System and method for monitoring downhole operation

Abstract

Systems and methods are discussed for characterizing usage of an operating tool configured for use within a wellbore. As an example, a system is discussed that includes detecting system and a processing device. The processing device receives information from the detecting systems and may use the information to, for example, determine an efficiency using the time period for each of a plurality of tool gestures and a respective expected time period for each of the plurality of tool gestures.

Description

BACKGROUND

[0001] This disclosure relates to the monitoring of subterranean operations. In particular, systems and methods are provided for monitoring downhole operations in the oil or gas industry.

[0002] Well interventions and many other operations are routinely performed in subterranean environments for a variety of reasons, such as to remove obstructions, reestablish isolation barriers, characterize reservoirs, and enhance production. Typical techniques for performing these types of operations include the use of service tools on slickline, electric line (wireline) or coiled tubing. These operations may be conducted by different vendors using different equipment and during the operations, collecting job-related data with different data collection formats. The variability of data collection formats and the type of job-related data that is maintained by different vendors make it difficult to determine the performance of the downhole operations by comparison from job to job and / or vender to vender.SUMMARY

[0003] This summary is provided to introduce a selection of concepts that are further described below in the detailed description. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used as an aid in limiting the scope of the claimed subject matter.

[0004] Various embodiments provide systems for evaluating usage efficiency of an operating tool configured for use within a wellbore. The systems may include a detecting system configured to be secured to the operating tool, where the detecting system includes: a first sensor of a first sensor type that provides a first sensor data; and a second sensor of a second sensor type that provides a second sensor data. The systems may further include a processing device configured to: receive a plurality of instances of each of the first sensor data and the second sensor data, wherein each of the plurality of instances corresponds to a respective time; use a combination of at least instances of the first sensor data and instances of the second sensor data from the plurality of instances to identify a plurality of tool gestures; determine a time period for each of the plurality of tool gestures based on the combination of at least instances of the first sensor data and instances of the second sensor data; and determine an efficiency using the time period for each of the plurality of tool gestures and a respective expected time period for each of the plurality of tool gestures.

[0005] Other embodiments provide methods for characterizing usage of an operating tool configured for use within a wellbore. Such methods may include: receiving, by a processing device, a plurality of instances of a first sensor data from a first sensor and a second sensor data from a second sensor, where the first sensor and the second sensor are attached to the operating tool; using a combination of at least instances of the first sensor data and instances of the second sensor data from the plurality of instances to identify, by the processing device, a plurality of tool gestures; determining, by the processing device, a time period for each of the plurality of tool gestures based on the combination of at least instances of the first sensor data and instances of the second sensor data; and determining, by the processing device, an efficiency using the time period for each of the plurality of tool gestures and a respective expected time period for each of the plurality of tool gestures.

[0006] Other aspects and / or advantages of the claimed subject matter will be apparent from the following description and the appended claims.BRIEF DESCRIPTION OF DRAWINGS

[0007] Specific embodiments of the disclosed technology will now be described in detail with reference to the accompanying figures. Like elements in the various figures are denoted by like reference numerals for consistency.

[0008] FIG. 1 shows a well environment in accordance with one or more embodiments.

[0009] FIG. 2 is a block diagram of a system for monitoring utilization of an operating tool in accordance with one or more embodiments.

[0010] FIG. 3 is a schematic diagram of an operating tool in which a detector is provided in accordance with one or more embodiments.

[0011] FIG. 4A is a side view of a detector and FIG. 4B is a cut-away view of detector of FIG. 4A in the direction of A-A in accordance with one or more embodiments.

[0012] FIG. 5 is a block diagram of a detecting system in accordance with one or more embodiments.

[0013] FIG. 6 is a schematic diagram of a computer system in accordance with one or more embodiments.

[0014] FIGS. 7A-7C are flow diagrams showing methods in accordance with some embodiments for determining efficiencies and an environment surrounding an operating tool.

[0015] FIG. 8 is a table of sensor data expected for different tool gestures for a given operating tool in accordance with one or more embodiments.

[0016] FIG. 9 is a table of tool gestures along with expected processing times, actual processing times and variance information in accordance with one or more embodiments.

[0017] FIG. 10 is a flow diagram showing a method for determining different types of efficiencies in accordance with one or more embodiments.

[0018] FIG. 11 is a flow diagram showing a method in accordance with some embodiments for characterizing usage of an operating tool configured for use within a wellbore.DETAILED DESCRIPTION

[0019] In the following detailed description of embodiments of the disclosure, numerous specific details are set forth in order to provide a more thorough understanding of the disclosure. However, it will be apparent to one of ordinary skill in the art that the disclosure may be practiced without these specific details. In other instances, well-known features have not been described in detail to avoid unnecessarily complicating the description.

[0020] Throughout the application, ordinal numbers (e.g., first, second, third, etc.) may be used as an adjective for an element (i.e., any noun in the application). The use of ordinal numbers is not intended to imply or create any particular ordering of the elements nor is it intended to limit any element to being only a single element unless expressly disclosed, such as using the terms “before”, “after”, “single”, and other such terminology. Rather, the use of ordinal numbers is to distinguish between the elements. By way of example, a first element is distinct from a second element, and the first element may encompass more than one element and succeed (or precede) the second element in an ordering of elements.

[0021] As used herein, the phrase “processing device” is used in its broadest sense to mean any electronic circuit capable of performing a sequence of operations or applying an algorithm. Accordingly, a processing device may be, but is not limited to, a general-purpose computer processor, a specific purpose computer processor, an application specific electronic circuit, or the like. Further, a processing device may be implemented as two or more processing devices that may be deployed in different locations. Based upon the disclosure provided herein, one of ordinary skill in the art will recognize a variety of processing devices that may be used in relation to different embodiments.

[0022] In general, embodiments of the disclosure include systems and methods for monitoring a downhole operation. The downhole operation may be any process performed with an operating tool in a subsurface, subterranean, downhole, or underground environment, including but not limited to oil and gas production, maintenance and reservoir transformation and other operations. The following discussion provides a description of scenarios that require or benefit from the availability of downhole operation monitoring, followed by a description of the systems and methods for monitoring downhole operations.

[0023] FIG. 1 shows a schematic diagram in accordance with one or more embodiments. FIG. 1 illustrates a well environment 100 that includes a hydrocarbon reservoir (“reservoir”) 102 located in a subsurface hydrocarbon-bearing formation 104 and a well system 106. The hydrocarbon-bearing formation 104 may include a porous or fractured rock formation that resides underground, beneath the earth's surface (“surface”) 108. In the case of the well system 106 being a hydrocarbon well, the reservoir 102 may include a portion of the hydrocarbon-bearing formation 104. The hydrocarbon-bearing formation 104 and the reservoir 102 may include different layers of rock having varying characteristics, such as varying degrees of permeability, porosity, and resistivity. In the case of the well system 106 being operated as a production well, the well system 106 may facilitate the extraction of hydrocarbons (or “production”) from the reservoir 102. In the case of the well system 106 being operated as an injection well, the well system 106 may be used in a tertiary recovery method to displace the produced hydrocarbons and / or to maintain the pressure profile of the reservoir 102.

