DRILLING OPERATIONS FRAMEWORK
A method may include acquiring real-time data during rig operations that include rig operations for drilling a borehole in a subsurface geologic region using a drillstring that includes a drill bit, where the drillstring includes stands of drill pipe; based on stand statistics, using at least a portion of the real-time data, calibrating a torque and drag model that models torque and drag of the drillstring in the borehole; based on operation statistics, calling for use of the torque and drag model to make a prediction; and, based at least in part on the prediction, detecting an anomaly.
This application claims priority to and the benefit of a U.S. Provisional Application having Ser. No. 63/417,728, filed 20 Oct. 2022, which is incorporated by reference herein in its entirety.
BACKGROUNDA resource field may be an accumulation, pool or group of pools of one or more resources (e.g., oil, gas, oil and gas) in a subsurface environment. A resource field may include at least one reservoir. A reservoir may be shaped in a manner that may trap hydrocarbons and may be covered by an impermeable or sealing rock. A bore may be drilled into an environment where the bore may be utilized to form a well that may be utilized in producing hydrocarbons from a reservoir.
A rig may be a system of components that may be operated to form a bore in an environment, to transport equipment into and out of a bore in an environment, etc. As an example, a rig may include a system that may be used to drill a bore and to acquire information about an environment, about drilling, etc. A resource field may be an onshore field, an offshore field or an on- and offshore field. A rig may include components for performing operations onshore and/or offshore. A rig may be, for example, vessel-based, offshore platform-based, onshore, etc.
Field planning may occur over one or more phases, which may include an exploration phase that aims to identify and assess an environment (e.g., a prospect, a play, etc.), which may include drilling of one or more bores (e.g., one or more exploratory wells, etc.). Other phases may include appraisal, development and production phases.
SUMMARYA method may include acquiring real-time data during rig operations that include rig operations for drilling a borehole in a subsurface geologic region using a drillstring that includes a drill bit, where the drillstring includes stands of drill pipe; based on stand statistics, using at least a portion of the real-time data, calibrating a torque and drag model that models torque and drag of the drillstring in the borehole; based on operation statistics, calling for use of the torque and drag model to make a prediction; and, based at least in part on the prediction, detecting an anomaly. A system may include a processor; memory accessible by the processor; processor-executable instructions stored in the memory and executable to instruct the system to: acquire real-time data during rig operations that include rig operations for drilling a borehole in a subsurface geologic region using a drillstring that includes a drill bit, where the drillstring includes stands of drill pipe; based on stand statistics, using at least a portion of the real-time data, calibrate a torque and drag model that models torque and drag of the drillstring in the borehole; based on operation statistics, call for use of the torque and drag model to make a prediction; and, based at least in part on the prediction, detect an anomaly.
One or more computer-readable storage media may include processor-executable instructions to instruct a computing system to: acquire real-time data during rig operations that include rig operations for drilling a borehole in a subsurface geologic region using a drillstring that includes a drill bit, where the drillstring includes stands of drill pipe; based on stand statistics, using at least a portion of the real-time data, calibrate a torque and drag model that models torque and drag of the drillstring in the borehole; based on operation statistics, call for use of the torque and drag model to make a prediction; and, based at least in part on the prediction, detect an anomaly. Various other apparatuses, systems, methods, etc., are also disclosed.
This summary is provided to introduce a selection of concepts that are further described below in the detailed description. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used as an aid in limiting the scope of the claimed subject matter.
Features and advantages of the described implementations may be more readily understood by reference to the following description taken in conjunction with the accompanying drawings.
The following description includes the best mode presently contemplated for practicing the described implementations. This description is not to be taken in a limiting sense, but rather is made merely for the purpose of describing the general principles of the implementations. The scope of the described implementations should be ascertained with reference to the issued claims.
The equipment 170 includes a platform 171, a derrick 172, a crown block 173, a line 174, a traveling block assembly 175, drawworks 176 and a landing 177 (e.g., a monkeyboard). As an example, the line 174 may be controlled at least in part via the drawworks 176 such that the traveling block assembly 175 travels in a vertical direction with respect to the platform 171. For example, by drawing the line 174 in, the drawworks 176 may cause the line 174 to run through the crown block 173 and lift the traveling block assembly 175 skyward away from the platform 171; whereas, by allowing the line 174 out, the drawworks 176 may cause the line 174 to run through the crown block 173 and lower the traveling block assembly 175 toward the platform 171. Where the traveling block assembly 175 carries pipe (e.g., casing, etc.), tracking of movement of the traveling block 175 may provide an indication as to how much pipe has been deployed.
A derrick may be a structure used to support a crown block and a traveling block operatively coupled to the crown block at least in part via line. A derrick may be pyramidal in shape and offer a suitable strength-to-weight ratio. A derrick may be movable as a unit or in a piece by piece manner (e.g., to be assembled and disassembled).
As an example, drawworks may include a spool, brakes, a power source and assorted auxiliary devices. Drawworks may controllably reel out and reel in line. Line may be reeled over a crown block and coupled to a traveling block to gain mechanical advantage in a “block and tackle” or “pulley” fashion. Reeling out and in of line may cause a traveling block (e.g., and whatever may be hanging underneath it), to be lowered into or raised out of a bore. Reeling out of line may be powered by gravity and reeling in by a motor, an engine, etc. (e.g., an electric motor, a diesel engine, etc.).
As an example, a crown block may include a set of pulleys (e.g., sheaves) that may be located at or near a top of a derrick or a mast, over which line is threaded. A traveling block may include a set of sheaves that may be moved up and down in a derrick or a mast via line threaded in the set of sheaves of the traveling block and in the set of sheaves of a crown block. A crown block, a traveling block and a line may form a pulley system of a derrick or a mast, which may enable handling of heavy loads (e.g., drillstring, pipe, casing, liners, etc.) to be lifted out of or lowered into a bore. As an example, line may be about a centimeter to about five centimeters in diameter as, for example, steel cable. Through use of a set of sheaves, such line may carry loads heavier than the line could support as a single strand.
As an example, a derrickman may be a rig crew member that works on a platform attached to a derrick or a mast. A derrick may include a landing on which a derrickman may stand. As an example, such a landing may be about 10 meters or more above a rig floor. In an operation referred to as trip out of the hole (TOH), a derrickman may wear a safety harness that enables leaning out from the work landing (e.g., monkeyboard) to reach pipe in located at or near the center of a derrick or a mast and to throw a line around the pipe and pull it back into its storage location (e.g., fingerboards), for example, until it a time at which it may be desirable to run the pipe back into the bore. As an example, a rig may include automated pipe-handling equipment such that the derrickman controls the machinery rather than physically handling the pipe.
As an example, a trip may refer to the act of pulling equipment from a bore and/or placing equipment in a bore. As an example, equipment may include a drillstring that may be pulled out of a hole and/or placed or replaced in a hole. As an example, a pipe trip may be performed where a drill bit has dulled or has otherwise ceased to drill efficiently and is to be replaced.
In the example system of
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The wellsite system 200 may provide for operation of the drillstring 225 and other operations. As shown, the wellsite system 200 includes the platform 211 and the derrick 214 positioned over the borehole 232. As mentioned, the wellsite system 200 may include the rotary table 220 where the drillstring 225 pass through an opening in the rotary table 220.
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As to a top drive example, the top drive 240 may provide functions performed by a kelly and a rotary table. The top drive 240 may turn the drillstring 225. As an example, the top drive 240 may include one or more motors (e.g., electric and/or hydraulic) connected with appropriate gearing to a short section of pipe called a quill, that in turn may be screwed into a saver sub or the drillstring 225 itself. The top drive 240 may be suspended from the traveling block 211, so the rotary mechanism is free to travel up and down the derrick 214. As an example, a top drive 240 may allow for drilling to be performed with more joint stands than a kelly/rotary table approach.
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The mud pumped by the pump 204 into the drillstring 225 may, after exiting the drillstring 225, form a mudcake that lines the wellbore which, among other functions, may reduce friction between the drillstring 225 and surrounding wall(s) (e.g., borehole, casing, etc.). A reduction in friction may facilitate advancing or retracting the drillstring 225. During a drilling operation, the entire drillstring 225 may be pulled from a wellbore and optionally replaced, for example, with a new or sharpened drill bit, a smaller diameter drillstring, etc. As mentioned, the act of pulling a drillstring out of a hole or replacing it in a hole is referred to as tripping. A trip may be referred to as an upward trip or an outward trip or as a downward trip or an inward trip depending on trip direction.
As an example, consider a downward trip where upon arrival of the drill bit 226 of the drillstring 225 at a bottom of a wellbore, pumping of the mud commences to lubricate the drill bit 226 for purposes of drilling to enlarge the wellbore. As mentioned, the mud may be pumped by the pump 204 into a passage of the drillstring 225 and, upon filling of the passage, the mud may be used as a transmission medium to transmit energy, for example, energy that may encode information as in mud-pulse telemetry.
As an example, mud-pulse telemetry equipment may include a downhole device configured to effect changes in pressure in the mud to create an acoustic wave or waves upon which information may modulated. In such an example, information from downhole equipment (e.g., one or more modules of the drillstring 225) may be transmitted uphole to an uphole device, which may relay such information to other equipment for processing, control, etc.
As an example, telemetry equipment may operate via transmission of energy via the drillstring 225 itself. For example, consider a signal generator that imparts coded energy signals to the drillstring 225 and repeaters that may receive such energy and repeat it to further transmit the coded energy signals (e.g., information, etc.).
As an example, the drillstring 225 may be fitted with telemetry equipment 252 that includes a rotatable drive shaft, a turbine impeller mechanically coupled to the drive shaft such that the mud may cause the turbine impeller to rotate, a modulator rotor mechanically coupled to the drive shaft such that rotation of the turbine impeller causes said modulator rotor to rotate, a modulator stator mounted adjacent to or proximate to the modulator rotor such that rotation of the modulator rotor relative to the modulator stator creates pressure pulses in the mud, and a controllable brake for selectively braking rotation of the modulator rotor to modulate pressure pulses. In such example, an alternator may be coupled to the aforementioned drive shaft where the alternator includes at least one stator winding electrically coupled to a control circuit to selectively short the at least one stator winding to electromagnetically brake the alternator and thereby selectively brake rotation of the modulator rotor to modulate the pressure pulses in the mud.
