WO2024059710A1

WO2024059710A1 - Drilling control system

Info

Publication number: WO2024059710A1
Application number: PCT/US2023/074188
Authority: WO
Inventors: Nathaniel Wicks; Shunfeng Zheng
Original assignee: Schlumberger Technology Corporation; Schlumberger Canada Limited; Services Petroliers Schlumberger; Schlumberger Technology B.V.
Priority date: 2022-09-14
Filing date: 2023-09-14
Publication date: 2024-03-21

Abstract

A method can include receiving real-time data during a controlled drilling operation performed by a controller, an instrumented rig and a drillstring that includes one or more downhole sensors, where the data include surface data from the instrumented rig and downhole data from the one or more downhole sensors; detecting a drilling behavior during the drilling operation; and generating a control recommendation to mitigate the drilling behavior.

Description

DRILLING CONTROL SYSTEM

RELATED APPLICATIONS

[0001] This application claims priority to and the benefit of a US Provisional Application having Serial No. 63/406,460, filed 14 September 2022, which is incorporated by reference herein in its entirety.

BACKGROUND

[0002] A reservoir can be a subsurface formation that can be characterized at least in part by its porosity and fluid permeability. As an example, a reservoir may be part of a basin such as a sedimentary basin. A basin can be a depression (e.g., caused by plate tectonic activity, subsidence, etc.) in which sediments accumulate. As an example, where hydrocarbon source rocks occur in combination with appropriate depth and duration of burial, a petroleum system may develop within a basin, which may form a reservoir that includes hydrocarbon fluids (e.g., oil, gas, etc.).

[0003] In oil and gas exploration, interpretation is a process that involves analysis of data to identify and locate various subsurface structures (e.g., horizons, faults, geobodies, etc.) in a geologic environment. Various types of structures (e.g., stratigraphic formations) may be indicative of hydrocarbon traps or flow channels, as may be associated with one or more reservoirs (e.g., fluid reservoirs). In the field of resource extraction, enhancements to interpretation can allow for construction of a more accurate model of a subsurface region, which, in turn, may improve characterization of the subsurface region for purposes of resource extraction. Characterization of one or more subsurface regions in a geologic environment can guide, for example, performance of one or more operations (e.g., field operations, etc.). As an example, a more accurate model of a subsurface region may make a drilling operation more accurate as to a borehole’s trajectory where the borehole is to have a trajectory that penetrates a reservoir, etc., where fluid may be produced via the borehole (e.g., as a completed well, etc.). As an example, one or more workflows may be performed using one or more computational frameworks and/or one or more pieces of equipment that include features for one or more of analysis, acquisition, model building, control, etc., for exploration, interpretation, drilling, fracturing, production, etc.

SUMMARY [0004] A method can include receiving real-time data during a controlled drilling operation performed by a controller, an instrumented rig and a drillstring that includes one or more downhole sensors, where the data include surface data from the instrumented rig and downhole data from the one or more downhole sensors; detecting a drilling behavior during the drilling operation; and generating a control recommendation to mitigate the drilling behavior. A system can include a processor; memory accessible to the processor; processor-executable instructions stored in the memory and executable by the processor to instruct the system to: receive real-time data during a controlled drilling operation performed by a controller, an instrumented rig and a drillstring that includes one or more downhole sensors, where the data include surface data from the instrumented rig and downhole data from the one or more downhole sensors; detect a drilling behavior during the drilling operation; and generate a control recommendation to mitigate the drilling behavior. One or more non- transitory computer-readable media can include computer-executable instructions executable by a system to instruct the system to: receive real-time data during a controlled drilling operation performed by a controller, an instrumented rig and a drillstring that includes one or more downhole sensors, where the data include surface data from the instrumented rig and downhole data from the one or more downhole sensors; detect a drilling behavior during the drilling operation; and generate a control recommendation to mitigate the drilling behavior. Various other apparatuses, systems, methods, etc., are also disclosed.

[0005] 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.

BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Features and advantages of the described implementations can be more readily understood by reference to the following description taken in conjunction with the accompanying drawings.

[0007] Fig. 1 illustrates an example system that includes various framework components associated with one or more geologic environments;

[0008] Fig. 2 illustrates examples of systems; [0009] Fig. 3 illustrates an example of a system;

[0010] Fig. 4 illustrates an example of a system;

[0011] Fig. 5 illustrates an example of a system;

[0012] Fig. 6 illustrates example graphics of drilling behaviors;

[0013] Fig. 7 illustrates an example of a graphical user interface;

[0014] Fig. 8 illustrates an example of a graphical user interface;

[0015] Fig. 9 illustrates an example of a graphical user interface;

[0016] Fig. 10 illustrates an example of a graphical user interface;

[0017] Fig. 11 illustrates examples of graphical user interfaces;

[0018] Fig. 12 illustrates an example of a graphical user interface;

[0019] Fig. 13 illustrates an example of a graphical user interface;

[0020] Fig. 14 illustrates an example of a graphical user interface;

[0021] Fig. 15 illustrates an example of a method and an example of a system;

[0022] Fig. 16 illustrates examples of computer and network equipment; and

[0023] Fig. 17 illustrates example components of a system and a networked system.

DETAILED DESCRIPTION

[0024] 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.

[0025] Fig. 1 shows an example of a system 100 that includes a workspace framework 110 that can provide for instantiation of, rendering of, interactions with, etc., a graphical user interface (GUI) 120. In the example of Fig. 1 , the GU1 120 can include graphical controls for computational frameworks (e.g., applications) 121 , projects 122, visualization 123, one or more other features 124, data access 125, and data storage [0026] In the example of Fig. 1 , the workspace framework 110 may be tailored to a particular geologic environment such as an example geologic environment 150. For example, the geologic environment 150 may include layers (e.g., stratification) that include a reservoir 151 and that may be intersected by a fault 153. As an example, the geologic environment 150 may be outfitted with a variety of sensors, detectors, actuators, etc. For example, equipment 152 may include communication circuitry to receive and to transmit information with respect to one or more networks 155. Such information may include information associated with downhole equipment 154, which may be equipment to acquire information, to assist with resource recovery, etc. Other equipment 156 may be located remote from a wellsite and include sensing, detecting, emitting or other circuitry. Such equipment may include storage and communication circuitry to store and to communicate data, instructions, etc. As an example, one or more satellites may be provided for purposes of communications, data acquisition, etc. For example, Fig. 1 shows a satellite in communication with the network 155 that may be configured for communications, noting that the satellite may additionally or alternatively include circuitry for imagery (e.g., spatial, spectral, temporal, radiometric, etc.).

[0027] Fig. 1 also shows the geologic environment 150 as optionally including equipment 157 and 158 associated with a well that includes a substantially horizontal portion that may intersect with one or more fractures 159. For example, consider a well in a shale formation that may include natural fractures, artificial fractures (e.g., hydraulic fractures) or a combination of natural and artificial fractures. As an example, a well may be drilled for a reservoir that is laterally extensive. In such an example, lateral variations in properties, stresses, etc. may exist where an assessment of such variations may assist with planning, operations, etc. to develop a laterally extensive reservoir (e.g., via fracturing, injecting, extracting, etc.). As an example, the equipment 157 and/or 158 may include components, a system, systems, etc. for fracturing, seismic sensing, analysis of seismic data, assessment of one or more fractures, etc.

[0028] In the example of Fig. 1 , the GUI 120 shows some examples of computational frameworks, including the DRILLPLAN, PETREL, TECHLOG, PETROMOD, ECLIPSE, PIPESIM, and INTERSECT frameworks (SLB, Houston, Texas). [0029] The DRILLPLAN framework provides for digital well construction planning and includes features for automation of repetitive tasks and validation workflows, enabling improved quality drilling programs (e.g., digital drilling plans, etc.) to be produced quickly with assured coherency.

[0030] The PETREL framework can be part of the DELFI cognitive E&P environment (SLB, Houston, Texas) for utilization in geosciences and geoengineering, for example, to analyze subsurface data from exploration to production of fluid from a reservoir.

[0031] The TECHLOG framework can handle and process field and laboratory data for a variety of geologic environments (e.g., deepwater exploration, shale, etc.). The TECHLOG framework can structure wellbore data for analyses, planning, etc.

[0032] The PETROMOD framework provides petroleum systems modeling capabilities that can combine one or more of seismic, well, and geological information to model the evolution of a sedimentary basin. The PETROMOD framework can predict if, and how, a reservoir has been charged with hydrocarbons, including the source and timing of hydrocarbon generation, migration routes, quantities, and hydrocarbon type in the subsurface or at surface conditions.

[0033] The ECLIPSE framework provides a reservoir simulator (e.g., as a computational framework) with numerical solutions for fast and accurate prediction of dynamic behavior for various types of reservoirs and development schemes.

[0034] The INTERSECT framework provides a high-resolution reservoir simulator for simulation of detailed geological features and quantification of uncertainties, for example, by creating accurate production scenarios and, with the integration of precise models of the surface facilities and field operations, the INTERSECT framework can produce reliable results, which may be continuously updated by real-time data exchanges (e.g., from one or more types of data acquisition equipment in the field that can acquire data during one or more types of field operations, etc.). The INTERSECT framework can provide completion configurations for complex wells where such configurations can be built in the field, can provide detailed chemical-enhanced-oil-recovery (EOR) formulations where such formulations can be implemented in the field, can analyze application of steam injection and other thermal EOR techniques for implementation in the field, advanced production controls in terms of reservoir coupling and flexible field management, and flexibility to script customized solutions for improved modeling and field management control. The INTERSECT framework, as with the other example frameworks, may be utilized as part of the DELFI cognitive E&P environment, for example, for rapid simulation of multiple concurrent cases. For example, a workflow may utilize one or more of the DELFI on demand reservoir simulation features.

[0035] The aforementioned DELFI environment provides various features for workflows as to subsurface analysis, planning, construction and production, for example, as illustrated in the workspace framework 110. Such an environment may be referred to as a process operations environment that can include a variety of frameworks (e.g., applications, etc.). As shown in Fig. 1 , outputs from the workspace framework 110 can be utilized for directing, controlling, etc., one or more processes in the geologic environment 150 and, feedback 160, can be received via one or more interfaces in one or more forms (e.g., acquired data as to operational conditions, equipment conditions, environment conditions, etc.).

