SYSTEMS AND METHODS FOR AUTOMATED INTERPRETED LITHOLOGY

Description

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of EP Application Serial No. 24307094.3 entitled “SYSTEMS AND METHODS FOR AUTOMATED INTERPRETED LITHOLOGY” filed Dec. 12, 2024, the disclosure of which is incorporated herein by reference in its entirety.

FIELD

The present disclosure relates to interpreted lithology, and more specifically, systems and methods for automated interpreted lithology.

BACKGROUND

Interpreted lithology refers to the analysis and identification of a rock type based on data collected from various sources such as well logs, core samples, and/or visual observations. While drilling a well, it is important to identify and interpret the lithology of the geological layers in the well. For example, knowledge of the rock types included in and/or other lithological information associated with geological layers in a well allows a drill operator at the surface to mitigate risk during drilling and/or improve drilling efficiency.

In conventional approaches to interpreted lithology, operators at the drill site manually identify and determine the respective lithologies of geological layers in a well. For example, an operator at the drill site combines surface drilling data and subsurface well logs, which can be acquired during drilling in real time using telemetry or retrieved after drilling when measurement tools are returned back to the surface, to determine the respective lithologies of the geological layers in the well.

At least one drawback to manual interpreted lithology, however, is that the respective lithologies of the geological layers can be incorrectly and/or inconsistently determined depending on the experience level and/or knowledge of the operator At least another drawback to manual interpreted lithology is that for instances in which there are many geological layers in a well (e.g., tens, hundreds, etc.), determining the respective lithology of each geological layer is a very time consuming process that can take as long as days or weeks. In that regard, drill operators are prevented from quickly and effectively adapting drill plans based on interpreted lithologies of geological layers in a well.

As the foregoing illustrates, what is needed in the art are more effective techniques for interpreted lithology.

SUMMARY

In one independent aspect, a method for automated interpreted lithology. The method includes drilling, using a drill bit coupled to a drill string, within a specified depth range of a subterranean formation; generating a first measurement log and a second measurement log while drilling; identifying, based on drill bit cuttings formed during drilling, a plurality of lithologies contained within the specified depth range of the subterranean formation, the plurality of lithologies including at least a first lithology and a second lithology; quantifying, based on the drill bit cuttings, a first percentage of the first lithology contained in the subterranean formation and a second percentage the second lithology contained in the subterranean formation; obtaining a category table that defines a first category score associated with the first lithology and a second category score associated with second lithology; determining, based in part on the first measurement log and the second measurement log, a plurality of combined measurement values, where each combined measurement value included in the plurality of combined measurement values corresponds to a respective depth within the specified depth range; associating, based in part on the first category score, the second category score, the first percentage, the second percentage, and the plurality of combined measurement values, at least a first depth included the specified depth range with a lithology included in the plurality of lithologies; generating a visual representation of an association between the first depth and the corresponding lithology; and displaying, on a display device, the visual representation.

In another independent aspect, a system for drilling a well in a subterranean formation. The system includes a drill string suspended at an upper end by a kelly and a traveling block; a drill bit attached to a lower end of the drill string, the drill bit adapted to rotate during drilling; a pump adapted pump drilling fluid through the drill string; a shale shaker adapted to remove drill bit cuttings from the drilling fluid; a logging-while-drilling (LWLD) module adapted to generate a first measurement log during drilling; a measurement-while-drilling (MWD) module adapted to generate a second measurement log during drilling; and a control system comprising one or more processors and a display device. The control system is adapted to receive, from the LWD module, a first measurement log that was generated during drilling within a specified depth range of the subterranean formation; receive, from the MWD module, a second measurement log that was generated during drilling within a specified depth range of the subterranean formation; identify, based on the drill bit cuttings, a plurality of lithologies contained within the specified depth range of the subterranean formation, the plurality of lithologies including at least a first lithology and a second lithology; quantify, based on the drill bit cuttings, a first percentage of the first lithology contained in the subterranean formation and a second percentage the second lithology contained in the subterranean formation; obtain a category table that defines a first category score associated with the first lithology and a second category score associated with second lithology; determine, based in part on the first measurement log and the second measurement log, a plurality of combined measurement values, where each combined measurement value included in the plurality of combined measurement values corresponds to a respective depth within the specified depth range; and associate, based in part on the first category score, the second category score, the first percentage, the second percentage, and the plurality of combined measurement values, at least a first depth included the specified depth range with a lithology included in the plurality of lithologies.