[0024] In some embodiments, the well system 106 includes a wellbore 120, a well sub-surface system 122, a well surface system 124, and a data acquisition system 126. The data acquisition system 126 may monitor and / or control various operations of the well system 106, such as well production operations, well completion operations, well maintenance operations, and reservoir monitoring, assessment and development operations. In some embodiments, the data acquisition system 126 includes a computer system that is the same as or similar to that of computer system 602 described below in FIG. 6 and the accompanying description.

[0025] The wellbore 120 may include a bored hole that extends from the surface 108 into a target zone of the hydrocarbon-bearing formation 104, such as the reservoir 102. An upper end of the wellbore 120, terminating at or near the surface 108, may be referred to as the “up-hole” end of the wellbore 120, and a lower end of the wellbore, terminating in the hydrocarbon-bearing formation 104, may be referred to as the “downhole” end of the wellbore 120. The wellbore 120 may facilitate the circulation of drilling fluids during drilling operations, the flow of hydrocarbon production (“production”) 121 (e.g., oil and gas) from the reservoir 102 to the surface 108 during production operations, the injection of substances (e.g., water) into the hydrocarbon-bearing formation 104 or the reservoir 102 during injection operations, or the communication of monitoring devices (e.g., logging tools) into the hydrocarbon-bearing formation 104 or the reservoir 102 during monitoring operations (e.g., during in situ logging operations).

[0026] In some embodiments, during operation of the well system 106, the data acquisition system 126 collects and records wellhead data 140 for the well system 106 and other data regarding downhole equipment and downhole sensors. The wellhead data 140 may include, for example, a record of measurements of wellhead pressure (P) (e.g., including flowing wellhead pressure (FWHP)), wellhead temperature (T) (e.g., including flowing wellhead temperature), wellhead production rate (R) over some or all of the life of the well 106, and / or water cut (WC) data. In some embodiments, the measurements are recorded in real time, and are available for review or use within seconds, minutes or hours of the condition being sensed. In such an embodiment, the wellhead data 140 may be referred to as “real-time” wellhead data 140. Real-time wellhead data 140 may enable an operator of the well to assess a relatively current state of the well system 106 and make real-time decisions regarding development of the well system 106 and the reservoir 102, such as on-demand adjustments in regulation of production flow from the well or injection flow to the well.

[0027] In some embodiments, the well surface system 124 includes a wellhead 130. The wellhead 130 may include a rigid structure installed at the “up-hole” end of the wellbore 120, at or near where the wellbore 120 terminates at the Earth's surface 108. The wellhead 130 may include structures for supporting (or “hanging”) casing and production tubing extending into the wellbore 120. Production 121 may flow through the wellhead 130, after exiting the wellbore 120 and the well sub-surface system 122, including, for example, the casing and the production tubing. In some embodiments, the well surface system 124 includes flow regulating devices that are operable to control the flow of substances into and out of the wellbore 120. For example, the well surface system 124 may include one or more chokes 132 that are operable to control the flow of production 121.

[0028] Keeping with FIG. 1, in some embodiments, the well surface system 124 includes a surface sensing system 134. The surface sensing system 134 may include sensor devices for sensing characteristics of substances, including production 121, passing through or otherwise located in the well surface system 124. The characteristics may include, for example, pressure, temperature and flow rate of production 121 flowing through the wellhead 130, or other conduits of the well surface system 124, after exiting the wellbore 120.

[0029] In some embodiments, well intervention operations may also be performed at a well site. For example, well intervention operations may include various operations carried out by one or more service entities for an oil or gas well during its productive life (e.g., fracking operations, CT, flow back, separator, pumping, wellhead and production tree maintenance, slickline, braded line, coiled tubing, snubbing, workover, subsea well intervention, etc.). For example, well intervention activities may be similar to well completion operations, well delivery operations, and / or drilling operations in order to modify the state of a well or well geometry. In some embodiments, well intervention operations are used to provide well diagnostics and / or manage the production of the well.

[0030] In one or more embodiments, the well system 106 further includes a system for monitoring a downhole operation (not shown). Embodiments of such a system for monitoring a downhole operation are discussed below with reference to the remaining figures.

[0031] While FIG. 1 illustrates various configurations of hardware components and / or software components, other configurations may be used without departing from the scope of the disclosure.

[0032] FIG. 2 is a block diagram of a system 200 for monitoring for monitoring utilization of an operating tool in accordance with one or more embodiments. The system 200 includes a detecting system 210 for detecting information about an operating tool both during downhole utilization of the operating tool and above surface utilization of the operating tool, and a processing device 220 for processing the information received from the detecting system 210. An example of the processing device 220 is illustrated in FIG. 6, which is discussed below in detail.

[0033] As an example, the detecting system 210 may be initialized by a well site supervisor and provided to an operator for incorporation into an operating tool. The detecting system 210 may be communicably coupled to the processing device 220 via a wired communication link that includes a wire extending from a surface of a well to an operating tool including the detecting system 210 within the well. During an operation, the detecting system 210 senses various information within a wellbore. In some embodiments, the information sensed by the detecting system 210 may be processed downhole using a processing device (not shown) included in the detecting system 210 and the results transmitted to processing device 220 in real time via the communication link between the detecting system 210 and the processing device 220. Alternatively, the information sensed by the detecting system 210 may be transmitted to the processing device 220 via the communication link between the detecting system 210 and the processing device 220, and the processing of the information may be done by the processing device 220 or another device to which the processing device 220 transfers the information. In yet other embodiments, either the processed information or the raw information is transmitted by the detecting system 210 to the processing device 220 only after the operating tool is pulled out of the wellbore. In such a situation, the communication link between the detecting system 210 and the processing device 220 may be a wireless communication link or may be a wired communication link that is enabled once the operating tool is pulled from the wellbore.

[0034] The detecting system 210 may be configured to be secured to an operating tool for performing the downhole operation. As such, when the operating tool is inserted into a wellbore to perform a downhole operation, the detecting system 210 is in the same downhole environment as the operating tool and performs the same movements or motions as the operating tool during the downhole operation. For example, the detecting system may be disposed in a tool casing that is fixed by a threaded connection to other elements of the operating tool, such that any motion, acceleration, deceleration of the detecting system will be substantially the same as the operating tool, assuming that the elastic properties of the operating tool are negligible at the stresses involved during normal movement.