[0036] As an example, a workflow may progress to a geology and geophysics (“G&G”) service provider, which may generate a well trajectory, which may involve execution of one or more G&G software packages. Examples of such software packages include the PETREL framework. As an example, a system or systems may utilize a framework such as the DELFI framework (SLB, Houston, Texas). Such a framework may operatively couple various other frameworks to provide for a multiframework workspace. As an example, the GUI 120 of Fig. 1 may be a GUI of the DELFI framework.

[0037] In the example of Fig. 1 , the visualization features 123 may be implemented via the workspace framework 110, for example, to perform tasks as associated with one or more of subsurface regions, planning operations, constructing wells and/or surface fluid networks, and producing from a reservoir.

[0038] As an example, a visualization process can implement one or more of various features that can be suitable for one or more web applications. For example, a template may involve use of the JAVASCRIPT object notation format (JSON) and/or one or more other languages/formats. As an example, a framework may include one or more converters. For example, consider a JSON to PYTHON converter and/or a PYTHON to JSON converter. Such an approach can provide for compatibility of devices, frameworks, etc., with respect to one or more sets of instructions.

[0039] As an example, visualization features can provide for visualization of various earth models, properties, etc., in one or more dimensions. As an example, visualization features can provide for rendering of information in multiple dimensions, which may optionally include multiple resolution rendering. In such an example, information being rendered may be associated with one or more frameworks and/or one or more data stores. As an example, visualization features may include one or more control features for control of equipment, which can include, for example, field equipment that can perform one or more field operations. As an example, a workflow may utilize one or more frameworks to generate information that can be utilized to control one or more types of field equipment (e.g., drilling equipment, wireline equipment, fracturing equipment, etc.).

[0040] As to a reservoir model that may be suitable for utilization by a simulator, consider acquisition of seismic data as acquired via reflection seismology, which finds use in geophysics, for example, to estimate properties of subsurface formations. As an example, reflection seismology may provide seismic data representing waves of elastic energy (e.g., as transmitted by P-waves and S-waves, in a frequency range of approximately 1 Hz to approximately 100 Hz). Seismic data may be processed and interpreted, for example, to understand better composition, fluid content, extent and geometry of subsurface rocks. Such interpretation results can be utilized to plan, simulate, perform, etc., one or more operations for production of fluid from a reservoir (e.g., reservoir rock, etc.).

[0041] Field acquisition equipment may be utilized to acquire seismic data, which may be in the form of traces where a trace can include values organized with respect to time and/or depth (e.g., consider 1 D, 2D, 3D or 4D seismic data). For example, consider acquisition equipment that acquires digital samples at a rate of one sample per approximately 4 ms. Given a speed of sound in a medium or media, a sample rate may be converted to an approximate distance. For example, the speed of sound in rock may be on the order of around 5 km per second. Thus, a sample time spacing of approximately 4 ms would correspond to a sample “depth” spacing of about 10 meters (e.g., assuming a path length from source to boundary and boundary to sensor). As an example, a trace may be about 4 seconds in duration; thus, for a sampling rate of one sample at about 4 ms intervals, such a trace would include about 1000 samples where latter acquired samples correspond to deeper reflection boundaries. If the 4 second trace duration of the foregoing example is divided by two (e.g., to account for reflection), for a vertically aligned source and sensor, a deepest boundary depth may be estimated to be about 10 km (e.g., assuming a speed of sound of about 5 km per second).

[0042] As an example, a model may be a simulated version of a geologic environment. As an example, a simulator may include features for simulating physical phenomena in a geologic environment based at least in part on a model or models. A simulator, such as a reservoir simulator, can simulate fluid flow in a geologic environment based at least in part on a model that can be generated via a framework that receives seismic data. A simulator can be a computerized system (e.g., a computing system) that can execute instructions using one or more processors to solve a system of equations that describe physical phenomena subject to various constraints. In such an example, the system of equations may be spatially defined (e.g., numerically discretized) according to a spatial model that that includes layers of rock, geobodies, etc., that have corresponding positions that can be based on interpretation of seismic and/or other data. A spatial model may be a cell-based model where cells are defined by a grid (e.g., a mesh). A cell in a cell-based model can represent a physical area or volume in a geologic environment where the cell can be assigned physical properties (e.g., permeability, fluid properties, etc.) that may be germane to one or more physical phenomena (e.g., fluid volume, fluid flow, pressure, etc.). A reservoir simulation model can be a spatial model that may be cell-based.

[0043] A simulator can be utilized to simulate the exploitation of a real reservoir, for example, to examine different productions scenarios to find an optimal one before production or further production occurs. A reservoir simulator does not provide an exact replica of flow in and production from a reservoir at least in part because the description of the reservoir and the boundary conditions for the equations for flow in a porous rock are generally known with an amount of uncertainty. Certain types of physical phenomena occur at a spatial scale that can be relatively small compared to size of a field. A balance can be struck between model scale and computational resources that results in model cell sizes being of the order of meters; rather than a lesser size (e.g., a level of detail of pores). A modeling and simulation workflow for multiphase flow in porous media (e.g., reservoir rock, etc.) can include generalizing real micro-scale data from macro scale observations (e.g., seismic data and well data) and upscaling to a manageable scale and problem size. Uncertainties can exist in input data and solution procedure such that simulation results too are to some extent uncertain. A process known as history matching can involve comparing simulation results to actual field data acquired during production of fluid from a field. Information gleaned from history matching, can provide for adjustments to a model, data, etc., which can help to increase accuracy of simulation.

[0044] As an example, a simulator may utilize various types of constructs, which may be referred to as entities. Entities may include earth entities or geological objects such as wells, surfaces, reservoirs, etc. Entities can include virtual representations of actual physical entities that may be reconstructed for purposes of simulation. Entities may include entities based on data acquired via sensing, observation, etc. (e.g., consider entities based at least in part on seismic data and/or other information). As an example, 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, etc.). Such properties may represent one or more measurements (e.g., acquired data), calculations, etc.

[0045] As an example, a simulator may utilize an object-based software framework, which may include entities based on pre-defined classes to facilitate modeling and simulation. As an example, an object class can encapsulate reusable code and associated data structures. Object classes can be used to instantiate object instances for use by a program, script, etc. For example, borehole classes may define objects for representing boreholes based on well data. A model of a basin, a reservoir, etc. may include one or more boreholes where a borehole may be, for example, for measurements, injection, production, etc. As an example, a borehole may be a wellbore of a well, which may be a completed well (e.g., for production of a resource from a reservoir, for injection of material, etc.).

[0046] While several simulators are illustrated in the example of Fig. 1 , one or more other simulators may be utilized, additionally or alternatively. For example, consider the VISAGE geomechanics simulator (SLB, Houston Texas) or the PIPESIM network simulator (SLB, Houston Texas), etc. The VISAGE simulator includes finite element numerical solvers that may provide simulation results such as, for example, results as to compaction and subsidence of a geologic environment, well and completion integrity in a geologic environment, cap-rock and fault-seal integrity in a geologic environment, fracture behavior in a geologic environment, thermal recovery in a geologic environment, CO2 disposal, etc. The PIPESIM simulator includes solvers that may provide simulation results such as, for example, multiphase flow results (e.g., from a reservoir to a wellhead and beyond, etc.), flowline and surface facility performance, etc. The PIPESIM simulator may be integrated, for example, with the AVOCET production operations framework (SLB, Houston Texas). As an example, a reservoir or reservoirs may be simulated with respect to one or more enhanced recovery techniques (e.g., consider a thermal process such as steam-assisted gravity drainage (SAGD), etc.). As an example, the PIPESIM simulator may be an optimizer that can optimize one or more operational scenarios at least in part via simulation of physical phenomena. The MANGROVE simulator (SLB, Houston, Texas) provides for optimization of stimulation design (e.g., stimulation treatment operations such as hydraulic fracturing) in a reservoir-centric environment. The MANGROVE framework can combine scientific and experimental work to predict geomechanical propagation of hydraulic fractures, reactivation of natural fractures, etc., along with production forecasts within 3D reservoir models (e.g., production from a drainage area of a reservoir where fluid moves via one or more types of fractures to a well and/or from a well). The MANGROVE framework can provide results pertaining to heterogeneous interactions between hydraulic and natural fracture networks, which may assist with optimization of the number and location of fracture treatment stages (e.g., stimulation treatment(s)), for example, to increased perforation efficiency and recovery.

[0047] The PETREL framework provides components that allow for optimization of exploration and development operations. The PETREL framework includes seismic to simulation software components that can 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, and reservoir engineers) can develop collaborative workflows and integrate operations to streamline processes (e.g., with respect to one or more geologic environments, etc.). Such a framework may be considered an application (e.g., executable using one or more devices) and may be considered a data-driven application (e.g., where data is input for purposes of modeling, simulating, etc.).

[0048] As mentioned, 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 can 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 can include various other frameworks, which can include, for example, one or more types of models (e.g., simulation models, etc.).

[0049] As an example, data can include geochemical data. For example, consider data acquired using X-ray fluorescence (XRF) technology, Fourier transform infrared spectroscopy (FTIR) technology and/or wireline geochemical technology.

[0050] As an example, one or more probes may be deployed in a bore via a wireline or wirelines. As an example, a probe may emit energy and receive energy where such energy may be analyzed to help determine mineral composition of rock surrounding a bore. As an example, nuclear magnetic resonance may be implemented (e.g., via a wireline, downhole NMR probe, etc.), for example, to acquire data as to nuclear magnetic properties of elements in a formation (e.g., hydrogen, carbon, phosphorous, etc.).

[0051] As an example, lithology scanning technology may be employed to acquire and analyze data. For example, consider the LITHO SCANNER technology marketed by SLB (Houston, Texas). As an example, a LITHO SCANNER tool may be a gamma ray spectroscopy tool.

[0052] As an example, a tool may be positioned to acquire information in a portion of a borehole. Analysis of such information may reveal 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 fractured reservoir, optionally where fractures may be natural and/or artificial (e.g., hydraulic fractures). Such information may assist with completions, stimulation treatment, etc. As an example, information acquired by a tool may be analyzed using a framework such as the aforementioned TECHLOG framework (SLB, Houston, Texas).

[0053] As an example, a workflow may utilize one or more types of data for one or more processes (e.g., stratigraphic modeling, basin modeling, completion designs, drilling, production, injection, etc.). As an example, one or more tools may provide data that can be used in a workflow or workflows that may implement one or more frameworks (e.g., PETREL, TECHLOG, PETROMOD, ECLIPSE, etc.).

