Patent Grant
11255142
The present disclosure relates in general to systems and methods for detecting discrete steps performed during connection make-up and break-out processes used for assembly or disassembly of tubular strings (such as drill strings and casing strings for oil and gas wells), for purposes of identifying process inefficiencies, particularly but not exclusively in association with well operations using “top drive” drilling rigs.
Operations related to the construction, maintenance, and abandonment of wells commonly involve the use of drilling rigs to manipulate tubular “strings” made up of tubular segments connected end-to-end by threaded connections. As used in this disclosure, the term “tubular” may be understood to mean any type of pipe, including pipe commonly known as casing, liner, tubing, drill pipe, or drill collars. Non-limiting examples of well operations involving strings of segmented tubulars include drilling operations, during which a borehole is formed by means of a rotating drill bit attached to a drill string, and casing running operations, during which a casing string is run into an existing borehole (for example, to provide the borehole with structural stability or to control the flow of fluids).
An individual tubular segment is referred to as a “joint”. Once assembled in a well, a length of tubular segments is referred to as a “string”. Sometimes, tubulars are pre-assembled into two-joint or three-joint units known as “stands” prior to a well operation to facilitate pipe handling. In this disclosure, the term “tubular element” is used to refer to either a single joint or a stand made up of multiple joints.
As used herein, the term “drilling rig” (or simply “rig”) denotes apparatus incorporating equipment for hoisting, lowering, and rotating tubular elements and tubular strings, with said equipment including a “travelling block” (or simply “block”), which will be readily understood by persons skilled in the art. As used herein, the term “block height” refers to the height of the travelling block relative to a selected reference datum. The term “drilling rig” is to be understood as set out above notwithstanding that it might be used in the context of a well operation that does not involve actual drilling.
The process of connecting or disconnecting tubulars and associated pipe-handling activities (collectively referred to herein as the “connection process”) can account for a significant portion of the time involved in a well operation. Considerable time savings can be realized by identifying and eliminating so-called “invisible lost time” in the connection process. As used in this disclosure, the term “invisible lost time” (or “ILT”) refers to the difference between the time that was actually required to perform an operation and a preselected target or benchmark time for performing that operation. ILT can have numerous sources, including inadequate training of drilling rig personnel, issues with rig equipment, and environmental factors outside of human control (e.g., inclement weather). If ILT can be detected and its sources determined, then steps can be taken to address the underlying causes of the ILT and thereby to improve the efficiency of the well operation.
Detecting ILT in the connection process has historically required that rig personnel measure the duration of the connection process and its steps using manual means, such as a stopwatch. This has required that an additional person be deployed to the rig to conduct the measurements, often at significant cost, or that additional responsibility be assigned to existing rig personnel. Identifying ILT by manual means has not typically been feasible at larger scales (e.g., across numerous rigs).
To assist with the identification of ILT, a number of companies have developed automated rig state detection systems. These systems analyze data collected by sensors on a drilling rig and attempt to classify the rig state (e.g., drilling, reaming, or tripping) at each point in time. The amount of time spent in each rig state can then be calculated, allowing inefficiencies to be identified.
The way in which time associated with the connection process is reported can vary between systems; however, one commonly-used metric is the “slip-to-slip connection time”. The “slips” are a component that is mounted in the rig floor and which can be selectively actuated or engaged to grip a tubular string passing therethrough, to support the weight of the tubular string (which would otherwise be supported by the hoisting system) during the connection process. The “slip-to-slip connection time” is the elapsed time between the engagement of the slips (which marks the start of the connection process) and the subsequent disengagement of the slips (which marks the end of the connection process). While the metric of slip-to-slip connection time is useful for overall optimization, it does not break down the connection process into smaller steps, and therefore is of minimal if any usefulness for purposes of pinpointing sources of ILT in the connection process.
