CHARACTERIZING CRITICAL PATHS OF DRILLING OPERATIONS

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application No. 62/863,951 entitled“Systems and Methods for Identifying and Characterizing Critical Paths of Drilling Operations,” filed June 20, 2019, the entire disclosure of which is incorporated herein by reference.

FIELD OF THE DISCLOSURE

[0002] Embodiments of the current disclosure are directed toward identifying and characterizing drilling operations, and more particularly, methods and systems for identifying and characterizing critical paths during tripping operations.

BACKGROUND

[0003] During offshore oil and gas well construction, a significant amount of time is spent on drilling operations. The operations can involve a sequence of manual, semi- automated, and fully-automated processes performed in unison as safely and efficiently as possible. While machines used during these operations may each operate independently, the discrete functions performed by each machine are often highly coupled or interdependent, meaning the delay of any single machine function can negatively impact the overall operation, which may be exacerbated by multiple other factors, such as, for example, variations in wellbore conditions, operating procedures, environmental conditions, equipment designs, drill floor layouts, etc., across the offshore drilling industry. The source(s) of these operational variations and inefficiencies, which may lead to lost time during drilling operations, may not be readily apparent, complicating efforts to improve drilling operation efficiencies. As such, there is a need for methods and systems for identifying and characterizing different aspects of drilling operations, such as but not limited to tripping operations, to limit and/or reduce inefficiencies and lost time BRIEF DESCRIPTION OF THE DRAWINGS

[0004] The skilled artisan will understand that the drawings primarily are for illustrative purposes and are not intended to limit the scope of the inventive subject matter described herein. The drawings are not necessarily to scale; in some instances, various aspects of the inventive subject matter disclosed herein may be shown exaggerated or enlarged in the drawings to facilitate an understanding of different features. In the drawings, like reference characters generally refer to like features (e.g., functionally similar and/or structurally similar elements).

[0005] FIG. 1 is an example drilling floor that includes a roughneck, a derrick pipe hoisting system and slips for stabilizing pipes inserted into a wellbore in the drilling floor, according to some embodiments.

[0006] FIG. 2 shows an example flowchart illustrating a model or methodology for characterizing critical paths during a tripping operation, according to some embodiments.

[0007] FIG. 3 shows an example plot illustrating values of hookloads and block speeds used in identifying events associated with a tripping operation such as a run-in-hole (RIH) tripping event, according to some embodiments.

[0008] FIG. 4 shows an example illustration of the decomposition of a system hierarchy for a system or machine participating in a tripping operation, according to some embodiments.

[0009] FIG. 5 shows an example illustration of a state machine model that captures the actions of a torque wrench based on a signal dataset of torque wrench activities, according to some embodiments.

[0010] FIGS. 6A-B show flowcharts illustrating the aggregation of state machine and discrete event processes to generate example simulations of a tripping operation, according to some embodiments.

[0011] FIG. 7 shows an example Gantt chart illustrating the critical path of a RIH tripping operation, according to some embodiments.

[0012] FIGS. 8A-C show a series of example snapshots of a tripping operation along with a corresponding progression timeline visually displaying the activities of the machines executing the various activities of the tripping operation, according to some embodiments.

[0013] FIG. 8D shows a state machine model that includes several state classifications for the activities of the pipe racking machine or system, according to some embodiments. [0014] FIG. 8E presents a graphical display showing the relative contributions of different machine activities to quantities of time related to the entire tripping operation, according to some embodiments.

[0015] FIG. 9 shows an example simulation result of the critical path contributions of the activities of a particular machine over a cycle of tripping operation, according to some embodiments.

[0016] FIGS. 10A-B show example simulation results of the critical path contributions of the activities of two arbitrary crews on the same drilling rig, according to some embodiments.

[0017] FIGS. 11A-B show example simulation results of the critical path contributions of the activities of crews on two different drilling rigs, according to some embodiments.

DETAILED DESCRIPTION

[0018] Offshore oil and gas well construction can involve a complex set of machineries and supporting processes to safely and effectively bore a well. These machineries and processes, as well as environmental conditions can be highly variable across the oil and gas well construction industry. For example, there can be large variations in the vessel design, equipment age and functionality, operational environments, water depth, drilling total depth, subsurface conditions, dynamic well conditions, personnel, etc. Given the complexity of drilling operations and the variations that exist therein, it can become highly challenging to objectively assess or measure (e.g., compare and contrast) the performance or efficiency of drilling operations between different rigs, or even between different drilling operations on the same rig. Further, such complexity may mask the sources of the variations and inefficiencies that might be present in the drilling operations, as, for example, multiple machines can be involved in the operations and it can be difficult to identify the machines that are responsible for the inefficiencies and their level of responsibility. For example, inefficiencies can manifest themselves as time lost that may not be readily apparent to drill operators (much less their causes). Added up over days and weeks, however, this“invisible lost time” could amount to a costly reduction in the productivity of the drilling rig with little to no insight into curing such defects.

[0019] In some instances, delays in machines or personnel action within a critical path (also referred to herein as“CP”) of an operation (e.g., a tripping operation) can be a source of the inefficiencies that lead to this“invisible lost time.” The critical path of an operation refers to the order or sequence of execution of multiple tasks performed by multiple machines and/or human operators engaged in the operation with little or no slack between the tasks so that the entire operation can be completed within some time duration (e.g., a minimum duration possible), i.e., the critical path time. In other words, the critical path for an operation may be viewed as“what activity is holding up the operation from moving on to the next activity.” In some implementations, if the operation can be managed or controlled (e.g., if delays can be avoided) by, for example, defining and following rules and/or dependencies e.g., dependencies as to which processes precede which, etc., for example), the critical path and a performance measurement thereof, may look at least substantially the same from one operation to another, since the operation would follow the same or nearly the same steps. In other words, the critical path may be a static snapshot of the operation (i.e., the critical path may not be dynamic), in the sense that the critical path may not change during the operation. This, however, may not be the case in many operations on a drilling rig, such as, for example, a tripping operation, as tripping operation are often dynamic with little or no rules (or with external factors interfering) and the typical dependencies may not hold. That is, the critical path of tripping operations may change dynamically based on what is occurring or what should be occurring at that moment in time. For example, a machine that is in the critical path may be delayed in completing its task, and the critical path may become dynamic as a result (e.g., the critical path may change in that a machine that is in the critical path may leave the critical path and/or a machine that is not in the critical path may join the critical path). In such instances, the delay can contribute to an increase in the critical path time, which may serve as an indicator of operational inefficiency, so long as this contribution to the critical path time can be readily identified.

[0020] In some implementations, some delays may not contribute to an increase in the critical path time, such as delays by machines and/or human operators that are not in the critical path. These, delays, over time, however, may cause the machines to enter or join the critical path at a later time. For example, if the operation includes multiple cycles of operations (e.g., such as a rig operation that includes repeatedly running pipes into and out of wellbores), then delays that may not affect the critical path time initially (e.g., delays that may not cause the machine to join the critical path initially) may start impacting the critical path time at a later time (e.g., may cause the machine and/or human operator to join the critical path and increase the critical path time). That is, the critical path can become dynamic, in the sense that it may shift to the activity (or the machine) that may be delaying the process at that given moment in time. For example, the CP can move in and/or out of an activity dynamically and may not require an activity to complete before it is out of the CP (e.g., different from a static CP in which an activity on the critical path remains on the critical path until the task is completed). More details on dynamic critical path (DCP) for continuous processes including multiprocessor rescheduling algorithms may be found in Dynamic Critical-Path Scheduling: An Effective Technique for Allocating Task Graphs to Multiprocessors, by Yu-Kwong Kwok (1996), the disclosure of which is incorporated by reference herein in its entirety.