[0054] Fig. 2 shows an example of a geologic environment 210 that includes reservoirs 211 -1 and 211-2, which may be faulted by faults 212-1 and 212-2, an example of a network of equipment 230, an enlarged view of a portion of the network of equipment 230, referred to as network 240, and an example of a system 250. Fig. 2 shows some examples of offshore equipment 214 for oil and gas operations related to the reservoir 211 -2 and onshore equipment 216 for oil and gas operations related to the reservoir 211 -1.

[0055] In the example of Fig. 2, the various equipment 214 and 216 can include drilling equipment, wireline equipment, production equipment, etc. For example, consider the equipment 214 as including a drilling rig that can drill into a formation to reach a reservoir target where a well can be completed for production of hydrocarbons. In such an example, one or more features of the system 100 of Fig. 1 may be utilized. For example, consider utilizing a drilling or well plan framework, a drilling execution framework, etc., to plan, execute, etc., one or more drilling operations.

[0056] In Fig. 2, the network 240 can be an example of a relatively small production system network. As shown, the network 240 forms somewhat of a tree like structure where flowlines represent branches (e.g., segments) and junctions represent nodes. As shown in Fig. 2, the network 240 provides for transportation of oil and gas fluids from well locations along flowlines interconnected at junctions with final delivery at a central processing facility.

[0057] In the example of Fig. 2, various portions of the network 240 may include conduit. For example, consider a perspective view of a geologic environment that includes two conduits which may be a conduit to Mani and a conduit to Man3 in the network 240. [0058] As shown in Fig. 2, the example system 250 includes one or more information storage devices 252, one or more computers 254, one or more networks 260 and instructions 270 (e.g., organized as one or more sets of instructions). As to the one or more computers 254, each computer may include one or more processors (e.g., or processing cores) 256 and memory 258 for storing the instructions 270 (e.g., one or more sets of instructions), for example, executable by at least one of the one or more processors. As an example, a computer may include one or more network interfaces (e.g., wired or wireless), one or more graphics cards, a display interface (e.g., wired or wireless), etc. As an example, imagery such as surface imagery (e.g., satellite, geological, geophysical, etc.) may be stored, processed, communicated, etc. As an example, data may include SAR data, GPS data, etc. and may be stored, for example, in one or more of the storage devices 252. As an example, information that may be stored in one or more of the storage devices 252 may include information about equipment, location of equipment, orientation of equipment, fluid characteristics, etc.

[0059] As an example, the instructions 270 can include instructions (e.g., stored in the memory 258) executable by at least one of the one or more processors 256 to instruct the system 250 to perform various actions. As an example, the system 250 may be configured such that the instructions 270 provide for establishing a framework, for example, that can perform network modeling (see, e.g., the PIPESIM framework of the example of Fig. 1 , etc.). As an example, one or more methods, techniques, etc. may be performed using one or more sets of instructions, which may be, for example, the instructions 270 of Fig. 2.

[0060] Fig. 3 shows an example of a wellsite system 300 (e.g., at a wellsite that may be onshore or offshore). As shown, the wellsite system 300 can include a mud tank 301 for holding mud and other material (e.g., where mud can be a drilling fluid), a suction line 303 that serves as an inlet to a mud pump 304 for pumping mud from the mud tank 301 such that mud flows to a vibrating hose 306, a drawworks 307 for winching drill line or drill lines 312, a standpipe 308 that receives mud from the vibrating hose 306, a kelly hose 309 that receives mud from the standpipe 308, a gooseneck or goosenecks 310, a traveling block 311 , a crown block 313 for carrying the traveling block 311 via the drill line or drill lines 312, a derrick 314, a kelly 318 or a top drive 340, a kelly drive bushing 319, a rotary table 320, a drill floor 321 , a bell nipple 322, one or more blowout preventers (BOPs) 323, a drillstring 325, a drill bit 326, a casing head 327 and a flow pipe 328 that carries mud and other material to, for example, the mud tank 301 .

[0061] A derrick can 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).

[0062] As an example, the drawworks 307 may include a spool, brakes, a power source and assorted auxiliary devices. The drawworks 307 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 can 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.).

[0063] As an example, a crown block can include a set of pulleys (e.g., sheaves) that can be located at or near a top of a derrick or a mast, over which line is threaded. A traveling block can include a set of sheaves that can 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 can 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.

[0064] 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 can 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 or pull out of hole (POOH), 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 pipehandling equipment such that the derrickman controls the machinery rather than physically handling the pipe.

[0065] In the example system of Fig. 3, a borehole 332 is formed in subsurface formations 330 by rotary drilling; noting that various example embodiments may also use one or more directional drilling techniques, equipment, etc.

[0066] As shown in the example of Fig. 3, the drillstring 325 is suspended within the borehole 332 and has a drillstring assembly 350 that includes the drill bit 326 at its lower end. As an example, the drillstring assembly 350 may be a bottom hole assembly (BHA).

[0067] The wellsite system 300 can provide for operation of the drillstring 325 and other operations. As shown, the wellsite system 300 includes the traveling block 311 and the derrick 314 positioned over the borehole 332. As mentioned, the wellsite system 300 can include the rotary table 320 where the drillstring 325 pass through an opening in the rotary table 320.

[0068] As shown in the example of Fig. 3, the wellsite system 300 can include the kelly 318 and associated components, etc., or the top drive 340 and associated components. As to a kelly example, the kelly 318 may be a square or hexagonal metal/alloy bar with a hole drilled therein that serves as a mud flow path. The kelly 318 can be used to transmit rotary motion from the rotary table 320 via the kelly drive bushing 319 to the drillstring 325, while allowing the drillstring 325 to be lowered or raised during rotation. The kelly 318 can pass through the kelly drive bushing 319, which can be driven by the rotary table 320. As an example, the rotary table 320 can include a master bushing that operatively couples to the kelly drive bushing 319 such that rotation of the rotary table 320 can turn the kelly drive bushing 319 and hence the kelly 318. The kelly drive bushing 319 can include an inside profile matching an outside profile (e.g., square, hexagonal, etc.) of the kelly 318; however, with slightly larger dimensions so that the kelly 318 can freely move up and down inside the kelly drive bushing 319. [0069] As to a top drive example, the top drive 340 can provide functions performed by a kelly and a rotary table. The top drive 340 can turn the drillstring 325. As an example, the top drive 340 can 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 325 itself. The top drive 340 can be suspended from the traveling block 311 , so the rotary mechanism is free to travel up and down the derrick 314. As an example, a top drive 340 may allow for drilling to be performed with more joint stands than a kelly/rotary table approach.

[0070] In the example of Fig. 3, the mud tank 301 can hold mud, which can be one or more types of drilling fluids. As an example, a wellbore may be drilled to produce fluid, inject fluid or both (e.g., hydrocarbons, minerals, water, etc.).

[0071] In the example of Fig. 3, the drillstring 325 (e.g., including one or more downhole tools) may be composed of a series of pipes threadably connected together to form a long tube with the drill bit 326 at the lower end thereof. As the drillstring 325 is advanced into a wellbore for drilling, at some point in time prior to or coincident with drilling, the mud may be pumped by the pump 304 from the mud tank 301 (e.g., or other source) via a the lines 306, 308 and 309 to a port of the kelly 318 or, for example, to a port of the top drive 340. The mud can then flow via a passage (e.g., or passages) in the drillstring 325 and out of ports located on the drill bit 326 (see, e.g., a directional arrow). As the mud exits the drillstring 325 via ports in the drill bit 326, it can then circulate upwardly through an annular region between an outer surface(s) of the drillstring 325 and surrounding wall(s) (e.g., open borehole, casing, etc.), as indicated by directional arrows. In such a manner, the mud lubricates the drill bit 326 and carries heat energy (e.g., frictional or other energy) and formation cuttings to the surface where the mud (e.g., and cuttings) may be returned to the mud tank 301 , for example, for recirculation (e.g., with processing to remove cuttings, etc.).

[0072] The mud pumped by the pump 304 into the drillstring 325 may, after exiting the drillstring 325, form a mudcake that lines the wellbore which, among other functions, may reduce friction between the drillstring 325 and surrounding wall(s) (e.g., borehole, casing, etc.). A reduction in friction may facilitate advancing or retracting the drillstring 325. During a drilling operation, the entire drillstring 325 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.

[0073] As an example, consider a downward trip where upon arrival of the drill bit 326 of the drillstring 325 at a bottom of a wellbore, pumping of the mud commences to lubricate the drill bit 326 for purposes of drilling to enlarge the wellbore. As mentioned, the mud can be pumped by the pump 304 into a passage of the drillstring 325 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.

[0074] 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 325) may be transmitted uphole to an uphole device, which may relay such information to other equipment for processing, control, etc.

[0075] As an example, telemetry equipment may operate via transmission of energy via the drillstring 325 itself. For example, consider a signal generator that imparts coded energy signals to the drillstring 325 and repeaters that may receive such energy and repeat it to further transmit the coded energy signals (e.g., information, etc.).

[0076] As an example, the drillstring 325 may be fitted with telemetry equipment 352 that includes a rotatable drive shaft, a turbine impeller mechanically coupled to the drive shaft such that the mud can 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.

[0077] In the example of Fig. 3, an uphole control and/or data acquisition system 362 may include circuitry to sense pressure pulses generated by telemetry equipment 352 and, for example, communicate sensed pressure pulses or information derived therefrom for process, control, etc.

[0078] The assembly 350 of the illustrated example includes a logging-while- drilling (LWD) module 354, a measurement-while-drilling (MWD) module 356, an optional module 358, a rotary-steerable system (RSS) and/or motor 360, and the drill bit 326. Such components or modules may be referred to as tools where a drillstring can include a plurality of tools.

[0079] 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 can 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.

[0080] One approach to directional drilling involves a mud motor; however, a mud motor can 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 can 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. [0081] 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 can 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.

[0082] As an example, a PDM mud motor can operate in a so-called sliding mode, when the drillstring is not rotated from the surface. In such an example, a bit RPM can be determined or estimated based on the RPM of the mud motor.

[0083] A RSS can drill directionally where there is continuous rotation from surface equipment, which can alleviate the sliding of a steerable motor (e.g., a PDM). A RSS may be deployed when drilling directionally (e.g., deviated, horizontal, or extended-reach wells). A RSS can aim to minimize interaction with a borehole wall, which can help to preserve borehole quality. A RSS can 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.