In another independent aspect, a computing device comprising a display device and a processor coupled to the display device. The processor is adapted to receive a first measurement log associated with a specified depth range in a subterranean formation; receive a second measurement log associated with the specified depth range in the subterranean formation; receive a lithology quantification associated with the specified depth range in the subterranean formation, the lithology quantification indicating a first percentage of a first lithology contained in the subterranean formation and a second percentage of a second lithology contained in the subterranean formation; obtain a category table that defines a first category score associated with the first lithology and a second category score associated with second lithology; determine, based in part on the first measurement log and the second measurement log, a plurality of combined measurement values, where each combined measurement value included in the plurality of combined measurement values corresponds to a respective depth within the specified depth range; associate, based in part on the first category score, the second category score, the first percentage, the second percentage, and the plurality of combined measurement values, at least a first depth included the specified depth range with a lithology included in the plurality of lithologies; generate a visual representation of an association between the first depth and the corresponding lithology; and display the visual representation on the display device.

Other aspects will become apparent by consideration of the detailed description and accompanying drawings.

At least one technical advantage of the disclosed techniques relative to conventional approaches is that interpreted lithologies of geological layers encountered during drilling can be determined much faster. In that regard, whereas conventional approaches can take days or even weeks to interpret the lithologies of geological layers encountered during drilling, with the disclosed techniques, operators at a drilling site can adjust drilling parameters in near real-time to mitigate risk during drill and/or improve drilling efficiency. At least another technical advantage of the disclosed techniques relative to the conventional approaches is that, with the disclosed techniques, lithologies of geological layers encountered during drilling can be determined more consistently and with higher degrees of accuracy.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example drilling system, according to aspects of the various embodiments.

FIG. 2 illustrates a close up view of a shale shaker included in the drilling system of FIG. 1, according to various embodiments.

FIG. 3 illustrates a close up view of a drill bit and a lower end of a drill string included in the drilling system of FIG. 1, according to various embodiments.

FIG. 4 is a block diagram of a control system implemented in conjunction with the drilling system of FIG. 1, according to various embodiments.

FIG. 5 illustrates an example lithology quantification of a specified depth range in a subterranean formation, according to some embodiments

FIG. 6 illustrates a category table associated with two types of measurements that are generated during a drilling operation, according to some embodiments.

FIG. 7 illustrates an example combined category score table, according to various embodiments.

FIG. 8 illustrates example gamma ray and formation strength measurement logs, according to the various embodiments.

FIG. 9 illustrates an example combined measurement log, according to the various embodiments.

FIG. 10 illustrates example measurement plots that are discretized with varying bit resolutions and normalized with respect to maximum measurement values, according to various embodiments.

FIG. 11 illustrates example histograms of bin size fifty for gamma ray measurements, formation strength measurements, and combined measurements, according to various embodiments.

FIG. 12 illustrates example histograms of bin size one hundred for gamma ray measurements, formation strength measurements, and combined measurements, according to various embodiments.

FIG. 13 illustrates an example interpreted lithology of geological layers in a subterranean formation, according to the various embodiments.

FIG. 14 is a flow diagram of method steps for automated interpreted lithology, according to various embodiments.

DETAILED DESCRIPTION

Before any embodiments are explained in detail, it is to be understood that the embodiments are not limited in its application to the details of the configuration and arrangement of components set forth in the following description or illustrated in the accompanying drawings. The embodiments are capable of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein are for the purpose of description and should not be regarded as limiting. The use of “including,” “comprising,” or “having” and variations thereof are meant to encompass the items listed thereafter and equivalents thereof as well as additional items. Unless specified or limited otherwise, the terms “mounted,” “connected,” “supported,” and “coupled” and variations thereof are used broadly and encompass both direct and indirect mountings, connections, supports, and couplings.

In addition, it should be understood that embodiments may include hardware, software, and electronic components or modules that, for purposes of discussion, may be illustrated and described as if the majority of the components were implemented solely in hardware. However, one of ordinary skill in the art, and based on a reading of this detailed description, would recognize that, in at least one embodiment, the electronic-based aspects may be implemented in software (e.g., stored on non-transitory computer-readable medium) executable by one or more electronic processors, such as a microprocessor and/or application specific integrated circuits (“ASICs”). As such, it should be noted that a plurality of hardware and software-based devices, as well as a plurality of different structural components, may be utilized to implement the embodiments. For example, “servers,” “computing devices,” “controllers,” “processors,” etc., described in the specification can include one or more electronic processors, one or more computer-readable medium modules, one or more input/output interfaces, and various connections (e.g., a system bus) connecting the components.

Relative terminology, such as, for example, “about,” “approximately,” “substantially,” etc., used in connection with a quantity or condition would be understood by those of ordinary skill to be inclusive of the stated value and has the meaning dictated by the context (e.g., the term includes at least the degree of error associated with the measurement accuracy, tolerances [e.g., manufacturing, assembly, use, etc.] associated with the particular value, etc.). Such terminology should also be considered as disclosing the range defined by the absolute values of the two endpoints. For example, the expression “from about 2 to about 4” also discloses the range “from 2 to 4.” The relative terminology may refer to plus or minus a percentage (e.g., 1%, 5%, 10%, or more) of an indicated value.