[0035] FIG. 3 is an exploded schematic diagram of an operating tool 300 in which the detecting system 210 is provided in accordance with one or more embodiments. As shown in FIG. 3, the operating tool 300 comprises a rope socket 310, one or more stem weight bars 320, a spang jar 330 and a bottom hole assembly (BHA) 340. The detecting system 210 may be secured between the rope socket 310 and a stem weight bar 320. The detecting system 210 may be configured to be a standardized passive monitoring device that operates in a downhole tool string regardless of operation, such that it does not compromise the primary mission of the tool deployment in a wellbore. During a downhole operation, the detecting system 210 continuously monitors the activities of the tool 300 and parameters of the downhole environment from the time it is switched on at the start of the operation until it is switched off at the end of the operation.

[0036] FIG. 4A shows a schematic plan view of the detecting system 210 and FIG. 4B shows a cut-away view of the detecting system 210 in accordance with one or more embodiments. The detecting system 210 may include a first end 211 having a sucker pod pin thread and a second end 212 having a sucker rod box thread. Between the first end 211 and the second end 212, there is a first section 213 threadedly connected to the first end 211 and a second section 214 threadedly connected to the second end 212. Electronic components such as a detecting system 216 and a communication port 217 may be disposed in a housing of the first section 213, and a battery 218 is disposed in a housing of the second section 214. The first section 213 and the second section 214 are threadedly connected by a sub-section 215 in which an electrical wire 219 is disposed for supplying power from the battery 218 to the detecting system 216 and any other electronic components. While the detecting system 210 is shown in this embodiment having various elements placed in certain relative placements, the present disclosure is not limited to a particular physical orientation of the elements within the detecting system 210 nor is it limited to a particular placement of the detecting system 210 relative to other downhole components.

[0037] FIG. 5 shows a block diagram of a detecting system 500 in accordance with some embodiments. The detecting system 500 is one example of detecting system 210. In some embodiments, detecting system 500 operates as an edge processor reporting data back to and / or controlled by, for example, processing device 220. Detecting system 500 may include a battery (not shown).

[0038] As shown, the detecting system 500 may include a plurality of sensors 510, a processing device 520, and a memory 530. The sensors 510 may include, but are not limited to, a strain gauge sensor 511, a pressure sensor 512, a temperature sensor 513, a 3-axis acceleration sensor 514, a 3-axis magnetometer sensor 515, a 3-axis inclination sensor 516, a capacitance sensor 517, and so on. The sensors 510 are configured to collect information about the environmental conditions and the tool movements during a downhole operation. Data collected from the sensors 510 may be provided to, for example, the processing device 220 via the processing device 520 using a communication interface. This communication interface may be a wired or a wireless interface. While the detecting system 500 is shown including a processing device and a memory separate from the sensors 510, in other embodiments each of the sensors 510 includes an embedded processor and memory. In such embodiments, data from the sensors 510 may be communicated directly to, for example, processing device 220 via a communication interface. Such a communication interface may be a wired or wireless communication interface.

[0039] The processing device 520 receives data from the sensors 510, processes the received data to yield processed data, and stores the processed data to the memory 530. In some embodiments, the processing device 520 is communicably coupled to the sensors 510 via a wired interface. Based upon the disclosure provided herein, one of ordinary skill in the art will recognize a variety of communication interfaces that may be used to communicably coupled the sensors 510 to the processing device 520 including both wireless and wired interfaces in accordance with different embodiments. The memory 530 is communicably coupled to the processing device 520.

[0040] In some embodiments, the memory 530 is implemented on the same substrate or the same chip package as the processing device 520, and in other embodiments the memory 530 and the processing device 520 are implemented in separate chip packages. In various embodiments, each of the sensors 510 includes an embedded processor (not shown) and memory (not shown). The memory 530 may be communicably coupled to the processing device 520 via a wired parallel interface or by a wired serial interface. In other embodiments, the memory 530 may be communicably coupled to the processing device 520 via a wireless interface. Based upon the disclosure provided herein, one of ordinary skill in the art will recognize a variety of implementations of the processing device 520 and the memory 530, and the communication coupling between the processing device 520 and the memory 530 that may be used in relation to different embodiments. The memory 530 may include a read-only memory (ROM) and / or a random-access memory (RAM). In some embodiments, the processing device 520 loads programs stored in the ROM into the RAM and executes various processing operations in cooperation with the RAM. The processing device 520 communicates with and receives information from the sensors 510, and after performing necessary processing of the information, further communicates with and stores data in the memory 530.

[0041] The processing device 520 may be configured to perform calculations by executing programs which are stored in and retrieved from the memory 530. In one or more embodiments, sensor fusion may be performed by the processing device 520 by aggregating or collecting information or data from a plurality of sensors recorded over a time domain to derive indirect measurements by executing pre-programmed algorithms.

[0042] In one or more embodiments, the processing device 520 is configured to execute algorithms to determine a vertical depth of the operating tool with which detecting system is deployed using pre-programmed calculation algorithms. For example, to determine vertical depth of the operating tool, two calibration data are determined. The two calibration data include the weight of the operating tool in a first fluid of known density and the weight of the operating tool in a second fluid of known density. A first of the two calibration data is determined by holding the operating tool stationary as indicated by the 3-axis acceleration sensor 514 in a first fluid of known density (e.g., air), and using the strain gauge sensor 511 to measure the strain on the operating tool. This strain is used to determine the weight of the operating tool in the first fluid. A second of the two calibration data is determined by holding the operating tool stationary as indicated by the 3-axis acceleration sensor 514 in a second fluid of known density (e.g., fresh water), and using the strain gauge sensor 511 to measure the strain on the operating tool. This strain is used to determine the weight of the operating tool in the second fluid. Using the aforementioned calibration data, the volume of the operating tool can be calculated where it is assumed that the operating tool is made of steel with a known density. This volume is a third calibration data.