In the example of
The assembly 250 of the illustrated example includes a logging-while-drilling (LWD) module 254 (e.g., a LWD tool), a measuring-while-drilling (MWD) module 256 (e.g., a MWD tool), an optional module 258, a roto-steerable system (RSS) and/or motor 260, and the drill bit 226. Such components or modules may be referred to as tools where a drillstring may include a plurality of tools.
As to a RSS, it involves technology utilized for directional drilling. Directional drilling involves drilling into the Earth to form a deviated bore such that the trajectory of the bore is not vertical; rather, the trajectory deviates from vertical along one or more portions of the bore. As an example, consider a target that is located at a lateral distance from a surface location where a rig may be stationed. In such an example, drilling may commence with a vertical portion and then deviate from vertical such that the bore is aimed at the target and, eventually, reaches the target. Directional drilling may be implemented where a target may be inaccessible from a vertical location at the surface of the Earth, where material exists in the Earth that may impede drilling or otherwise be detrimental (e.g., consider a salt dome, etc.), where a formation is laterally extensive (e.g., consider a relatively thin yet laterally extensive reservoir), where multiple bores are to be drilled from a single surface bore, where a relief well is desired, etc.
One approach to directional drilling involves a mud motor; however, a mud motor may present some challenges depending on factors such as rate of penetration (ROP), transferring weight to a bit (e.g., weight on bit, WOB) due to friction, etc. A mud motor may be a positive displacement motor (PDM) that operates to drive a bit (e.g., during directional drilling, etc.). A PDM operates as drilling fluid is pumped through it where the PDM converts hydraulic power of the drilling fluid into mechanical power to cause the bit to rotate.
As an example, a PDM may operate in a combined rotating mode where surface equipment is utilized to rotate a bit of a drillstring (e.g., a rotary table, a top drive, etc.) by rotating the entire drillstring and where drilling fluid is utilized to rotate the bit of the drillstring. In such an example, a surface RPM (SRPM) may be determined by use of the surface equipment and a downhole RPM of the mud motor may be determined using various factors related to flow of drilling fluid, mud motor type, etc. As an example, in the combined rotating mode, bit RPM may be determined or estimated as a sum of the SRPM and the mud motor RPM, assuming the SRPM and the mud motor RPM are in the same direction.
As an example, a PDM mud motor may operate in a so-called sliding mode, when the drillstring is not rotated from the surface to drive a drill bit in a particular cutting direction. In such an example, a bit RPM may be determined or estimated based on the RPM of the mud motor. As an example, during a sliding mode, oscillation of a drillstring may be provided by surface equipment, for example, to oscillate the drillstring in a clockwise and a counter-clockwise direction, which may, for example, help to reduce risk of sticking, etc.
An RSS may drill directionally where there is continuous rotation from surface equipment, which may alleviate the sliding of a steerable motor (e.g., a PDM). An RSS may be deployed when drilling directionally (e.g., deviated, horizontal, or extended-reach wells). An RSS may aim to minimize interaction with a borehole wall, which may help to preserve borehole quality. An RSS may aim to exert a relatively consistent side force akin to stabilizers that rotate with the drillstring or orient the bit in the desired direction while continuously rotating at the same number of rotations per minute as the drillstring.
The LWD module 254 may be housed in a suitable type of drill collar and may contain one or a plurality of selected types of logging tools. It will also be understood that more than one LWD and/or MWD module may be employed. Where the position of a module is mentioned, as an example, it may refer to a module at the position of the LWD module 254, the MWD module 256, etc. An LWD module may include capabilities for measuring, processing, and storing information, as well as for communicating with the surface equipment. In the illustrated example, the LWD module 254 may include a seismic measuring device.
The MWD module 256 may be housed in a suitable type of drill collar and may contain one or more devices for measuring characteristics of the drillstring 225 and the drill bit 226. As an example, the MWD module 256 may include equipment for generating electrical power, for example, to power various components of the drillstring 225. As an example, the MWD module 256 may include the telemetry equipment 252, for example, where the turbine impeller may generate power by flow of the mud; it being understood that other power and/or battery systems may be employed for purposes of powering various components. As an example, the MWD module 256 may include one or more of the following types of measuring devices: a weight-on-bit measuring device, a torque measuring device, a vibration measuring device, a shock measuring device, a stick slip measuring device, a direction measuring device, and an inclination measuring device.
As an example, a drilling operation may include directional drilling where, for example, at least a portion of a well includes a curved axis. For example, consider a radius that defines curvature where an inclination with regard to the vertical may vary until reaching an angle between about 30 degrees and about 60 degrees or, for example, an angle to about 90 degrees or possibly greater than about 90 degrees.
As an example, a directional well may include several shapes where each of the shapes may aim to meet particular operational demands. As an example, a drilling process may be performed on the basis of information as and when it is relayed to a drilling engineer. As an example, inclination and/or direction may be modified based on information received during a drilling process.
As an example, deviation of a bore may be accomplished in part by use of one or more of an RSS, a downhole motor and/or a turbine. As to a motor, for example, a drillstring may include a positive displacement motor (PDM).
As an example, a system may be a steerable system and include equipment to perform a method such as geosteering. As an example, a steerable system may include a PDM or a turbine on a lower part of a drillstring which, just above a drill bit, a bent sub may be mounted. As an example, above a PDM, MWD equipment that provides real time or near real time data of interest (e.g., inclination, direction, pressure, temperature, real weight on the drill bit, torque stress, etc.) and/or LWD equipment may be installed. As to the latter, LWD equipment may make it possible to send to the surface various types of data of interest, including for example, geological data (e.g., gamma ray log, resistivity, density and sonic logs, etc.).
The coupling of sensors providing information on the course of a well trajectory, in real time or near real time, with, for example, one or more logs characterizing the formations from a geological viewpoint, may allow for implementing a geosteering method. Such a method may include navigating a subsurface environment, for example, to follow a desired route to reach a desired target or targets.
As an example, a drillstring may include an azimuthal density neutron (ADN) tool for measuring density and porosity; a MWD tool for measuring inclination, azimuth and shocks; a compensated dual resistivity (CDR) tool for measuring resistivity and gamma ray related phenomena; one or more variable gauge stabilizers; one or more bend joints; and a geosteering tool, which may include a motor and optionally equipment for measuring and/or responding to one or more of inclination, resistivity and gamma ray related phenomena.
As an example, geosteering may include intentional directional control of a wellbore based on results of downhole geological logging measurements in a manner that aims to keep a directional wellbore within a desired region, zone (e.g., a pay zone), etc. As an example, geosteering may include directing a wellbore to keep the wellbore in a particular section of a reservoir, for example, to minimize gas and/or water breakthrough and, for example, to maximize economic production from a well that includes the wellbore.
Referring again to
As an example, one or more of the sensors 264 may be provided for tracking pipe, tracking movement of at least a portion of a drillstring, etc.
As an example, the system 200 may include one or more sensors 266 that may sense and/or transmit signals to a fluid conduit such as a drilling fluid conduit (e.g., a drilling mud conduit). For example, in the system 200, the one or more sensors 266 may be operatively coupled to portions of the standpipe 208 through which mud flows. As an example, a downhole tool may generate pulses that may travel through the mud and be sensed by one or more of the one or more sensors 266. In such an example, the downhole tool may include associated circuitry such as, for example, encoding circuitry that may encode signals, for example, to reduce demands as to transmission. As an example, circuitry at the surface may include decoding circuitry to decode encoded information transmitted at least in part via mud-pulse telemetry. As an example, circuitry at the surface may include encoder circuitry and/or decoder circuitry and circuitry downhole may include encoder circuitry and/or decoder circuitry. As an example, the system 200 may include a transmitter that may generate signals that may be transmitted downhole via mud (e.g., drilling fluid) as a transmission medium.
As an example, one or more portions of a drillstring may become stuck. The term stuck may refer to one or more of varying degrees of inability to move or remove a drillstring from a bore. As an example, in a stuck condition, it might be possible to rotate pipe or lower it back into a bore or, for example, in a stuck condition, there may be an inability to move the drillstring axially in the bore, though some amount of rotation may be possible. As an example, in a stuck condition, there may be an inability to move at least a portion of the drillstring axially and rotationally.
As to the term “stuck pipe”, this term may refer to a portion of a drillstring that cannot be rotated or moved axially. As an example, a condition referred to as “differential sticking” may be a condition whereby the drillstring cannot be moved (e.g., rotated or reciprocated) along the axis of the bore. Differential sticking may occur when high-contact forces caused by low reservoir pressures, high wellbore pressures, or both, are exerted over a sufficiently large area of the drillstring. Differential sticking may have time and financial cost.
As an example, a sticking force may be a product of the differential pressure between the wellbore and the reservoir and the area that the differential pressure is acting upon. This means that a relatively low differential pressure (delta p) applied over a large working area may be just as effective in sticking pipe as may a high differential pressure applied over a small area.
As an example, a condition referred to as “mechanical sticking” may be a condition where limiting or prevention of motion of the drillstring by a mechanism other than differential pressure sticking occurs. Mechanical sticking may be caused, for example, by one or more of junk in the hole, wellbore geometry anomalies, cement, keyseats or a buildup of cuttings in the annulus.
In the example of
As an example, a framework may be implemented within or in a manner operatively coupled to the DELFI cognitive exploration and production (E&P) environment (SLB, Houston, Texas), which is a secure, cognitive, cloud-based collaborative environment that integrates data and workflows with digital technologies, such as artificial intelligence and machine learning. As an example, such an environment may provide for operations that involve one or more frameworks. The DELFI environment may be referred to as the DELFI framework, which may be a framework of frameworks. As an example, the DELFI framework may include various other frameworks, which may include, for example, one or more types of models (e.g., simulation models, etc.).
As an example, a framework may include entities that may include earth entities, geological objects or other objects such as wells, surfaces, reservoirs, etc. Entities may include virtual representations of actual physical entities that are reconstructed for purposes of one or more of evaluation, planning, engineering, operations, etc. Entities may include entities based on data acquired via sensing, observation, etc. (e.g., seismic data and/or other information). An entity may be characterized by one or more properties (e.g., a geometrical pillar grid entity of an earth model may be characterized by a porosity property). Such properties may represent one or more measurements (e.g., acquired data), calculations, etc.
As an example, a framework may include an analysis component that may allow for interaction with a model or model-based results (e.g., simulation results, etc.). As to simulation, a framework may operatively link to or include a simulator such as the ECLIPSE reservoir simulator (SLB, Houston Texas), the INTERSECT reservoir simulator (SLB, Houston Texas), etc.