[0084] The LWD module 354 may be housed in a suitable type of drill collar and can 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 can be employed, for example, as represented at by the LWD module 354 and/or the MWD module 356 of the drillstring assembly 350. Where the position of an LWD module is mentioned, as an example, it may refer to a module at the position of the LWD module 354, the MWD module 356, etc. An LWD module can include capabilities for measuring, processing, and storing information, as well as for communicating with the surface equipment. In the illustrated example, the LWD module 354 may include a seismic measuring device.

[0085] The MWD module 356 may be housed in a suitable type of drill collar and can contain one or more devices for measuring characteristics of the drillstring 325 and the drill bit 326. As an example, the MWD module 356 may include equipment for generating electrical power, for example, to power various components of the drillstring 325. As an example, the MWD module 356 may include the telemetry equipment 352, for example, where the turbine impeller can 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 356 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.

[0086] Fig. 3 also shows some examples of types of holes that may be drilled. For example, consider a slant hole 372, an S-shaped hole 374, a deep inclined hole 376 and a horizontal hole 378.

[0087] As an example, a drilling operation can 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.

[0088] As an example, a directional well can 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.

[0089] As an example, deviation of a bore may be accomplished in part by use of a downhole motor and/or a turbine. As to a motor, for example, a drillstring can include a positive displacement motor (PDM).

[0090] As an example, a system may be a steerable system and include equipment to perform method such as geosteering. As mentioned, a steerable system can be or include an RSS. As an example, a steerable system can include a PDM or of a turbine on a lower part of a drillstring which, just above a drill bit, a bent sub can 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 can 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.).

[0091] 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, can allow for implementing a geosteering method. Such a method can include navigating a subsurface environment, for example, to follow a desired route to reach a desired target or targets.

[0092] As an example, a drillstring can 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.

[0093] As an example, geosteering can 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.

[0094] Referring again to Fig. 3, the wellsite system 300 can include one or more sensors 364 that are operatively coupled to the control and/or data acquisition system 362. As an example, a sensor or sensors may be at surface locations. As an example, a sensor or sensors may be at downhole locations. As an example, a sensor or sensors may be at one or more remote locations that are not within a distance of the order of about one hundred meters from the wellsite system 300. As an example, a sensor or sensor may be at an offset wellsite where the wellsite system 300 and the offset wellsite are in a common field (e.g., oil and/or gas field).

[0095] As an example, one or more of the sensors 364 can be provided for tracking pipe, tracking movement of at least a portion of a drillstring, etc. [0096] As an example, the system 300 can include one or more sensors 366 that can 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 300, the one or more sensors 366 can be operatively coupled to portions of the standpipe 308 through which mud flows. As an example, a downhole tool can generate pulses that can travel through the mud and be sensed by one or more of the one or more sensors 366. In such an example, the downhole tool can include associated circuitry such as, for example, encoding circuitry that can 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 300 can include a transmitter that can generate signals that can be transmitted downhole via mud (e.g., drilling fluid) as a transmission medium.

[0097] As an example, one or more portions of a drillstring may become stuck. The term stuck can 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.

[0098] As to the term “stuck pipe”, this can refer to a portion of a drillstring that cannot be rotated or moved axially. As an example, a condition referred to as “differential sticking” can 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 can have time and financial cost.

[0099] As an example, a sticking force can 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 can be just as effective in sticking pipe as can a high differential pressure applied over a small area.

[00100] As an example, a condition referred to as “mechanical sticking” can be a condition where limiting or prevention of motion of the drillstring by a mechanism other than differential pressure sticking occurs. Mechanical sticking can 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.

[00101] Fig. 4 shows an example of a wellsite system 400, specifically, Fig. 4 shows the wellsite system 400 in an approximate side view and an approximate plan view along with a block diagram of a system 470.

[00102] In the example of Fig. 4, the wellsite system 400 can include a cabin 410, a rotary table 422, drawworks 424, a mast 426 (e.g., optionally carrying a top drive, etc.), mud tanks 430 (e.g., with one or more pumps, one or more shakers, etc.), one or more pump buildings 440, a boiler building 442, an HPU building 444 (e.g., with a rig fuel tank, etc.), a combination building 448 (e.g., with one or more generators, etc.), pipe tubs 462, a catwalk 464, a flare 468, etc. Such equipment can include one or more associated functions and/or one or more associated operational risks, which may be risks as to time, resources, and/or humans.

[00103] As shown in the example of Fig. 4, the wellsite system 400 can include a system 470 that includes one or more processors 472, memory 474 operatively coupled to at least one of the one or more processors 472, instructions 476 that can be, for example, stored in the memory 474, and one or more interfaces 478. As an example, the system 470 can include one or more processor-readable media that include processor-executable instructions executable by at least one of the one or more processors 472 to cause the system 470 to control one or more aspects of the wellsite system 400. In such an example, the memory 474 can be or include the one or more processor-readable media where the processor-executable instructions can be or include instructions. As an example, a processor-readable medium can be a computer-readable storage medium that is not a signal and that is not a carrier wave.

[00104] Fig. 4 also shows a battery 480 that may be operatively coupled to the system 470, for example, to power the system 470. As an example, the battery 480 may be a back-up battery that operates when another power supply is unavailable for powering the system 470. As an example, the battery 480 may be operatively coupled to a network, which may be a cloud network. As an example, the battery 480 can include smart battery circuitry and may be operatively coupled to one or more pieces of equipment via a SMBus or other type of bus.

[00105] In the example of Fig. 4, services 490 are shown as being available, for example, via a cloud platform. Such services can include data services 492, query services 494 and drilling services 496. As an example, the services 490 may be part of a system such as the system 300 of Fig. 3.

[00106] As an example, the system 470 may be utilized to generate one or more rate of penetration drilling parameter values, which may, for example, be utilized to control one or more drilling operations.

[00107] Fig. 5 shows an example of a system 500 that includes a downhole data block 510, a telemetry block 514, a surface acquisition block 518, a surface data block 520, and a combined surface and downhole data acquisition and visualization system block 540 that includes a data analytics engine 545. As shown, the system 500 may include and/or be operatively coupled to one or more control system blocks 560 and one or more controllers, which can include, for example, controllers for autodriller control, top drive control, drawworks control, shown in Fig. 5 as an autodriller controller 562, a top drive controller 564 and a drawworks controller 566. In the example of Fig. 5, an approach can acquire surface data and downhole data and optionally synchronizes them automatically. In Fig. 5, an example of a top drive 570 and an example of a drawworks 580 are also shown, which may be operatively coupled and/or include respective controllers.

[00108] In the example of Fig. 5, the data analytics engine 545 can be a processor-based computation engine that can analyze data, diagnostics dysfunction, recommend corrective actions, and automatically feed one or more recommended actions to one or more of the one or more control systems 560. In such an example, output of the system 500 may be generated and appropriately directed in a timely manner (e.g., on-demand, responsive to output, according to a schedule, according to a trigger, according to an event, etc.) without user intervention.

[00109] The system 500 can be utilized to perform one or more methods, which may be part of one or more workflows. For example, the system 500 can acquire data from a variety of sources, which include downhole sources and surface sources. As an example, the system 500 can generate visualizations based on combined results, which can provide insights into which equipment is operating, interacting with rock, etc. As explained, a system, a method, a workflow, etc., may be configured to run in real-time. In such instances, real-time data channels may be utilized, which may provide for real-time control.

[00110] As to drawworks control, it can be utilized to control a drillstring going into and out of a borehole. As an example, rate of penetration (ROP) can be determined using drawworks information. As to top drive control, it can be utilized for one or more purposes, which can include rotary drilling, oscillation while slide drilling, etc. As an example, an autodriller can be a type of controller that may control drawworks to achieve a certain ROP, WOB, etc.

[00111] As to slide drilling, it can be a particular mode of drilling that utilizes a mud motor driven by mud (drilling fluid) for rotating a bit of a drillstring downhole without rotating the drillstring from the surface (e.g., noting that oscillation may be utilized to oscillate the drillstring from the surface). Slide drilling may be conducted when a BHA has been fitted with a bent sub or a bent housing mud motor, or both, for directional drilling. Slide drilling may be utilized to build and control or correct hole angle in directional drilling operations. Directional drilling can involve pointing a bit in a desired direction where such pointing may be accomplished through a bent sub, which has a small angle offset from the axis of the drillstring, and a measurement device to determine the direction of offset. As explained, in slide drilling, without turning the drillstring, the bit can be rotated with a mud motor, and drill in the direction it points. With steerable motors, when the desired wellbore direction is attained, the entire drillstring may be rotated and, for example, drill straight rather than at an angle. By controlling the amount of hole drilled in the sliding versus the rotating mode, a system may generate a trajectory in a more precisely controlled manner.

[00112] As shown in Fig. 5, the top drive 570 can turn a string, for example, via one or more motors (e.g., electric, hydraulic, etc.). As an example, a top drive can include gearing that can be coupled to a short section of pipe called a quill, which, in turn, may be screwed into a saver sub or a string. As an example, a top drive may be suspended from a hook. In such an example, the rotary mechanism can travel up and down a derrick or a mast. A top drive arrangement may be used with or without a rotary table and kelly for turning a string (e.g., a drillstring).

[00113] As shown in Fig. 5, the drawworks 580 can be operatively coupled to line where the line includes a so-called deadline and a supply reel line operatively coupled to a body. The drawworks 580 can include one or more drivers, such as, for example, one or more motors that can control rotation of a reel, line, etc. For example, consider one or more electric motors (e.g., DC or AC). In the example of Fig. 5, a deadline tiedown anchor of the body can firmly grip one end of the drilling line and keeps it from moving; noting that the body itself is anchored, for example, via an anchoring mechanism (e.g., bolted to a rig’s substructure or to another heavy, stationary part of the rig).

[00114] Besides anchoring the drilling line, the drawworks 580 can also serve as a mount for a weight indicator sensor such as a load sensor. Such a sensor may be operatively coupled to a hydraulic line that can output a weight indication to a gauge, etc. For example, a drilling console can include a gauge that indicates to an operator how much a traveling block load may be and, for example, how much weight is on a bit. As an example, a load may be referred to as a hookload, which indicates how much weight is hanging from a hook. As an example, weight on a bit may be how much drill stem weight is pressing on the bit.

[00115] As an example, a load sensor may be a strain sensor (e.g., a strain gauge). As an example, as weight of a load on a deadline flexes the deadline, the load sensor can pick up the flexes and send a signal to the weight indicator gauge (e.g., on the rig floor, drilling console, etc.). The weight indicator may be configured to translate such a signal into weight on the bit and the hookload.