Functionality described herein as being performed by one component may be performed by multiple components in a distributed manner. Likewise, functionality performed by multiple components may be consolidated and performed by a single component. Similarly, a component described as performing particular functionality may also perform additional functionality not described herein. For example, a device or structure that is “configured” in a certain way is configured in at least that way but may also be configured in ways that are not explicitly listed.

FIG. 1 illustrates an example drilling system 100, according to aspects of the various embodiments. The drilling system 100, which hereinafter may be referred to as a “rig,” is used, for example, to drill a well. As shown, the rig 100 includes a drill string 102 that is suspended at an upper end by a kelly and a traveling block 104 and terminated at a lower end by a drill bit 106. A rotary table 108 supported on a driller floor 110 is adapted to rotate the drill string 102 and the drill bit 106, thereby drilling a borehole 112 into a subterranean formation 114. In some examples, a portion of the borehole 112 is encased by a casing 116.

The rig 100 further includes a mud pump 118 that is adapted to pump drilling fluid, or “mud,” 120 into an upper end of the drill string 102 through a connecting mud line 122. From there, the mud 120 is pumped downward through the drill string 102 and exits the drill string 102 through an opening in the drill bit 106. Mud 120 that exits drill string 102 through an opening in the drill bit 106 is forced to return to the surface via an annulus formed between the borehole 112 and an outer diameter of the drill string 102. In the illustrated example of FIG. 1, mud 120 returning to the surface is represented using upward facing arrows. Once at the surface, the mud 120 flows into a return flow line 124 via a bell nipple 126. In some examples, the rig 100 includes a blowout preventer 128 positioned near the bell nipple 126. The blowout preventer 128 is adapted to prevent the occurrence of blowouts during a drilling operation.

During a drilling operation, drill bit cuttings are formed as the drill bit 106 rotates and crushes rocks within the subterranean formation 114. These drill bit cuttings are returned to the surface with the mud 120 that flows upward through the annulus formed between the borehole 112 and outer diameter of the drill string 102. To remove drill bit cuttings from the mud 120 such that the mud 120 can be reused for injection in the drilling operation, a shale shaker 130 is disposed along the return flow line 124. For example, the shale shaker 130 includes a shaker pit 132 that is adapted to remove the drill bit cuttings from the mud 120. Mud 120 then flows out of the shaker pit 132 into a mud pit 134 from which the mud pump 118 may draw the mud 120 to pump into the upper end of the drill string 102 through connecting mud line 122.

As further shown in FIG. 1, the shale shaker 130 includes and/or is coupled to a gas trap 136. The gas trap 136 is adapted to extract gas contained in the mud 120. For example, the gas trap 136 can extract a gas compound, such as a hydrocarbon including alkane, hydrogen sulfide, and/or helium, from the mud 120. Gas extracted by the gas trap 136 is transported via a gas line 138 to a control system 140 (e.g., a mud logging unit) for analysis. In some examples, the gas trap 136 extracts gas from the mud 120 before drill bit cuttings are removed from the mud 120 by the shale shaker 130. In other examples, the gas trap 136 extracts gas from the mud 120 after drill bit cuttings are removed from the mud 120 by the shale shaker 130.

FIG. 2 illustrates a close up view of the shale shaker 130 included in the rig 100, according to various embodiments. As shown in FIG. 2, the shaker pit 132 removes the drill bit cuttings 200 from the mud 120 flowing into the mud pit 134. As further shown in the illustrated example of FIG. 2, the shale shaker 130 includes one or more cameras 202. The one or more cameras 202 are adapted to capture images of the drill bit cuttings 200 being removed from the mud 130. In some examples, the control system 140 (e.g., a mud logging unit) is adapted to analyze the images of the drill bit cuttings 200 captured by the one or more cameras 202. In some examples, the shale shaker 130 does not include one or more cameras 202. In some examples, the one or more cameras 202 are positioned elsewhere at the drilling site 100.

FIG. 3 illustrates a close up view of the drill bit 106 and the lower end of the drill string 102 included in the rig 100, according to various embodiments. As shown in FIG. 3, drill bit cuttings 200 created by the drill bit 106 during a drilling operation flow upward towards the surface within the mud 120. For example, the mud 120 and drill bit cuttings 200 contained therein flow upward through the annulus formed between the wall of the borehole 112 and the outer diameter of the drill string 102.