The aforementioned PETREL framework provides components that allow for optimization of exploration and development operations. The PETREL framework includes seismic to simulation software components that may output information for use in increasing reservoir performance, for example, by improving asset team productivity. Through use of such a framework, various professionals (e.g., geophysicists, geologists, well engineers, reservoir engineers, etc.) may develop collaborative workflows and integrate operations to streamline processes. Such a framework may be considered an application and may be considered a data- driven application (e.g., where data is input for purposes of modeling, simulating, etc.).
As an example, the system 300 may be used to perform one or more workflows. A workflow may be a process that includes a number of worksteps. A workstep may operate on data, for example, to create new data, to update existing data, etc. As an example, a workflow may operate on one or more inputs and create one or more results, for example, based on one or more algorithms. As an example, a system may include a workflow editor for creation, editing, executing, etc. of a workflow. In such an example, the workflow editor may provide for selection of one or more pre-defined worksteps, one or more customized worksteps, etc.
As an example, one or more tools may be utilized in the field to acquire various types of information. For example, consider formation information that may reveal features such as, for example, vugs, dissolution planes (e.g., dissolution along bedding planes), stress-related features, dip events, etc. As an example, a tool may acquire information that may help to characterize a reservoir, which may be a fractured reservoir where fractures may be natural and/or artificial (e.g., hydraulic fractures). As an example, information acquired by a tool or tools may be analyzed using a framework such as the TECHLOG framework. As an example, the TECHLOG framework may be interoperable with one or more other frameworks such as, for example, the PETREL framework, which may be hosted within a DELFI environment.
As an example, various aspects of a workflow may be completed automatically, may be partially automated, or may be completed manually, as by a human user interfacing with a software application (e.g., via one or more graphical user interfaces, etc.). As an example, a workflow may be cyclic, and may include, as an example, four stages such as, for example, an evaluation stage (see, e.g., the evaluation equipment 310), a planning stage (see, e.g., the planning equipment 320), an engineering stage (see, e.g., the engineering equipment 330) and an execution stage (see, e.g., the operations equipment 340). As an example, a workflow may commence at one or more stages, which may progress to one or more other stages (e.g., in a serial manner, in a parallel manner, in a cyclical manner, etc.).
As an example, a workflow may commence with an evaluation stage, which may include a geological service provider evaluating a formation (see, e.g., the evaluation block 314). As an example, a geological service provider may undertake the formation evaluation using a computing system executing a software package tailored to such activity; or, for example, one or more other suitable geology platforms may be employed (e.g., alternatively or additionally). As an example, the geological service provider may evaluate the formation, for example, using earth models, geophysical models, basin models, petrotechnical models, combinations thereof, and/or the like. Such models may take into consideration a variety of different inputs, including offset well data, seismic data, pilot well data, other geologic data, etc. The models and/or the input may be stored in the database maintained by the server and accessed by the geological service provider.
As an example, a workflow may progress to a geology and geophysics (“G&G”) service provider, which may generate a well trajectory (see, e.g., the generation block 324), which may involve execution of one or more G&G frameworks (e.g., the PETREL framework, etc.). As an example, a G&G service provider may determine a well trajectory or a section thereof, based on, for example, one or more model(s) provided by a formation evaluation (e.g., per the evaluation block 314), and/or other data, e.g., as accessed from one or more databases (e.g., maintained by one or more servers, etc.). As an example, a well trajectory may take into consideration various “basis of design” (BOD) constraints, such as general surface location, target (e.g., reservoir) location, and the like. As an example, a trajectory may incorporate information about tools, bottom-hole assemblies, casing sizes, etc., that may be used in drilling the well. A well trajectory determination may take into consideration a variety of other parameters, including risk tolerances, fluid weights and/or plans, bottom-hole pressures, drilling time, etc.
As an example, a workflow may progress to a first engineering service provider (e.g., one or more processing machines associated therewith), which may validate a well trajectory and, for example, relief well design (see, e.g., the validation block 328). Such a validation process may include evaluating physical properties, calculations, risk tolerances, integration with other aspects of a workflow, etc. As an example, one or more parameters for such determinations may be maintained by a server and/or by the first engineering service provider; noting that one or more model(s), well trajectory(ies), etc. may be maintained by a server and accessed by the first engineering service provider. For example, the first engineering service provider may include one or more computing systems executing one or more software packages. As an example, where the first engineering service provider rejects or otherwise suggests an adjustment to a well trajectory, the well trajectory may be adjusted or a message or other notification sent to the G&G service provider requesting such modification.
As an example, one or more engineering service providers (e.g., first, second, etc.) may provide a casing design, bottom-hole assembly (BHA) design, fluid design, and/or the like, to implement a well trajectory (see, e.g., the design block 338). In some embodiments, a second engineering service provider may perform such design using one of more frameworks.
As an example, a second engineering service provider may seek approval from a third engineering service provider for one or more designs established along with a well trajectory. In such an example, the third engineering service provider may consider various factors as to whether the well engineering plan is acceptable, such as economic variables (e.g., oil production forecasts, costs per barrel, risk, drill time, etc.), and may request authorization for expenditure, such as from the operating company's representative, well-owner's representative, or the like (see, e.g., the formulation block 334). As an example, at least some of the data upon which such determinations are based may be stored in one or more database maintained by one or more servers. As an example, a first, a second, and/or a third engineering service provider may be provided by a single team of engineers or even a single engineer, and thus may or may not be separate entities.
As an example, where economics may be unacceptable or subject to authorization being withheld, an engineering service provider may suggest changes to casing, a bottom-hole assembly, and/or fluid design, or otherwise notify and/or return control to a different engineering service provider, so that adjustments may be made to casing, a bottom-hole assembly, and/or fluid design. Where modifying one or more of such designs is impracticable within well constraints, trajectory, etc., the engineering service provider may suggest an adjustment to the well trajectory and/or a workflow may return to or otherwise notify an initial engineering service provider and/or a G&G service provider such that either or both may modify the well trajectory.
As an example, a workflow may include considering a well trajectory, including an accepted well engineering plan, and a formation evaluation. Such a workflow may then pass control to a drilling service provider, which may implement the well engineering plan, establishing safe and efficient drilling, maintaining well integrity, and reporting progress as well as operating parameters (see, e.g., the blocks 344 and 348). As an example, operating parameters, formation encountered, data collected while drilling (e.g., using logging-while-drilling or measuring-while-drilling technology), may be returned to a geological service provider for evaluation. As an example, the geological service provider may then re-evaluate the well trajectory, or one or more other aspects of the well engineering plan, and may, in some cases, and potentially within predetermined constraints, adjust the well engineering plan according to the real-life drilling parameters (e.g., based on acquired data in the field, etc.).
Whether a well is entirely drilled, or a section thereof is completed, depending on the specific embodiment, a workflow may proceed to a post review (see, e.g., the evaluation block 318). As an example, a post review may include reviewing drilling performance. As an example, a post review may further include reporting the drilling performance (e.g., to one or more relevant engineering, geological, or G&G service providers).
Various activities of a workflow may be performed consecutively and/or may be performed out of order (e.g., based partially on information from templates, nearby wells, etc. to fill in gaps in information that is to be provided by another service provider). As an example, undertaking one activity may affect the results or basis for another activity, and thus may, either manually or automatically, call for a variation in one or more workflow activities, work products, etc. As an example, a server may allow for storing information on a central database accessible to various service providers where variations may be sought by communication with an appropriate service provider, may be made automatically, or may otherwise appear as suggestions to the relevant service provider. Such an approach may be considered to be a holistic approach to a well workflow, in comparison to a sequential, piecemeal approach.
As an example, various actions of a workflow may be repeated multiple times during drilling of a borehole (e.g., a wellbore). For example, in one or more automated systems, feedback from a drilling service provider may be provided at or near real-time, and the data acquired during drilling may be fed to one or more other service providers, which may adjust its piece of the workflow accordingly. As there may be dependencies in other areas of the workflow, such adjustments may permeate through the workflow, e.g., in an automated fashion. In some embodiments, a cyclic process may additionally or instead proceed after a certain drilling goal is reached, such as the completion of a section of the wellbore, and/or after drilling of an entire wellbore, or on a per-day, week, month, etc. basis.
Well planning may include determining a path of a well that may extend to a reservoir, for example, to economically produce fluids such as hydrocarbons therefrom. Well planning may include selecting a drilling and/or completion assembly which may be used to implement a well plan. As an example, various constraints may be imposed as part of well planning that may impact design of a well. As an example, such constraints may be imposed based at least in part on information as to known geology of a subterranean domain, presence of one or more other wells (e.g., actual and/or planned, etc.) in an area (e.g., consider collision avoidance), etc. As an example, one or more constraints may be imposed based at least in part on characteristics of one or more tools, components, etc. As an example, one or more constraints may be based at least in part on factors associated with drilling time and/or risk tolerance.
As an example, a system may allow for a reduction in waste, for example, as may be defined according to LEAN. In the context of LEAN, consider one or more of the following types of waste: transport (e.g., moving items unnecessarily, whether physical or data); inventory (e.g., components, whether physical or informational, as work in process, and finished product not being processed); motion (e.g., people or equipment moving or walking unnecessarily to perform desired processing); waiting (e.g., waiting for information, interruptions of production during shift change, etc.); overproduction (e.g., production of material, information, equipment, etc. ahead of demand); over processing (e.g., resulting from poor tool or product design creating activity); and defects (e.g., effort involved in inspecting for and fixing defects whether in a plan, data, equipment, etc.). As an example, a system that allows for actions (e.g., methods, workflows, etc.) to be performed in a collaborative manner may help to reduce one or more types of waste.
As an example, a system may be utilized to implement a method for facilitating distributed well engineering, planning, and/or drilling system design across multiple computation devices where collaboration may occur among various different users (e.g., some being local, some being remote, some being mobile, etc.). In such a system, the various users via appropriate devices may be operatively coupled via one or more networks (e.g., local and/or wide area networks, public and/or private networks, land-based, marine-based and/or areal networks, etc.).