Modern drilling rigs are commonly equipped with data acquisition systems known as electronic data recorders (“EDRs”). A typical EDR includes various sensors for measuring such parameters as the block height, the rotation rate of the top drive, and the torque applied by the top drive. However, EDR systems do not typically include a sensor for diagnosing or determining the slips state (i.e., whether the slips are engaged or disengaged). Therefore, to calculate slip-to-slip connection times, it is typically necessary to infer the slips state from one or more of the available sensor measurements.
One common method for determining the slips state is to compare the load on the hoisting system of the drilling rig (commonly referred to as the “hook load”) to a specified value. If the measured hook load is close to the specified value, then it is assumed that the weight of the tubular string is supported by the slips (i.e., the slips are engaged). If the measured hook load is not close to the specified value, then it is assumed that the slips are disengaged and that the hoisting system is bearing the weight of the tubular string. The specified hook load value is typically equal to the block weight (i.e., the weight of the rig components supported by the hoisting system, such as the travelling block and the top drive) plus a tolerance to account for such things as the weight of a tubular element, friction in the hoisting system, and measurement error.
There are conditions under which this method does not accurately determine the slips state, leading to error in corresponding slip-to-slip connection times. For example, during well operations at shallow depths, the weight of the tubular string can be insufficient to reliably determine whether the hoisting system is supporting the tubular string based solely on the hook load. The same problem can occur during well operations involving light tubulars (e.g., small-diameter and/or thin-wall tubing). Furthermore, it can be challenging to estimate the slips state during operations in deviated or horizontal wells. Frictional drag on the tubular string in such wells can require the driller to reduce the hook load significantly in order to advance the tubular string into the well, such that the hook loads measured with the slips engaged and with the slips disengaged are similar, thus complicating accurate determination of the slips state.
Recently, there have been efforts to identify ILT in the connection process using video cameras in combination with machine learning methods, an example of which is the approach described in “Application of Real-time Video Streaming and Analytics to Breakdown Rig Connection Process” (paper presented by Hegde, C., Awan, O., and Wiemers, T. at the Offshore Technology Conference in Houston, Tex., Apr. 30 to May 3, 2018). In this approach, one or more video cameras are positioned on the rig floor to record the actions of the crew. The video data is transmitted to image recognition software that attempts to classify the operation being performed by the crew at any given time.
This approach to identifying ILT has several significant challenges and limitations. First, the image recognition software must be “trained” to recognize the actions of the crew. This is accomplished by means of a training dataset, which consists of numerous images that have been manually classified by humans. The size of dataset required to train the image recognition software is large (e.g., 10,000 images or more), and the process of manually classifying images to create the training dataset is labour-intensive. In addition, the general applicability of this type of system is uncertain. For example, image recognition software that has been trained using a training dataset from one drilling rig might not be effective for classifying video data from a different drilling rig.
The present disclosure teaches embodiments of systems and methods for detecting one or more steps in the connection process in a well operation involving a tubular string. In this disclosure, references to “detecting” a step in the connection process are to be understood as meaning determining the start time and end time of the step. The systems and methods disclosed herein provide a means of tracking the time required to perform a given step in the connection process over the course of a well operation. By enabling a time duration to be attributed to a specific step in the connection process, the disclosed systems and methods make it easier to identify and eliminate sources of ILT relative to conventional systems that estimate only the slip-to-slip connection time.
In basic embodiments, a system in accordance with the present disclosure comprises one or more sensors and one or more processors. The sensors are located at a wellsite. The processors may be located at the same wellsite or at one or more network-connected locations remote from the wellsite.
The sensors are configured to obtain measurements indicative of one or more of the following variables: the block height; the torque applied to the tubular element involved in the connection process; and the rotation rate of the tubular element involved in the connection process.