As further shown in FIG. 3, the lower end of the drill string 102 comprises a drill string assembly 300. The drill string assembly 300 may be, for example, a bottom hole assembly (BHA). In some examples, the drill string assembly 300 is fitted with telemetry equipment 302. The telemetry equipment 302 can, for example, include one or more of a rotatable drive shaft, a turbine impeller mechanically coupled to the drive shaft such that the mud 120 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 120, and a controllable brake for selectively braking rotation of the modulator rotor to modulate pressure pulses. In some examples, an alternator may be coupled to the aforementioned drive shaft, the alternator including 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 120. In some examples, surface equipment 142 included in and/or coupled to the control system 140 includes circuitry adapted to sense pressure pulses generated by the telemetry equipment 302 and communicates the sensed pressure pulses to the control system 140.

As further shown in the illustrated example of FIG. 3, the drill string assembly 300 can include a logging-while-drilling (LWD) module 304, a measurement-while-drilling (MWD) module 306, and a rotary-steerable system (RSS) and/or motor 308. The drill bit 106, the LWD module 304, the MWD module 306, and/or the RSS 308 may be referred to as downhole tools of the drill string 102.

In some examples, the LWD module 304 is housed in a suitable type of drill collar and can contain one or more logging tools. In some examples, more than one LWD 304 can be included in the drill string assembly 300. In some examples, the LWD module 254 includes a seismic measuring device. The LWD module 304 can be adapted to measure, or log, one or more properties of the well being drilled in the subterranean formation 114. For example, the LWD module 304 generates well log data and/or well logs during a drilling operation. Well log data generated by the LWD module 304 can include, for example, geological data such as gamma ray log data, resistivity log data, density log data, sonic log data, and/or other types of log data. The LWD module 304 can then transmit the generated well log data and/or other information associated with the subterranean formation 114 to surface equipment 142 and/or the control system 140.

In some examples, the MWD module 306 is housed in a suitable type of drill collar and can contain one or more devices for measuring characteristics of the drill string 102 and/or the drill bit 106. In some examples, the MWD module 306 includes equipment for generating electrical power used to power various components of the drill string 102. In some examples, the MWD module 306 includes one or more measuring devices adapted to generated log data associated with the drill string 102 and/or the drill bit 106. For example, MWD module 306 includes one or more of a weight-on-bit measuring device, a rotation 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. Log data generated by the one or more measuring devices included in the MWD module 306 can be transmitted by the MWD module 306 and/or the LWD module 304 to surface equipment 142 and/or the control system 140.

The RSS 308 includes equipment used for directional drilling. Directional drilling involves drilling into the subterranean formation 114 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. For example, consider a target that is located at a lateral distance from a surface location of the drill site 100. 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. In that regard, directional drilling can be implemented when a target is inaccessible from a vertical location at the surface above the subterranean formation 114, when material exists in the subterranean formation 114 that may impede drilling or otherwise be detrimental (e.g., consider a salt dome, etc.), when a formation is laterally extensive (e.g., consider a relatively thin yet laterally extensive reservoir), when multiple bores are to be drilled from a single surface bore, when a relief well is desired, and/or for some other reason.

FIG. 4 is a block diagram of the control system 140 implemented in conjunction with the rig of FIG. 1, according to various embodiments. In the illustrated example of FIG. 4, the control system 140 includes the surface equipment 142, the drill string assembly 300, and a computing device 400. However, persons skilled in the art should understand that in other examples, the control system 140 can includes additional components not shown in FIG. 4 and/or can include less components than the components shown in FIG. 4.

The computing device 400 can be implemented as, for example, a smartphone, a tablet, a laptop, a desktop computer, a server and/or any other suitable computing device. Persons skilled in the art will understand that the central computing device 400 shown in FIG. 4 provides just one non-limiting example architecture that can be used to implement the computing device 400 included in the control system 140. Moreover, other suitable computing devices not described herein may be used to implement the computing device 400. In some examples, the computing device 400 is located onsite at the rig 100. In other examples, the computing device 400 is located offsite at a remote location.

As shown in FIG. 4, the computing device 400 can include, without limitation, a processor 402, a graphics subsystem 404, an I/O devices interface 406, a network interface 408, an interconnect 410, a memory subsystem 412, and a system disk 414. The interconnect, or bus, 410 can include one or more wires, cables, traces, contacts, analog components, digital components, wireless connection components, and/or other suitable means for interconnecting hardware components of the computing device 400.

In some embodiments, the processor 402 (e.g., a CPU or similar processor) is adapted to retrieve and execute programming instructions stored in the memory subsystem 412. Similarly, the processor 402 is adapted to store and retrieve application data (e.g., software libraries) residing in the memory subsystem 412 and/or the system disk 414. The interconnect 410 is adapted to facilitate transmission of data, such as programming instructions and application data, between the processor 402, the graphics subsystem 404, the I/O devices interface 406, the network interface 408, the memory subsystem 412, and the system disk 414.