[00116] As an example, the drawworks 580 can be used to estimate depth of equipment in a bore in a geologic environment. For example, depth of a drill bit may be of interest, depth of a tool may be of interest, etc. As an example, where a tool can acquire measurements in a bore, these may be recorded, plotted, analyzed, etc., with respect to depth. As an example, a depth tracking system based on a rotary encoder records movement of a travelling block in between joints to infer measurement of pipe length as it is lowered into or pulled out of the ground. Other measurements may be derived from a rotary encoder process. For example, it may be possible to track rate of penetration while drilling, or pipe speed when tripping (e.g., measurements that help provide for safe and efficient operations).

[00117] As an example, a drawworks sensor can be easier and safer to install than a geolograph and utilize a more compact approach by installing the rotary encoder directly on a main shaft of a drill hoisting drum. Depending on length of cable wrapped onto a drawworks drum, to allow for a complete block travel on a derrick, it may wrap onto itself, for example, about 2 or 3 times. In such an approach, the effective diameter of the drum changes, and one revolution of the rotary encoder corresponds to different lengths of line spooling off the drum, hence different distances travelled by the block. Due to multi-wrapping, use of a drawworks encoder involves a relatively complicated calibration procedure, which is to be repeated each time the drill line is replaced due to wear. Further, to calibration, a block reference is often to be reset. Being mechanical in nature and being in-line with the main drawworks shaft means that operations are stopped to perform replacement.

[00118] Knowledge of depth can help inform an operator as to a well’s actual location, how much casing to bring to a well site, where perforating may be performed, and log information (e.g., to answer a question as to whether a log shows an actual extent of a reservoir). Such concerns can exist where there are mismatches between a driller’s tally, wireline depth, and while drilling depth.

[00119] Fig. 6 shows example graphics 610, 620 and 630 as to various types of behaviors that may arise during drilling. In particular, such behaviors can be drillstring vibrations, which may be divided into three types, or modes: axial, torsional, and lateral. The destructive nature of each type of vibration is different. Axial vibrations can cause bit bounce, which may damage bit cutters and bearings. Torsional vibrations can cause irregular downhole rotation. Stick/slip may be seen while drilling and can be characterized as a severe form of drillstring torsional oscillation in which the bit becomes stationary for a period. As the seventy of stick/slip increases, the length of the “stuck” period increases, as do the rotational accelerations as the bit breaks free. The graphic 610 shows some examples of axial, torsional and lateral vibrations while the graphic 620 shows an example of stick-slip where downhole RPM goes to zero (e.g., stuck) for some periods of time on the order of a second or less. Torsional fluctuations fatigue drill collar connections and can damage bits. The use of a mud motor may help to address stick/slip if a primary source of excitation is from the bit, but the presence of a motor does not prevent stick/slip. A drillstring and BHA above a motor can enter into a stick/slip motion even when the motor is turning the bit at a steady rate.

[00120] Lateral vibrations tend to be the most destructive type of vibration and can create large shocks as the BHA impacts the wellbore wall. The interaction between BHA and drillstring contact points may, in certain circumstances, drive a system into backward whirl. Backward whirl is a severe form of vibration, creating high-frequency large-magnitude bending moment fluctuations that result in high rates of component and connection fatigue. Imbalance in an assembly can cause centrifugally induced bowing of a drillstring, which may produce forward whirl and result in one-sided wear of components. In Fig. 6, the graphic 630 shows some actions associated with whirl.

[00121] Vibrations of the three types (axial, torsional, and lateral) may occur during rotary drilling and can be coupled. Induced axial vibrations at the bit can lead to lateral vibrations in the BHA, and axial and torsional vibrations observed at the rig floor may actually be related to severe lateral vibrations downhole near the bit. At other times, severe axial vibrations near the bit may show no visible vibrations at the surface.

[00122] Fig. 7 shows an example of a graphical user interface (GUI) 700 that can include various features for controller set up where, for example, a system such as the system 500 of Fig. 5 can be utilized to help guide an operator or operators when using a controller. For example, a controller may operate according to one or more control routines that aim to address common scenarios; however, during actual drilling, one or more other scenarios may arise. The GUI 700 may provide for issuing notifications as to one or more types of scenarios, which can include one or more control notifications. As an example, a control notification may be consumable by a controller and/or by an operator (e.g., via graphical presentation, etc.). For example, if a scenario arises that may not be within the scope of a controller’s routines, a notification can be generated that may act to adjust control and/or notify an operator as to appropriate control action.

[00123] As an example, the GUI 700 may be implemented as part of a computational framework such as, for example, the TECHLOG framework, which may be part of the DELFI environment. As shown, a framework may provide for acquisition of and rendering of tracks of data that can include surface data and downhole data. As an example, a track may be a log, which may be rendered with respect to time, with respect to depth, etc. As an example, a framework may operate using one or more application programming interfaces (APIs) and provide for use of scripts such as, for example, PYTHON language scripts.

[00124] In the example of Fig. 7, the GUI 700 can include access to set points, tunable controller parameters, notifications, etc. As shown, monitoring and/or control may be set up to import various surface data and various downhole data, which may occur automatically upon selection of one or more types of behaviors (see, e.g., Fig. 6). As explained, where a behavior may be outside the scope of a controller’s control domain, the system 500 may be utilized to generate appropriate control recommendations, which may be implemented automatically and/or upon review by an operator or operators.

[00125] As an example, a system can be built into or built on top of an autodriller and/or another controller. In such an example, the system may be local and/or remote. For example, consider a local implementation where the system 500 operates using a system such as the system 470 of Fig. 4, which can be at a wellsite and operatively coupled to equipment for both surface and downhole data acquisition. In such an example, an autodriller may be implemented using the system 470 where, as mentioned, the autodriller controller 562 and the system 500 may be operatively coupled. As explained, a system and/or services for a system may be remote, for example, operable in a cloud environment. As an example, the GUI 700 may provide for setting up a system locally and/or remotely to enhance control of equipment at a wellsite or wellsites.

[00126] As an example, a controller such as an autodriller may be proprietary such that its routines are not readily accessible to an operator. As an example, the system 500 can be utilized to check on behavior of a proprietary controller without having access to routines of the controller. For example, the system 500 may provide for behavior observation and diagnostics of a proprietary controller that may appear somewhat as a black box to an operator. Such an approach can provide for safety and information as to how a proprietary controller handles certain scenarios or does not handle certain scenarios. As explained, a system can generate recommendations, which may be specific to a particular controller, whether the controller is capable of acting on such recommendations or not. For example, a system may indicate that a particu lar parameter can be tuned even where an operator may not be able to access that particular parameter for tuning. In such a situation, the operator may disable the controller or one or more routines thereof, if such selection of a routine or routines is provided for by the controller.

[00127] As an example, the system 500 of Fig. 5 can provide indications of when a controller can be enabled and/or disabled. For example, where behavior is exhibited that is beyond the scope of a controller, it may be disabled, optionally automatically with a notification to an operator (e.g., a driller, etc.). In a situation where a controller is disabled and conditions change, the system 500 may provide for issuing a notification that the controller may be enabled as the conditions, as determined by downhole and/or surface data, are within the scope of the controllers domain.

[00128] As an example, the system 500 can provide for assurances that may lead to more widespread adoption of one or more controllers such as, for example, a stick-slip mitigation controller, a bounce mitigation controller, a vibration mitigation controller, etc., which may be implemented using one or more of the one or more control systems 560.

[00129] As explained, a system can provide for monitoring the drilling of oil and gas wells where such monitoring can be utilized to improve drilling performance, which may be via one or more controllers. As indicated in the example of Fig. 5, a system can stream live drilling data from multiple sources into one data visualization platform, which may include features for automated, semi-automated and/or manual control of equipment operations. As to automation, a system may provide for multiple levels of automation. As an example, a system may provide for automated transitions between levels of automation. For example, consider a system that may detect one or more issues where a particular level of automation may be challenged. In such an example, the system may select and transition to another level of automation that may involve a human in the loop (HITL), which may be a semi-automated level of automation where, for example, a GUI can provide for visualization of information that can guide the HITL in control of equipment to perform one or more operations. In such an example, the one or more operations may be to extend a borehole via drilling using a drill bit, mitigate a behavior, pull a drillstring out of a borehole (POOH), run a drillstring into a borehole (RIH), etc. Multiple sources of data can provide for data that include rig control system (RCS) data (e.g., surface data) as well as data received via telemetry from one or more downhole tools (e.g., MWD, LWD, steering tools, etc.). As an example, the system 500 can provide for intuitive real-time visualization of data that combines surface and downhole data to give an operator insight into the combined surface and downhole behavior while drilling, which may be performed at least in part using one or more automated controllers (e.g., an autodriller, etc.).

[00130] As explained, the system 500 can operate in real-time where a system (e.g., a control system) and/or a human operator can, based on acquired data, modify settings of surface and downhole control in order to improve the performance/behavior. As explained, such a system may provide for detection of one or more behaviors and mitigation of one or more of such behaviors, which via mitigation improve one or more drilling operations. In such an approach, improvement may be due to preservation of equipment life (e.g., drill bit life), increased borehole integrity, use of lesser resources (e.g., equipment, energy, human labor, etc.), generation of lesser emissions, less non-productive time (NPT), etc.

[00131] As an example, the system 500 may provide for observing and mitigating dysfunction in real-time via diagnosis using surface RCS individual controller data, diagnosis using combined surface RCS controller data complementary to downhole tool data, and diagnosis of interaction between multiple surface controllers, and may provide recommendations to cure dysfunctions of one or more controllers. In such an example, the system 500 may provide for different case scenarios where the aforementioned three types of diagnosis may be implemented individually and/or in a combined manner (e.g., of two or more). As an example, the system 500 may automatically implement generated recommendations to one or more of the one or more control systems 560 to cure dysfunctions of a controller or controllers without human intervention (e.g., without intervention by a human driller).