[0021] In some implementations, a delay by a machine in the critical path of an operation may cause machines that are slated to execute a later task to join or leave the critical path. For example, a first machine may be tasked with relocating itself to the location of a second machine, and the task may not be part of the critical path. In such cases, a delay by a third machine (e.g., a machine that is in the critical path) that delays the relocation of the first machine may cause the first machine to enter the critical path, as the second machine (and other machines engaged in the entire operation) may have to wait for the first machine to arrive before the machines start executing their own tasks. In other words, a delay by a machine in the critical path may cause another machine that is not in the critical path to join the critical path. In some implementations, a delay by a machine that is in the critical path may instead cause another machine that is in the critical path to leave the critical path. Referring to the above example, and assuming both the first machine and the third machine are both in the critical path, the delay by the third machine may give the first machine adequate time to relocate while the third machine is still executing. That is, the relocation task by the first machine may be completed without the tasks of other machines in the operation being held up by the relocation task. In other words, the delay by the third machine (in the critical path) has caused the first machine (which is in the critical path) to leave the critical path.

[0022] In some instances, an analysis of the critical path of a tripping operation may be beneficial in identifying the inefficiencies in a rig drilling operation, such as, for example, a tripping operation, as tripping operations can consume a large portion of the time allocated for rig drilling operations. Further, tripping operations (as well as other rig drilling operations) can have significant variability between instances of operations, and/or between rigs, and the sources or causes of such variability may not be readily apparent, making it challenging to apply a blanket solution across all rigs and/or instances of tripping operations in an attempt to reduce or eliminate operational inefficiencies. To identify and/or analyze the critical path of a tripping operation, in some implementations, the machine activities may be codified by defining the activities and the time frames associated therewith. For example, a tripping operation cycle may be defined as the cycle from“slips-to-slips”, that is, the cycle from removing a slip (a device used to hold a drill string in place on a drill floor) to access the drill string out of the wellbore to placing the slip back on after a pipe connection activity takes place and the drill string is put back onto the wellbore (or vice versa). A connection activity may be defined as a tripping activity in between run-in-hole (RIH) or“tripping in” activities and pull-out-of-hole (POOH) or“tripping out” activities that includes a makeup activity (e.g., a connection activity resulting in the connection of two pipes) and/or a breakout activity (e.g., a connection activity resulting in the disconnection of two pipes). RIH and POOH activities are examples of tripping operation activities, RIH referring to the running a drill string (which includes a drill bit for cutting into the earth to form a wellbore and drill pipes interconnected by tool joints) into the ground to form a wellbore and POOH referring to the pulling out of the drill string from the wellbore. In some implementations, RIH and POOH activities can be marked with their start and end events. In some implementations, after the machine activities are identified, the activity duration could be broken down and the critical path can be classified in real-time, which can then be utilized for further statistical analysis, integration with other datasets and communication with stakeholders.

[0023] For example, with reference to FIG. 1, multiple machines may be used during a tripping operation, including a derrick hoisting system 102 for lifting pipes into and/or lowering pipes out of a wellbore, a pipe racking system (not shown) for handling the movement of pipes between the wellbore and a pipe rack, a pipe connector system 104 for connecting pipes during RIH and POOH and slips 106 for stabilizing pipes inserted into a wellbore. In some implementations, the pipe connector system 104 may include a roughneck having a spinning wrench and a torque wrench that may be used to attach or disconnect pipes at the tool-joints. For example, during a tripping out process, a drill string may be pulled out of a wellbore by the derrick hoisting system 102, thereby exposing a pipe connection point at the tool joints of the pipes. In such implementations, the torque wrench of a roughneck may be used to stabilize the drill string by locking onto the drill string below the pipe connection point while the spinning wrench locks onto the drill string above the pipe connection point and disconnect the threaded connection point by rotating the pipe (e.g., breakout activity). During the tripping in process, the reverse may take place, and a pipe may be added to the drill string with the use of the roughneck. For example, the spinning wrench may lock onto the pipe that is being added, and turn to tighten the pipe onto the drill string at the tool joints (e.g., makeup activity). The drill string can then be lowered into the wellbore with the aid of the derrick hoisting system 102. In some implementations, the slips 106 can then be placed onto the mouth of the wellbore to, amongst other things, stabilize the drill string within the wellbore.

[0024] In some implementations, the machines used for a tripping operation may be independently designed and operated, and changes to the critical path time of the tripping operation can be determined by analyzing delays experienced by any of these components as each machine is executing its assigned tasks as well as delays in transitioning from one machine to another.

[0025] In some embodiments, to characterize the critical path of a tripping operation, a multi-method modeling technique may be employed to model the processes and activities of the machines involved in the tripping operation. Non-limiting examples of the modeling techniques include leveraged discrete event modeling, state machine modeling, agent based modeling, etc. In general, the multi-method modeling technique can be used to analyze complex processes, such as but not limited to drill floor activities and/or other rig operations. For example, in employing these modeling techniques, a section of a drill string (e.g., a pipe in the drill string) may be considered as an“agent” that contains different physical properties, and a machine that handles or performs some kind of work on the pipe (i.e., agent) during the tripping operation can be modeled as an“agent-resource”. In such embodiments, a machine may follow a specific logic when performing work, and the logic can be incorporated into the models as a state machine model. For example, a drill pipe passing through a tripping operation as it is being handled by a machine can be represented by an agent (i.e., the pipe) flowing through a discrete event process of the state machine model applied to the agent- resource (i.e., the machine). In such embodiments, if a machine is not available to be used when it is needed, the process cannot continue and the CP time is increased (and efficiency is decreased). In some embodiments, the efficiency of the process can be governed by some or all the interactions between the agents, the agent-resources, the process and/or the logic.

[0026] In some embodiments, the multi-method modeling technique can be extended to include system dynamics to understand the impacts of external influencing factors, such as but not limited to well bore conditions, materials consumption, power usage, crew competency, etc. Further, the multi-method modeling technique may also be utilized to simulate data, run real-time data, be applied to other applications, integrate with other rig processes, etc. Additional techniques related to multi-method modeling techniques for analyzing complex processes (such as tripping operations, for example) can include agent- based and discrete event models, physics-based models, statistical models, stochastic models, deterministic models, and/or the like.

[0027] In some implementations, as noted above, the tripping operation can be modelled by codifying machine activities that occur within the process, which may be facilitated by the fact that at least some machine functions can be stored in the form of digital signals (which may also be retrieved for a later analysis). In some implementations, the real time machine signals can be used to determine the state of the machine or equipment. The state of a machine, in some embodiments, may be a discrete single identifiable condition based on (e.g., based solely on or nearly solely on) one signal with little or no need for any further processing or transformation. For example, the state can be a memoryless function with little or no history (for instance, a Boolean logic). In some implementations, the state of a machine can be correlated with other machine states to provide inference into the higher (e.g., system) level process activity. In some implementations, an activity of a machine (e.g., higher level of machine functions) can be determined by combining or collectively analyzing one or more states and/or signals of one or more machines while using history and inference to determine the start and end conditions of the activity. For example, the state of a derrick hoisting system and the state of a pipe connection equipment may be correlated with each other to obtain at least some insight about the entire tripping activity, including, e.g., insight into the activities being performed (in some instances, including the completion status of each activity) by the machines used in the tripping activity.

[0028] FIG. 2 shows a flowchart illustrating an example implementation of the above- described modelling technique for characterizing critical paths during a tripping process. In some instances, sensors and other devices monitoring the machines participating in the tripping operation, such as but not limited to the derrick hoisting system 102, the pipe racking system (not shown), the pipe connector system 104 and the slips 106, may be used to generate signals that include data 202 about the tripping operation. In some implementations, the signals that include the data 202 (e.g., digital signals, analog signals, time stamps, pressures, positions of tools and/or machines, weights, and/or the like) may be derived from manually driven equipment with varying levels of sophistication and instrumentation. For example, the signals can be generated by sensors strategically located to monitor machine statuses (e.g., a device or component being opened or closed; a position of a machine, such as, for example, being at well center, in setback, in the derrick, or at the fingerboard; holding a pipe or not holding the pipe; making or breaking a connection, etc.)· In some implementations, the signals may have a varying degree of reliability. In some implementations, the sensors may have limited purpose or functionality. For example, some of the sensors may be limited in the sense that that they are configured to provide feedback to the drill floor control system to aid in confirming that a function or task has been completed. In such cases, the sensor measurements can be complimented by user inputs (e.g., provided into a human machine interface). Upon obtaining the signals/measurements from sensors and/or user input, in some embodiments, the signals may be processed, cleansed (e.g., filtered), resampled and/or verified (e.g., including manually) to produce useful and clean data 202 for detailed analysis, including statistical analysis.