In some embodiments, the graphics subsystem 404 is adapted to generate frames of image and/or video data and transmit the frames of image and/or video data to display device 416. In some embodiments, the graphics subsystem 404 may be integrated into an integrated circuit, along with the processor 402. The display device 416 may comprise any technically feasible means for generating an image for display. For example, the display device 416 may be fabricated using liquid crystal display (LCD) technology, cathode-ray technology, and light-emitting diode (LED) display technology. The display device 416 may include, for example, one or more monitors.

The input/output (I/O) devices interface 406 is adapted to receive input data from user I/O devices 418 and transmit the input data to the processor 402 via the interconnect 410. For example, user I/O devices 418 may comprise one or more buttons, a touchscreen, a keyboard, and a mouse or other pointing device. The I/O devices interface 406 also includes an audio output unit adapted to generate an electrical audio output signal. User I/O devices 418 may comprise one or more speakers adapted to generate an acoustic output in response to the electrical audio output signal.

In alternative embodiments, the display device 416 may include the speaker. In some examples, the I/O devices 418 can include a gas analyzer adapted to analyze gas removed from the mud 120 by the gas trap 136. In such examples, the I/O device interface 406 receives gas data from the gas analyzer. In some examples, the I/O devices interface 406 can be connected to one or more modules of the drill string assembly 300 and/or the surface equipment 142. For example, the I/O devices interface 406 can be connected to the telemetry equipment 302, the LWD module 304, the MWD module 306, and/or the RSS 308. In some examples, the computing device 400 can receive, via the I/O devices interface 406, well log data and/or other measurements generated by the LWD module 304 and/or the MWD module 306. In some examples, the computing device 400 can transmit, via the I/O devices interface 406, commands for controlling drilling to the telemetry equipment 302 and/or the RSS 308.

The network interface 408 is adapted to transmit and receive packets of data via one or more network connections 420. For example, the network interface 408 is adapted to receive, via one or more network connections 420, well log data and/or other measurement data from one or more of the LWD module 304, the MWD module 306, and/or the surface equipment 142. As another example, the network interface 408 is adapted to transmit, via one or more network connections 420, one or more signals for controlling drilling to the telemetry equipment 302 and/or the RSS 308. In some examples, the network interface 408 is adapted to communicate, via one or more network connections 420, with one or more external computing devices.

The one or more network connections 420 can be established, for example, via one or more of a wide area network (WAN) (e.g., the Internet, a TCP/IP based network, a cellular network, such as, for example, a Global System for Mobile Communications [GSM] network, a General Packet Radio Services [GPRS] network, a Code Division Multiple Access [CDMA] network, an Evolution-Data Optimized [EV-DO] network, an Enhanced Data Rates for GSM Evolution [EDGE] network, a 3 GSM network, a 4GSM network, a Digital Enhanced Cordless Telecommunications [DECT] network, a Digital AMPS [IS-136/TDMA] network, or an Integrated Digital Enhanced Network [iDEN] network, etc.). In other examples, the one or more network connections 420 are established using a local area network (LAN), a neighborhood area network (NAN), a home area network (HAN), and/or a personal area network (PAN) employing any of a variety of communications protocols, such as Wi-Fi, Bluetooth, ZigBee, etc. In some examples, the one or more network connections 420 are established using one or more of a wide area network (WAN), a local area network (LAN), a neighborhood area network (NAN), a home area network (HAN), or personal area network (PAN). In some examples, the one or more network connections 420 are established using wired connections.

The system disk 414, such as a hard disk drive or flash memory storage drive, is adapted to store non-volatile data. For example, the system disk 414 stores one or more files, applications, and/or programs to be implemented by the processor 402. In some examples, the system disk 414 stores well log data and/or other measurement data 422. For example, the system disk 414 stores one or more gamma ray depth well logs, one or more formation strength depth well logs, and/or other types of well logs comprising well log data and/or other measurement data generated by the LWD module 304, the MWD module 306, and/or one or more other sensors. As will be described in more detail herein, in some examples, the system disk 414 can also store one or more lithology category tables 424.

In some examples, the memory subsystem 412 includes programming instructions and application data that comprise an operating system 426, a user interface 428, a drilling control application 430, and an interpreted lithology application 432. The operating system 426 performs system management functions such as managing hardware devices including graphics subsystem 404, I/O devices interface 406, the network interface 408, and system disk 414. The operating system 426 also provides process and memory management models for the user interface 428, the drilling control application 430, and/or the interpreted lithology application 432. The user interface 428, such as a window and object metaphor, provides a mechanism for user interaction with computing device 400. Persons skilled in the art will recognize the various operating systems and user interfaces that are well-known in the art and suitable for incorporation into the computing device 400.