[00132] While drilling, data from an RCS and from downhole tools may be available to a driller, however, in different systems. Real-time data analysis may not be a driller’s focus and a driller may lack the expertise, tools, and time required to synthesize data provided by disparate systems. At the same time, remote engineers may have access to downhole and surface data in real-time (or quasi-real-time), but do not have access to RCS controller data, which can limit their ability to fully understand the status of the drilling system and to give improvement recommendations. As an example, the system 500 of Fig. 5 may provide features that can address such limitations, which may provide for increased automation and/or confidence in automation. For example, if confidence in automation is lacking for one or more reasons, the system 500 may provide for particular outputs that can increase confidence in a data-driven manner, which, as explained, may provide for automated selection of and/or transition to a level of automation from a number of levels of automation and/or to a manual level of control where appropriate, which may be via manual control locally and/or remotely. In such an example, the system 500 can improve confidence in automation in a manner that can help to reduce human interventions, particularly local, on-site human interventions, which may be resource intensive, pose risks to humans, etc.

[00133] As an example, a system such as the system 500 of Fig. 5 can provide for integration of a rig control system (RCS) with downhole data where results can be conveyed in real-time (or quasi-real-time) to a visualization platform where an operator can visualize the combined data. The combined data streams may be made available to a user and/or a system at a rigsite, in town and/or at one or more other locations. Combined data can then be used to observe drilling behavior and dysfunctions and make recommendations to modify surface and/or downhole controls in order to mitigate drilling dysfunction and enable more efficient drilling. As explained, in various instances, such recommendations may be automatically communicated to one or more controllers for curing of dysfunctions without human intervention.

[00134] As to some example scenarios that can be handled by a system such as the system 500, consider (i) diagnosis using surface RCS individual controller data, (ii) diagnosis using combined surface RCS controller data complementary to downhole tool data, and (iii) diagnosis of interaction between multiple surface controllers. In such example scenarios, control may be implemented responsive to diagnosis and/or to enhance diagnosis. As to enhancing diagnosis, consider, for example, a controller that may introduce one or more changes to operation of equipment to provoke a response where data may be acquired indicative of the response where such data may be assessed to determine whether the response is expected or unexpected in view of a possible diagnosis. In such an example, one or more machine learning models may be employed, which may call for issuance of one or more instructions to control one or more pieces of equipment (e.g., according to a time schedule, etc.), where a response or responses to implementation of such control may be analyzed for purposes of diagnosis and/or further control. In such an example, consider a machine learning model such as a tree-based model that can provide for decision making to arrive at a diagnosis and/or control action. Such a machine learning model may be trained using data from a well being drilled and/or one or more offset wells. In such an example, as explained, a control action may be an action that may select and/or transition a level of control (e.g., from one level of automation to another, etc.).

[00135] As to the aforementioned scenarios, consider, as some examples, diagnosis of autodriller instability as utilizing scenario (i), stick-slip diagnosis from surface data as utilizing scenario (i), stick-slip diagnosis from surface and downhole data as utilizing scenario (ii), slide drilling assessment from surface and downhole data as utilizing scenario (ii), surface autodriller instability causing downhole vibrations as utilizing scenarios (ii) and (iii), and slide drilling assessment from surface and downhole data with top drive torque limit as utilizing scenarios (ii) and (iii). As explained, a system may provide for diagnosis of one or more other types of behaviors where, for example, the system may provide for generation of one or more control actions.

[00136] As an example, the system 500 may implement a workflow that includes monitoring surface and RCS channels for dysfunction, monitoring downhole indicators and channels for indications of equipment dysfunction, and, if dysfunction is detected, modify surface controls to attempt to mitigate.

[00137] Fig. 8 shows an example GUI 800 suitable for diagnosis of autodriller instability. As shown, the GUI 800 can include graphical renderings for various channels of data, which may include surface and/or downhole channels of data (see, e.g., RPM, torque as TQA orTOR, weight-on-bit as WOB, and block velocity as BVEL). As to BVEL, it may be provided for drilling of a length of drillpipe (e.g., consider a length of drillpipe that may be in a range of approximately 5 m to approximately 30 m). As an example, a length of drillpipe may be a stand, which may be multiple pieces of drillpipe coupled together (e.g., consider three lengths of approximately 10 m each for a total length of approximately 30 m). Further, the GUI 800 can include various control data, which may include one or more set point values (SPs) and one or more present values (PVs), where a present value (PV) can be a measured value (e.g., as measured by one or more sensors). As an example, one or more gains and/or set points may be adjusted (e.g., tuned, etc.) to address one or more types of behaviors. As to gains, consider a controller that may implement a proportional type of control and/or an integral type of control that may have associated gains (e.g., proportional gain and integral gain). As an example, a system may dynamically adjust one or more gains and/or one or more set points.

[00138] In the example of Fig. 8, an autodriller (AD) is undergoing instability where a user and/or a system can determine the AD ROP set point and the measured block velocity (BVEL) and see large fluctuations. A user and/or a system can also observe that the measured SWOB is undergoing fluctuations, rising above the AD WOB set point and then dropping well below the set point. As an example, a system and/or a user can make a recommendation to adjust autodriller settings (gains and/or set points) to attempt to mitigate this dysfunction. A recommendation (e.g., change of a gain, a set point, etc.) may be communicated to one or more controllers automatically for curing the instability. In such an example, conditions of an actual instability and/or an impending instability may be detected and mitigated without human intervention, optionally where details of the recommendation and implementation thereof may be rendered to one or more displays such that a human can be aware of the recommendation, action(s) taken and operational behavior(s).

[00139] Fig. 9 shows an example GUI 900 for stick-slip detection from surface data. In the example of Fig. 9, stick-slip is present. In such an example, user can observe the fluctuations in the surface torque (e.g., STQA or STOR) to see that stickslip is occurring and/or a data analytics engine (see, e.g., the data analytics engine 545) can automatically, or responsive to user input, perform an analysis, make a diagnosis, generate a recommendation, a control action, etc., based on such data. In the example of Fig. 9, one or more analyses may be complemented by a surface torque measurement (STQA or STOR) and/or a downhole torque measurement (DTQA or DTOR), which may provide a relatively high frequency torque measurement that can indicate whether large torque oscillations exist (e.g., consider a surface or downhole torque oscillation indicator). As an example, a user and/or a system can also observe that, in this case, a soft torque routine is active but, per the acquired data, not successfully mitigating stick-slip. In such an example, the user and/or the system (e.g., the data analytics engine 545) can assess the soft torque routine settings and modify one or more of the settings to achieve better stick-slip mitigation. [00140] As shown in the example of Fig. 9, the torque fluctuations may be complemented by STOPI, which is a relatively high frequency measurement inside a control system. As explained, data may be acquired from different sources where, for example, torque visualized remotely may be at a lower frequency (e.g., 1 Hz) whereas torque acquired by a control system may be at a higher frequency, which may provide for performance indications at surface as to oscillations.

[00141] Fig. 10 shows an example GUI 1000 for stick-slip from surface and downhole data. In the example of Fig. 10, stick-slip is present. A user and/or a system can observe the fluctuations in the surface torque to determine that stick-slip is occurring. Such data may be complemented by a surface torque and/or a downhole torque oscillation indicator. Such behavior may be confirmed by downhole sensor data indicating severe downhole stick-slip as well as elevated torsional vibrations. A user and/or a system may also determine that, in this case, a soft torque routine is not active. As an example, enabling a soft torque routine may be recommended. For example, consider a system that can automatically enable a soft torque routine responsive to one or more determinations and/or a system that can generate a recommendation that can be rendered to a GUI where a user may interact with the GUI such that the recommendation is acted upon (e.g., consider a graphical control that can receive input and, responsive to the input, transmit a signal to enable a soft torque routine). As an example, a recommendation may be to implement a soft torque routine for a period of time where, for example, behavior is monitored to determine whether the recommendation is mitigation an issue or issues.

[00142] Fig. 11 shows an example GUI 1100 for slide drilling data from surface and downhole. In the example of Fig. 11 , a surface oscillator system is in use during slide drilling (e.g., oscillation controller, etc.). As an example, a user and/or a system can determine that the oscillator is achieving the target oscillation by noting that the top drive orientation is moving back and forth between target set points. However, the user and/or the system can also determine that the downhole toolface measurement is changing substantially, rather than remaining close to a desired toolface (TF). Based on such information, a user and/or a system can modify one or more of the oscillator settings to attempt to achieve the desired downhole toolface (TF). As explained, oscillations may be achieved via top drive control where a drill bit is rotated for extending a borehole, for example, via a mud motor driven by flow of drilling fluid (e.g., mud).

[00143] In the example of Fig. 11 , downhole gravity toolface (GTF) is measured from 0 degrees to 360 degrees while the top drive orientation is oscillating between clockwise and counter-clockwise rotations where the oscillations are greater in one direction than the other. As explained, a controller may act to aim a toolface (TF).

[00144] Fig. 12 shows an example GUI 1200 for surface autodriller instability causing downhole vibrations. In the example of Fig. 12, a user and/or a system can assess surface AD data as well as a top drive torque limit. As an example, a user and/or a system can determine that large fluctuations in the surface parameters exist and that the surface torque is regularly reaching the torque limit, resulting in repeated drops in surface RPM. In the example of Fig. 12, at the same time, the downhole data are showing large WOB fluctuations and the downhole sensors are showing severe torsional vibrations, bit bounce, and lateral vibrations. In response to such behavior, a user and/or a system can recommend modifications to one or more surface controllers (e.g., autodriller and top drive torque limit) in an effort to mitigate this dysfunction.

[00145] In the example of Fig. 12, the bottom track shows block velocity and, in a black dotted line, AD ROP set point. The third track includes average downhole maximum and minimum WOB where, as the WOB downhole max and min are so far apart, a system can detect a downhole axial oscillation. In the example of Fig. 12, the drilling operation is for a single stand of drill pipe. As to the second track, it includes measured surface torque, which flat-lines and drops. In the second track, from the vertical line to about 11 :06 in time, the AD torque set point and the top drive torque limit are at the same value. In such an example, the AD torque set point can be reduced to be below that of the top drive torque limit.