[0029] The data 202 may include information related to tripping activities such as RIH and POOH activities and/or information related to the machines operating during the tripping process. In some implementations, at 204 and 206, the trip data signals and the machine data signals, respectively, may be processed for use in analyzing the tripping operation. For example, at 204, the data 202 may be processed to identify and isolate data signals that are related to trips (i.e., the trip data signals), and at 208, the processed trip data signals may be clustered, for example, by identifying the start and end events of the RIH and POOH activities. For instance, portions of the processed trip data signals representing activities occurring between consecutive slip opening and closing may be considered to include either an RIH or POOH activity (and clustered as such). As another example, portions of the processed trip data signals representing activities occurring between consecutive RIH and/or POOH may be considered to include a pipe connection activity (e.g., a makeup activity, a break out activity, etc.), and may be clustered as such. In such implementations, after clustering the trip data signals, the clustered signals may be further analyzed to identify the types of connection activities and/or trip activities. For example, at 210, the clustered signals may be analyzed to identify connection activities such as but not limited to makeup activities, breakout activities, etc., while at 212, the clustered signals may be analyzed to identify the trip and cycle activities such as but not limited to RIH, POOH, etc. The identifications of tripping activities, connection activities, slip-to-slip cycles are discussed in further detailed below with reference to FIG. 3

[0030] As noted above, in some implementations, the data 202 that includes or represents information about the processes or activities of the tripping operation (e.g., the trip data signals) may also include information related to the functions and state of the machines (e.g., the machine data signals). For example, the data 202 may include or represent digital signals (e.g., real-time machine data signals) that can be used to determine the state of machines. By correlating the machine data signals of different machines, in some implementations, the processes or activities of the tripping operation may also be determined. In some implementations, the correlation of the machine data signals may be facilitated by the above-discussed identification of tripping activities, connection activities, slip-to-slip cycles that is achieved based on the trip data signals. That is, the“machine level” analysis of the tripping operation may be augmented based on the results of the“tripping process or activity level” analysis of the tripping operation. For example, at 206, the machine data signals of the data 202 may be processed, with the aid of the identification of the tripping activities, connection activities, slip-to-slip cycles, etc., achieved at 212 from analyzing the trip data signals, to in turn identify the critical path of the tripping operation. For example, at 214, the multi-method modeling techniques discussed above may be developed and applied, at 216, to the processed machine data signals to analyze the tripping operation, and identify, at 218, the critical path of the tripping operation. The identification of the critical path of a tripping operation is discussed in further detailed below with reference to FIGS. 4-6.

[0031] In some implementations, at 220, the identified tripping activities and connection cycles as well as the critical path may be further analyzed (e.g., statistically) and the results may be presented visually (e.g., via animation, color coding, etc.). The visual presentation of the tripping activities as well as the critical path is discussed in further detail herein with reference to FIGS. 7 and 8. In some embodiments, at 222, data from external datasets may also be incorporated into the statistical analysis, examples of such data including information about wellbore conditions, materials consumption, power usage, crew competency, etc.

[0032] some embodiments, as noted above with reference to FIG. 2, analysis of the data 202 may facilitate the identification of tripping activities such as but not limited to RUT and POOH activities. In some implementations, to identify or classify the RIH and/or POOH activities, a derived signal may be generated by analyzing system mechanical data of the machine or equipment used in hoisting the pipes during the tripping process. For example, an algorithm may be used to analyze the hookload and/or the block speed of an equipment of a derrick hoisting system, the hookload representing the weight of the downhole assembly (e.g., including a drill string) being supported by the elevators of the hoisting system and the block speed representing the relative velocity of the hoisting system block position (e.g., the piece of equipment that secures the top of the drill pipe or tubular in place as the string is being hoisted or lowered into the well). In some embodiments, RIH and POOH events may be identified by, respectively, when the hookload has a positive block speed and a negative block speed (e.g., direction can be derived based on a positive indicating upwards and negative indicating downwards). That is, RIH events can be identified when the hookload is closely correlated with a positive block speed and the POOH events can be identified when the hookload is closely correlated with a negative block speed. FIG. 3 shows an example plot illustrating values of hookloads and block speeds used in identifying events associated with a tripping process such as a RIH event, according to some implementations. In some instances, a block speed at or close to zero can indicate that the block is not moving, and therefore a connection could take place. Likewise, in such instances, if the hookload differential is at or close to zero kg, indicating that the block is not holding pipe, it can be understood that a connection could occur. Collectively such block speed and hookload differential data can indicate that a connection is occurring. As another example, if a signal indicates that jaws of a pipe holder are open (e.g., a jaws closed signal indicates zero), but it is known the pipe racker is holding a pipe due to a load signal, it can be derived that the jaws are closed (since open jaws could not hold a pipe). Similarly with respect to slips, if pipe is being run, as indicated by a hookload above a certain threshold (e.g., 95,000 lbs), and an elevator position is changing in a downward position, it can be derived that the slips are open.

[0033] In some embodiments, identifying or classifying RIH and POOH events or activities can facilitate the identification of the pipe connection activities or events as well. For example, in some implementations, the connection events that exist between consecutive RIH events may be identified as makeup connections. Similarly, the connection activities that exist between consecutive POOH events may be identified as breakout connections. As such, by segmenting the RIH events, the POOH events and the makeup/breakout connections by direction and length of the connection, in some embodiments, individual cycles and trips of a tripping process can be identified and bookended by the relevant start and end timestamps.

[0034] In some embodiments, a classifier for RIH, POOH and connection events or activities can be implemented by employing a multilayer process that leverages both supervised and unsupervised classifiers. In some implementations, a combination of data analysis techniques including but not limited to clustering techniques and expert system regressions can be used in various combinations to arrive at a functioning model. Using discrete event analysis, in some implementations, bookends for connection events can be determined using the timestamps for the RIH and POOH events, since, as discussed above, connections exist during the time between consecutive RIH or POOH events. In some embodiments, an expert system may be used to determine these connections.

[0035] In some embodiments, the identification of a tripping in and/or a tripping out activity can be performed or completed using an expert system. For example, a tripping in activity can be identified by analyzing clusters of makeup connections and RIH events. As another example, a tripping out activity can be identified by analyzing clusters of breakout connections and POOH events. Once those activities are identified, in some implementations, trips can be bookended by the start and end times of these clusters. For example, the expert system can define the terms of the trip, such as but not limited to the minimum number of connections and/or the minimum durations of non-activity between events required for classification as a trip, etc.

[0036] As noted above with reference to FIG. 2, the data 202 may include information related to the machines operating during the tripping process (e.g., machine data signals), examples of such machines including a derrick hoisting system, a pipe racking system, a pipe connector system, and slips. In some implementations, a state machine model may be developed and used to analyze the data related to the machines (e.g., the machine data signals) to identify the critical path of the tripping operation. In some embodiments, to develop a state machine model for each function or activity of a machine (as captured by the machine data signals, for example), each machine and its processes may be decomposed into a hierarchy of states. For example, FIG. 4 shows an example illustration of the decomposition of a system hierarchy for a system participating in a tripping operation, including pipe connection equipment or machine, according to some embodiments. As noted above, in some instances, the system 402 for operating tripping operations may include four primary machines or equipment, including a pipe racking system 404, a derrick hoisting system 406, a pipe connection equipment 408 and slips 410. In some instances, each system, equipment or machine may be decomposed hierarchically into further composite functional states. For example, the pipe connection equipment 408 may be decomposed or broken into the composite states of“locate tool joint” 412,“movement” 414,“spin pipe” 416 and“torque pipe” 418, which can further be decomposed into sub-states. Further, the“torque pipe” 418 composite state can in turn be decomposed into the states of“torque wrench closed” 420 and “torque wrench open” 422. In some implementations, the other machines of the system 402 for operating a tripping operation, including but not limited to the pipe racking system 404, the derrick hoisting system 406, the slips 410, etc., can be hierarchically decomposed into model states (of a component of a machine part, for example) in similar manner as shown above with reference to the pipe connection equipment 408. The derrick hoisting system 406, for example, can be decomposed into“in lower position,”“hoisting,”“lowering,” and“in upper position.” Similarly, the pipe racking system 404, for example, can be decomposed into “moving to well center,”“at well center,”“at standby position,”“moving to FB,”“at FB position,”“stabbing in,” and“guiding pipe.” As yet another example, the slips 410 can be decomposed into“opening,”“open,”“closing,” and“closed.”