The processors are configured to detect one or more steps in the connection process using the measurements from the sensors. In well operations that involve connecting additional tubular elements to a tubular string, the steps detected by the processors can include the hoist step (during which the tubular element that is to be connected to the tubular string is hoisted into the derrick of the drilling rig) and the connection make-up step (during which the tubular element in the derrick is connected to the tubular string by means of a threaded connection). In well operations that involve disconnecting tubular elements from a tubular string, the steps can include the connection break-out step (during which the threaded connection joining the uppermost tubular element to the tubular string is disconnected) and the lowering step (during which the disconnected tubular element is laid down).
Systems and methods in accordance with the present disclosure reduce or eliminate the need for rig personnel to measure the duration of steps in the connection process manually, and can be readily implemented at larger scales (e.g., across numerous rigs). Embodiments of the disclosed systems and methods do not necessarily require sensors additional to those typically included as standard equipment in EDR systems. Additionally, embodiments of the disclosed systems and methods can perform well over a range of applications with minimal human intervention and without need for a training dataset.
In one aspect, the present disclosure teaches embodiments of a method for detecting the occurrence of connection make-up or connection break-out in a well operation involving manipulation of tubular elements by a drilling rig, where the method comprises the steps of:
The error function may be defined such that a lower error function value indicates a higher degree of correspondence between the first one of the one or more selected time intervals and either connection make-up or connection break-out, and the first one of the one or more selected time intervals may be designated as corresponding either to connection make-up or to connection break-out if the value of the error function in respect of the selected time interval is less than or equal to a specified maximum value. The method may comprise the further step of obtaining time-series measurements indicative of a block height and/or indicative of the rotation rate of the one or more tubular elements; and the one or more time intervals may be selected to span sequential combinations of rotation events. Calculation of the error function value may use one or more inputs selected from the group consisting of:
The method may also include the step of isolating the time-series measurements corresponding to a specific tubular element before selecting the one or more time intervals, by the steps of:
The prominence value may be selected to correspond to the length of the shortest tubular element expected to be involved in the well operation.
In a variant embodiment of this method, the time-series measurements include measurements indicative of a block height, and the method comprises the further steps of:
In another aspect, the present disclosure teaches embodiments of a method for detecting transitions between tubular elements in a well operation involving manipulation of tubular elements by a drilling rig, where the method comprises the steps of:
The prominence threshold value may be selected to correspond to the length of the shortest tubular element expected to be involved in the well operation.
In a further aspect, the present disclosure teaches embodiments of a method for detecting the hoist step or the lowering step in a well operation involving manipulation of tubular elements by a drilling rig, where the method comprises the steps of:
In an additional aspect, the present disclosure teaches embodiments of a method for detecting a change in slips state in a well operation involving manipulation of tubular elements by a drilling rig, where the method comprises the steps of:
The present disclosure also teaches embodiments of systems for performing the methods outlined above.
Embodiments will now be described with reference to the accompanying Figures, in which numerical references denote like parts, and in which:
Tubular string 50 is made up of tubular joints 52 connected end-to-end by threaded couplings 54. A shoe, drill bit, or other downhole tool or device (not shown) will typically be connected to the bottom (or lower end) 56 of tubular string 50, depending on the nature and purpose of the particular well operation being conducted. As well, tubular string 50 may incorporate any of various types of “subs” or other components that are not shown in
The sensors are configured to obtain time-series measurements that can be used to directly or indirectly determine values for one or more of the following variables: the block height; the torque applied to the tubular element involved in the connection process; and the rotation rate of the tubular element involved in the connection process. As used in this specification, the term “time-series measurements” refers to measurements that are obtained periodically over time. The time-series measurements may be obtained at regular intervals (e.g., every second) or at irregular intervals (e.g., more frequently when the variable of interest is changing rapidly, and less frequently when the variable of interest is changing slowly).