[00146] As to the top track in the example of Fig. 12, the data can be from a reading memory in a tool, which may be interrogated at surface. For example, a tool can acquire sensor measurements and store them in local, downhole memory. Once the tool is brought to surface, the memory may be read. As an example, where a drillstring includes a telemetry system that provides for lesser delay than mud-pulse telemetry, such type of data may be acquired in real-time or near real-time and utilized to detect one or more behaviors. [00147] Fig. 13 shows an example of a GUI 1300 that corresponds to the example of the GUI 1200. In the example of Fig. 13, the GUI 1300 shows vertical tracks with respect to time where vibration events are indicated. As an example, a system may provide for rendering of vertical and/or horizontal tracks, which may be with respect to time and/or with respect to depth (e.g., measured depth). In particular, the tracks include block position (BROS), rig state, stick-slip index, standpipe pressure (SPPA), flow rate (FLWI), surface torque (STOR), downhole torque (DTOR), vibration index, surface weight-on-bit (SWOB), downhole weight-on-bit (DWOB), bounce index, bend (BND), whirl type, whirl index, bend dogleg severity (BND DLS), vibration lateral, vibration lateral index, vibration axial, vibration axial index, gamma ray data (GRM), rate of penetration (ROP), depth (e.g., true vertical depth or TVD) and hole depth (HDTH). As an example, an index may be graded such as, for example, low, moderate, high and severe, which may be color-coded and/or otherwise coded. As shown in the example of Fig. 13, various indexes may be computed based on acquired data, which may provide for levels of risk, which may, in turn, be utilized for making one or more decisions, recommendations, etc., and/or calling for implementation of one or more control actions. As explained, a system may provide for selection of and/or transitioning of a level of control, which may be a level of automation selection and/or transition.

[00148] As an example, control actions may pertain to one or more of an autodriller (AD), a top drive, a flow rate (e.g., mud pumps), a drawworks, etc. As an example, a diagnosis may lead to issuance of one or more types of control actions directed to one or more pieces of equipment. As explained, a drawworks can provide for control of a speed at which a drillstring moves in a borehole (e.g., into or out of) where, for example, a drawworks may provide for control of ROP. As explained, stickslip is a rotational oscillation of a drillstring where changes in rotational speed at a bit and surface torsional oscillations may be observed in downhole and surface data, respectively. In such an example, a top drive may provide for control at the surface that aims to damp such behavior. Stick-slip behavior may complicate directional drilling, increase bit wear, etc., as such, stick-slip mitigation can provide for various improvements.

[00149] Fig. 14 shows an example of a GUI 1400 for slide drilling data from surface and downhole, top drive torque limit. In the example of Fig. 14, a surface oscillator system is in use during slide drilling. In such an example, a user and/or a system can determine that the oscillator is not achieving the target oscillation by noting that the top-drive orientation is moving back and forth between the target set points but falling short of the set point on one side. In such an example, the user and/or the system can also determine that the downhole toolface measurement is not moving towards the desired toolface. Additionally, the user and/or the system can determine that the surface torque is regularly reaching the top drive torque limit. Recommendations for modifications of one or more surface controllers (e.g., top drive torque limit and/or oscillator settings) can be made in an effort to mitigate this dysfunction.

[00150] As explained, oscillation of a drillstring using a top drive during slide drilling (e.g., using a mud motor to rotate a drill bit to extend a borehole) may provide for better load transfer from surface to a bit. As an example, amplitude of oscillation may be controlled in clockwise and counter-clockwise directions which may be performed dynamically for controlling direction of a drill bit operatively coupled to a mud motor. As an example, downhole data may include toolface (TF) data, which may be available at a frequency of tens of seconds (e.g., 20 seconds to a minute or more). In such an example, TF data may be utilized to assess behavior, which may include diagnosing behavior. As an example, a system may aim to maintain a more steady TF, which may involve calling for one or more control actions that can help to stabilize TF toward a desired value. As an example, a control action may call for halting slide drilling and switching to rotary drilling where a risk of stick-slip may be above a threshold. In such an example, rotary drilling may be halted where, for example, the risk of stick-slip is reduced.

[00151] As an example, a system may acquire various measurements that may provide further insight into a state of drilling. For example, a downhole tool could provide an additional channel that includes a dominant rotational speed fluctuation frequency. Such data can provide a system to generate insight for a user into what actions to take to mitigate stick-slip. As another example, consider an RCS that can provide an additional channel that includes a dominant surface torque fluctuation frequency, which may be used in a similar manner to the downhole measurement.

[00152] As an example, if a downhole rotation speed fluctuation frequency is found to be very high frequency (e.g., >10 Hz), a system may indicate that the downhole vibration occurring is not stick-slip, but rather a higher frequency torsional oscillation (HFTO). In such an example, the surface response will be different for HFTO as the stick-slip mitigation controls do not effectively mitigate HFTO. On the other hand, if the frequency is found to be in the nominal range of surface stick-slip mitigation controls, the measured frequency can be compared with frequencies targeted by the surface controller and modifications made to the surface controller if these do not match.

[00153] As an example, a system can provide for acquiring a dominant stick-slip frequency from downhole (e.g., a dominant undesirable type of vibration). As an example, a soft torque controller can benefit from having an indication of frequency of stick-slip. For example, a drillstring can include a downhole sensor that measures rotational speed fluctuations and transmitting the information to surface. In such an example, a system may detect existence of stick-slip with a period of oscillation of 8 seconds where a recommendation can call for tuning the soft torque controller to address the 8 second period of oscillation. As an example, an RCS can use torsional fluctuations for determining an oscillation frequency for use in mitigation of stick-slip.

[00154] As explained, a system can include one or more controllers and may be referred to as an autodriller system. For example, consider a weight on bit (WOB) controller, a drilling torque (TQA or TOR) controller, a differential pressure (DIFF_P) controller and a rate of penetration (ROP) controller. Each of the controllers may receive a corresponding set point (SP) value where each of the controllers receives a measured value (e.g., a WOB measurement, a TQA measurement and a DIFF_P measurement, respectively). Each of the controllers may output a normalized (NM) value (e.g., scaled from 0 to 1 , etc.) that is received by the ROP controller where the ROP controller can utilize the normalized (NM) values and a ROP set point (SP) value to generate a ROP output.

[00155] As an example, such a system can be operatively coupled to and/or include a degradation and/or efficiency system (e.g., a degradation and/or efficiency engine, framework, etc.) where, for example, control signals for drilling may be based at least in part on one or more of degradation and efficiency of a mud motor, where a mud motor is utilized (e.g., as part of a drillstring). As an example, sliding mode and/or rotating mode decisions and/or operations may be based at least in part on one or more of degradation and efficiency. Such decisions and/or operations may aim to maintain sufficient life in a power section of a mud motor to complete a run without having to pull a drillstring out of hole (POOH) for servicing, etc. Such an approach can help to reduce non-productive time (NPT) during drilling operations for one or more wells.

[00156] As explained, a data acquisition framework (e.g., consider a TECHLOG plugin framework, etc.) may be utilized, for example, integrated into a system or operatively coupled to a system. As explained, a system may provide for selections, recommendations, etc., as to one or more drilling parameters (e.g., consider a parameter advisory system, etc.). As explained, a system may provide for manual, semi-automated and/or automated control. For example, a system may be operatively coupled to one or more controllers (see, e.g., the one or more control systems 550 of Fig. 5).

[00157] Fig. 15 shows an example of a method 1500 and an example of a system 1590. In the example of Fig. 15, the method can include a reception block 1510 for receiving real-time data during a controlled drilling operation performed by a controller, an instrumented rig and a drillstring that includes one or more downhole sensors, where the data include surface data from the instrumented rig and downhole data from the one or more downhole sensors; a detection block 1520 for detecting a drilling behavior during the drilling operation; a generation block 1530 for generating a control recommendation to mitigate the drilling behavior; and a control block 1540 for controlling the drilling operation according to the control recommendation.

[00158] In the example of Fig. 15, the system 1590 includes one or more information storage devices 1591 , one or more computers 1592, one or more networks 1595 and instructions 1596. As to the one or more computers 1592, each computer may include one or more processors (e.g., or processing cores) 1593 and memory 1594 for storing the instructions 1596, for example, executable by at least one of the one or more processors. As an example, a computer may include one or more network interfaces (e.g., wired or wireless), one or more graphics cards, a display interface (e.g., wired or wireless), etc.

[00159] The method 1500 is shown along with various computer-readable media blocks 1511 , 1521 , 1531 and 1541 (e.g., CRM blocks). Such blocks may be utilized to perform one or more actions of the method 1500. For example, consider the system 1590 of Fig. 15 and the instructions 1596, which may include instructions of one or more of the CRM blocks 1511 , 1521 , 1531 and 1541 .

[00160] As an example, one or more machine learning techniques may be utilized to enhance process operations, a process operations environment, a communications framework, etc. As explained, various types of information can be generated via operations where such information may be utilized for training one or more types of machine learning models to generate one or more trained machine learning models, which may be deployed within one or more frameworks, environments, etc.

[00161] As an example, the system 500 of Fig. 5 can include one or more trained machine learning models and may provide for training of one or more machine learning models. As an example, one or more of the one or more control systems 550 of Fig. 5 may include one or more trained machine learning models and may provide for training of one or more machine learning models. As an example, the system 500 may generate a recommendation that pertains to training of a machine learning model, implementing a trained machine learning model, re-training a trained machine learning model, enabling and/or disabling a trained machine learning model, acquisition of data (e.g., synthetic and/or real) for purposes of training and/or testing a machine learning model, etc. As explained, various GUIs can be utilized to graphically present data and/or trends. As an example, a machine learning model may be configured for processing images, time series data, etc., to make classifications and/or to make predictions. As an example, the data analytics engine 545 of the system 500 of Fig. 5 may include features for use and/or training of one or more machine learning models for one or more purposes (e.g., analytics, diagnosis, recommendation, control actions, etc.).

[00162] 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 can 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., naive Bayes, average on-dependence estimators, Bayesian belief network, Gaussian naive Bayes, multinomial naive 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.

[00163] As an example, a machine 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 shortterm 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.

[00164] 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 can be implemented for machine learning applications that can include neural networks. As an example, the CAFFE framework may be implemented, which is a DL framework developed by Berkeley Al 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 Al framework may be utilized (APOLLO. Al GmbH, Germany). As an example, a framework such as the PYTORCH framework may be utilized (Facebook Al Research Lab (FAIR), Facebook, Inc., Menlo Park, California).

[00165] As an example, a training method can include various actions that can operate on a dataset to train a ML model. As an example, a dataset can be split into training data and test data where test data can provide for evaluation. A method can include cross-validation of parameters and best parameters, which can be provided for model training.

[00166] The TENSORFLOW framework can 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.

[00167] TENSORFLOW computations can 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 can be referred to as "tensors".