[0043] In some embodiments, the volume of the operating tool can be calculated using the following equation:Vt=(Fltw-Flta)ρw⁢g,where Vt is the tool volume, Fltw is the line tension in water which can be found by measurement using a strain gauge, Flta is the line tension in air which can be found by measurement using a strain gauge, ρw is the density freshwater (i.e., a known or assumed constant), and g is acceleration or gravity in some cases. The preceding equation can be derived as follows. The line tension in the air (Flta) (i.e., the value sensed by a strain gauge sensor) is represented by the following equation:Flta=mg-Fba,where Fba is the buoyant force in air, m is the mass of the tool. As the buoyant force in air is negligible, the following holds:Flta=mg.Line tension in water (Fltw) (i.e., the value sensed by a strain gauge sensor) is represented by the following equation:Fltw=mg-Fbw,where Fbw is the buoyant force in freshwater. From Archimedes Principle, buoyancy force of the tool submerged in water (Fbw) is represented as:Fbw=-ρw⁢gVt.Through substitution in the preceding equations the following equivalence is shown:Fltw=Flta-Fbw.Now, substituting Archimedes Principle for Fbw you get:Fltw=Flta+ρw⁢gVt,and by solving for Vt, the equation for volume is found.Once the operating tool is deployed in a wellbore, it is possible for processing device 520 to first determine that it is not moving using data from the 3-axis acceleration sensor 514, and then use strain data from strain gauge sensor 511 to determine the weight of the operating tool. Using the previously determined calibration data, the density of fluid at the location of the operating tool in the wellbore can be calculated. An equation that can be used for calculating density of the fluid using tool mass and the tool volume is:ρf=(Fltf-mg)gVt,where ρf is the density of well fluid to be calculated, Fltf is the line tension in well fluid which is measured (i.e., measured parameter at rope socket, static, variable), m is the mass of the tool measured at the start of the process in the air, g is acceleration or in some cases gravity, and Vt is the tool volume. This calculation may be done using strain data from the strain gauge sensor 511 while the operating tool is maintained stationary in the wellbore as indicated by the 3-axis acceleration sensor 514. This process of calculating fluid density may be repeated multiple times yielding a number of logged values each corresponding to a different time. These logged values may be compared with pressure data from the same times and true vertical depths for the same times measured by other sensors to discern the accuracy of the fluid densities provided by the detecting system 500.While the processing device 520 is discussed as performing the fluid density calculations, in other embodiments the various data from the sensors 510 obtained over time may be provided to, for example, the processing device 220 that then performs the fluid density calculations. In yet other embodiments, the processing device 520 performs a subset of the processes for determining fluid density and provides its interim results to, for example, the processing device 220 that completes the fluid density calculations.In one or more embodiments, the processing device 520 is configured to determine a change of a downhole environment based on data from the sensors 510. As an example, the problem of inorganic or organic scale growth in wellbores may be determined by the processing device 520 using data from the sensors 510. Scale growth restrictions grow over time on internal surfaces within a wellbore, increasing the friction factor as a tool is moved in a well. By comparing the friction factor in a wellbore during one instance of well intervention to the friction factor in the wellbore during another instance of well intervention, the processing device 520 may be able to identify an increase in friction at certain locations, leading to a probability indication that scale is forming. As another example a declining reservoir pressure or an increase in water cut may be identified by the processing device 520 using data from the sensors 510. Either of these conditions can be identified by comparing the reservoir pressure profile (e.g., pressure vs. depth) in a well at one time during a well intervention with a later data set taken some time later. If the reservoir pressure declines, the later readings will be lower.While the processing device 520 is discussed as determining the change in the downhole environment, in other embodiments the various data from the sensors 510 obtained over time may be provided to, for example, processing device 220 that then determines the change in the downhole environment. In yet other embodiments, the processing device 520 performs a subset of the processes for determining changes in the downhole environment and provides its interim results to, for example, the processing device 220 that completes the determination of changes in the downhole environment.In various embodiments, the operating tool may be used to perform one or more standard sequences of operations followed by movement to another location where the standard sequence of operations is repeated. Each element of this repetitive processing may be referred to herein as a tool gesture, and each tool gesture may have an expected time to complete. Further, an expected set of information from the sensors 510 indicating each of the tool gestures is maintained in the memory 530. FIG. 8 which is more fully discussed below shows an example of such an expected set of information from the sensors 510 corresponding to a number of different tool gestures.In one or more embodiments, the processing device 520 may be configured to monitor and record the motion status of the operating tool using one or more of the sensors 510. The monitored and recorded motion status of the operating tool includes both motion within a wellbore and transit between well sites and is stored in the memory 530 as a tool gesture. The recorded motion status may be categorized into job activities at specific times into subgroups such as, for example, motionless (i.e., non-productive time), respective above ground operations, and respective downhole activities. The respective above ground operations may include, but are not limited to, equipment preparation (e.g., tool bottom hole assembly make up), tool assembly (e.g., rig up), pick up tool and lubricate, lubricator land on wellhead, lubricator pressure test (e.g., pressure test), open well, close well, bleed off / open lubricator, rig down lubricator, and tool disassembly (e.g., operating tool break out), The respective downhole activities may include, but are not limited to, run in hole, run through restriction, jarring operation, mission at depth, tool stuck (e.g., stuck in hole), freefall (e.g., tool lost in hole), and cable cycling fatigue warning.The actions in each of the subgroups are indicated when a combination of data from the sensors 510 meet a predefined criteria. Turning to FIG. 8, a table 800 of tool gestures (i.e., job activities) for an example operating tool are shown in relation to a combination of data expected from the sensors 510. In particular, job gestures are shown in a column 810 and corresponding data from the sensors 510 are shown in columns 820. The columns 820 include: a column 821 for data from the 3-axis acceleration sensor 514, a column 822 for data from the 3-axis inclination sensor 516, a column 823 for data from the 3-axis magnetometer sensor 515, a column 824 for data from the pressure sensor 512, a column 825 for data from the temperature sensor 513, a column 826 for data from the strain gauge sensor 511, a column 827 for data from a shock sensor (not shown), and a column 828 for data from the capacitance sensor 517. As shown in the table 800, each row shows a particular tool gesture in the column 810 and an expected data output from the sensors listed in columns 820 for the particular tool gesture.Returning to FIG. 5, the processing device 520 may compare the job activities for the operating tool with an expected set of tool gestures to determine and / or evaluate activity efficiency and performance of a given job or performance by a given operator and / or vendor. This information may be gathered during use of the operating tool in a variety of operations and over an extended period of time and used to calculate an efficiency and / or determine a competence of an operator and / or vendor using the operating tool.In some embodiments, the memory 530 stores a number of standard sequences of operations each including a number of processing steps. An expected processing time and a set of information expected from sensors 510 is included for each of the processing steps. In such embodiments, the processing device 520 may record an actual processing time used to complete individual steps of a standard sequence of operations for the operating tool and time that the operating tool remained motionless (i.e., non-productive time). The processing device 520 stores the recorded times in the memory 530.In some embodiments, each of the standard sequences of operations and corresponding actual recorded times may be stored in the memory 530 in a table similar to that discussed below in relation to FIG. 9 Turning to FIG. 9, a table 900 includes a column 910 of tool gestures expected for a given standard sequence of operations. For each tool gesture in the column 910 there is: an expected processing time in a column 920, an actual processing time in a column 940, a variance information (i.e., a difference between the time in the column 920 and the time in the column 940) in a column 930, and a percentage of overall time spent in a column 950.In some embodiments, these recorded times may be transmitted to the processing device 220 where they are used to generate a graphic showing the usage of the operating tool. Such a graphic may be, for example, a pie chart that allows a supervisor of the operating tool to quickly evaluate whether the operating tool is being used efficiently.Returning to FIG. 5, the processing device 520 may compare the recorded times with corresponding expected processing times accessed from the memory 530 for each of the processing steps. Using the time recorded for performing different steps of the standard sequence of operations and time recorded for when the operating tool was motionless (i.e., non-productive time) over a single deployment of the operating tool or over an extended period of time including different deployments of the operating tool, the processing device 520 may calculate a variance of the actual time required to complete steps to the corresponding expected processing times. The processing device 520 stores this variance information to the memory 530. In some embodiments, the variance information may be stored in a table similar to that discussed below in relation to FIG. 9.The aforementioned variance information may be used by processing device 520 to evaluate activity efficiency and performance of a given operational step by a given operating tool, operator, and / or vendor. As an example, the variance may be divided by the expected processing time to yield an efficiency value. In some embodiments, variance information corresponding to a number of instances of the given operational step are combined and the efficiency value is calculated based upon the combined data. In other embodiments, variance information corresponding to a number of different operational steps and / or multiple instances of one or more of the operational steps are combined and the efficiency value is calculated based upon the combined data. The process of calculating the efficient value may rely upon information gathered over an extended period of time including different deployments of the operating tool to generate an overall efficiency of the given operating tool, operator, and / or vendor.As another example, processing device 520 may compare information from sensors 510 to determine ongoing behavior corresponding to a certain processing step of one of the standard sequences of operations over an extended period. This comparison may be used by processing device 520 to determine if the sequence of operations performed by the operating tool substantially match one of the number of standard sequences of operations in memory 530. Where there is a substantial match, it is assumed that the operating tool is being used appropriately. Alternatively, where a substantial match is not found, an exception is noted and further investigation of the health status of the downhole tool and / or competence of the vendor may be investigated. This information may be gathered over an extended period of time where the operating tool is used in many circumstances to determine competence of an operator and / or vendor.As mentioned above, while the processing device 520 is discussed as performing the various processes, in other embodiments the various data from the sensors 510 obtained over time may be provided to, for example, the processing device 220 that then performs the various processes of determining variance information and / or efficiencies. In yet other embodiments, the processing device 520 performs a subset of the processes and provides its interim results to, for example, the processing device 220 that completes the processes for determining various information and / or efficiencies.