In embodiments involving measurement of the block height, the sensors can include a sensor for counting revolutions of the drawworks of the drilling rig. The number of revolutions made by the drawworks can be related to the length of drilling line that has been unspooled and, in turn, to the block height. In embodiments involving measurement of the torque applied to the tubular element involved in the connection process, the sensors can include a top drive torque sensor. In embodiments involving measurement of the rotation rate of the tubular element involved in the connection process, the sensors can include a top drive rotation rate sensor. Alternatively, the sensors can include a sensor for measuring an angular position of the tubular element involved in the connection process, from which the rotation rate can be calculated. The variables of interest (block height, torque, and/or rotation rate) can alternatively be obtained using forms of sensors other than the non-limiting examples provided.
Other types of sensors that can optionally be used to enhance the performance of a system, but which are not required for performance of basic system functionalities, include (but are not limited to):
Embodiments of systems in accordance with the present disclosure can additionally include one or more devices for user input (“user input devices”) and one or more displays for configuring the system and showing the results of the calculations to the user of the system (“displays”). Individual processors, user input devices, and displays may be situated in different locations, separate from each other and separate from the sensors. An example of this may be seen in
A system in accordance with the present disclosure may be part of a network with intermediate systems between sensors, processors, user input devices, and/or displays. Measurements, results, inputs, and other data may be transmitted between sensors, processors, input devices, and displays using any data transmission or networking protocol and any wired or wireless connection. Examples include but are not limited to serial cables, radio transmissions, ethernet cables, internet protocols, and satellite or cellular networks.
In one embodiment of a system in accordance with the present disclosure, processors, displays, and user input devices form part of a computer system that is located at the wellsite. Additional components of the computer system can include but are not limited to:
In one embodiment, a dedicated physical cable, such as a serial cable, can be used to connect the computer system to a data acquisition system, which in turn is connected to the sensors. The connection between the computer system and the data acquisition system can alternatively be made using a dedicated wireless connection or a general-purpose connection, such as wired or wireless ethernet. The computer system can alternatively be connected directly to the sensors.
Steps in the Connection Process
In accordance with the systems and methods of the present disclosure, the connection process when connecting additional tubular elements to a tubular string can be broken down into two main steps:
In addition to the two main steps described above, there are additional steps when connecting tubular elements to a tubular string that contribute to the total time required for the connection process. In accordance with systems and methods disclosed herein, these additional steps can be broken down as follows:
In accordance with systems and methods disclosed herein, the connection process when disconnecting tubular elements from a tubular string can similarly be broken down into two main steps:
The connection process when disconnecting tubular elements from a tubular string can be further broken down into the following additional steps:
As described previously, the hoist step of the connection process is characterized by upward motion of the travelling block prior to connection make-up. It is challenging to automate detection of the hoist step for several reasons:
To overcome these challenges, in embodiments of systems in accordance with the present disclosure, the processors may be configured to detect the hoist step of the connection process using the following method steps:
In this disclosure, to “step through” a data sample means to give consideration to individual data points contained in the data sample in a consecutive or sequential manner, advancing from one data point to the next. To “step forward” through a data sample means to step through the data sample in the positive time direction; to “step backwards” through a data sample means to step through the data sample in the negative time direction.
Testing has indicated that a value of approximately 3 metres (10 feet) is suitable for the specified tolerances with respect to hoist step detection, but the optimal value of the specified tolerances can vary depending on rig equipment and operating procedures. The values of the specified tolerances from the minimum and maximum block heights may differ.
In cases where there is significant noise in the block height measurement, the performance of the present method may be improved by pre-processing the time-series block height data to reduce or eliminate the noise. Alternative embodiments of methods in accordance with the present disclosure include an initial step wherein the time-series block height data is pre-processed using a noise-reduction filter.
Lowering Detection
As described previously, when disconnecting tubular elements from a tubular string, the connection process includes a lowering step that is characterized by downward (rather than upward) motion of the travelling block. In embodiments of systems in accordance with the present disclosure, the processors may be configured to perform a generalized method that is suitable for detecting either the hoist step or lowering step, depending on whether tubular elements are being connected to or disconnected from a tubular string. This generalized method includes the following steps:
To make up the connection between a tubular element suspended in the derrick and a tubular string suspended in the slips, the tubular element is rotated relative to the string. This rotation can be achieved by means of power tongs, an iron roughneck, a top drive, or other equipment.