When executed by the processor 402, the drilling control application 430 can be used to control one or more parameters of a drilling operation. For example, the drilling control application 430 can be used to control the telemetry equipment 302 and/or the RSS 308 to perform a drilling operation as described herein. In some examples, the drilling control application 430 uses well log data and/or other measurement data generated by the LWD module 304 and/or the MWD module 306 to control a drilling operation. In some examples, the drilling control application 430 provides an interface through which an operator at the rig 100 can interact with the drilling control application 430 to control a drilling operation. For example, the drilling control application 430 enables an operator at the rig 100 to input one or more command for controlling a drilling operation via the I/O devices 418.

As described herein, the rig 100 is used for drilling a borehole 112 into the subterranean formation 114 to form a well. When executed by the processor 402, the interpreted lithology application 432 can automatically identify, or determine, the respective lithologies of geological layers in the subterranean formation 114 encountered during drilling. Determining a respective lithology of a geological layer can include, for example, generating a description of the rock type included in a geological layer, a depth spanned by a particular geological layer (e.g., amount of feet spanning between the top and bottom depths of a geological layer), and/or other lithological information associated with a geological layer encountered during drilling. As will be described in more detail herein, in some examples, the interpreted lithology application 432 determines the respective lithologies of geological layers encountered during drill based on surface measurements (e.g., drilling parameters such as rate of penetration, rotary speed and weight on bit) and/or subsurface measurements (e.g., measurement logs generated during drilling by the LWD module 304 and/or the MWD module 306) generated during drilling, associated category tables of lithological properties, and information associated with drill bit cuttings 200 that are formed and returned to the surface during drilling.

As described herein, drill bit cuttings 200 are formed as the drill bit 106 rotates and crushes rocks within the subterranean formation 114. In that regard, the drill bit cuttings 200 contain pieces of rock contained in the geological layers through which the drill bit 106 is drilling. Thus, when the drill bit cuttings 200 are returned to the surface (e.g., by flowing upward through the borehole in the mud 120), the drill bit cuttings 200 can be analyzed to determine one or more types of rocks included in the geological layers through which the drill bit 106 is drilling.

In some examples, the rock pieces included in drill bit cuttings 200 indicate a percentage breakdown of rock types contained within a specified depth range of the subterranean formation 114. For example, if drill bit cuttings 200 formed while drilling within a first depth range in the subterranean formation 114 comprise a percentage breakdown of 20% pieces of a first type of rock, 30% pieces of a second type of rock, and 50% pieces of a third type of rock, it can be inferred that approximately 20% of the subterranean formation 114 within the first depth range is the first type of rock, 30% of the subterranean formation 114 within the first depth range is the second type of rock, and the remaining 50% of the subterranean formation 114 within the first depth range is the third type of rock. However, since drill bit cuttings 200 do not necessarily return to the surface in the same order in which the drill bit cuttings 200 are formed during drilling, the exact depths of the respective geological layer(s) that contain the first, second, or third rock types cannot be determined directly from the drill bit cuttings 200. Rather, as will be described in more detail herein, information regarding the types and relative percentages of rock pieces included in the drill bit cuttings 200 is just one of a few different inputs that can be used by the interpreted lithology application 432 to determine respective depths and lithologies of geological layers in the subterranean formation 114. Hereinafter, a percentage breakdown of rock types contained within a particular depth range within the subterranean formation 114 may be referred to as a “lithology quantification” of the particular depth range within the subterranean formation 114.

FIG. 5 illustrates an example lithology quantification 500 of a specified depth range in the subterranean formation 114, according to some embodiments. As shown in the illustrated example of FIG. 5, the lithology quantification 500 indicates a percentage breakdown of rock types included in the subterranean formation 114 between depths of 11910-11970 feet. In particular, the lithology quantification 500 indicates that subterranean formation 114 comprises 30% clay-shale, 10% coal-lignite, 60% fine sand, 0% dolomite, and 0% silt between depths of 11910-11970 feet. Notably, however, the lithology quantification 500 does not indicate particular depths of geological layers formed of clay-shale, coal-ignite, or fine sand within the subterranean formation 114 between depths of 11910-11970 feet. Rather, as will be described in more detail herein, the interpreted lithology application 432 can determine particular depths of geological layers formed of clay-shale, coal-ignite, or fine sand within the subterranean formation 114 between depths of 11910-11970 feet based in part on the lithology quantification 500.