As an example, a system may allow well engineering, planning, and/or drilling system design to take place via a subsystems approach where a wellsite system is composed of various subsystem, which may include equipment subsystems and/or operational subsystems (e.g., control subsystems, etc.). As an example, computations may be performed using various computational platforms/devices that are operatively coupled via communication links (e.g., network links, etc.). As an example, one or more links may be operatively coupled to a common database (e.g., a server site, etc.). As an example, a particular server or servers may manage receipt of notifications from one or more devices and/or issuance of notifications to one or more devices. As an example, a system may be implemented for a project where the system may output a well plan, for example, as a digital well plan, a paper well plan, a digital and paper well plan, etc. Such a well plan may be a complete well engineering plan or design for the particular project.
As an example, the blocks 402, 404, 406 and 408 may be described in a pyramidal architecture where, from peak to base, a pyramid includes the orchestration block 402, the integration block 404, the core and services block 406 and the equipment block 408.
As an example, the orchestration block 402 may be associated with a well management level (e.g., well planning and/or orchestration) and may be associated with a rig management level (e.g., rig dynamic planning and/or orchestration). As an example, the integration block 404 may be associated with a process management level (e.g., rig integrated execution). As an example, the core and services block 406 may be associated with a data management level (e.g., sensor, instrumentation, inventory, etc.). As an example, the equipment block 408 may be associated with a wellsite equipment level (e.g., wellsite subsystems, etc.).
As an example, the orchestration block 402 may receive information from a drilling workflow framework and/or one or more other sources, which may be remote from a wellsite.
In the example of
As mentioned, a portion of the system 400 may be remote from a wellsite. For example, to one side of a dashed line appear a remote operation command center block 492, a database block 493, a drilling workflow framework block 494, an enterprise resource planning (ERP) block 495 and a field services delivery block 496. Various blocks that may be remote may be operatively coupled to one or more blocks that may be local to a wellsite system. For example, a communication link 412 is illustrated in the example of
As an example, the system 400 of
As an example, a wellbore may be drilled according to a drilling plan that is established prior to drilling. Such a drilling plan, which may be a well plan or a portion thereof, may set forth equipment, pressures, trajectories and/or other parameters that define drilling process for a wellsite. As an example, a drilling operation may then be performed according to the drilling plan (e.g., well plan). As an example, as information is gathered, a drilling operation may deviate from a drilling plan. Additionally, as drilling or other operations are performed, subsurface conditions may change. Specifically, as new information is collected, sensors may transmit data to one or more surface units. As an example, a surface unit may automatically use such data to update a drilling plan (e.g., locally and/or remotely).
As an example, the drilling workflow framework 494 may be or include a G&G system and a well planning system. As an example, a G&G system corresponds to hardware, software, firmware, or a combination thereof that provides support for geology and geophysics. In other words, a geologist who understands the reservoir may decide where to drill the well using the G&G system that creates a three-dimensional model of the subsurface formation and includes simulation tools. The G&G system may transfer a well trajectory and other information selected by the geologist to a well planning system. The well planning system corresponds to hardware, software, firmware, or a combination thereof that produces a well plan. In other words, the well plan may be a high-level drilling program for the well. The well planning system may also be referred to as a well plan generator.
In the example of
As an example, various blocks in the system 400 of
The orchestration block 402 may be referred to as a well plan execution system. For example, a well plan execution system corresponds to hardware, software, firmware or a combination thereof that performs an overall coordination of the well construction process, such as coordination of a drilling rig and the management of the rig and the rig equipment. A well plan execution system may be configured to obtain the general well plan from well planning system and transform the general well plan into a detailed well plan. The detailed well plan may include a specification of the activities involved in performing an action in the general well plan, the days and/or times to perform the activities, the individual resources performing the activities, and other information.
As an example, a well plan execution system may further include functionality to monitor an execution of a well plan to track progress and dynamically adjust the plan. Further, a well plan execution system may be configured to handle logistics and resources with respect to on and off the rig. As an example, a well plan execution system may include multiple sub-components, such as a detailer that is configured to detail the well planning system plan, a monitor that is configured to monitor the execution of the plan, a plan manager that is configured to perform dynamic plan management, and a logistics and resources manager to control the logistics and resources of the well. In one or more embodiments, a well plan execution system may be configured to coordinate between the different processes managed by a process manager collection (see, e.g., the integration block 404). In other words, a well plan execution system may communicate and manage resource sharing between processes in a process manager collection while operating at, for example, a higher level of granularity than process manager collection.
As to the integration block 404, as mentioned, it may be referred to as a process manager collection. In one or more embodiments, a process manager collection may include functionality to perform individual process management of individual domains of an oilfield, such as a rig. For example, when drilling a well, different activities may be performed. Each activity may be controlled by an individual process manager in the process manager collection. A process manager collection may include multiple process managers, whereby each process manager controls a different activity (e.g., activity related to the rig). In other words, each process manager may have a set of tasks defined for the process manager that is particular to the type of physics involved in the activity. For example, drilling a well may use drilling mud, which is fluid pumped into well in order to extract drill cuttings from the well. A drilling mud process manager may exist in a process manager collection that manages the mixing of the drilling mud, the composition, testing of the drilling mud properties, determining whether the pressure is accurate, and performing other such tasks. The drilling mud process manager may be separate from a process manager that controls movement of drill pipe from a well. Thus, a process manager collection may partition activities into several different domains and manages each of the domains individually. Amongst other possible process managers, a process manager collection may include, for example, a drilling process manager, a mud preparation and management process manager, a casing running process manager, a cementing process manager, a rig equipment process manager, and other process managers. Further, a process manager collection may provide direct control or advice regarding the components above. As an example, coordination between process managers in a process manager collection may be performed by a well plan execution system.
As to the core and services block 406 (e.g., CS block), it may include functionality to manage individual pieces of equipment and/or equipment subsystems. As an example, a CS block may include functionality to handle basic data structure of the oilfield, such as the rig, acquire metric data, produce reports, and manages resources of people and supplies. As an example, a CS block may include a data acquirer and aggregator, a rig state identifier, a real-time (RT) drill services (e.g., near real-time), a reporter, a cloud, and an inventory manager.
As an example, a data acquirer and aggregator may include functionality to interface with individual equipment components and sensor and acquire data. As an example, a data acquirer and aggregator may further include functionality to interface with sensors located at the oilfield.
As an example, a rig state identifier may include functionality to obtain data from the data acquirer and aggregator and transform the data into state information. As an example, state information may include health and operability of a rig as well as information about a particular task being performed by equipment.
As an example, real-time (RT) drill services may include functionality to transmit and present information to individuals. In particular, the RT drill services may include functionality to transmit information to individuals involved according to roles and, for example, device types of each individual (e.g., mobile, desktop, etc.). In one or more embodiments, information presented by RT drill services may be context specific, and may include a dynamic display of information so that a human user may view details about items of interest.
As an example, in one or more embodiments, a reporter may include functionality to generate reports. For example, reporting may be based on requests and/or automatic generation and may provide information about state of equipment and/or people.
As an example, a wellsite “cloud” framework may correspond to an information technology infrastructure locally at an oilfield, such as an individual rig in the oilfield. In such an example, the wellsite “cloud” framework may be an “Internet of Things” (IoT) framework. As an example, a wellsite “cloud” framework may be an edge of the cloud (e.g., a network of networks) or of a private network.
As an example, an inventory manager may be a block that includes functionality to manage materials, such as a list and amount of each resource on a rig.
In the example of
As mentioned, the system 400 of
Various types of data associated with field operations may be 1-D series data. For example, consider data as to one or more of a drilling system, downhole states, formation attributes, and surface mechanics being measured as single or multi-channel time series data.
The hoisting system 700 may be part of a wellsite system (see, e.g.,
As to the distance range of a traveling block, it may be sufficient for adding and removing drill pipe and/or other components. As an example, a stand may be two or three single joints of drill pipe or drill collars that remain screwed together during tripping operations. As an example, a stand may be a three-joint stand. As an example, a drill pipe length may be approximately 10 m (e.g., consider from about 27 ft to about 30 ft); noting that shorter or longer drill pipe may be utilized. Where a stand is composed of three lengths of approximately 10 m drill pipe, the stand may have an over length of approximately 30 m (e.g., approximately 100 ft). As such, a traveling block that has a total excursion of approximately 50 m may be raised and lowered to accommodate a stand of approximately 30 m (e.g., for addition to a drillstring or removal from a drillstring).
BPOS is a type of real-time channel that reflects surface mechanical properties of a rig. Another example of a channel is hook load, which may be referred to as HKLD. HKLD may be a 1-D series measurement of the load of a hook. As to a derivative, a first derivative may be a load velocity and a second derivative may be a load acceleration. Such data channels may be utilized to infer and monitor various operations and/or conditions. In some examples, a rig may be represented as being in one or more states, which may be referred to as rig states.
As to the HKLD channel, it may help to detect if a rig is “in slips”, while the BPOS channel may be a primary channel for depth tracking during drilling. For example, BPOS may be utilized to determine a measured depth in a geologic environment (e.g., a borehole being drilled, etc.). As to the condition or state “in slips”, HKLD is at a much lower value than in the condition or state “out of slips”.
The term slips refers to a device or assembly that may be used to grip a drillstring (e.g., drill collar, drill pipe, etc.) in a relatively non-damaging manner and suspend it in a rotary table. Slips may include three or more steel wedges that are hinged together, forming a near circle around a drill pipe. On the drill pipe side (inside surface), the slips are fitted with replaceable, hardened tool steel teeth that embed slightly into the side of the pipe. The outsides of the slips are tapered to match the taper of the rotary table. After the rig crew places the slips around the drill pipe and in the rotary, a driller may control a rig to slowly lower the drillstring. As the teeth on the inside of the slips grip the pipe, the slips are pulled down. This downward force pulls the outer wedges down, providing a compressive force inward on the drill pipe and effectively locking components together. Then the rig crew may unscrew the upper portion of the drillstring (e.g., a kelly, saver sub, a joint or stand of pipe) while the lower part is suspended. After some other component is screwed onto the lower part of the drillstring, the driller raises the drillstring to unlock the gripping action of the slips, and a rig crew may remove the slips from the rotary.
A hook load sensor may be used to measure a weight of load on a drillstring and may be used to detect whether a drillstring is in-slips or out-of-slips. When the drillstring is in-slips, motion from the blocks or motion compensator do not have an effect on the depth of a drill bit at the end of the drillstring (e.g., it will tend to remain stationary). Where movement of a traveling block is via a drawworks encoder (DWE), which may be mounted on a shaft of the drawworks, acquired DWE information (e.g., BPOS) does not augment the recorded drill bit depth. When a drillstring is out-of-slips (e.g., drilling ahead), DWE information (e.g., BPOS) may augment the recorded bit depth. The difference in hook load weight (HKLD) between in-slips and out-of-slips tends to be distinguishable. As to marine operations, heave of a vessel may affect bit depth whether a drillstring is in-slips or out-of-slips. As an exmaple, a vessel may include one or more heave sensors, which may sense data that may be recorded as 1-D series data.