[00168] As an example, a device may utilize TENSORFLOW LITE (TFL) or another type of lightweight framework. TFL is a set of tools that enables on-device machine learning where models may run on mobile, embedded, and loT devices. TFL is optimized for on-device machine learning, by addressing latency (no round-trip to a server), privacy (no personal data leaves the device), connectivity (Internet connectivity is demanded), size (reduced model and binary size) and power consumption (e.g., efficient inference and a lack of network connections). TFL provides for multiple platform support, covering ANDROID and iOS devices, embedded LINUX, and microcontrollers. TFL provides for diverse language support, which includes JAVA, SWIFT, Objective-C, C++, and PYTHON. TFL provides for high performance, with hardware acceleration and model optimization. Machine learning tasks may include, for example, one or more of classification, regression, prediction, object detection, pose estimation, question answering, text classification, etc., on multiple platforms.

[00169] As an example, a workflow may include supervised and/or unsupervised learning using one or more types of data, which may include actual sensor-based data and/or synthetic data (e.g., from augmentation, simulation, etc.). As an example, a workflow may include labeling where, for example, types of behavior may be labeled in association with data that may be utilized for training one or more machine learning models. In such an example, a trained machine learning model may provide for one or more of detection of behavior, prediction of behavior, etc., as part of a diagnostic system where, for example, one or more control actions may be recommended, which may be machine learning model recommendations and/or other recommendations. As explained, a recommendation may involve adjusting a level of control, which may be a level of automation, which may provide for more confidence in implementation of automation for various drilling operations; noting that a lack of confidence in automation may be a barrier to implementation of automation.

[00170] As an example, a method can include receiving real-time data during a controlled drilling operation performed by a controller, an instrumented rig and a drillstring that includes one or more downhole sensors, where the data include surface data from the instrumented rig and downhole data from the one or more downhole sensors; detecting a drilling behavior during the drilling operation; and generating a control recommendation to mitigate the drilling behavior. In such an example, the controller may be a type of controller that does not automatically respond to the drilling behavior, which may be a specific type of drilling behavior (e.g., consider a drilling behavior of a type for which the controller is not configured to handle). In such an example, the method can include instructing the controller according to the control recommendation. In such an approach, the controller can be effectively augmented such that various behaviors can be addressed, optionally without human intervention. Such an approach may help to streamline a controller for a number of behaviors while a number of other behaviors are handled by a system that augments control. For example, the data analytics engine 545 of the system 500 may provide for augmenting control of one or more controllers where, in various examples, the one or more controllers may not be “aware” of whether instructions are from human recommendations or from machine recommendations; noting that a controller may be configured to have awareness of such a data analytics engine.

[00171] As an example, a control recommendation can call for disabling a controller. As an example, a controller can be or include a drawworks controller. As an example, a controller can be or include a top drive controller. As an example, a controller can be or include an autodriller controller.

[00172] As an example, a controller can include at least one set point and/or at least one tunable parameter. In such an example, a control recommendation can call for adjusting at least one of the at least one set point and/or the at least one tunable parameter. For example, the controller may include memory that stores parameter values where a set point and a tunable parameter are parameters that can be assigned a value. In such an example, a system may generate a recommendation that can be communicated (e.g., transmitted) to a controller where the recommendation may be to change a set point and/or a tunable parameter.

[00173] As an example, drilling behavior can be or include vibration behavior. In such an example, a control recommendation can aim to address the vibration behavior depending on whether the vibration behavior is axial, torsional and/or lateral.

[00174] As an example, drilling behavior can be or can include stick-slip behavior. In such an example, a control recommendation may be for one or more controllers that can address stick-slip behavior.

[00175] As an example, a control recommendation can call for reducing a maximum torque of the controller to below a maximum torque limit of a top drive of a rig. [00176] As an example, a control recommendation can call for adjusting oscillation of a top drive. In such an example, oscillation may be performed during slide drilling and/or during one or more other operations (e.g., to reduce friction when moving a drillstring in a borehole, etc.).

[00177] As an example, a method can include rendering a visualization to a display, where the visualization includes a portion of surface data and a portion of downhole data.

[00178] As an example, a method can include receiving downhole data that are transmitted to surface via mud-pulse telemetry and/or via wire.

[00179] As an example, a system can include a processor; memory accessible to the processor; processor-executable instructions stored in the memory and executable by the processor to instruct the system to: receive real-time data during a controlled drilling operation performed by a controller, an instrumented rig and a drillstring that includes one or more downhole sensors, where the data include surface data from the instrumented rig and downhole data from the one or more downhole sensors; detect a drilling behavior during the drilling operation; and generate a control recommendation to mitigate the drilling behavior.

[00180] As an example, one or more non-transitory computer-readable media can include computer-executable instructions executable by a system to instruct the system to: receive real-time data during a controlled drilling operation performed by a controller, an instrumented rig and a drillstring that includes one or more downhole sensors, where the data include surface data from the instrumented rig and downhole data from the one or more downhole sensors; detect a drilling behavior during the drilling operation; and generate a control recommendation to mitigate the drilling behavior.

[00181] As an example, a computer program product can include one or more computer-readable storage media that can include processor-executable instructions to instruct a computing system to perform one or more methods and/or one or more portions of a method.

[00182] In some embodiments, a method or methods may be executed by a computing system. Fig. 16 shows an example of a system 1600 that can include one or more computing systems 1601-1 , 1601 -2, 1601 -3 and 1601 -4, which may be operatively coupled via one or more networks 1609, which may include wired and/or wireless networks.

[00183] As an example, a system can include an individual computer system or an arrangement of distributed computer systems. In the example of Fig. 16, the computer system 1601 -1 can include one or more modules 1602, which may be or include processor-executable instructions, for example, executable to perform various tasks (e.g., receiving information, requesting information, processing information, simulation, outputting information, etc.).

[00184] As an example, a module may be executed independently, or in coordination with, one or more processors 1604, which is (or are) operatively coupled to one or more storage media 1606 (e.g., via wire, wirelessly, etc.). As an example, one or more of the one or more processors 1604 can be operatively coupled to at least one of one or more network interface 1607. In such an example, the computer system 1601 -1 can transmit and/or receive information, for example, via the one or more networks 1609 (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 1608 can be included.

[00185] As an example, the computer system 1601-1 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 1601 -2, etc. A device may be located in a physical location that differs from that of the computer system 1601 -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.

[00186] 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.

[00187] As an example, the storage media 1606 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. [00188] 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.

[00189] 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.

[00190] 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.

[00191] 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.

[00192] Fig. 17 shows components of an example of a computing system 1700 and an example of a networked system 1710 with a network 1720. The system 1700 includes one or more processors 1702, memory and/or storage components 1704, one or more input and/or output devices 1706 and a bus 1708. In an example embodiment, instructions may be stored in one or more computer-readable media (e.g., memory/storage components 1704). Such instructions may be read by one or more processors (e.g., the processor(s) 1702) via a communication bus (e.g., the bus 1708), which may be wired or wireless. The one or more processors may execute such instructions to implement (wholly or in part) one or more attributes (e.g., as part of a method). A user may view output from and interact with a process via an I/O device (e.g., the device 1706). In an example embodiment, a computer-readable medium may be a storage component such as a physical memory storage device, for example, a chip, a chip on a package, a memory card, etc. (e.g., a computer-readable storage medium). [00193] In an example embodiment, components may be distributed, such as in the network system 1710. The network system 1710 includes components 1722-1 , 1722-2, 1722-3, . . . 1722-N. For example, the components 1722-1 may include the processor(s) 1702 while the component(s) 1722-3 may include memory accessible by the processor(s) 1702. Further, the component(s) 1722-2 may include an I/O device for display and optionally interaction with a method. A network 1720 may be or include the Internet, an intranet, a cellular network, a satellite network, etc.

[00194] 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.

[00195] 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).

[00196] 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 can 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.).

[00197] Although only a few example embodiments have been described in detail above, those skilled in the art will readily appreciate that many modifications are possible in the example embodiments. 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.

Claims

CLAIMS What is claimed is:

1 . A method comprising: receiving real-time data during a controlled drilling operation performed by a controller, an instrumented rig and a drillstring that comprises one or more downhole sensors, wherein the data comprise surface data from the instrumented rig and downhole data from the one or more downhole sensors; detecting a drilling behavior during the drilling operation; and generating a control recommendation to mitigate the drilling behavior.

2. The method of claim 1 , wherein the controller does not automatically respond to the drilling behavior.

3. The method of claim 2, comprising instructing the controller according to the control recommendation.

4. The method of claim 1 , wherein the control recommendation calls for disabling the controller.

5. The method of claim 1 , wherein the controller comprises a drawworks controller.

6. The method of claim 1 , wherein the controller comprises a top drive controller.

7. The method of claim 1 , wherein the controller comprises an autodriller controller.

8. The method of claim 1 , wherein the controller comprises at least one set point.

9. The method of claim 8, wherein the control recommendation calls for adjusting at least one of the at least one set point.

10. The method of claim 1 , wherein the controller comprises at least one tunable parameter.

11 . The method of claim 10, wherein the control recommendation calls for adjusting at least one of the at least one tunable parameter.

12. The method of claim 1 , wherein the drilling behavior comprises vibration behavior.

13. The method of claim 12, wherein the control recommendation addresses the vibration behavior depending on whether the vibration behavior is axial, torsional and/or lateral.

14. The method of claim 1 , wherein the drilling behavior comprises stick-slip behavior.

15. The method of claim 1 , wherein the control recommendation calls for reducing a maximum torque of the controller to below a maximum torque limit of a top drive of the rig.

16. The method of claim 1 , wherein the control recommendation calls for adjusting oscillation of a top drive.

17. The method of claim 1 , comprising rendering a visualization to a display, wherein the visualization comprises a portion of the surface data and a portion of the downhole data.

18. The method of claim 1 , wherein the downhole data are transmitted to surface via mud-pulse telemetry and/or via wire.

19. A system comprising: a processor; memory accessible to the processor; processor-executable instructions stored in the memory and executable by the processor to instruct the system to: receive real-time data during a controlled drilling operation performed by a controller, an instrumented rig and a drillstring that comprises one or more downhole sensors, wherein the data comprise surface data from the instrumented rig and downhole data from the one or more downhole sensors; detect a drilling behavior during the drilling operation; and generate a control recommendation to mitigate the drilling behavior.

20. One or more non-transitory computer-readable media comprising computerexecutable instructions executable by a system to instruct the system to: receive real-time data during a controlled drilling operation performed by a controller, an instrumented rig and a drillstring that comprises one or more downhole sensors, wherein the data comprise surface data from the instrumented rig and downhole data from the one or more downhole sensors; detect a drilling behavior during the drilling operation; and generate a control recommendation to mitigate the drilling behavior.