Although only three types of rocks are included in the lithology quantification 500 shown in in FIG. 5, in other examples, a different number (e.g., one, two, four, five, etc.) of rock types may be included in a lithology quantification of a specified depth range in the subterranean formation 114. Moreover, in other examples, lithology quantifications are determined for depth ranges smaller or larger than sixty feet within the subterranean 114.

In some examples, an operator of the rig 100 manually inspects the drill bit cuttings 200 to determine the lithology quantification of a specified depth range in the subterranean formation 114 based on the types and/or percentages of rock pieces contained in the drill bit cuttings 200. For example, an operator of the rig 100 can inspect the drill bit cuttings 200 that were removed from the mud 120 by the shaker pit 132 included in the shale shaker 130. In some examples, the one or more cameras 202 included in and/or supported on the shale shaker 130 are adapted to capture images of the drill bit cuttings 200. In some examples, the interpreted lithology application 432 can analyze the captured images of the drill bit cuttings 200 to determine the lithology quantification within a specified depth range of the subterranean formation 114. In other examples, an operator of the rig 100 can view the captured images of the drill bit cuttings 200 on a display device 416 of the computing 400 to manually determine the lithology quantification of a specified depth range in the subterranean formation 114. In some examples, the operator can provide the lithology quantification of the specified depth range as an input to the interpreted lithology application 432.

In addition to lithology quantifications of depth ranges in the subterranean formation 114, the interpreted lithology application 432 can also use surface measurements (e.g., drilling parameters such as rate of penetration, rotary speed, weight on bit, etc.) and/or subsurface measurements (e.g., measurement logs generated during drilling by the LWD module 304 and/or the MWD module 306) generated during drilling and associated category tables of lithological properties to determine respective lithologies of the geological layers encountered during drilling. As will be described in more detail herein, category tables are used for discriminating individual lithologies from specific combinations of corresponding measurements (e.g., gamma ray measurements, formation strength measurements, etc.). Moreover, some or all of the information included in category tables can be determined prior to a drilling operation based on existing knowledge of lithologies and measurements that were generated during previous drilling of wells at the subterranean formation 114. Assuming M types of measurements and/or logs will be generated during a drilling operation, a category table that includes information associated with each type of measurement M is determined prior to use by the interpreted lithology application 432. Ordering in a given category table reflects the ordering of the expected amplitudes of the measurement M for each lithology li described in the category table. In that regard, c_m(l_i) will be used to denote the category of the lithology l_i corresponding to the m^th measurements.

FIG. 6 illustrates a category table 600 associated with two types of measurements that are generated during a drilling operation, according to some embodiments. As shown in the illustrated example of FIG. 6, the first measurement is a gamma ray (GR) measurement denoted as c₁(l_i). GR measurements can be generated, for example, as GR logs by the LWD module 304, the MWD 306, or some other type of wireline equipment connected to the drill string 102. As further shown in the illustrated example of FIG. 6, the second measurement is a formation strength (FORS) measurement denoted as c₂(l_i). FORS measurements can be determined, for example, based on one or more measurements of drilling parameters (e.g., rate of penetration, rotary speed, weight on bit, etc.) during a drilling operation. The lithologies li described in the category table 600 (e.g., coal-lignite, dolomite, fined sand, silt, and clay-shale) are the same as the lithologies indicated in the lithology quantification 500 in the illustrated example of FIG. 5.

The category table 600 is provided and described herein as a non-limiting example. In that regard, persons skilled in the art should understand that in other examples, category tables can describe a different number and/or different types of lithologies than the lithologies included in the combined category table 600. Moreover, persons skilled in the art should understand that category tables can describe different types of measurements than the measurement types (e.g., GR and FORS) described in the category table 600. In some examples, category tables can also describe more than two types of measurements that will be generated during drilling. By including more than two types of measurements in a category table, there is less likely to be overlap between respective combined category scores that are determined for each lithology described in the category table. Combined category scores will be described in more detail herein with respect to FIG. 7.

In the illustrated example of FIG. 6, the lithologies are ordered in the category table 600 according to their respective expected GR measurement values. In that regard, coal-lignite is ordered first with an expected GR measurement value of zero, dolomite is ordered second with an expected GR measurement value of one, fine sand is ordered third with an expected GR measurement value of one, silt is ordered fourth with an expected GR measurement value of two, and clay-shale is ordered fifth with an expected GR measurement value of three. In other examples, the lithologies can be ordered in the category table 600 according to their respective expected FORS measurement values. However, when lithologies are ordered in the category table 600 according to their respective expected FORS measurement values, the order changes. For example, based on an FORS measurement value ordering, coal-lignite would be ordered first with an expected FORS measurement value of zero, clay-shale would be ordered second with an expected FORS measurement value of one, fine sand would be ordered third with an expected FORS measurement value of two, silt would be ordered fourth with an expected FORS measurement value of three, and dolomite would be ordered fifth with an expected measurement value of four.

