties and spatial variation of a specific parameter (such as gamma ray intensity) by an empirical covariance model. The model specifies the lateral covariance and the vertical covariance between sensor measurements for the same, as well as for different well logs.
The lateral covariance across well logs can empirically be estimated by using a large sample of vertical wells in a representative area and fitting a model specifying the covariance as a function of spatial separation. Correspondingly, the lateral covariance along a single well log can empirically be estimated from horizontal wells in a representative area, again fitting a model specifying the covariance as a function of spatial separation. The vertical covariances along a vertical wellbore and across horizontal wellbores can be empirically estimated in the same way.
The empirical covariance model enables assembling a covariance matrix for a specific combination of measurements on subject and offset wells. This matrix specifies the covariances for all relevant pairs of differences between subject and offset well measurements.
The covariance model can be used to specify a misfit m(MD) between a measurement on the subject well and the measurements at the corresponding stratigraphic depth on the offset wells, using a statistical norm, such as m(MD, SVD)=dT cov−1 d, where d is the vector of differences between subject well measurement at MD and offset well measurements at the depths mapped to SVD, and cov−1 is the inverse of the covariance matrix given by the statistical model.
A stratigraphic heat map displays the misfit between the measurements of the subject wellbore and the offset wells. Different choices for the x and y coordinates may be made when displaying the misfit as a heat map. One choice is to display MD on the x-axis, while displaying SVD on the y-axis.
Geosteering can be a process of solving for the drillbit's stratigraphic location while drilling. Geosteering solutions can focus on correlating a subject well's near-bit measurements to a type-log representative of the stratigraphic column. Traditionally, this can be done by matching sections of each log with a depth and amplitude stretch applied. This can be a single-solution-at-a-time approach where only the best correlation is represented, as picked either subjectively by a human or via an algorithmic minimization of differences between measurements. Geosteering techniques can be improved by considering the full space of possible options supported by the measurements, assigning a correctness likelihood to solutions, and incorporating the path by which a solution arrived at a particular state.
A variety of techniques are available for correlating information from one or more offset wells or amalgams of one or more offset wells, and/or one or more portions of the wellbore that is being drilled, to current information obtained from a BHA and its sensors, and/or surface sensors, to determine the location of the BHA relative to one or more geological formations, such as a target zone for the wellbore. In U.S. Pat. No. 8,818,279, issued on Aug. 26, 2014 to Stokeld et al., and entitled “System and Method for Formation Detection and Evaluation,” systems and methods are disclosed for automatically correlating log information from a well being drilled to log information from an offset well. In U.S. Pat. No. 10,920,576, issued on Feb. 16, 2021 to Benson et al., and titled “System and Method for Determining BHA Position During Lateral Drilling,” systems and methods are disclosed which use dynamic depth warping to help determine the location of a BHA relative to a geological formation. In addition, U.S. Published Patent Application No. 2020/0248545, published Aug. 6, 2020, and titled “Geosteering Methods and Systems for Improved Drilling Performance,” systems and methods of geosteering are disclosed. And in U.S. Published Patent Application No. 2020/0300064, published Sep. 24, 2020, and titled “Steering a Wellbore Using Stratigraphic Misfit Heat Maps,” additional techniques using misfit heat maps to steer a wellbore are disclosed. U.S. Pat. Nos. 8,818,279 and 10,920,576, and U.S. published patent application nos. 2020/0248545 and 2020/0300064 are hereby incorporated by reference as if fully set forth herein.
It should be understood that the following disclosure of geosteering methods and systems may be implemented with one or more computer systems, which may be coupled to one or more control systems of a drilling rig and its associated equipment. It should be further understood that the geosteering methods and systems disclosed below may be implemented as part of the steering control system 168 or may be a separate computer system coupled to the steering control system 168 discussed above. Similarly, it should be noted that the methods and systems for geosteering discussed below may be coupled to one or more databases which may have information from one or more previously drilled wells (e.g., offset well information) and/or from one or more previously drilled portions of the well being drilled.
To directly illustrate the deviation between actual and supposed stratigraphic depth, another possible choice is to display MD on the x-axis, while displaying the Relative Stratigraphic Vertical Depth (RSVD=SVD−TVD) on the y-axis.
For given (MD, RSVD)i point, misfit is normalized difference between gamma measured at MDi and gamma on type log at RSVDi. This does not consider solution history, nor type log trends.