[0037] In some implementations, the hierarchical system decomposition of the machines operating a tripping operation facilitates the development of a state machine model for the functions of the machines. For example, with reference to FIG. 4, in some instances, the sequential system decomposition of the pipe connection equipment 408 to a torque pipe 418 state, and further to the torque wrench closed 420 and the torque wrench open 422 states, allows one to develop a state machine model for the functions of the torque wrench. For example, FIG. 5 shows an illustration of a state machine model that captures the functions of a torque wrench. In some implementations, the state machine model can include the torque wrench closed state 520 and the torque wrench open state 522, as well as an unknown state 524 configured to account for and/or represent signal quality issues. In some embodiments, the state machine model can executed to at least substantially mimic the actual machine being modeled based on the dataset gathered by the sensors monitoring the machine. In some implementations, the gathered dataset, however, may not actually represent the completion of a given function of the machine, but inferences can be made. For example, the gathered dataset may indicate a change in signal that signifies a function was initiated but not completed (e.g., when the signals include commands). As such, in some embodiments, additional logic may be employed to determine the activities of the machine. As an example, data may indicate that a machine, such as a roughneck, has initiated making a connection, but then further data from the roughneck drops out, e.g., such that an expected data set is missing. As such, one or more other signals can be assessed to determine / infer if the connection was made. For example, assessing signals on the block and/or pipe racker can indicate that the pipe was lowered, and so it can be inferred that the connection was made (as lowering the pipe requires connecting the pipe). In this manner, if a signal drops, activities can be verified using other related signals. [0038] In the example provided above, it was described that the pipe connection equipment 408 can be decomposed or broken into the four composite states (e.g., machine functions) of“locate tool joint” 412,“movement” 414,“spin pipe” 416 and“torque pipe” 418. In some embodiments, the machines or agent-resources (of which the pipe connection equipment 408 is an example) can be decomposed into more states or less states, and the choice of the number of states to decompose the machine into can be based on the amount of detail that would be desired or required for the resulting states to sufficiently describe the decomposed machine. For example, the pipe connection equipment 408 (e.g., a roughneck) may include more than four composite states (and may have more than four functions or may utilize more than four signals (e.g., hundreds of states and signals)). In some implementations, the decomposition into four composite states may, however, be at least sufficient to adequately describe the pipe connection equipment 408. That is, the number of composite states into which a machine or equipment is decomposed may be at least large enough to adequately describe the machine or equipment. In some implementations, the number of composite states into which to decompose a machine, and the resulting states themselves may be determined following an iterative process. In some implementations, an object oriented state machine model can be used to produce a model that at least substantially parallels the functionality of the machine (and hence facilitate the analysis of the functions of the machine by, for example, operations personnel and management).

[0039] FIGS. 6A-B show a flowchart illustrating the aggregation of state machine and discrete event processes to generate an example simulation of a tripping operation, according to an embodiment. In some implementations, the grouping of some or all of the state machines may result in an underlying logic for that particular agent-resource or machine. In some implementations, a discrete event model can be developed to define the operations of the machines. For example, the model states (example of which are the model/functional states depicted in FIG. 5) can be aggregated, e.g., at 604, to form a machine process 606 and the machine processes can further be integrated, e.g., at 608, to form the operational processes. In some implementations, the process blocks 606 may either inhibit or permit the process to continue relative to and/or based on the underlying states, and/or activities and the dependencies between them. For example, decision gates may be used, where the process could change based on RIH/POOH state or loop back on itself depending on dynamic conditions. For instance, if multiple attempts at making a connection between pipes (i.e., agents) occurred, the process may not restart at the beginning, but rather reenters either the torque wrench or spin wrench as an off-nominal activity (e.g., a failure to function properly, such as, for example, if the threads of a section of pipe are stripped and the roughneck thus couldn’t make up the connection). In some embodiments, simulations may be employed to dynamically interface with the state machine model and other machine processes, according to the physical process, as well as perform logic calculations to identify the critical path. In some implementations, the entering time, the exiting time, the duration and the critical path impact can be calculated for each process block (in FIG. 6A) to obtain descriptive statistics for the machine operations. In some implementations, this process can be continuous, such that as long as tripping activities are occurring, the discrete event model may continue to execute in a loop. In such implementations, the modeling may end when the higher-level process terminates. For example, the modeling may terminate at the end of the trip data. In some embodiments, integrating the individual machine discrete event models allows the full tripping operation to be simulated. In some embodiments, additional logic may be added for initial conditions and anomaly detection to allow entry and exit of any process if certain conditions were met. This flexibility improves the modeling since in actual operations the process can be halted and restarted for a number of reasons and as needed.

[0040] The above discussion can be illustrated as follows with reference to FIG. 6A, according to an embodiment. At 602, the functional model states are aggregated to form a machine logic, at 604, and/or process, at 606. For example, as shown for the composite state “torque pipe” 418 (where the“torque pipe” 418 composite state is decomposed into the “torque wrench closed” 420 and“torque wrench open” 422 states, for example), in some implementations, a state machine model can be developed for each of the composite states, “locate tool joint” 412,“movement” 414 and“spin pipe” 416, to identify the functional model states of the composite states. For instance, with reference to FIG. 5, a state machine model can be used to identify the torque wrench closed state 520, the torque wrench open state 522 and the unknown torque wrench state 524 (e.g., configured to account for signal quality issues) as the functional model states of the composite state“torque pipe” 418. At 604, in some implementations, the functional model states of the different composite states may be aggregated to form a machine process 606. That is, with reference to the example embodiments of FIG. 4, the functional model states of the composite state“torque pipe” 418 (which include, for example, the torque wrench closed state 520, the torque wrench open state 522 and the unknown torque wrench state 524) and the functional model states of each of the composite states,“locate tool joint” 412,“movement” 414 and“spin pipe” 416, may be aggregated at 604 to form the machine process 606 for the pipe connection equipment 408.

[0041] FIG. 6B provides an example illustration of a discrete event model developed to define the operations of a machine engaged in a tripping operation, i.e., the pipe connection machine (e.g., a roughneck). The model identifies the discrete events or activities on which a machine such as the roughneck is spending a large amount of time. For example, the modeling may identify the roughneck remaining in the“at rest” position, the roughneck moving to the well center and the roughneck locating the tool joints of pipes as the three activities on which the roughneck spends a large amount of time when engaged in pipe connection activity (and as such, possibly contribute to the lost time, inefficiencies, etc.). Similarly, the model may identify the activities of the roughneck’s torque wrench stabilizing a drill string (e.g., by locking onto the drill string below the pipe connection point) and the roughneck’s spinning wrench disconnecting the threaded connection point (e.g., by locking onto the drill string above the pipe connection point and spinning) as discrete events or activities that are time- consuming (and as such, possibly contributors to the lost time, inefficiencies, etc.). In some implementations, the identification of discrete activities facilitates the determination of the critical path of tripping operations as discussed below.