[0059] FIG. 6 is a block diagram of a computer system 600 that may be used in place of the processing device 220. The computer system 600 provides computational functionalities associated with described algorithms, methods, functions, processes, flows, and procedures as described in the instant disclosure, according to an implementation.

[0060] The computer system 600 includes a computer 602 which is communicably coupled with a network 630. The illustrated computer 602 is intended to encompass any computing device such as a high-performance computing (HPC) device, a server, desktop computer, laptop / notebook computer, wireless data port, smart phone, personal data assistant (PDA), tablet computing device, one or more processors within these devices, or any other suitable processing device, including both physical or virtual instances (or both) of the computing device. Additionally, the computer 602 may include a computer that includes an input device, such as a keypad, keyboard, touch screen, or other device that can accept user information, and an output device that conveys information associated with the operation of the computer 602, including digital data, visual, or audio information (or a combination of information), or a GUI.

[0061] The computer 602 can serve in a role as a client, network component, a server, a database or other persistency, or any other component (or a combination of roles) of a computer system for performing the subject matter described in the instant disclosure. The illustrated computer 602 is communicably coupled with a network 630. In some implementations, one or more components of the computer 602 may be configured to operate within environments, including cloud-computing-based, local, global, or other environment (or a combination of environments).

[0062] At a high level, the computer 602 is an electronic computing device operable to receive, transmit, process, store, or manage data and information associated with the described subject matter. According to some implementations, the computer 602 may also include or be communicably coupled with an application server, e-mail server, web server, caching server, streaming data server, business intelligence (BI) server, or other server (or a combination of servers).

[0063] The computer 602 can receive requests over network 630 from a client application (for example, executing on another computer 602) and responding to the received requests by processing the said requests in an appropriate software application. In addition, requests may also be sent to the computer 602 from internal users (for example, from a command console or by other appropriate access method), external or third-parties, other automated applications, as well as any other appropriate entities, individuals, systems, or computers.

[0064] Each of the components of the computer 602 can communicate using a system bus 603. In some implementations, any or all of the components of the computer 602, both hardware or software (or a combination of hardware and software), may interface with each other or the interface 604 (or a combination of both) over the system bus 603 using an application programming interface (API) 612 or a service layer 613 (or a combination of the API 612) and service layer 613. The API 612 may include specifications for routines, data structures, and object classes. The API 612 may be either computer-language independent or dependent and refer to a complete interface, a single function, or even a set of APIs. The service layer 613 provides software services to the computer 602 or other components (whether or not illustrated) that are communicably coupled to the computer 602. The functionality of the computer 602 may be accessible for all service consumers using this service layer. Software services, such as those provided by the service layer 613, provide reusable, defined business functionalities through a defined interface. For example, the interface may be software written in JAVA, C++, or other suitable language providing data in extensible markup language (XML) format or other suitable format. While illustrated as an integrated component of the computer 602, alternative implementations may illustrate the API 612 or the service layer 613 as stand-alone components in relation to other components of the computer 602 or other components (whether or not illustrated) that are communicably coupled to the computer 602. Moreover, any or all parts of the API 612 or the service layer 613 may be implemented as child or sub-modules of another software module, enterprise application, or hardware module without departing from the scope of this disclosure.

[0065] The computer 602 includes an interface 604. Although illustrated as a single interface 604 in FIG. 6, two or more interfaces 604 may be used according to particular needs, desires, or particular implementations of the computer 602. The interface 604 is used by the computer 602 for communicating with other systems in a distributed environment that are connected to the network 630. Generally, the interface 604 includes logic encoded in software or hardware (or a combination of software and hardware) and operable to communicate with the network 630. More specifically, the interface 604 may include software supporting one or more communication protocols associated with communications such that the network 630 or interface's hardware is operable to communicate physical signals within and outside of the illustrated computer 602.

[0066] The computer 602 includes at least one computer processor 605. Although illustrated as a single computer processor 605 in FIG. 6, two or more processors may be used according to particular needs, desires, or particular implementations of the computer 602. Generally, the computer processor 605 executes instructions and manipulates data to perform the operations of the computer 602 and any algorithms, methods, functions, processes, flows, and procedures as described in the instant disclosure.

[0067] The computer 602 also includes a memory 606 that holds data for the computer 602 or other components (or a combination of both) that can be connected to the network 630. For example, memory 606 can be a database storing data consistent with this disclosure. Although illustrated as a single memory 606 in FIG. 6, two or more memories may be used according to particular needs, desires, or particular implementations of the computer 602 and the described functionality. While memory 606 is illustrated as an integral component of the computer 602, in alternative implementations, memory 606 can be external to the computer 602.

[0068] The application 607 is an algorithmic software engine providing functionality according to particular needs, desires, or particular implementations of the computer 602, particularly with respect to functionality described in this disclosure. For example, application 607 can serve as one or more components, modules, applications, etc. Further, although illustrated as a single application 607, the application 607 may be implemented as multiple applications 607 on the computer 602. In addition, although illustrated as integral to the computer 602, in alternative implementations, the application 607 can be external to the computer 602.