In embodiments of systems in accordance with the present disclosure, the processors may be configured to detect the connection make-up step of the connection process using time-series measurements indicative of the rotation rate of the tubular element involved in the connection process and/or the torque applied to the tubular element. The functionality of the method does not depend on the specific equipment used for connection make-up, provided that rotation rate data and/or torque data are available. This method includes the following steps:
One possible definition for the error function is as follows:
The preceding exemplary error function formula involves comparing the measured value mi of one or more parameters to an expected value ei. The larger the difference between the measured and expected values, the larger the associated contribution to the error function value. To enable the error function to include parameters with dissimilar magnitudes and units, the difference between the measured and expected values is normalized with respect to a basis value bi. In this context, to “normalize” a value means to express the value as a ratio relative to a basis value with like units. The magnitude of the basis value is selected such that the ratio falls within a desired range (typically, but not necessarily, from zero to one). In the computation of the error function value E, the contribution of each parameter i is weighted according to the corresponding weighting wi. The higher the weighting for a given parameter, the greater the influence of that parameter on the error function value.
In some embodiments of the method, the error function may have the form set out in the formula above, and the measured parameters of the error function may include one or more of the parameters listed in Table 1 below.
In Table 1, the “peak torque” is defined as the maximum torque applied to the tubular element involved in the connection process during a selected time interval. The “elapsed time until peak torque” is defined as the elapsed time between the start of the selected time interval and the occurrence of the peak torque. “Interruptions” are defined as intervals in time over which the rotation rate of the tubular element or the torque applied to the tubular element was less than or equal to a specified threshold value.
In alternative method embodiments, the error function may be defined as follows:
where the variables are as defined previously. In these embodiments, an error function value closer to one (1) indicates a higher degree of correspondence between a selected time interval and the connection make-up step, and time intervals having error function values sufficiently close to one (1) are designated as corresponding to the connection make-up step.
In embodiments of the method involving an error function with two or more measured parameters, the optimal value for the weighting of each parameter will depend on the specific parameters selected and the nature of the well operation being analyzed. In one embodiment, the basis values used for normalization are selected such that, under normal conditions, the method provides good performance with equal weighting of the measured parameters. If exceptional conditions are encountered under which the performance of the method is inadequate, the method can be “tuned” to improve performance by adjusting one or more of the weightings.
Various methods can be used to select the time intervals for which the error function is to be evaluated. One method involves considering numerous overlapping time intervals of equal length, with each time interval being offset from the previous time interval by a specified time offset. With large datasets, however, this method is computationally intensive. Therefore, in embodiments of systems in accordance with the present disclosure, one or more sensors may be used to obtain measurements indicative of the rotation rate of the tubular element involved in the connection process, and the processors may be configured to select the time intervals using the following method:
In cases involving large quantities of data, the computational efficiency of the present methods can be improved by isolating a sample of time-series rotation rate data and/or time-series torque data corresponding to an individual tubular element prior to detecting the connection make-up step for that element. If the hoist step has been detected, the start of the sample can be selected to coincide with the end of the hoist step; otherwise, the start of the sample can be selected to coincide with the engagement of the slips. The end of the sample can be selected to coincide with the disengagement of the slips. Alternative methods for isolating the data sample may be used for purposes of methods disclosed herein without departing from the scope of the present disclosure.
The methods described herein do not require the connection process to include only a single connection make-up step; multiple connection make-up steps may be detected. This is the expected outcome when a connection make-up is rejected by rig personnel, requiring the connection to be broken out and made up again.
When it is not feasible or desirable to isolate a data sample corresponding to an individual tubular element, or when analyzing data from a well operation in real time, methods disclosed herein can be used to search for connection make-up steps in time-series measurements.