[0042] It is to be noted that, even though the above discussion refers to the composite states 412, 414, 416 and 418 of the pipe connection equipment 408 (and the state machine model states 420, 422 and 424 thereol), similar discussions may apply to the other machines or equipment used to perform operations (e.g., tripping operations), including but not limited to the pipe racking system 404, the derrick hoisting system 406 and the slips 410, to obtain corresponding machine processes (similar to the machine process 606 for the pipe connection equipment or machine 408). In some embodiments, these machine processes (e.g., machine processes of the pipe racking system 404, the derrick hoisting system 406, the pipe connection equipment 408 and the slips 410, for example) may then be integrated, at 608, to obtain the operational processes for the tripping operation performed by the system 402. In obtaining the operational processes starting with the functional model states at 602, in some embodiments, the critical path, and the associated critical path time, may be determined based on, amongst other things, the start time and the end time of the machine processes (such as the machine process 606).

[0043] In some embodiments, once the discrete activities of the machines engaged in the tripping operation are identified, the critical path of the tripping operation may be determined. For example, a logical process that compares the various discrete activities and establishes their order of operation so that the entire tripping operation can be completed efficiently can be used to determine the critical path (for instance, software that includes“if- then-else” type of codes may be used to determine the order of the activities, from which the critical path may be obtained). In some implementations, a truth table (e.g., Table. 1 below) including some or all possible combinations of machine activities, and the machine/activity at which the critical path is for that combination of activities, may be developed and used to identify the critical path. For example, as discussed above, the discrete activities of the pipe connection machine (e.g., roughneck) include the roughneck being at rest (e.g., in the setback position), moving towards the well center, locating the pipe tool joint, applying torque (using a torque wrench), spinning (using a spinning wrench) and moving back to the setback position after connecting (e.g., RIH operation) or disconnecting (e.g., POOH operation) pipes. Similarly, each machine may be capable of performing multiple activities. As such, the combination of the above six activities of the roughneck and the activities of the other machines would produce hundreds of combinations (for each of tripping in and tripping out operations), some of which are shown in Table 1. In some cases, some of the combinations may be physically impractical or impossible. For example, if the pipe racking machine is at well center, then the block or derrick hoisting system cannot lower pipes lest the machines collide (these impractical or impossible combinations are marked by“Not Classified” under the“machine in critical path” column in Table 1). Using atruth table such as Table 1, in some implementations, one may map out the critical path by identifying the activi ties/ machines that are in the critical path for a combination of activities that are being executed by the machines of the tripping operation throughout the operation.

[0044] In some instances, it may be desirable to have a visual depiction of the activities of the various machines involved in a tripping operation, so that the complex interplays of the machines (e.g., which tripping activity comes before or after which activity) may become apparent quickly and efficiently understandable, e.g., to an operator associated with one or more of the machines involved in the tripping operations. Further, such a visual depiction may be a convenient way to display the critical path in a graphical manner that elucidates the trajectory of the critical path (e.g., which machine in the critical path comes before or after which other machine) as well as changes in the trajectory due to factors such as machine delays, external interferences, etc. For example, a supervisor of a tripping operation may wish to identify in real-time or nearly real-time the machines that are in the critical path of the tripping operation so that the supervisor can avoid or reduce increases in the critical path time due to machine delays, etc. In some implementations, a visual display of the critical path may aid the supervisor in identifying machines that might in the future join or enter the critical path. For example, repeated small delays by a first machine that is in the critical path may result in a second machine that is not in the critical path joining the critical path at a later time. In such cases, the visual display may provide the supervisor real-time or nearly real-time information on the circumstances (e.g., timing, etc.) of the second machine joining the critical path, which would allow the supervisor to take any corrective action that would alter the trajectory of the critical path (e.g., corrective action so that the second machine does not join the critical path). Additionally, in some instances, it may be desirable to have such a visual depiction of the tripping operation and associated critical path after the tripping operation has commenced and/or been completed as a look-back to identify contributors to the critical path time for future optimization of a tripping operation. Similarly, such a visual depiction of multiple tripping operations (e.g., within a single rig, or across various rigs) can aid in identifying variations across the multiple tripping operations.

[0045] Accordingly, in some embodiments, a Gantt chart may be used to present or display critical paths of tripping operations. Gantt charts are visual representations of a schedule or sequence of tasks or activities in a project or operation, and can be used to show the dependencies (e.g., order) between the tasks. As such, Gantt charts can be used to present the critical path of the operation. Details on the use of Gantt charts to manage a project or operation can be found in U.S. Patent Publication No. US 2009/0193353, titled“Gantt Chart Map Display and Method,” which in incorporated by reference herein in its entirety.

[0046] FIG. 7 shows an example Gantt chart illustrating a non-dynamic critical path of a run-in-hole (RIH) tripping operation, according to an embodiment. As discussed above, the critical path can be viewed as a static snapshot of a tripping operation as it relates to the various components that make up the system and execute at least some aspects of the operation, the components including machines or equipment such as the pipe racking equipment, the derrick hoisting system, the pipe connections equipment, the slips, etc. For example, FIG. 7 shows a snapshot of the activities or processes of the slips 702, the block (the derrick hoisting system) 704, the pipe racking equipment 706 and the roughneck 708, where it is shown that some activities of a given machine may have dependencies on activities of other machines (e.g., the preceding activities have to be completed before the later activities can commence) and some activities are independent of each other (e.g., they can be performed simultaneously). For example, the slips 702, the pipe racking equipment 706 and the roughneck 708 can initialize simultaneously, at 710, at 712 and at 714, respectively, while the block has to wait for the slips 702 to be closed, at 716, before the elevators of the hoisting system are unlatched, at 718, which indicates that the unlatching of the elevators is dependent on the closing of the slips while the activities of the slips 702, the pipe racking equipment 706 and the roughneck 708 are not dependent on each other. As another example, the roughneck 708 may move to standby, at 720, waiting for the pipe racking equipment 706 to stab in the pipe (i.e., place the pipe in position to make connection with the drill string in the wellbore), at 722, before the roughneck 708 can move from standby to WC, which indicates that the movement of the roughneck 708 can be dependent on the racking equipment 706 stabbing in the pipe.

[0047] In some instances, the identification of the critical path may allow one to anticipate delays that may cause the critical path time to increase, thereby diminishing the efficiency of the tripping operation. For example, with reference to the example above, if the closing of the slips 702 takes longer than a standard duration, then the unlatching of the elevators cannot happen at the pre-determined time, which in turn delays the retraction of the dolly at 724, which then delays the stabbing in of the pipe, at 722, by the pipe racking equipment 706, etc. As such, by analyzing and characterizing the critical path, a supervisor or operator of a tripping operation would be able to take corrective actions that would avoid, for example, an increase in the critical path time. For example, after identifying what is in critical path, one may attempt to reschedule the tasks (e.g., in addition to identifying and reporting which activities can be causes of delays). As an example, during RIH, as the roughneck operator sees the pipe racker moving the pipe into WC to stab in the pipe, the operator does not need to wait for the pipe to be completely stabbed in, rather, the operator can move the roughneck into position to be ready to start spinning in. If the roughneck, on the other hand, waits in its setback position until the pipe is fully stabbed in, additional time will be required to complete the task / activity. In some implementations, multiprocessor task rescheduling methods or algorithms, discussed in the above-noted Dynamic Critical-Path Scheduling: An Effective Technique for Allocating Task Graphs to Multiprocessors, by Yu-Kwong Kwok, may be used to estimate time to completion, in particular for fairly controlled environments (e.g., processes or operations with machines having little or no delays in starting or completing their assigned tasks).