[0069] There may be any number of computers 602 associated with, or external to, a computer system containing computer 602, each computer 602 communicating over network 630. Further, the term “client,”“user,” and other appropriate terminology may be used interchangeably as appropriate without departing from the scope of this disclosure. Moreover, this disclosure contemplates that many users may use one computer 602, or that one user may use multiple computers 602.

[0070] In some embodiments, the computer 602 is implemented as part of a cloud computing system. For example, a cloud computing system may include one or more remote servers along with various other cloud components, such as cloud memory units and edge servers. In particular, a cloud computing system may perform one or more computing operations without direct active management by a user device or local computer system. As such, a cloud computing system may have different functions distributed over multiple locations from a central server, which may be performed using one or more Internet connections. More specifically, a cloud computing system may operate according to one or more service models, such as infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS), mobile “backend” as a service (MBaaS), serverless computing, artificial intelligence (AI) as a service (AIaaS), and / or function as a service (FaaS).

[0071] Turning to FIGS. 7A-7C, flow diagrams 700, 720, 780 show methods in accordance with some embodiments for determining efficiencies and an environment surrounding an operating tool. Following flow diagram 700 of FIG. 7A, a detecting system is secured to an operating tool (block 702). In some embodiments, the attached detecting system is detecting system 500 discussed above.

[0072] Such securing may include, but is not limited to, installing the detecting system in an interior portion of the operating tool or connecting a housing including the detecting system to a operating tool. In some embodiments, the securing results in permanently attaching the detecting system to the operating tool. In other embodiments, the securing results in a non-permanent attachment of the detecting system to the operating tool. Based upon the disclosure provided herein, one of ordinary skill in the art will appreciate a number of approaches that may be used to attach the detecting system to the operating tool in accordance with different embodiments.

[0073] Once attached, the detecting system begins monitoring use of the operating tool (block 704). This includes monitoring sensor data provided from one or more sensors in the detecting system. The sensors may include, but are not limited to, a strain gauge sensor, an acceleration sensor, an inclination sensor, a magnetometer sensor, a pressure sensor, a temperature sensor, and / or a capacitance sensor.

[0074] It is determined whether efficiencies of the operating tool are to be determined (block 708). Where efficiencies are to be determined (block 708), the processes of flow diagram 720 (represented as a dashed block in FIG. 7A and shown in detail in FIG. 7B) are performed. Alternatively, where efficiencies are not to be determined (block 708), it is determined whether a downhole environment is to be determined (block 710). Where a downhole environment is to be determined (block 710), the processes of flow diagram 770 (represented as a dashed block in FIG. 7A and shown in detail in FIG. 7C) are performed.

[0075] Turning to FIG. 7B and following flow diagram 720, monitoring of the operating tool using the detecting system is continued (block 722). As data is received from the sensors in the detecting system, it is determined whether the data corresponds to a known tool gesture (block 724). Table 800 in FIG. 8 described above shows a number of tool gestures in a column 810 and corresponding data from sensors in columns 820.

[0076] Where the sensor data matches a known tool gesture (block 724), a tool gesture timer is reset (i.e., started) (block 726). This tool gesture timer times the period when the operating tool remains in the identified tool gesture. The sensor data is continually monitored to determine whether a new tool gestured is identified (i.e., the tool gesture changes to a different tool gesture) (block 728). Where a new tool gesture is not identified (block 728), the tool gesture timer continues increasing. Alternatively, where a new tool gesture is identified (block 728), the previously identified tool gesture is recorded to memory along with the time indicated on the tool gestured timer (i.e., the time to complete the previously identified tool gesture) (block 730). In addition, the tool gesture timer is reset to start timing the newly identified tool gesture. The recorded time may be stored to a table in a memory. FIG. 9 described above shows table 900 including actual times recorded in relation to each tool gesture.

[0077] In addition, the previously identified tool gesture is assembled into a plurality of recent tool gestures (block 732). This plurality of recent tool gestures is organized into a sequence of tool gestures or operations representing a current process. The sequence of the plurality of recent tool gestures is compared with one or more standard sequences of operations to determine whether the sequence of the plurality of recent tool gestures matches a standard sequence of operations (block 734). Where no match is found (block 734), the process reverts to block 728).

[0078] Alternatively, where a match is found (blocks 734), a variance between a time to complete each tool gesture in the plurality of tool gestures and a corresponding expected time include in the matching standard sequence of operations is calculated (block 736). FIG. 9 described above shows table 900 including variances and corresponding actual times and expected times for each tool gesture.

[0079] An efficiency for each tool gesture of the ongoing operation is calculated (block 738). The efficiency for each tool gesture of the ongoing operation may be represented in a number of manners. In one embodiment, the efficiency is simply the calculated variance. In other embodiments, the efficiency is calculated as the actual time divided by the expected time. Based upon the disclosure provided herein, one of ordinary skill in the art will recognize a variety of manners in which the efficiency for each tool gesture of the ongoing operation may be represented in accordance with different embodiments. This efficiency is recorded in the memory along with the identity of an operator using the operating tool.

[0080] An overall efficiency of the entirety of the plurality of tool gestures is calculated (block 740). The efficiency of the entirety of the plurality of tool gestures may be represented in a number of manners. In one embodiment, the efficiency is simply a sum of the calculated variances for each tool gesture in the ongoing operation. In other embodiments, the efficiency is calculated by summing the actual times for each tool gesture in the ongoing operation and summing the expected times for each tool gesture in the ongoing operation, and then dividing the sum of actual times by the sum of expected times. Based upon the disclosure provided herein, one of ordinary skill in the art will recognize a variety of manners in which the overall efficiency of the entirety of the plurality of tool gestures may be represented in accordance with different embodiments. This efficiency is recorded in the memory along with the identity of an operator using the operating tool.

[0081] It is determined if the operating tool is not moving in such a way that it indicates that the operating tool has completed a series of operations and is now awaiting its next deployment (i.e., it is not in productive use) (block 742). Where the operating tool is not between deployments (block 742), the processing reverts to block 728.

[0082] Alternatively, the efficiency of the operating tool is calculated over a defined period of time (block 744). The efficiency of the operating tool over the defined period of time may be represented in a number of manners. In one embodiment, the efficiency of the operating tool over the defined period of time is calculated by summing all of the non-productive time over the defined period of time and dividing that sum by the defined period of time. In another embodiment, the efficiency of the operating tool over the defined period of time is calculated by summing all of the variances over the defined period of time. Based upon the disclosure provided herein, one of ordinary skill in the art will recognize a variety of manners in which the efficiency of the operating tool over the defined period of time may be represented in accordance with different embodiments. This efficiency is recorded in the memory.