In one method embodiment employing a “moving window” approach, rotation events in the data are first identified. Beginning at a first rotation event, a data sample is defined that has a specified duration (e.g., five minutes) and terminates at the end of the first rotation event. All sequential combinations of rotation events within the data sample are evaluated using an error function as described previously to identify rotation event combinations likely to correspond to the connection make-up step. Then, stepping forward to a second rotation event, the data sample is redefined to terminate at the end of the second rotation event while maintaining the same specified duration. All sequential combinations of rotation events within the data sample are once again evaluated using an error function. The method repeats, stepping forward through the data from one rotation event to the next, and redefining the data sample at each step.
In disclosed method embodiments, rotation rate data may be used in combination with a specified threshold value to define rotation events. In alternative embodiments, torque data may be used in combination with an alternative threshold value to define “torque events”, and sequential combinations of torque events may be evaluated using an error function to identify torque event combinations likely to correspond to the connection make-up step.
Embodiments of methods in accordance with the present disclosure may include an initial step wherein the time-series rotation rate and/or torque data are pre-processed using a noise-reduction filter to improve performance in cases where there is noise in the rotation rate measurement and/or torque measurement.
Method embodiments may use a “deadband” approach to identify rotation events or torque events. With this approach, the start of a rotation event (torque event) is defined based on the rotation rate (or the applied torque if identifying torque events) exceeding a first threshold value, and the end of a rotation event (or torque event, as the case may be) is defined based on the rotation rate (or torque) decreasing to a second, lower threshold value, with the difference between the two threshold values being termed the “deadband”.
Connection Break-Out Detection
In embodiments of systems in accordance with the present disclosure, the processors may be configured to detect the connection break-out step using a method similar to that described previously for detecting the connection make-up step, but with a modified error function.
One embodiment uses an error function selected from the forms shown previously with parameters similar to those listed in Table 1; for connection break-out step detection, however, the expected value for the “elapsed time until peak torque” is zero. The rationale for this modification is that the peak torque is typically expected to occur at or near the start of connection break-out (rather than at or near the end of connection make-up).
In embodiments involving the use of sensors that provide measurements indicative of the direction of rotation of the tubular element involved in the connection process (not just the rate of rotation), connection make-up and connection break-out can be differentiated by the rotation direction. One such embodiment uses an error function selected from the forms shown shown previously with parameters similar to those listed in Table 1. However, the “number of rotations made by the tubular element in the derrick” can be a positive or negative value, with positive values representing clockwise rotation of the tubular element (when viewed from above), and with negative values representing counter-clockwise rotation. As the majority of tubular connections use right-handed threads, the expected value is typically positive if detecting connection make-up, and typically negative if detecting connection break-out.
Systems and methods for detecting connection break-out find utility not only when a tubular string is being pulled out of a well, but also when a tubular string is being run into a well. When a tubular string is being run into a well, it is common for a connection make-up to be rejected by rig personnel (e.g., for exhibiting unusual torque-turn characteristics), requiring the connection to be broken out. Embodiments of systems and methods in accordance with the present disclosure can enable the number of connection break-outs during a tubular running operation to be readily determined or inferred with a high degree of reliability. An unusually high number of connection break-outs can indicate equipment or training issues.
Determining Type of Well Operation
In some embodiments of systems in accordance with the present disclosure, the user of the system can specify whether the tubular string is being run into the well or pulled out of the well, and the system can detect steps in the connection process accordingly (e.g., the system can detect the hoist step if the tubular string is being run into the well, or can detect the lowering step if the tubular string is being pulled out of the well).
In alternative embodiments, the type of well operation being performed can be determined automatically. One such embodiment uses the methods described previously for detecting connection make-up or connection break-out to determine whether the tubular string is being run into the well or pulled out of the well. The detection of consecutive connection make-ups, without intervening connection break-outs, indicates that the tubular string is being run into the well. The detection of consecutive connection break-outs, without intervening connection make-ups, indicates that the tubular string is being pulled out of the well.