[0048] FIGS. 8A-C show a series of example image snapshots of an animated color- coded rendering of a tripping operation having a dynamic CP along with a corresponding progression timeline in each image visually displaying the activities of the machines executing the various activities of the tripping operation, according to an embodiment. The example tripping operation in FIGS.8A-C relates to an RIH operation in which a pipe racking machine 802, a pipe connection machine 804, a derrick hoisting system 806 and slips 808, among other things, are used in an RIH or tripping in operation to attach the pipe 810 onto a drill string 812 before the drill string 812 is lowered into a wellbore at a well center (WC) 814 of a drill floor. A display board 816 presents a snapshot at a moment in time of a timeline 818 of the activities of the aforementioned machines from the start of the tripping operation up to the moment and includes a panel 820 providing a summary of the current activities (e.g., for that duration, from the start of the operation to that moment in time), the machine(s) / activity(ies) currently in the critical path, the invisible time lost, the type of tripping operation, etc. In some implementations, the timeline 818 may be coded (e.g., color-coded) or otherwise appropriately marked to compare the performance of an activity of the coded machine with that of a pacesetter performance. A pacesetter performance of an activity of a machine, in some implementations, can be a given percentiles of performances for each activity of the machine over a period of time such as but not limited to the top about 1%, about 3%, about 5%, about 7%, about 10%, about 12%, about 15%, etc., including values and subranges therebetween. The period of time may be from about a week to about a year (or longer), about three months, about six months, including values and subranges therebetween. In some implementations, the pacesetter performance for each activity can be a predetermined performance (e.g., a performance assumed to take a predetermined amount of time to complete an activity). The pacesetter performance is useful, for example, in revealing whether a machine is performing as expected, or if it takes longer than expected. For example, in FIGS.8A-C, the colors yellow (indicated by“Y”) and red (indicated by“R”) are codes indicating that the machine is taking longer to execute the activity compared to a pacesetter while pink (indicated by“P”) and blue (indicated by“B”) are codes indicating the opposite (the differences between the color codes yellow and red, and the color codes pink and blue, relate to whether the machine/activity is in the critical path of the tripping operation, discussed in detail below).

[0049] As an illustration, the derrick hoisting system 806 may engage in several activities, such as but not limited to lowering into a lower position with a pipe, lowering into a lower position without a pipe, being in a lower position, being in an upper position, lifting up without a pipe, lifting up with a pipe (e.g., hoisting a pipe), and/or the like. For each of these activities, a pacesetter performance can be, for example, the top 10% of historical performances of each activity performed by this particular derrick hoisting system 806 (or a fleet of derrick hoisting systems, on this particular rig or others, for example). As such, when a red or yellow bar is shown in FIGS. 8A-C for the“hoisting a pipe” activity, the colors indicate that at that moment in time the derrick hoisting system 806 is running late compared to the top 10% of“pipe hoisting” activity performances by the derrick hoisting system 806 (the color bars and additional details of the display board 816 are presented below). In some implementations, the pacesetter performances, which can depend on the specifications of the original equipment manufacturer (e.g., design limits, technical performance limits, etc.), the installation and/or the configuration of the machines, and/or etc., can be updated over time as more activities are logged in (and processed). In some implementations, the machines in the image 822 may themselves be coded to correspond to the coding of the activities in the display board 816 (e.g., the color bars in the timeline 818) to aid with visual correlating the machines in the image 822 to their activities as shown in the timeline 818.

[0050] As noted above, in some implementations, the display board 816 presents a snapshot at a moment in time of an animated depiction of a timeline 818 of the activities of the aforementioned machines from the start of the tripping operation up to the moment and includes a panel 820 providing a summary of the current activities (e.g., for that duration, from the start of the operation to that moment in time). In some implementations, such a visual presentation of the activities of the machines engaged in tripping operation activities can facilitate the determination of the critical path, and variations thereof, of the operation. For example, an operator of a tripping operation can view a display board such as those shown in FIGS. 8A-C for a cycle of the tripping operation (in some cases, in an animated form) to visualize and readily understand the critical path and/or the dynamical critical path, if variations exist, of the operation, as discussed below.

[0051] After determining pacesetter performances (and correspondingly pacesetter times) for performing each activity of the machines engaged in the tripping operation, in some embodiments, the timeline 818 for a tripping operation, having on the x-axis the time/duration of the operation and on the y-axis the activities of the operation, may be obtained as follows. With reference to FIG. 8A, in some implementations, the slips 808 are initially open having allowed the derrick hoisting system 806 to descend with a pipe or a drill string 812 into the well center 814. At this time, the pipe connection machine 804 may not be active, as it may be waiting for a pipe 810 to be brought to the well center 814 for attachment to the drill string 812. For example, the pipe racking machine 802 may be transporting the pipe 810 from the fingerboard or pipe rack (not shown) to towards the well center 814. These activities by the machines, the slips 808 being open, the derrick hoisting system 806 being in a lower position after having lowered a pipe/drill string 812, the pipe connection machine 804 being at rest and the pipe racking machine 802 transporting a pipe 810 towards the well center 814 for attachment to the drill string 812 can be represented on the timeline 818 using a coding system (e.g., color coding) that encodes whether each activity is exceeding or failing to exceed the pacesetter and/or whether each activity is in the critical path. [0052] For example, a bar 824 (extending from the start of the operation to sometime later) indicates that the slips 808 are in the“slips open” state, i.e., the slips are open. The bar is shown in blue, which indicates, according to the code identification table 832, that the activity (the slips being open) is under the pacesetter and not in the critical path (an activity being“under” or“over” the pacesetter means the activity is taking less or more time compared to the pacesetter, respectively). Since the slips 808, and/or activities thereof, are not in the critical path, and/or the activity is shown to be under the pacesetter, the opening of the slips 808 did not cause any lost time. As to the derrick hoisting system 806, the pink bar 826 indicates, again according to the code identification table 832, that the derrick hoisting system 806 is in the state of being in the“lower position” and that this activity is under the pacesetter (taking less time than the pacesetter would) and in the critical path, which means that the machine/activity is not causing any lost time. That is, even though the machine/activity is in the critical path and as such in a position to cause lost time if delayed, it was not delayed (i.e., taking less time than the pacesetter performance), and as such did not cause any lost time. The indication that the machine/activity is in the critical path, i.e., it is holding up all other activities in the critical path that come after it, follows because these subsequent activities by other machines (e.g., the pipe 810 being placed at the well center 814) may not occur as long as the derrick hoisting system 806 is in the“lower position” and blocking the well center 814 and its vicinity.

[0053] The transport of the pipe 810 from the fingerboard or pipe rack towards the well center 814 by pipe racking machine 802 is shown in the timeline 818 by the yellow bar 828, which indicates, according to the code identification table 832, that the activity (the pipe racking machine 802 bringing the pipe 810 towards the well center 814) is not in the critical path. Here again, even though the activity is taking longer than the pacesetter, there is no lost time as the activity is not in the critical path (although, as described with respect to other embodiments herein, in some instances, an activity that is repeatedly exceeding the paceseher, over time, may eventually enter the critical path, and thus eventually contribute to associated efficiencies (e.g., lost time)). Similarly, the pipe connection machine 804, being in the“at rest” state as shown by the blue bar 830, is neither in the critical path nor exceeding the pacesetter performance (and hence would not contribute to lost time).

[0054] In some implementations, the information encoded within the bars 824, 826, 828, 830 on the timeline 818 of the display board 816 may be summarized in the panel 820. As discussed above, none of the activities represented by the bars 824, 826, 828, 830 caused or contributed to any lost time, and this information may be presented in the panel 820 (e.g., the invisible time lost is shown as zero for each machine or system). In some implementations, the panel 820 may also provide information about the type of the tripping operation (e.g., “tripping in” operation in the example embodiment of FIGS. 8A-C), the instant activities the machines are engaged in, the number of cycles the tripping operation has been performed up until that time, etc. Further, the machine and/or activity that is in the critical path at the moment of the snapshot is also disclosed, corresponding to the machine and/or the activity with a pink or red bar at the moment of the snapshot, as these colors indicate the machine and/or the activity being in the critical path. As such, the display board 816 is configured to present information related to the tripping operation graphically (e.g., via the tripping operation timeline 818) and/or numerically/textually (e.g., via the panel 820), according to the code identification table 832.