As to marine operations, a vessel may expeirence various types of motion, such as, for example, one or more of heave, sway and surge. Heave is a linear vertical (up/down) motion, sway is linear lateral (side-to-side or port-starboard) motion, and surge is linear longitudinal (front/back or bow/stern) motion imparted by maritime conditions. As an exmaple, a vessel may include one or more heave sensors, one or more sway sensors and/or one or more surge sensors, each of which may sense data that may be recorded as 1-D series data.
As an exmaple, BPOS alone, or combined with one or more other channels, may be used to detect whether a rig is “on bottom” drilling or “tripping”, etc. An inferred state may be further consumed by one or more systems such as, for example, an automatic drilling control system, which may be a dynamic field operations system or a part thereof. In such an exmaple, the conditions, operations, states, etc., as discerned from BPOS and/or other channel data may be predicates to making one or more drilling decisions, which may include one or more control decisions (e.g., of a controller that is operatively coupled to one or more pieces of field equipment, etc.).
A block may be a set of pulleys used to gain mechanical advantage in lifting or dragging heavy objects. There may be two blocks on a drilling rig, the crown block and the traveling block. Each may include several sheaves that are rigged with steel drilling cable or line such that the traveling block may be raised (or lowered) by reeling in (or out) a spool of drilling line on the drawworks. As such, block position may refer to the position of the traveling block, which may vary with respect to time.
A hook may be high-capacity J-shaped equipment used to hang various equipment such as a swivel and kelly, elevator bails, or a topdrive.
Hook load may be the total force pulling down on a hook as carried by a traveling block. The total force includes the weight of the drillstring in air, the drill collars and ancillary equipment, reduced by forces that tend to reduce that weight. Some forces that might reduce the weight include friction along a bore wall (especially in deviated wells) and buoyant forces on a drillstring caused by its immersion in drilling fluid (e.g., and/or other fluid). If a blowout preventer (BOP) (e.g., or BOPs) is closed, pressure in a bore acting on cross-sectional area of a drillstring in the BOP may also exert an upward force.
A standpipe may be a rigid metal conduit that provides a high-pressure pathway for drilling fluid to travel approximately one-third of the way up the derrick, where it connects to a flexible high-pressure hose (e.g., kelly hose). A large rig may be fitted with more than one standpipe so that downtime is kept to a minimum if one standpipe demands repair.
As to surface torque, such a measurement may be provided by equipment at a rig site. As an example, one or more sensors may be utilized to measure surface torque, which may provide for direct and/or indirect measurement of surface torque associated with a drillstring. As an example, equipment may include a drill pipe torque measurement and controller system with one or more of analog frequency output and digital output. As an example, a torque sensor may be associated with a coupling that includes a resilient element operatively joining an input element and an output element where the resilient element allows the input and output elements to twist with respect to one another in response to torque being transmitted through the torque sensor where the twisting may be measured and used to determine the torque being transmitted. As an example, such a coupling may be located between a drive and drill pipe. As an example, torque may be determined via an inertia sensor or sensors. As an example, equipment at a rig site may include one or more sensors for measurement and/or determination of torque (e.g., in units of Nm, etc.).
As an example, equipment may include a real-time drilling service system that may provide data such as weight transfer information, torque transfer information, equivalent circulation density (ECD) information, downhole mechanical specific energy (DMSE) information, motion information (e.g., as to stall, stick-slip, etc.), bending information, vibrational amplitude information (e.g., axial, lateral and/or torsional), rate of penetration (ROP) information, pressure information, differential pressure information, flow information, etc. As an example, sensor information may include inclination, azimuth, total vertical depth, etc. As an example, a system may provide information as to whirl (e.g., backward whirl, etc.) and may optionally provide information such as one or more alerts (e.g., “severe backward whirl: stop and restart with lower surface RPM”, etc.).
As to DMSE, it may be a MSE as associated with downhole energy. MSE may be utilized as a measure of drilling efficiency. MSE may be defined as the energy required to remove a unit volume of rock. For optimal drilling efficiency, field operations may aim to minimize the MSE and to maximize ROP. As an example, to control MSE, field equipment may be controlled as to factors such as, for example, one or more of WOB, torque, ROP and RPM.
A drill bit may be defined as a tool used to crush and/or cut rock. As explained, various rig equipment may directly and/or indirectly assist a drill bit in crushing and/or cutting the rock. Various drill bits may work by scraping or crushing the rock, or both, usually as part of a rotational motion; noting that some bits, known as hammer bits, pound rock. During drilling, various equipment may be controlled to deliver energy to a drill bit to crush and/or cut rock to thereby lengthen a borehole. As explained, drilling may aim to minimize MSE and maximize ROP while maintaining borehole quality (e.g., integrity, etc.). As an example, various equipment may be controlled as to energy delivered to a drillstring and/or a drill bit, for example, to address one or more conditions, which may include, for example, one or more conditions that may cause sticking of a drillstring and/or increase risk of sticking of a drillstring and/or one or more conditions involving actual sticking of a drillstring (e.g., getting a drillstring unstuck, etc.). As various physical interactions may occur between a drillstring and a formation (e.g., a borehole wall), controlled delivery of energy, material(s) (e.g., drilling fluid additives, etc.), etc., may provide for reduced risk of damage to the drillstring and/or the formation.
As explained, a drillstring may include a tool or tools that include various sensors that may make various measurements. For example, consider the OPTIDRILL tool (SLB, Houston, Texas), which includes strain gauges, accelerometers, magnetometer(s), gyroscope(s), etc. For example, such a tool may acquire weight on bit measurements (WOB) using a strain gauge (e.g., 10 second moving window with bandwidth of 200 Hz), torque measurements using a strain gauge (e.g., 10 second moving window with bandwidth of 200 Hz), bending moment using a strain gauge (e.g., 10 second moving window with bandwidth of 200 Hz), vibration using one or more accelerometers (e.g., 30 second RMS with bandwidth of 0.2 to 150 Hz), rotational speed using a magnetometer and a gyroscope (e.g., 30 moving window with bandwidth of 4 Hz), annular and internal pressures using one or more strain gauges (e.g., 1 second average with bandwidth of 200 Hz), annular and internal temperatures using one or more temperature sensors (1 second average with bandwidth of 10 Hz), and continuous inclination using an accelerometer (30 second average with bandwidth of 10 Hz).
As mentioned, channels of real time drilling operation data may be received and characterized using generated synthetic data, which may be generated based at least in part on one or more operational parameters associated with the real time drilling operation. Such real time drilling operation data may include surface data and/or downhole data. As mentioned, data availability may differ temporally (e.g., frequency, gaps, etc.) and/or otherwise (e.g., resolution, etc.). Such data may differ as to noise level and/or noise characteristics. While various types of sensors are mentioned, equipment may be utilized that may not include one or more types of downhole sensors. In such instances, a method may be utilized that may determine one or more downhole values.
In
Pre-connection may be where a downhole tool (e.g., a drill bit) has completed drilling operations for a current section of pipe, but the slips assembly has not begun to move (e.g., radially-inward) into engagement with the drillstring. During pre-connection, the flow rate of fluid being pumped into the drillstring may increase and/or decrease, the rate of rotation of the drillstring may increase and/or decrease, the downhole tool (e.g., the drill bit) may move upwards and/or downwards, or a combination thereof.
Connection may be where a slips assembly is engaged with, and supports, a drillstring (e.g., the drillstring is “in-slips”). When a connection is occurring, a segment (e.g., a pipe, a stand, etc.) may be added to the drillstring to increase the length of the drillstring, or a segment may be removed from the drillstring to reduce the length of the drillstring.
Post-connection may be where the drillstring is released by a slips assembly, and a downhole tool (e.g., the drill bit) are lowered to be on-bottom (e.g., bottom of hole or BOH). During post-connection, the flow rate of fluid being pumped into a drillstring may increase/and/or decrease, the rate of rotation of a drillstring may increase and/or decrease, a downhole tool (e.g., the drill bit) may move upwards and/or downwards, or a combination thereof.
As to an absent state, it may indicate a scenario where data are not being received (e.g., at least one of a plurality of inputs is missing).
As an example, a method may be utilized to determine a slips status. For example, slips status may include one or more of the following: In-slips where a slips assembly is engaged with, and supports, a drillstring (“in-slips”); out-of-slips where the slips assembly is not engaged with, and does not support, the drillstring; and absent where data are not received (e.g., at least one of the inputs is missing).
The method 800 of
As an example, in the method 800, measurements (e.g., data) may include a depth of a wellbore (e.g., a measured depth), a depth of a drill bit (e.g., a measured depth), a position of a travelling block (e.g., BPOS), or a combination thereof. A set of measurements may or may not include weight on hook (e.g., HKLD), or weight on a drill bit (e.g., WOB). Each set of measurements may be captured/received a predetermined amount of time after a previous set of measurements is captured/received. A predetermined amount of time may be, for example, about three seconds; however, the predetermined amount of time may be shorter or longer.
A PCT publication WO 2017/221046 A1 of 28 Dec. 2017 is incorporated by reference herein and entitled “Automatic drilling activity detection” ('046 publication). The '046 publication describes a method of determining a drilling activity that includes receiving a set of measurements at different times. The set of measurements may include a depth of a wellbore, a depth of a drill bit, and a position of a travelling block. The method may also include identifying a connection by determining when the position of the travelling block changes but the depth of the drill bit does not change. The method may also include determining when the depth of the wellbore does not increase between two different connections. The method may also include determining a direction that the drill bit moves between the two connections.
As an example, a GUI may provide for rendering one or more broomstick model plots with respect to time (e.g., horizontally, vertically, etc.). In such an example, a broomstick model plot may be utilized to ascertain one or more friction factors with respect to time. As an example, a broomstick plot or broomstick model plot (e.g., a plot of model results, etc.), may be a full broomstick plot, a half broomstick plot or another portion of a broomstick plot. For example, where PU and SO are concerned, they may correspond to different directions such that a full broomstick plot may be generated; noting that a half broomstick plot for PU and/or a half broomstick plot for SO may be generated. As to TQLS, where the torque is in a particular rotational direction (e.g., a rotational direction of a bit for drilling), a broomstick plot may be a half broomstick plot; noting that torque may be acquired in two rotational directions (e.g., clockwise and counterclockwise), which may provide for rendering a plot in a full broomstick manner.