If the slips state can be estimated reliably (e.g., using conventional hook-load-based methods), then the type of well operation being performed can be determined or inferred using block height measurements. If the motion of the travelling block is predominantly downwards while the slips are disengaged, then the tubular string is being run into the well. If the motion of the travelling block is predominantly upwards while the slips are disengaged, then the tubular string is being pulled out of the well. Many EDR systems use slips state estimates in combination with block height measurements to estimate the depth of the tubular string in the well. If such a depth estimate is available, then the direction of the change in the depth estimate (i.e., increasing or decreasing) can be used to determine the type of well operation being performed.
Duration of Steps in Connection Process
When connecting additional tubular elements to a tubular string, the duration of each step in the connection make-up process can be calculated once the hoist and connection make-up steps have been detected, as follows:
When disconnecting tubular elements from a tubular string, the duration of each step in the connection break-out process can be calculated as follows:
In embodiments of systems in accordance with the present disclosure, when one or more time intervals cannot be associated with a known step in the connection process, the time intervals may be labelled as “unknown” (or similar) to alert the user of the system to potential anomalies.
Tubular Element Detection
As discussed previously, drilling rigs do not typically have a sensor for detecting the slips state. The slips state is commonly estimated by comparing the measured hook load to a specified value, but this method is prone to error, particularly during operations at shallow depths, operations involving light tubulars, and operations in deviated or horizontal wells. Error in the estimated slips state can make it challenging to isolate samples of time-series data corresponding to the connection process, and can lead to error when estimating the duration of the different connection steps.
To overcome these challenges, in embodiments of systems in accordance with the present disclosure, the processors may be configured to perform an alternative method to isolate a sample of time-series data corresponding to the connection process for a given tubular element. These method embodiments take advantage of the periodic motion of the travelling block typical of well operations involving tubular strings, and use a peak-finding algorithm in combination with time-series block height data. Given the time-series block height data corresponding to a well operation, the method steps involved include the following:
Various peak-finding algorithms are available. One basic approach for finding peaks in time-series data involves stepping through the data and comparing each value to its neighbouring values (i.e., the values immediately before and immediately after the given value). If a given value is greater than its neighbouring values, then the given value corresponds to a peak. In this approach, plateaus in the data (i.e., two or more consecutive values that are equal) can be treated as a single data point, such that a plateau is identified as a peak if it is preceded and followed by smaller values.
The “prominence” of a peak, as used in this disclosure, is a measure of the peak's height relative to a selected benchmark value associated with its surroundings. Given negated block height data expressed as a curve on a plot of negated block height against time, one exemplary method for defining the prominence of a peak is as follows:
In cases where the data from a well operation is being analyzed in real time, methods for defining the prominence of a peak that consider only past data may be employed.
In essence, this method embodiment involves searching for prominent minima in the time-series block height data from a well operation, and interpreting those minima as transitions between tubular elements. It is effective when the most prominent minima in the block height time-series data coincide approximately with the engagement of the slips, which is commonly the case for tubular running operations.
In the preceding description, the block height data is negated to enable the use of established peak-finding algorithms. In an alternative embodiment, however, the method involves searching for minima in the original (i.e., non-negated) block height data.
In a further alternative embodiment, a peak-finding algorithm is used in combination with the original (non-negated) block height data to locate maxima in the original block height data. However, testing has shown that the resulting maxima may not coincide consistently with a particular step in the connection process.
The performance of the method embodiments described above depends on the selected prominence threshold value. A smaller prominence threshold value means that the method will be more likely to detect transitions between tubular elements, but it also means that the method will be more prone to “false positives” (indications that a transition between tubular elements occurred when, in reality, no transition occurred). A larger prominence threshold value means that the method will be less prone to false positives, but it also increases the likelihood that the method will fail to identify a transition between tubular elements. Typically, the prominence threshold value should be no greater than the length of the shortest tubular element to be run into the well. If the length range of the tubulars involved in a well operation is known, the prominence threshold value can be selected to correspond to the lower end of the length range.