At a given (MD, RSVD)i pair, the darker or lighter value represents a normalized probability that γRSVD
This can be roughly analogous to the probability of measuring γi±ε in the vicinity of MDi if RSVDi were the correct depth. This can account for not only point measurements but surrounding distributions. At a given (MD, RSVD)i pair, a the darker or lighter value can represent a normalized probability of measuring γi±ε in the vicinity of MDi if RSVDi were the correct depth. This can account not only for point measurements but surrounding distributions. The Probability Matrix contains probabilities that an observation (a given set of measurements at a given time obtained during drilling, or during a time period during drilling, such as from a beginning of a slide drilling operation to the completion of the slide) would be observed given a candidate state.
This can be accomplished by application of a transition function, where staying the course is most likely and the transition function is tuned to geologic reality.
The Transition Function can describes the probability of transitioning from one state to another. The Viterbi algorithm is a dynamic programming algorithm for obtaining the maximum a posteriori probability estimate of the most likely sequence of hidden states—called the Viterbi path—that results in a sequence of observed events, especially in the context of Markov information sources and hidden Markov models (HMM). The Viterbi algorithm can takes two elements and produces two more matrices describing the likelihood of being in a given state at a given time, (e.g., a State Likelihood Matrix) and the most likely state sequence leading up to it (e.g., a Path Matrix).
This can provide a clear path, taking into account both measurement corroboration and state transition likelihood.
If all possible mappings are considered, it becomes possible to assign a probability to any individual mapping. This would be a prohibitively large space to explore via traditional optimization/inversion but doing so is possible through application of the Viterbi algorithm to a Bayesian state space matrix, as described next. For each subject well measurement (or transformed subset), the possible depths in the stratigraphic column are represented as states. The probability matrix associating subject well measurements with stratigraphic depths is then constructed elementwise in the following manner.
Consider the subject well measurement at depth x (e.g., the location of the BHA in the wellbore), then assign a probability that this measurement would be observed if the wellbore were in state y (the stratigraphic/type log depth related to state y). The assignment of probabilities of each state y for a given location of the BHA can be generated by a computer system through an iterative process. The computer system may comprise or be coupled to the control steering system 168 if desired. The assignment of probabilities of the plurality of state y conditions by the computer system can apply an algorithm that calculates the probabilities based on historical information from offset wells and/or from current drilling information.
For example, historical information may include geological information regarding the likely vertical depth of one or more formations, their likely bed dip angle, and/or the likelihood and severity of potential faults from one or more offset wells or from other information. If drilling occurs at a rate of penetration of ten feet/hour, for example, and the drilling period of interest is thirty minutes, the likelihood of drilling seven feet during that time period and into a different formation, as opposed to the likelihood of drilling six feet within the same formation, can be assigned different probabilities based on the information available from the database and/or the sensor information obtained during the relevant drilling period.
After considering all available wellbore measurements, a Bayesian state space matrix, or emission matrix, has been produced, and the Viterbi algorithm can be applied. To do this, a transition function can be applied to this probability matrix, which describes the probability of transitioning from one state to another, and is related to real geologic possibility, such as based upon the information from one or more offset wells and/or previously drilled portions of the wellbore. This approach thus produces a state likelihood matrix, which contains comprehensive information about the likelihood of all possible states. It includes the probability that a measurement comes from a specific state and the probability that the system could have transitioned to that state for a substantial number of possible states.
Also recorded is a paths matrix, which for each point records the index of the previous state that most likely led to that state. Finally, the highest-probability endpoint may be identified from the state likelihood matrix and the matrix may be followed backward using indices from the paths matrix to produce a full solution. This highest probability endpoint and the corresponding path may be used as a starting point for a next iteration of determining the location of the borehole, such as by providing a quicker estimate of the borehole's location, especially for situations in which a subsequent drilling period essentially follows the same drilling parameters as a preceding drilling period (e.g., the second ten minutes of a slide drilling operation that is intended to last for thirty minutes following the same toolface orientation and drilling laterally through the same geological formation).
The Bayesian solutions can compare very competitively with those produced by a residual minimizing inversion/optimization but are believed to be capable of running over 50 times faster and produces solutions that are closer to the known true solution averaged over one thousand synthetic test cases. Thus, it is believed that the methods and systems provided herein can provide essentially real-time information regarding the location of a BHA within a wellbore and its location within a geological formation. This real-time information can be used by an operator to adjust drilling as necessary or can be used by a computer system (such as steering control system 168) to generate and send one or more control signals to adjust or modify one or more drilling parameters as necessary to adjust drilling as needed to maintain a desired drilling path.