[0083] An efficiency of the operator using the operating tool over a defined period of time is calculated (block 746). This may be done by accessing all recorded uses associated with the operator, and calculating an efficiency based upon the accessed information. The efficiency of the operator over the defined period of time may be represented in a number of manners. In one embodiment, the efficiency of the operator over the defined period of time is calculated by summing all of the non-productive time over the defined period of time and dividing that sum by the defined period of time. In another embodiment, the efficiency of the operator over the defined period of time is calculated by summing all of the variances over the defined period of time. Based upon the disclosure provided herein, one of ordinary skill in the art will recognize a variety of manners in which the efficiency of the operator over the defined period of time may be represented in accordance with different embodiments. This efficiency is recorded in the memory along with the identity of the operator to which it applies.

[0084] Turning to FIG. 7C and following flow diagram 770, the operating tool is suspended in a first fluid (block 772), and while suspended substantially motionless in the first fluid a weight of the operating tool is measured (block 774). The weight may be determined based on sensor data from a strain gauge sensor in the detecting system, and the motion (or lack of motion) may be determined by a 3-axis acceleration sensor in the detecting system. In some embodiments, the first fluid is air.

[0085] The operating tool is additionally suspended in a second fluid (block 776), and while suspended substantially motionless in the second fluid a weight of the operating tool is measured (block 778). The weight may be determined based on sensor data from a strain gauge sensor in the detecting system, and the motion (or lack of motion) may be determined by a 3-axis acceleration sensor in the detecting system. In some embodiments, the second fluid is fresh water.

[0086] A volume of the operating tool is determined using a combination of the weight of the operating tool in the first fluid, the weight of the operating tool in the second fluid, the density of the first fluid, and the density of the second fluid (block 780). In some embodiments, the volume of the operating tool can be calculated using the following equation:Vt=(Fltw-Flta)ρw⁢gwhere Vt is the tool volume, Fltw is the line tension in water which can be found by measurement using a strain gauge, Flta is the line tension in air which can be found by measurement using a strain gauge, ρw is the density freshwater (i.e., a known or assumed constant), and g is acceleration or gravity in some cases.Once the operating tool is deployed in a wellbore, a density of fluid surrounding the operating tool is determined based upon a sensed weight of the operating tool and the volume of the operating tool. (block 782). An equation that can be used for calculating density of the fluid using tool mass and the tool volume is:ρf=(Fltf-mg)gVt,where ρf is the density of well fluid to be calculated, Fltf is the line tension in well fluid which is measured (i.e., measured parameter at rope socket, static, variable), m is the mass of the tool measured at the start of the process in the air, g is acceleration or in some cases gravity, and V, is the tool volume.A vertical depth of the operating tool is determined based upon the density of the fluid surrounding the operating tool and a pressure data from a pressure sensor in the detecting system (block 784). In some embodiments, the depth may be calculated in accordance with the following equation:htvd=(Psensor-PSIWHP)ρf⁢g,where htvd is the height (i.e., true vertical depth) of the fluid, Psensor is the pressure at the sensor which is a measured variable, PSIWHP is the shut in well head pressure measured at the start of the job when the well is opened, ρf is the density of the well fluid that was previously calculated, and g is acceleration or in some cases gravity.Turning to FIG. 10, a flow diagram 1000 shows a method for determining different types of efficiencies in accordance with one or more embodiments. In some embodiments, the different types of efficiencies discussed in relation to flow diagram 1000 may be determined using efficiency and operator information recorded in memory as part of the processes discussed above in relation to FIG. 7B.Following flow diagram 1000, operating efficiencies of a plurality of operations are obtained (block 1010). In some embodiments, the aforementioned operating efficiencies are obtained by calculating an average of different overall efficiencies for a number of the plurality of tool gestures described above in relation to block 740 of FIG. 7C. Thus, the operating tool is used to perform a number of different plurality of tool gestures and the overall efficiency for each of the plurality of tool gestures are averaged to yield the operating efficiencies of a plurality of operations. In some embodiments, each of the plurality of tool gestures includes the same sequence of tool gestures corresponding to a single operation type. In other embodiments, some of the plurality of tool gestures include a different sequence of tool gestures from a sequence of tool gestures in other of the plurality of tool gestures (i.e., corresponding to different operation types).A trend of changes in efficiency of an operator is determined (block 1020). This may be done, for example, by accessing efficiency information recorded to memory in the processes discussed above in relation to FIG. 7C for a particular operator, and determining whether the particular operator's efficiency is improving or degrading.

[0092] Operating efficiencies for a plurality of operators is obtained (block 1030. This may be done, for example, by accessing efficiency information recorded to memory in the processes discussed above in relation to FIG. 7C for two or more operators. In some cases, this efficiency information may be compared to identify that one operator is more efficient than another (block 1040).

[0093] Turning to FIG. 11, a flow diagram 1100 shows a method in accordance with some embodiments for characterizing usage of an operating tool configured for use within a wellbore. Following flow diagram 1100, a plurality of instances of a first sensor data from a first sensor and a second sensor data from a second sensor are received by a processing device (block 1110). The first sensor and the second sensor are attached to the operating tool. A plurality of tool gestures is identified by the processing device (block 1120). Such identification is done using a combination of at least instances of the first sensor data and instances of the second sensor data from the plurality of instances. A time period for each of the plurality of tool gestures is determined by the processing device based on the combination of at least instances of the first sensor data and instances of the second sensor data (block 1130). An efficiency is determined by the processing device using the time period for each of the plurality of tool gestures and a respective expected time period for each of the plurality of tool gestures (block 1140).

[0094] Although only a few example embodiments have been described in detail above, those skilled in the art will readily appreciate that many modifications are possible in the example embodiments without materially departing from this invention. Accordingly, all such modifications are intended to be included within the scope of this disclosure as defined in the following claims.

Claims

1. A system for evaluating usage efficiency of an operating tool configured for use within a wellbore, the system comprising:a detecting system configured to be secured to the operating tool, the detecting system comprising:a first sensor, wherein the first sensor is of a first sensor type and provides a first sensor data; anda second sensor, wherein the second sensor is of a second sensor type and provides a second sensor data;a processing device configured to:receive a plurality of instances of each of the first sensor data and the second sensor data, wherein each of the plurality of instances corresponds to a respective time;use a combination of at least instances of the first sensor data and instances of the second sensor data from the plurality of instances to identify a plurality of tool gestures;determine a time period for each of the plurality of tool gestures based on the combination of at least instances of the first sensor data and instances of the second sensor data; anddetermine an efficiency using the time period for each of the plurality of tool gestures and a respective expected time period for each of the plurality of tool gestures.

2. The system of claim 1, wherein the first sensor type is selected from a group consisting of: a strain gauge sensor, an acceleration sensor, an inclination sensor, a magnetometer sensor, a pressure sensor, a temperature sensor, and a capacitance sensor.