As an example, a system may provide for real-time (RT) torque and drag (T&D) monitoring. Abnormal torque and drag, which commonly refers to overpull, underpull, and high-torque load, are indications of excess frictional effects between the drillstring and the wellbore. Various conditions may cause these effects, including tight hole, differential sticking, poor hole cleaning, key seats, etc. Failing to detect these anomalies may cause excessive wear on a drillstring and may eventually lead to severe stuck pipe conditions.
As an example, a T&D workflow may be executed using surface sensor measurements and contextual data for extraction of information from relevant operations. Such information may then be used for modeling calibration and predictions, for example, based on a finite element method-based stiff-string T&D model. In such an approach, a T&D workflow may generate alarms, instructions, etc., based on one or more detected anomalies.
As an example, a workflow may use one or more physical models together with knowledge acquired from drilling data. A workflow may be fully automatic without demand for manual calibration and fixed thresholds. In such an example, the workflow may be adaptive to changing conditions of a well being drilled. Trial data and results are presented herein that demonstrate some aspects of usability and rationality when dealing with actual operation scenarios.
Considerable effort has been placed into T&D analysis for well construction processes. As mentioned, a physical model may be used to predict T&D from multiple parameters and variables. For example, soft string (see, e.g., Johancsik et al. 1984) and stiff sting (see, e.g., Ho 1988) are examples of T&D modeling assumptions that tend to be used in the drilling industry (see also, e.g., Gorokhova et al. 2014; Mirhaj et al. 2016; Zhang and Samuel 2019; Ohia et al. 2021). As an example, a framework for T&D monitoring, control, etc., may include T&D prediction, which may be more accurate and efficient as additional comprehensive physics are considered and extra computing capacity is available.
While a physical model may provide for more accurate predictions, a challenge remains to performing real-time T&D analysis. Challenges may stem from aspects such as the changing drilling conditions and the continuous data streams from multiple sources. With the detailed analysis of drilling operations, various friction factors may be determined and updated from measured data by model inversion to evaluate wellbore conditions (see, e.g., Reiber et al. 1999; Vos and Reiber 2000). For example, simulated hook load and torque depth curves for a set of friction factors may be plotted together with additional measured data as a drilling operation progresses. As explained, one type of plot is referred to as a broomstick plot (see, e.g., Kucs et al. 2008). As an example, a workflow may utilize a broomstick plot or plots and/or one or more aspects thereof. Such a workflow may provide for increased automation in a manner that includes real-time T&D modeling (see, e.g., Shahri et al. 2018; Cao et al. 2020; Carpenter 2021). As an example, a framework may employ one or more types of machine learning methods into T&D analysis, which may be combined with physical modeling or physics-based modeling (see, e.g., Hedge et al. 2015; Zhu et al. 2022; Bai et al. 2022).
As an example, a T&D data monitoring framework may provide for real-time T&D monitoring using a high level of automation with acquisition of in-depth information from data mining. Such an approach may provide for enhanced prediction accuracy and supply a triggering role of program execution for one or more workflow actions. As an example, a framework may include one or more data visualization components. As an example, a framework may deliver and update T&D information for one or more users, machines, etc., in an efficient manner (e.g., real-time or near real-time).
As shown, the method 1000 may include a start block 1010 for commencing the method 1000, an input block 1012 for receiving input, an alignment block 1014 for aligning input, a synchronization block 1016 for synchronizing input, and a state determination block 1018 for determining a rig state (e.g., rig state detection). As shown, the method 1000 may include branches such as a branch for operational identifications and a branch for stand identifications. As shown, an identification block 1020 may provide for identifying an operation, which may be referred to as operational identification (e.g., Op ID), a decision block 1022 may provide for deciding if a relevant operation is identified, a statistics block 1024 may provide for acquiring statistics for a relevant operation that has been identified, a prediction block 1026 may provide for interacting with a torque and drag engine 1025 (e.g., T&D engine) for making predictions, a detection block 1040 may provide for detecting one or more anomalies, a decision block 1042 may provide for deciding whether an anomaly or anomalies were detected, and an issuance block 1044 may, responsive to detection of one or more anomalies, provide for issuing an instruction, which may be a notification, a control instruction, etc. As to the branch for stand identifications, it may include a detection block 1030 for detecting a stand, a decision block 1032 for deciding if a stand has been detected, a statistics block 1034 for acquiring statistics and a calibration block 1036 for calibrating the T&D engine 1025. In such an approach, the T&D engine 1025 may be calibrated for making predictions as called for by the prediction block 1026.
In the example of
The method 1000 may be a real-time workflow that provides for abnormal T&D monitoring. As explained, streaming data may be aligned and synchronized before being input into a framework. Then, related features such as rig state, operation state (e.g., operational identification), and stands information may be extracted. In such an example, statistics of hook load with other information such as depths may be transmitted to a modeling stage. As an example, stand-based statistics may be used for calibration at a lower frequency, while operation-based statistics may trigger the prediction for a smaller time scale and a higher frequency than stand-based statistics. As an example, predicted results may be compared with actual measurements where an abnormal event generates an alarm and/or control action (e.g., a signal, instructions, etc.).
As to the data preparation stage, surface sensor measurements for well construction may be received as time-series channels, including, for example, block position, hole depth, bit depth, hook load, surface torque, surface rotary speed, standpipe pressure, and input mud flow rate. Contextual data, including tubulars (drillstring, casing, liner, etc.), wellbore geometry, trajectory, and mud density profiles may be manually entered by one or more users. However, preprocessing of such data may be complicated due to one or more issues encountered in a real-time system. Data from multiple sources may be a major challenge that might lead to various latencies and different frequencies. To reduce the consequences of rejecting excessive amounts of data or poor timeliness due to alignment and synchronization, a time window may be implemented to balance data completeness and response time. As to some examples of other issues, including, for example, invalid data, data gap, low-frequency data, etc., challenges may exist to resolving one or more of such issues; however, various components of a framework may provide for proper handling of data to establish a robust and efficient system.
As to feature extraction, various rig states, such as in or out of slips, on or off-bottom, pumping or not, rotating or not, static or moving, and moving up or down, may be identified, for example, in a frequency of 1 Hz (see, e.g., Laurent et al. 2021). Such an approach may utilize inputs of time-series channels from surface sensors.
Various rig states may be used to identify specific operations of pick-up, slack-off, free-rotation, and in-slips, with which a workflow may be concerned. The hook load and surface torque statistics during each operation period may be extracted and recorded with a system of measurements of min, max, P10, P50, and P90. On the other hand, statistics at a larger time scale with the duration of each stand may also be summarized for each relevant operation. In this case, one stand may refer to one to four pipe sections that is handled as a single pipe in a drilling process. Corresponding depth ranges for these statistics may also be collected as input for modeling.
As to modeling, a modeling framework may be, for example, a 3D finite element method-based stiff-string model for T&D (e.g., a T&D engine). In such an example, within the finite element approach, tubular (e.g., drillstring, casing, liner, etc.) displacements and rotations may be interpolated using 3D beams. In such an example, each beam may be defined by two nodes with six degrees of freedom at each node. Also, the mechanical behavior of the tubular may be determined by the equilibrium displacements caused by externally applied forces. Attention may be given to various tubular mechanical properties (e.g., outer diameter, inner diameter, length, weight etc. of each component), tubular contact points with the borehole, 3D trajectory, wellbore geometry, mud weight, and operating parameters.
As shown, the T&D engine 1225 (e.g., modeling engine, etc.) may be calibrated using stand statistics while operational statistics may drive predictions using the T&D engine 1225 as calibrated. As shown, operation mode (Op mode), hook load (HKLD), torque (TQ) and block weight (BLKW) may be transmitted to the T&D engine 1225 while the calibration block 1236 receives one or more types of information from the T&D engine 1225 (e.g., linear weight coefficient (LWC) information, friction factor (FF) information, etc.). As indicated, the prediction block 1226 may transmit operation mode, bit depth, LWC and FF information to the T&D engine 1225 while the T&D engine 1225 may supply hook load (HKLD) and torque (TQ).
As an example, in addition to the contextual input mentioned, friction factor (FF) and linear weight coefficient (LWC) may be two relatively uncertain variables that may not be acquired or updated from real-time measurements. In various instances, it may be inconvenient, inaccurate, and not sufficiently timely to rely on one or more users to realize a deviation and then update one or more variables manually.
The approach shown in the example of
As explained, a method may provide for data driven model calibration and prediction. Such a method may account for operation modes include free-rotation, slack-off, and pick-up and provide for calibrations as to linear weight coefficient and friction factor.
As to anomaly capturing, a difference between modeled and measured values may be used to evaluate an anomaly (e.g., anomaly detection, assessment, etc.). As various metrics of percentiles may be collected, such collection provides the possibility for examining measurements from various perspectives. As an example, P50 values may be used to supervise an overall trend of friction. P10 and P90 values may be useful for indicating uncertainty, which may be relevant in evaluating friction variation. An abnormal event may be measured by a predefined threshold, and may be brought to the attention of a user by one or more generated alarms and may be, for example, utilized for controlling one or more processes (e.g., field equipment operations, etc.). As an example, where an abnormal event is detected, one or more operational actions may be taken in response to address the abnormal event.
As an example, a framework may provide for handling one or more RT scenarios. Apart from the existing shared components, such as the rig state generation algorithm, T&D engine, etc., several techniques may be specific to dispense with a real-time computing scenario. Such techniques may be handled in consideration of one or more processing unit (e.g., cores, processors, etc.) and associated memory usage or data flow (see, e.g., the methods 1000 and 1200).
As to online statistics, these may be collected during a T&D monitoring workflow. In various instances, caching raw data may not be performed for calculating percentiles or the mean. As an example, consider use of Welford's online algorithm (see, e.g., Welford 1962), which may be adapted to compute the average and variance in a numerically stable way with limited memory usage as follows:
In equations (1) and (2), N is the number of values. The average μN may be calculated based on the average μN−1 of previous N−1 values and the new value of xN. Further, the variance σN2 may be calculated plus consideration of the previous variance σN−12.