Viterbi is an established algorithm with applications in many fields, but the splitting of stratigraphic mappings into a Bayesian state space and application of Viterbi is believed to be novel. This allows for probabilistic solution-finding, which allows for the whole space of possible solutions to be considered at once, and implicitly gives solution likelihoods, both of which are believed to be novel. The technique also takes into account the likelihood of the path history through stratigraphy that a solution has taken. Previous techniques have traditionally been performed either by human art or algorithmic penalization. It is believed that the systems and methods disclosed herein are much more direct and more resilient to poor algorithmic tuning or human training.
At block 1410, process 1400 may include obtaining information relating to a location of a bottom hole assembly (BHA) in a wellbore. For example, the computing device may obtain information relating to a location of a bottom hole assembly (BHA) in a wellbore, as described above.
At block 1420, process 1400 may include receiving second information related to a geological formation associated with the wellbore. For example, the computing device may receive second information related to a geological formation associated with the wellbore, as described above. In various embodiments, the second information can be stored in a memory (e.g., a server). The second information can be obtained from one or more previous drilling operations in the formation. The second information can be historical geological formation information associated with the wellbore.
At block 1430, process 1400 may include generating a probability matrix responsive to the information. The probability matrix can include a plurality of probabilities each of which corresponds to a probability of the BHA's location relative to a geological formation. For example, the computing device may generate a probability matrix responsive to the second information.
At block 1440, responsive to the probability matrix, process 1400 may include determining, a BHA location that has a highest probability. For example, responsive to the probability matrix, the computing device may determine, a BHA location that has a highest probability, as described above.
Process 1400 may include additional implementations, such as any single implementation or any combination of implementations described below and/or in connection with one or more other processes described elsewhere herein.
In a first implementation, the step of generating a probability matrix comprises assigning a probability to each of a plurality of possible states, wherein each of the plurality of possible states corresponds to a possible location of the BHA relative to the geological formation.
In a second implementation, the probability matrix comprises a Bayesian state space matrix or an emission matrix.
In a third implementation, generating a probability matrix further comprises assigning a probability to each of a plurality of possible states responsive to the obtained information relating to the location of the BHA and to information relating to the geological formation.
In a fourth implementation, process 1400 includes advancing the wellbore by a drilling rig responsive to the determining of the BHA location having the highest probability.
In a fifth implementation, advancing the wellbore further comprises adjusting a direction of drilling or one or more drilling parameters responsive to the determined location of the BHA.
Although
The above disclosed subject matter is to be considered illustrative, and not restrictive, and the appended claims are intended to cover all such modifications, enhancements, and other embodiments which fall within the true spirit and scope of the present disclosure. Thus, to the maximum extent allowed by law, the scope of the present disclosure is to be determined by the broadest permissible interpretation of the following claims and their equivalents and shall not be restricted or limited by the foregoing detailed description.
This application claims the benefit of U.S. Provisional Patent Application No. 63/267,352, entitled “System and Method for Bayesian Geosteering,” filed Jan. 31, 2022, hereby incorporated by reference in its entirety and for all purposes. This application is related to U.S. Pat. App. No. 16, 821,397, entitled “Steering a Wellbore Using Stratigraphic Misfit Heat Maps,” filed Mar. 17, 2020, that claims the benefit of priority of U.S. Patent Application No. 62/820,191, filed Mar. 18, 2019, and entitled “Optimal Steering of a Wellbore Using Stratigraphic Misfit Heatmaps,” U.S. Patent Application No. 62/834,154, filed on Apr. 15, 2019, and entitled “Integrating Reference Data for Steering of a Wellbore Using Stratigraphic Misfit Heat Maps,” U.S. Patent Application No. 62/985,224, filed on Mar. 4, 2020, and entitled “Optimal Steering of a Wellbore Using Stratigraphic Misfit Heatmaps,” and U.S. Patent Application No. 62/844,488, filed on May 7, 2019, and entitled “Determining the Likelihood and Uncertainty of the Wellbore Being at a Particular Stratigraphic Vertical Depth,” each of which is hereby incorporated by reference herein.
Number | Date | Country | |
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63267352 | Jan 2022 | US |