[0055] In some implementations, as time progresses during the tripping operation, the critical path can migrate between machines and/or between activities. For example, FIG. 8B shows that as time progressed (along the positive x-axis), relative to point in time illustrated by FIG. 8A the derrick hoisting system 806 that was in the“lower position” state and as such in the critical path (e.g., as demonstrated by the red bar 832), left the critical path when it was raised or lifted up, as shown by the blue bar 834, and the pipe racking machine 802, and its activity of transporting the pipe 810 from the pipe rack or fingerboard to the well center 814, entered the critical path, as shown by the red bar 836 (e.g., as the tripping operation could not continue without the pipe 810 being brought to the well center 814 for attachment with the drill string 812). For example, the pipe racking machine 802 may have taken too long (e.g., compared to a pacesetter’s performance) in retrieving the pipe 810 from a pipe rack or fingerboard and transporting the pipe 810 to the well center 814, which results in the pipe racking machine 802 and its activity entering the critical path, as other tripping activities that are in the critical path cannot continue until the pipe racking machine’s 802 activity is completed.

[0056] In some implementations, a red bar (or any other suitable indicator) appearing anywhere in the tripping operation timeline 818 may serve as an indication that there is a lost time during the operation (compared to the pacesetter performance, for example). Since, as noted in the code identification table 832, the color red is a code indicating that the performance of the activity worse than the performance of the pacesetter (i.e., the performance time of the activity is over or higher than the pacesetter performance time) and that that activity was in the critical path, such activity would contribute to a time lost. As discussed above, this graphical information about the time lost is reflected textually in the panel 820, which shows non-zero values of times lost for the derrick hoisting system 806 (labeled as“block ILT”) and the pipe racking machine 802 (labeled“piperacker ILT”). It is to be noted that the“roughneck ILT”, representing the time lost as a result of activities by the pipe connection machine 804, is still zero, as the pipe connection machine has not yet been in the critical path (even though its activities have taken longer than the pacesetter performance, indicated by the yellow bars 838a, 838b. In other implementations, the information contained within the panel 820 may also (or instead) be displayed graphically in a manner that allows a human to quickly grasp the relative contributions of machine activities to the invisible time lost (e.g., FIG. 8E, where “drawbacks” refers to the pipe connection system (e.g., roughneck)).

[0057] In some embodiments, the determination of the critical path and the pacesetter for each machine activity may be codified in a state machine model or logic. For example, FIG. 8D shows a state machine model that includes several state classifications for the activities of the pipe racking machine or system, such as the activity being over the pacesetter (i.e., taking longer than the performance of the pacesetter) and in the critical path or not in the critical path, labelled“PR OPSNOTCP” and“PR OPSINCP”, respectively, the activity being under the pacesetter (i.e., taking less time than the performance of the pacesetter) and in the critical path or not in the critical path, labelled“PR UPSNOTCP” and“PR UPSINCP”, the activity being physically impossible or impractical (e.g., a machine moving into a location while another machine is still at the location, which may be blocked by collision avoidance systems), labelled“PR_NotClassified”. In some implementations, such a state machine model may allow for passing through multiple classifications within any given activity which can be recorded in arrays until the activity completes (e.g., the pipe racking machine can be in the under the pacesetter states at some point but can go into the over the pacesetter states while still executing the same activity). In some implementations, rules that may restrict the state transition can be defined and applied. For example, once an activity exceeds the pacesetter time it may not be able to return to an under pacesetter state during that operation. Conversely, if an activity is in the critical path, it can transition out of the critical path and then transition back into the critical path based on other simultaneous activities. It is to be noted that although FIG. 8D and the related description refer to the pipe racking machine, similar state machine model or logic can be constructed to determine the critical path and the pacesetter for the activities of the other machines engaged in tripping operations (or any other suitable rig operations).

[0058] In some implementations, after a full cycle of a tripping operation is undertaken (e.g., between slips closing at 841a and a full cycle of tripping operation ending at 841b with a closing of the slips), the tripping operation timeline 850 can be used to map the critical path as the critical path migrates from one machine to another and/or from one activity to another. Said another way, the tripping operation timeline 850 can be used to identify machines and/or activities that enter and/or leave the critical path as time progresses. In some implementations, this may be accomplished by scanning the tripping operation timeline along the x-axis (which corresponds to the passage of time) and identifying machines/activities that are marked with the code that indicates that the machines/activities are in the critical path (e.g., the colors red and pink in FIGS. 8A-C, according to the code identification table 832)). For example, with reference to FIG. 8C, at 841a, a cycle of tripping in operation may commence when the slips close, and at that time, the machine and the activity that are in the critical path are the derrick hoisting system and its activity of being in the“lower position”, respectively (i.e., the machine and activity with the color (or code, in general) that indicates that the machine/activity are in the critical path and the machine is taking longer than the pacesetter to complete the activity). Proceeding along the x-axis (corresponding to the progress of time), in some implementations, the derrick hoisting system may be raised, exiting the critical path at 842. The next machine and its activity along the x-axis that are marked with red or pink are, respectively, the pipe racking machine and the movement of the pipe from the fingerboard to the well center, and the critical path may migrate this machine/activity, as shown schematically with the dashed line 852. In some implementations, the critical path may migrate across activities of the same machine, as shown by the migration of the critical path (shown schematically with the dashed line 854) from the activity of the“moving the pipe from the fingerboard to the well center” to the activity of“stabbing in” the pipe onto the drill string, both of these activities belonging to the pipe racking machine. As such, by following and tracing the red or pink bars in FIG. 8C (or in general bars or markings that indicate that the machines/activities are in the critical path), the critical path of a tripping operation may be mapped.

[0059] For instance, for the full cycle of the tripping in operation in FIG. 8C, the critical path starts with the derrick hoisting system being in the lower position and then migrates, at 852, to the pipe racking machine executing the activity of moving the pipe from the fingerboard to the well center, before migrating to another activity of the same machine, at 854, as the pipe racking machine shifts from moving the pipe to the well center to piping in the pipe into the well center (e.g., placing it in alignment with the drill string). Once the pipe is stabbed in, in some instances, the critical path may then migrate to the pipe connection machine, at 856, as the next step in the critical path of the tripping operation is to attach or connect the pipe to the drill string onto which it is piped in. At this stage, the critical path stays with the same machine, but transitions from one activity to another activity, as the machine transitions, at 858, from locating the tool joints of the pipes to spinning and applying torque to the pipes using the pipe connection machine (e.g., the roughneck). The critical path then migrates again, at 862, to the derrick hoisting system that is at the“upper position”, as the next critical path step in the tripping operation is for the hoisting system to lower itself with another pipe, at 864 (and occupy the lower position at 866), so that another cycle of a tripping operation can be performed starting at 841b. Migration of the critical path between machines and/or activities is that the machines and/or activities are entering and/or leaving the critical path as time progresses is readily apparent by the coded display (e.g., the red and pink bars) which can be easily scanned or viewed along the x-axis to better understand the efficiency (or lack thereof) of the operation, and the contributors thereto at any given point in time.

[0060] In some embodiments, the critical path may be dynamic, i.e., the critical path may not be the same from one cycle of the tripping operation to another and/or the critical path may leave a machine/activity before the activity is completed. For example, with reference to FIG. 8C, it is shown that the pipe connection machine may take longer than the pacesetter in executing the activity of being at rest (the yellow bar 868). In some implementations, the pipe connection machine may, however, take progressively more time during each cycle of the tripping operation, which may lead to the“at rest position” activity entering the critical path. This can happen, for example, when then pipe racking machine has piped in a pipe into a drill string and the rest of the machines in the critical path are waiting for the pipe connection machine to arrive at the well center to attach the pipe to the drill string.

[0061] In some embodiments, since the tripping process can be dynamic and continuous, the activity can be traced backward to see how the DCP drifts over time. For example, an activity may not be in the DCP at some point in time, but it may enter the DCP after a number of cycles (e.g., from about five to about ten cycles) if it is delayed even by a little bit during every cycle. As an example illustration, this type of trend may appear in the pipe racking equipment activity when it is indexing pipes further and further away from WC, since traveling a longer distance takes more time. In some instances, this may allow one to predict the DCP and, in a real-time feedback system, potentially correct the delays before the activity enters, if desired.