As an example, a method may include taking time decay effect into account as a weight function W(t) as shown in the following example equations:
As an example, a depth decay effect may be considered similarly. Furthermore, it may be mathematically impractical to count exact percentiles without the presence of a complete data sample. Thus, a percentile estimation algorithm may be implemented to approximately calculate percentiles when new data are obtained that exceed a quantity limit of cached data. In such an example, the two nearest data in values may be merged with the low and high bounds and data count recorded. Such logic may group similar values and save different values to minimize error as much as possible for the percentiles.
As to stand detection, a pipe stand detection algorithm may be implemented as part of a T&D monitoring workflow (see, e.g., feature extraction). Inputs for such an algorithm may be or include rig state and block position. Such an algorithm may immediately process received data with relatively few values cached. A new pipe stand may be detected without delay when a rig state indicates just out-of-slips with a connection or disconnection. The stand type, including drilling, tripping in, and tripping out, may also be determined at the same time, for example, based on the previous stand type and the pipe adding or removing status.
As to depth correction, bit depth can be an input to a T&D monitoring workflow. Although depth data may come from data streams directly, it is not generally a direct measurement (e.g., as may be hook load or surface torque). Depth jump, bit depth deeper than hole depth, missing data, no update depth data, etc., may be issues frequently encountered during a workflow. A methodology to improve the depth data quality may include using block position data. For example, bit depth may be counted based on block position changes when a drillstring is out-of-slips between two connections and may be corrected by received bit depth data when it is just out-of-slips after a pipe connection or disconnection. Such an approach helps to ensures stability of depth data within a stand and still considers the pipe tally for depth calibration when a T&D analysis is not triggered. A no-update case may also be considered to rely on block position for the depth inference until valid depth data are available.
As mentioned, a trial results demonstrated robust detection of anomalies. The trial results are based on surface measurement data and contextual data of a North America land well where a stuck incident was reported at approximately 3700 m.
Specifically, the GUI 1300 shows real-time data visualization of T&D with a hook load versus depth plot (top left) with model (lines representing the friction factor range from 0.0 to 0.7) and stand-based statistics (points and horizontal bars); surface torque versus depth plot (top right) with model (lines representing the friction factor range from 0.0 to 0.7) and stand-based means (points); hook load time data (bottom); and hook load anomalies (middle). Relevant metrics may be represented by different colors, for example, consider colors including red for pick-up force, gold for slack-off force, green for free rotation force, and purple for free rotation torque.
In the GUI 1300, broomstick models are displayed to track the overall T&D along measured depth trends computed by the T&D engine with a set of friction factors. To improve readability, stand-based statistics of the measurements are displayed as a function of the models instead of the raw measurements. In addition, the confidence interval between P10 and P90 is indicated as horizontal bars for pick-up and slack-off measurements instead of using one mean value. Such an approach provided for optimized monitoring of the adherence to the model and the variation in the measurements.
As an example, a time data visualization may provide insights from another perspective in a more time-efficient way. For example, actual measurements may be displayed with labeled operation states of pick-up, slack-off, free rotation, and in slips, which are of concern in T&D analysis. Anomalies may be captured by drawing a difference between the measured and the modeled limits as vertical lines.
As an example, a GUI such as the GUI 1500 may be utilized to visualize downhole phenomena that are otherwise not visible to the human eye. As an example, the GUI 1500 may be interactive and provide for setting one or more limits, taking one or more control actions, etc. As an example, the GUI 1500 may provide for automatically issuing a control signal to take a control action responsive to one or more metrics violating one or more limits. For example, consider a control action that is issued to alter drilling operations in a manner that reduces risk of a stuck pipe event, that provides for assessment of one or more pumps, etc.
As explained, an integrated workflow for T&D monitoring and/or control may include data preparation, feature extraction, modeling and calibration, anomaly detection, and data visualization and/or control. Such a workflow may make use of data available to reduce user effort, leading to useful information, which may be used to calibrate a T&D engine. As explained, a calibrated engine may be adapted to changing conditions of a well being drilled (see, e.g., the method 1200 of
Various example techniques have been adopted for handling streaming data processing or analysis. As shown in the trial, stuck pipe was identified along with possible precursors in a manner that demonstrated the benefits of data assessment and/or visualization in both depth and time dimensions, which helps solve for overall trends and instant situations. As an example, a framework may provide for anomaly detection and/or assessment in a real-time manner with a high level of automation, which may further progress digital transformations in the oil and gas industry. Such a framework, per trial results, demonstrates how data may be leveraged for drilling optimization.
In the example of
As to types of machine learning models, consider one or more of a support vector machine (SVM) model, a k-nearest neighbors (KNN) model, an ensemble classifier model, a neural network (NN) model, etc. As an example, a machine learning model may be a deep learning model (e.g., deep Boltzmann machine, deep belief network, convolutional neural network, stacked auto-encoder, etc.), an ensemble model (e.g., random forest, gradient boosting machine, bootstrapped aggregation, AdaBoost, stacked generalization, gradient boosted regression tree, etc.), a neural network model (e.g., radial basis function network, perceptron, back-propagation, Hopfield network, etc.), a regularization model (e.g., ridge regression, least absolute shrinkage and selection operator, elastic net, least angle regression), a rule system model (e.g., cubist, one rule, zero rule, repeated incremental pruning to produce error reduction), a regression model (e.g., linear regression, ordinary least squares regression, stepwise regression, multivariate adaptive regression splines, locally estimated scatterplot smoothing, logistic regression, etc.), a Bayesian model (e.g., naïve Bayes, average on-dependence estimators, Bayesian belief network, Gaussian naïve Bayes, multinomial naïve Bayes, Bayesian network), a decision tree model (e.g., classification and regression tree, iterative dichotomiser 3, C4.5, C5.0, chi-squared automatic interaction detection, decision stump, conditional decision tree, M5), a dimensionality reduction model (e.g., principal component analysis, partial least squares regression, Sammon mapping, multidimensional scaling, projection pursuit, principal component regression, partial least squares discriminant analysis, mixture discriminant analysis, quadratic discriminant analysis, regularized discriminant analysis, flexible discriminant analysis, linear discriminant analysis, etc.), an instance model (e.g., k-nearest neighbor, learning vector quantization, self-organizing map, locally weighted learning, etc.), a clustering model (e.g., k-means, k-medians, expectation maximization, hierarchical clustering, etc.), etc.
As an example, a machine model, which may be a machine learning model (ML model), may be built using a computational framework with a library, a toolbox, etc., such as, for example, those of the MATLAB framework (MathWorks, Inc., Natick, Massachusetts). The MATLAB framework includes a toolbox that provides supervised and unsupervised machine learning algorithms, including support vector machines (SVMs), boosted and bagged decision trees, k-nearest neighbor (KNN), k-means, k-medoids, hierarchical clustering, Gaussian mixture models, and hidden Markov models. Another MATLAB framework toolbox is the Deep Learning Toolbox (DLT), which provides a framework for designing and implementing deep neural networks with algorithms, pretrained models, and apps. The DLT provides convolutional neural networks (ConvNets, CNNs) and long short-term memory (LSTM) networks to perform classification and regression on image, time-series, and text data. The DLT includes features to build network architectures such as generative adversarial networks (GANs) and Siamese networks using custom training loops, shared weights, and automatic differentiation. The DLT provides for model exchange various other frameworks.
As an example, the TENSORFLOW framework (Google LLC, Mountain View, CA) may be implemented, which is an open-source software library for dataflow programming that includes a symbolic math library, which may be implemented for machine learning applications that may include neural networks. As an example, the CAFFE framework may be implemented, which is a DL framework developed by Berkeley AI Research (BAIR) (University of California, Berkeley, California). As another example, consider the SCIKIT platform (e.g., scikit-learn), which utilizes the PYTHON programming language. As an example, a framework such as the APOLLO AI framework may be utilized (APOLLO.AI GmbH, Germany). As an example, a framework such as the PYTORCH framework may be utilized (Facebook AI Research Lab (FAIR), Facebook, Inc., Menlo Park, California).
As an example, a training method may include various actions that may operate on a dataset to train a ML model. As an example, a dataset may be split into training data and test data where test data may provide for evaluation. A method may include cross-validation of parameters and best parameters, which may be provided for model training.
The TENSORFLOW framework may run on multiple CPUs and GPUs (with optional CUDA (NVIDIA Corp., Santa Clara, California) and SYCL (The Khronos Group Inc., Beaverton, Oregon) extensions for general-purpose computing on graphics processing units (GPUs)). TENSORFLOW is available on 64-bit LINUX, MACOS (Apple Inc., Cupertino, California), WINDOWS (Microsoft Corp., Redmond, Washington), and mobile computing platforms including ANDROID (Google LLC, Mountain View, California) and IOS (Apple Inc.) operating system based platforms.
TENSORFLOW computations may be expressed as stateful dataflow graphs; noting that the name TENSORFLOW derives from the operations that such neural networks perform on multidimensional data arrays. Such arrays may be referred to as “tensors”.
A method may include acquiring real-time data during rig operations that include rig operations for drilling a borehole in a subsurface geologic region using a drillstring that includes a drill bit, where the drillstring includes stands of drill pipe; based on stand statistics, using at least a portion of the real-time data, calibrating a torque and drag model that models torque and drag of the drillstring in the borehole; based on operation statistics, calling for use of the torque and drag model to make a prediction; and, based at least in part on the prediction, detecting an anomaly.
As an example, an anomaly may be stuck drill pipe and/or a precursor to struck drill pipe. For example, consider a precursor that includes a variation in one or more of pick-up forces and slack-off forces.
As an example, a method may include determining stand statistics responsive to detection of a rig state indicative of adding a stand for increasing length of a drillstring. As an example, a method may include determining operation statistics responsive to detection of a rig state indicative of type of rig operation.
As an example, a method may include processing real-time data, for example, to generate processed real-time data. In such an example, the processed real-time data may be improved as to quality, for example, processing may involve aligning data from one or more sources, scaling data, identifying missing data (e.g., gaps, etc.), identifying and/or removing outliers, etc. As an example, a method may include detecting a rig state based at least in part on real-time data.
As an example, a method may include calibrating, calling and detecting in a manner that occurs automatically.
As an example, a method may include responsive to detecting an anomaly, issuing a signal. In such an example, the signal may include an alarm and/or a control signal for control of at least one piece of equipment.