To reduce the frequency of false positives, system embodiments may use the preceding method for detecting transitions between tubular elements in combination with the methods described previously for detecting connection make-up or connection break-out. The connection process for any tubular element is expected to involve at least one connection make-up step or one connection break-out step. Failure to detect any connection make-up or connection break-out steps can therefore indicate a false positive.
In the context of this disclosure, the preceding method for detecting transitions between tubular elements is useful for dividing the time-series data from a well operation into samples that can be associated with the connection process for individual tubular elements, and can be used with methods described earlier in this disclosure for detecting the hoist, lowering, connection make-up, and connection break-out steps. More generally, however, the method has utility wherever there is a desire to track individual tubular elements. For example, the method could form the basis of an automated pipe tally system.
Slips State Estimation
Frequently, the most prominent minima in the time-series block height data from a well operation will coincide approximately with the engagement of the slips. Accordingly, the particular method embodiment described in the preceding section for detecting transitions between tubular elements can be considered as a method for detecting engagement of the slips. This method is useful for estimating the slips state in scenarios where conventional hook-load-based methods fail (e.g., operations at shallow depths, operations involving light tubulars, and operations in deviated or horizontal wells).
To obtain a complete slips state estimate, disengagement of the slips must also be detected. In embodiments of systems in accordance with the present disclosure, the processors may be configured to detect disengagement of the slips using a method for detecting connection make-up, such as that described previously in this disclosure, in combination with time-series block height data. Given the time-series block height data from a well operation, the steps in this method include the following:
This method relies on the fact that significant motion of the travelling block is not possible after the tubular element in the derrick has been connected to the tubular string unless the slips are disengaged. Testing has indicated that a value of 0.1 metres (4 inches) is typically suitable for the specified tolerance used to identify the point in time at which the slips were disengaged. However, the optimal value for the specified tolerance can vary depending on rig equipment and operating procedures.
Method Combinations
Systems in accordance with the present disclosure may use embodiments of methods described herein either individually or in combination.
Extensions to Systems and Methods Described Herein
The preceding discussion has been focused on well operations typically performed by drilling rigs. However, systems and methods in accordance with the present disclosure are adaptable for use in any operation in a wellbore involving segmented pipe with threaded connections. The disclosed systems and methods can be applied to operations performed by a drilling rig, a service rig, or any other type of rig.
It will be readily appreciated by those skilled in the art that various modifications to embodiments in accordance with the present disclosure may be devised without departing from the present teachings, including modifications which may use structures or materials later conceived or developed. It is to be especially understood that the scope of the present disclosure should not be limited by or to any particular embodiments described, illustrated, and/or claimed herein, but should be given the broadest interpretation consistent with the disclosure as a whole. It is also to be understood that the substitution of a variant of a claimed element or feature, without any substantial resultant change in functionality, will not constitute a departure from the scope of the disclosure or claims.
In this patent document, any form of the word “comprise” is intended to be understood in a non-limiting sense, meaning that any element or feature following such word is included, but elements or features not specifically mentioned are not excluded. A reference to an element or feature by the indefinite article “a” does not exclude the possibility that more than one such element or feature is present, unless the context clearly requires that there be one and only one such element.
Any use of any form of any term describing an interaction between elements or features is not meant to limit the interaction to direct interaction between the elements or features in question, but may also extend to indirect interaction between the elements such as through secondary or intermediary structure.
Any use herein of any form of the term “typical” is to be interpreted in the sense of being representative of common usage or practice, and is not to be interpreted as implying essentiality or invariability.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/CA2020/000101 | 8/13/2020 | WO | 00 |
| Publishing Document | Publishing Date | Country | Kind |
|---|---|---|---|
| WO2021/026632 | 2/18/2021 | WO | A |
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| 20210262300 A1 | Aug 2021 | US |
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| 62886026 | Aug 2019 | US |