[0062] In some embodiments, the visual presentation of the critical path of tripping operations as discussed above with the use of a tripping operation timeline and a panel summarizing the information displayed in the timeline may allow an operator of the tripping operations to make adjustments so as to improve or enhance the efficiency of the operations. For example, an operator may perceive quickly, from a review of the timeline of FIG. 8C, that the main (or substantial) culprit for a substantial invisible lost time is the derrick hoisting system. Further, even more specifically, the operator may understand from the visual display that a major portion of the time lost is lost when the hoisting system is at the lower position and the upper position. As such, based on this information obtained by reviewing or studying the timeline, the operator may make changes or reschedule the activities of machines that can reduce the time the hoisting system spends at the lower and upper positions, thereby enhancing the efficiency of the entire tripping operation. In some implementations, the reason for such significant amount of time may not be discoverable from the machine data, and as such may have to be obtained from external datasets. That is, in some embodiments, external datasets may be used to supplement data obtained from sensors monitoring machines to determine the critical path (e.g., which may be a dynamic critical path).

[0063] In some embodiments, one may measure the frequency distribution of activity combinations and compare these measurements against a benchmark (e.g., optimal) sequence to determine the operations of equipment or machines and correlations with crew competency, performance, maintenance and failures of machines, etc. In some implementations, for example, this may allow one to identify, based on the activity data, the efficient crews on the rigs and their work routine (for example, to introduce the efficient work routines of one team to other teams or crews with less efficiency). In some embodiments, the data may suggest that an activity combination may not be physically practicable, which may be understood as an indication of an issue with the data or the logic, which can then be followed up with further investigation. In some embodiments, additional indications and confidence intervals may be added to the assessment, where data was not of a sufficient quality to make a determination with certainty.

Simulations of the Model Disclosed Herein [0064] FIGS.9, 10A-B and 11A-B show example simulation results of the critical path contributions of the activities of (a) a particular machine over a cycle of tripping operation, (b) two arbitrary crews on the same drilling rig, and (c) crews on two different drilling rigs, using the model or methodology disclosed herein for characterizing critical paths, according to some embodiments. FIG. 9 shows a relatively wide variation in the duration for a tripping cycle over time, which indicates that the tripping performance is far from uniform over time. In particular, the large values of the duration indicate inefficient tripping performance (and delayed critical path) and may need to be reduced to improve performance. In some embodiments, a root cause analysis on the outliers and anomalies may reveal that some or all of these data points may be erroneous and may not represent actual events.

[0065] FIGS. 10A-B show that the performance of different crews can be compared based on an analysis of the CP of a tripping process undertaken using the same set of machines. The disclosed methods and systems for identifying and classifying critical paths during tripping operations allows one to improve the performances of oil rig crews as the routines or work habits of the more efficient crew can be transferred to the team with less efficiency, as measured by the comparison. FIGS. 11A-B, on the other hand, show results for two different arbitrary oil rigs, and the results show a marked difference between the performances of the machines or equipment on the different rigs. Here again, such comparisons allow for identifying machines that are contributing to inefficiency in tripping performances (and addressing the issues as desired). In general, results such as those depicted in FIGS. 9, 10A- B and 11A-B provide powerful insight into system performance and trends that can be used to provide real-time feedback to operations personnel, as well as for post event analysis to help improve operational efficiency. For example, even if a short amount of time (e.g., seconds) is saved per machine function, accumulated over thousands of connections across the entire fleet, the savings can have a significant impact on efficiency.

[0066] While various inventive embodiments have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein, and each of such variations and/or modifications is deemed to be within the scope of the inventive embodiments described herein. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the inventive teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific inventive embodiments described herein. It is, therefore, to be understood that the foregoing embodiments are presented by way of example only and that, within the scope of the appended claims and equivalents thereto; inventive embodiments may be practiced otherwise than as specifically described and claimed. Inventive embodiments of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the inventive scope of the present disclosure.

[0067] The above-described embodiments can be implemented in any of numerous ways. For example, embodiments of the present technology may be implemented using hardware, firmware, software or a combination thereof. When implemented in firmware and/or software, the firmware and/or software code can be executed on any suitable processor or collection of logic components, whether provided in a single device or distributed among multiple devices.

[0068] In this respect, various inventive concepts may be embodied as a computer readable storage medium (or multiple computer readable storage media) (e.g., a computer memory, one or more floppy discs, compact discs, optical discs, magnetic tapes, flash memories, circuit configurations in Field Programmable Gate Arrays or other semiconductor devices, or other non-transitory medium or tangible computer storage medium) encoded with one or more programs that, when executed on one or more computers or other processors, perform methods that implement the various embodiments of the invention discussed above. The computer readable medium or media can be transportable, such that the program or programs stored thereon can be loaded onto one or more different computers or other processors to implement various aspects of the present invention as discussed above.

[0069] The terms“program” or“software” are used herein in a generic sense to refer to any type of computer code or set of computer-executable instructions that can be employed to program a computer or other processor to implement various aspects of embodiments as discussed above. Additionally, it should be appreciated that according to one aspect, one or more computer programs that when executed perform methods of the present invention need not reside on a single computer or processor, but may be distributed in a modular fashion amongst a number of different computers or processors to implement various aspects of the present invention.

[0070] Computer-executable instructions may be in many forms, such as program modules, executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Typically, the functionality of the program modules may be combined or distributed as desired in various embodiments.

[0071] Also, data structures may be stored in computer-readable media in any suitable form. For simplicity of illustration, data structures may be shown to have fields that are related through location in the data structure. Such relationships may likewise be achieved by assigning storage for the fields with locations in a computer-readable medium that convey relationship between the fields. However, any suitable mechanism may be used to establish a relationship between information in fields of a data structure, including through the use of pointers, tags or other mechanisms that establish relationship between data elements.

[0072] Also, various inventive concepts may be embodied as one or more methods, of which an example has been provided. The acts performed as part of the method may be ordered in any suitable way. Accordingly, embodiments may be constructed in which acts are performed in an order different than illustrated, which may include performing some acts simultaneously, even though shown as sequential acts in illustrative embodiments.

[0073] All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms.

[0074] The indefinite articles“a” and“an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean“at least one.”

[0075] The phrase“and/or,” as used herein in the specification and in the claims, should be understood to mean“either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with“and/or” should be construed in the same fashion, i.e.,“one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the“and/or” clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to“A and/or B”, when used in conjunction with open-ended language such as“comprising” can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc.

[0076] As used herein in the specification and in the claims,“or” should be understood to have the same meaning as“and/or” as defined above. For example, when separating items in a list,“or” or“and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as“only one of’ or“exactly one of,” or, when used in the claims,“consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term“or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e.“one or the other but not both”) when preceded by terms of exclusivity, such as“either,”“one of,”“only one of,” or “exactly one of.”“Consisting essentially of,” when used in the claims, shall have its ordinary meaning as used in the field of patent law.

[0077] As used herein in the specification and in the claims, the phrase“at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase“at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example,“at least one of A and B” (or, equivalently,“at least one of A or B,” or, equivalently “at least one of A and/or B”) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.

[0078] It should be appreciated that all combinations of the foregoing concepts and additional concepts discussed in greater detail below (provided such concepts are not mutually inconsistent) are contemplated as being part of the inventive subject matter disclosed herein. In particular, all combinations of claimed subject matter appearing at the end of this disclosure are contemplated as being part of the inventive subject matter disclosed herein. It should also be appreciated that terminology explicitly employed herein that also may appear in any disclosure incorporated by reference should be accorded a meaning most consistent with the particular concepts disclosed herein.

[0079] In the claims, as well as in the specification above, all transitional phrases such as“comprising,”“including,”“carrying,”“having, ”“containing,”“involving,”“holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases“consisting of’ and“consisting essentially of’ shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03.

[0080] Although various embodiments described herein focus on drill floor operations such as tripping operations, any of the embodiments described herein can be utilized in any operation in which identifying and characterizing a critical path would be useful, such as, for example, any construction-related operation.