3. The system of claim 1, wherein the plurality of tool gestures is a first plurality of tool gestures, wherein the first plurality of tool gestures includes at least two tool gestures in a first sequence, wherein the processing device is communicably coupled to a memory that has stored therein a standard sequence of operations, wherein the standard sequence of operations includes a second plurality of tool gestures and the respective expected time period for each of the second plurality of tool gestures, wherein the second plurality of tool gestures includes at least two tool gestures in a second sequence, and wherein the processing device is further configured to:compare the at least two tool gestures of the first plurality of tool gestures and the first sequence with the at least two tool gestures of the second plurality of tool gestures and the second sequence; andbased at least in part on the comparison, determine that the at least two tool gestures of the first plurality of tool gestures and the first sequence correspond to the at least two tool gestures of the second plurality of tool gestures and the second sequence.

4. The system of claim 1, wherein one or more of the plurality of tool gestures is selected from a group consisting of: an above ground operation, a downhole operation, and a non-productive time.

5. The system of claim 4, wherein the above ground operation is selected from a group consisting of: an equipment preparation, a tool assembly, a pick up tool and lubricate, a lubricator land on wellhead, a lubricator pressure test, an open well, a close well, a bleed off / open lubricator, a rig down lubricator, and a tool disassembly.

6. The system of claim 4, wherein the downhole operation is selected from a group consisting of: a run in hole, a run through restriction, a jarring operation, a mission at depth, a tool stuck, a freefall, and a cable cycling fatigue warning.

7. The system of claim 1, wherein the processing device is disposed apart from the operating tool and outside of the wellbore.

8. The system of claim 1, wherein the receiving the plurality of instances of each of the first sensor data and the second sensor data, using the combination of at least instances of the first sensor data and instances of the second sensor data from the plurality of instances to identify the plurality of tool gestures, determining the time period for each of the plurality of tool gestures based on the combination of at least instances of the first sensor data and instances of the second sensor data, and determining the efficiency are together operations of the processing device; wherein the processing device includes a first processing device and a second processing device; wherein the first processing device is disposed apart from the operating tool and outside of the wellbore, and wherein the second processing device is incorporated with the first sensor and the second sensor in the detecting system, and wherein at least a first subset of operations of the processing device is performed by the first processing device and at least a second subset of operations of the processing device is performed by the second processing device.

9. The system of claim 1, wherein the processing device is incorporated with the first sensor and the second sensor in the detecting system configured to be secured to the operating tool.

10. The system of claim 9, wherein the first sensor type is a weight sensor and the first sensor data is a weight data, and wherein the processing device is further configured to:receive the weight data when the operating tool is stationary in a first fluid to yield a first weigh data;receive the weight data when the operating tool is stationary in a second fluid to yield a second weight data;calculate a volume of the operating tool based on a combination of the first weight data and the second weight data; anddetermine a density of a fluid in the wellbore based upon a combination of the first weight data, the second weight data, and the volume.

11. The system of claim 10, wherein the first fluid is air and the second fluid is fresh water.

12. The system of claim 10, wherein the second sensor type is a pressure sensor and the second sensor data is pressure data, and wherein the processing device is further configured to:determine a vertical depth of the operating tool in the wellbore by comparing the density of the fluid in the wellbore with the pressure data from the pressure sensor.

13. The system of claim 1, wherein the plurality of tool gestures is a first plurality of tool gestures, wherein the combination of at least instances of the first sensor data and instances of the second sensor data from the plurality of instances is a first combination of at least instances of the first sensor data and instances of the second sensor data from the plurality of instances, and wherein the processing device is further configured to:use a second combination of at least instances of the first sensor data and instances of the second sensor data from the plurality of instances to identify a second plurality of tool gestures;determine a time period for each of the second plurality of tool gestures based on the second combination of at least instances of the first sensor data and instances of the second sensor data; andwherein determining the efficiency using the time period for each of the plurality of tool gestures and the respective expected time period for each of the plurality of tool gestures comprises:determining a multi-process efficiency using the time period for each of the first plurality of tool gestures, the time period for each of the second plurality of tool gestures, and the respective expected time period for each of the first plurality of tool gestures and each of the second plurality of tool gestures.

14. The system of claim 13, wherein the first plurality of tool gestures correspond to a first standard sequence of operations and the second plurality of tool gestures correspond to a second standard sequence of operations that is different from the first standard sequence of operations.

15. The system of claim 1, wherein operation of the operating tool is managed by an operator, and wherein the processing device is further configured to:use the efficiency along with at least one other efficiency for the operator to determine a trend of changes of efficiency for the operator.

16. The system of claim 1, wherein the efficiency is a first efficiency corresponding to a first operator, and wherein the processing device is further configured to:obtain a second efficiency corresponding to a second operator; anddetermine an efficiency comparison between the first operator and the second operator of the operating tool based at least in part on the first efficiency and the second efficiency.

17. A method for characterizing usage of an operating tool configured for use within a wellbore, the method comprising:receiving, by a processing device, a plurality of instances of a first sensor data from a first sensor and a second sensor data from a second sensor, wherein the first sensor and the second sensor are attached to the operating tool;using a combination of at least instances of the first sensor data and instances of the second sensor data from the plurality of instances to identify, by the processing device, a plurality of tool gestures;determining, by the processing device, a time period for each of the plurality of tool gestures based on the combination of at least instances of the first sensor data and instances of the second sensor data; anddetermining, by the processing device, an efficiency using the time period for each of the plurality of tool gestures and a respective expected time period for each of the plurality of tool gestures.

18. The method of claim 17, wherein the first sensor is selected from a group consisting of: a strain gauge sensor, an acceleration sensor, an inclination sensor, a magnetometer sensor, a pressure sensor, a temperature sensor, and a capacitance sensor.

19. The method of claim 17, wherein the plurality of tool gestures is a first plurality of tool gestures, wherein the first plurality of tool gestures includes at least two tool gestures in a first sequence, wherein the processing device communicably coupled to a memory that has stored therein a standard sequence of operations, wherein the standard sequence of operations includes a second plurality of tool gestures and the respective expected time period for each of the plurality of tool gestures, wherein the second plurality of tool gestures includes at least two tool gestures in a second sequence, the method further comprising:accessing, by the processing device, the standard sequence of operations from the;comparing, by the processing resource, at least two tool gestures of the first plurality of tool gestures and the first sequence with the at least two tool gestures of the second plurality of tool gestures and the second sequence; andbased at least in part on the comparison, determining, by the processing resource, that the at least two tool gestures of the first plurality of tool gestures and the first sequence correspond to the at least two tool gestures of the second plurality of tool gestures and the second sequence.

20. The method of claim 17, wherein one or more of the plurality of tool gestures is selected from a group consisting of: a non-productive time, an equipment preparation, a tool assembly, a pick up tool and lubricate, a lubricator land on wellhead, a lubricator pressure test, an open well, a close well, a bleed off / open lubricator, a rig down lubricator, a tool disassembly, a run in hole, a run through restriction, a jarring operation, a mission at depth, a tool stuck, a freefall, and a cable cycling fatigue warning.

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