As an example, a method may include calibrating that occurs at a connection of a stand to a drillstring and/or calibrating that occurs during drilling using a stand added to a drillstring.
As an example, a method may include generating a visualization in real-time for assessing torque and drag with respect to measured depth of a drill bit. In such an example, the visualization may include indicators of friction factors.
As an example, a method may include calibrating that utilizes a friction factor and/or a linear weight coefficient. As an example, calibrating may calibrate a model using one or more parameters, which may include a friction factor parameter and/or a linear weight coefficient parameter, optionally amongst one or more other parameters.
As an example, a system may include a processor; memory accessible by the processor; processor-executable instructions stored in the memory and executable to instruct the system to: acquire real-time data during rig operations that include rig operations for drilling a borehole in a subsurface geologic region using a drillstring that includes a drill bit, where the drillstring includes stands of drill pipe; based on stand statistics, using at least a portion of the real-time data, calibrate a torque and drag model that models torque and drag of the drillstring in the borehole; based on operation statistics, call for use of the torque and drag model to make a prediction; and, based at least in part on the prediction, detect an anomaly.
As an example, one or more computer-readable storage media may include processor-executable instructions to instruct a computing system to: acquire real-time data during rig operations that include rig operations for drilling a borehole in a subsurface geologic region using a drillstring that includes a drill bit, where the drillstring includes stands of drill pipe; based on stand statistics, using at least a portion of the real-time data, calibrate a torque and drag model that models torque and drag of the drillstring in the borehole; based on operation statistics, call for use of the torque and drag model to make a prediction; and, based at least in part on the prediction, detect an anomaly.
As an example, a method may be implemented in part using computer-readable media (CRM), for example, as a module, a block, etc. that include information such as instructions suitable for execution by one or more processors (or processor cores) to instruct a computing device or system to perform one or more actions. As an example, a single medium may be configured with instructions to allow for, at least in part, performance of various actions of a method. As an example, a computer-readable medium (CRM) may be a computer-readable storage medium (e.g., a non-transitory medium) that is not a carrier wave. As an example, a computer-program product may include instructions suitable for execution by one or more processors (or processor cores) where the instructions may be executed to implement at least a portion of a method or methods.
According to an embodiment, one or more computer-readable media may include computer-executable instructions to instruct a computing system to output information for controlling a process. For example, such instructions may provide for output to sensing process, an injection process, drilling process, an extraction process, an extrusion process, a pumping process, a heating process, etc.
In some embodiments, a method or methods may be executed by a computing system.
As an example, a system may include an individual computer system or an arrangement of distributed computer systems. In the example of
As an example, a module may be executed independently, or in coordination with, one or more processors 1704, which is (or are) operatively coupled to one or more storage media 1706 (e.g., via wire, wirelessly, etc.). As an example, one or more of the one or more processors 1704 may be operatively coupled to at least one of one or more network interface 1707. In such an example, the computer system 1701-1 may transmit and/or receive information, for example, via the one or more networks 1709 (e.g., consider one or more of the Internet, a private network, a cellular network, a satellite network, etc.). As shown, one or more other components 1708 may be included in the computer system 1701-1.
As an example, the computer system 1701-1 may receive from and/or transmit information to one or more other devices, which may be or include, for example, one or more of the computer systems 1701-2, etc. A device may be located in a physical location that differs from that of the computer system 1701-1. As an example, a location may be, for example, a processing facility location, a data center location (e.g., server farm, etc.), a rig location, a wellsite location, a downhole location, etc.
As an example, a processor may be or include a microprocessor, microcontroller, processor module or subsystem, programmable integrated circuit, programmable gate array, or another control or computing device.
As an example, the storage media 1706 may be implemented as one or more computer-readable or machine-readable storage media. As an example, storage may be distributed within and/or across multiple internal and/or external enclosures of a computing system and/or additional computing systems.
As an example, a storage medium or storage media may include one or more different forms of memory including semiconductor memory devices such as dynamic or static random access memories (DRAMs or SRAMs), erasable and programmable read-only memories (EPROMs), electrically erasable and programmable read-only memories (EEPROMs) and flash memories, magnetic disks such as fixed, floppy and removable disks, other magnetic media including tape, optical media such as compact disks (CDs) or digital video disks (DVDs), BLUERAY disks, or other types of optical storage, or other types of storage devices.
As an example, a storage medium or media may be located in a machine running machine-readable instructions, or located at a remote site from which machine-readable instructions may be downloaded over a network for execution.
As an example, various components of a system such as, for example, a computer system, may be implemented in hardware, software, or a combination of both hardware and software (e.g., including firmware), including one or more signal processing and/or application specific integrated circuits.
As an example, a system may include a processing apparatus that may be or include a general purpose processors or application specific chips (e.g., or chipsets), such as ASICs, FPGAs, PLDs, or other appropriate devices.
As an example, a device may be a mobile device that includes one or more network interfaces for communication of information. For example, a mobile device may include a wireless network interface (e.g., operable via IEEE 802.11, ETSI GSM, BLUETOOTH, satellite, etc.). As an example, a mobile device may include components such as a main processor, memory, a display, display graphics circuitry (e.g., optionally including touch and gesture circuitry), a SIM slot, audio/video circuitry, motion processing circuitry (e.g., accelerometer, gyroscope), wireless LAN circuitry, smart card circuitry, transmitter circuitry, GPS circuitry, and a battery. As an example, a mobile device may be configured as a cell phone, a tablet, etc. As an example, a method may be implemented (e.g., wholly or in part) using a mobile device. As an example, a system may include one or more mobile devices.
As an example, a system may be a distributed environment, for example, a so-called “cloud” environment where various devices, components, etc. interact for purposes of data storage, communications, computing, etc. As an example, a device or a system may include one or more components for communication of information via one or more of the Internet (e.g., where communication occurs via one or more Internet protocols), a cellular network, a satellite network, etc. As an example, a method may be implemented in a distributed environment (e.g., wholly or in part as a cloud-based service).
As an example, information may be input from a display (e.g., consider a touchscreen), output to a display or both. As an example, information may be output to a projector, a laser device, a printer, etc. such that the information may be viewed. As an example, information may be output stereographically or holographically. As to a printer, consider a 2D or a 3D printer. As an example, a 3D printer may include one or more substances that may be output to construct a 3D object. For example, data may be provided to a 3D printer to construct a 3D representation of a subterranean formation. As an example, layers may be constructed in 3D (e.g., horizons, etc.), geobodies constructed in 3D, etc. As an example, holes, fractures, etc., may be constructed in 3D (e.g., as positive structures, as negative structures, etc.).
Although only a few examples have been described in detail above, those skilled in the art will readily appreciate that many modifications are possible in the examples. Accordingly, all such modifications are intended to be included within the scope of this disclosure as defined in the following claims. In the claims, means-plus-function clauses are intended to cover the structures described herein as performing the recited function and not only structural equivalents, but also equivalent structures. Thus, although a nail and a screw may not be structural equivalents in that a nail employs a cylindrical surface to secure wooden parts together, whereas a screw employs a helical surface, in the environment of fastening wooden parts, a nail and a screw may be equivalent structures.
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Claims
1. A method comprising:
- acquiring real-time data during rig operations that comprise rig operations for drilling a borehole in a subsurface geologic region using a drillstring that comprises a drill bit, wherein the drillstring comprises stands of drill pipe;
- based on stand statistics, using at least a portion of the real-time data, calibrating a torque and drag model that models torque and drag of the drillstring in the borehole;
- based on operation statistics, calling for use of the torque and drag model to make a prediction; and
- based at least in part on the prediction, detecting an anomaly.
2. The method of claim 1, wherein the anomaly comprises stuck drill pipe.
3. The method of claim 1, wherein the anomaly comprises a precursor to struck drill pipe.
4. The method of claim 3, wherein the precursor comprises a variation in one or more of pick-up forces and slack-off forces.
5. The method of claim 1, comprising determining the stand statistics responsive to detection of a rig state indicative of adding a stand for increasing length of the drillstring.
6. The method of claim 1, comprising determining the operation statistics responsive to detection of a rig state indicative of type of rig operation.
7. The method of claim 1, comprising processing the real-time data to generate processed real-time data.
8. The method of claim 1, comprising detecting a rig state based at least in part on the real-time data.
9. The method of claim 1, wherein the calibrating, calling and detecting occur automatically.
10. The method of claim 1, comprising, responsive to the detecting, issuing a signal.
11. The method of claim 10, wherein the signal comprises an alarm.
12. The method of claim 10, wherein the signal comprises a control signal for control of at least one piece of equipment.
13. The method of claim 1, wherein the calibrating occurs at a connection of a stand to the drillstring.
14. The method of claim 1, wherein the calibrating occurs during drilling using a stand added to the drillstring.
15. The method of claim 1, comprising generating a visualization in real-time for assessing torque and drag with respect to measured depth of the drill bit.
16. The method of claim 15, wherein the visualization comprises indicators of friction factors.
17. The method of claim 1, wherein the calibrating utilizes a friction factor.
18. The method of claim 1, wherein the calibrating utilizes a linear weight coefficient.
19. A system comprising:
- a processor;
- memory accessible by the processor;
- processor-executable instructions stored in the memory and executable to instruct the system to: acquire real-time data during rig operations that comprise rig operations for drilling a borehole in a subsurface geologic region using a drillstring that comprises a drill bit, wherein the drillstring comprises stands of drill pipe; based on stand statistics, using at least a portion of the real-time data, calibrate a torque and drag model that models torque and drag of the drillstring in the borehole; based on operation statistics, call for use of the torque and drag model to make a prediction; and based at least in part on the prediction, detect an anomaly.
20. One or more computer-readable storage media comprising processor-executable instructions to instruct a computing system to:
- acquire real-time data during rig operations that comprise rig operations for drilling a borehole in a subsurface geologic region using a drillstring that comprises a drill bit, wherein the drillstring comprises stands of drill pipe;
- based on stand statistics, using at least a portion of the real-time data, calibrate a torque and drag model that models torque and drag of the drillstring in the borehole;
- based on operation statistics, call for use of the torque and drag model to make a prediction; and
- based at least in part on the prediction, detect an anomaly.
Type: Application
Filed: Oct 18, 2023
Publication Date: Apr 25, 2024
Inventors: Kewen SUN (Beijing), Chao MU (Beijing), Tao YU (Beijing), Graeme PATERSON (Beijing)
Application Number: 18/489,874