In some cases, such as in the illustrated example of FIG. 6, different lithologies have expected measurement values that are equal. For example, dolomite and fine sand both have expected GR measurement values that are equal to one. In that regard, it would be difficult to discriminate between dolomite and fine sand when determining respective lithologies of geological layers if only GR measurement logs are considered. Notably, however, dolomite and fine sand do not have equal expected FORS measurement values. Rather, dolomite has an expected FORS measurement value of four and fine sand has an expected FORS measurement value of two. Thus, to further distinguish between lithologies li described in a category table, a respective combined category score can be determined for each lithology included in the category table. Then, as will be described in more detail herein, the determined combined category scores can be used to discriminate between different lithologies.

In some examples, the combined category score for a particular lithology present in the category table can be determined as function of the various measurement values that correspond to the particular lithology. For example, Equation 1 below denotes a generic function ƒ_c for determining a combined category score s_i for a particular lithology l_i. In some examples, the function ƒ_c for determining a combined category score s_i for a particular lithology l_i is a linear function. In other examples, the function ƒ_c for determining a combined category score s_i for a particular lithology l_i is non-linear.

s i = f C ( c 1 ( l i ) , … , c M ( l i ) ) Equation ⁢ 1

In some examples, the function ƒ_c for determining a combined category score s_i for a particular lithology l_i can be a weighted sum that more heavily weights measurements of a first type than measurements of other types. For example, Equation 2 below denotes a weighted sum function for determining a combined category score s_i for a particular lithology l_i.

s i = ∑ m = 1 M w m * c m ( l i ) Equation ⁢ 2

In some examples, respective values for the weight w_m in Equation 2 can be set directly by an operator. In other examples, respective values for the weight w_m in Equation 2 can be determined using one or more functions. Equation 3 below denotes a function for determining the weight values used in calculating a combined category score with Equation 2.

w i = N j - 1 Equation ⁢ 3

With respect to the illustrated example of FIG. 6 in which there are two types of measurements per category of lithology described in the category table 600, using Equation 3 to determine the respective weight values results in w₁=5 and w₂=1.

FIG. 7 illustrates an example combined category score table 700, according to various embodiments. In generating the combined category score table 700, Equations 2 and 3 are used to calculate the respective combined category scores for the lithologies described in the example category table 600. In some examples, the combined category score table 700 and the combined category scores contained therein are determined and/or generated by the interpreted lithology application 432. For example, the interpreted lithology application 432 uses Equations 2 and 3 to determine combined category scores for the lithologies described in category table 600 and subsequently populate the combined category score table 700 with the determined combined category scores. In some examples, the interpreted lithology application 432 can use one or more other equations and/or algorithms to determine combined category scores for lithologies described in category tables.

As shown in the illustrated example of FIG. 7, the combined category score for coal-lignite is zero, the combined category score for dolomite is nine, the combined category score for fine sand is seven, the combined category score for silt is thirteen, and the combined category score for clay-shale is sixteen. Notably, in the illustrated example of FIG. 7, no two lithologies have equivalent combined category scores. In that regard, the determined combined category scores can be more effectively used to discriminate between different lithologies when compared to individual types of measurements (e.g., GR, FORS, etc.).

As further shown in the illustrated example of FIG. 7, each lithology described in the combined category score table 700 is assigned a respective combined category number. The combined category numbers are assigned to the lithologies based on the ordering of the respective combined category scores for the lithologies. For example, combined category numbers are assigned to lithologies in ascending order based on the respective amplitudes of the combined category scores for the lithologies. In that regard, coal-lignite is assigned a combined category number of zero because the combined category score for dolomite has the lowest amplitude (e.g., zero), fine sand is assigned a combined category number of one because the combined category score for fine sand has the second lowest amplitude (e.g., seven), dolomite is assigned a combined category number of two because the combined category score dolomite has the third lowest amplitude (e.g., nine), silt is assigned a combined category number of three because the combined category score for silt has the fourth lowest amplitude (e.g., thirteen), and clay-shale is assigned a combined category number of four because the combined category score for clay-shale has the highest amplitude (e.g., sixteen).

When using Equations 2 and 3 to calculate combined category scores for the lithologies described in the category table 600, the GR depth measurements were designated as c₁(l_i) and the FORS depth measurements were designated as c₂(l_i). However, in other examples, the order in which the GR and FORS depth measurements are designated in Equation 2 can be reversed. For example, the FORS depth measurements can designated as c₁(l_i) and the GR depth measurements can be designated as c₂(l_i). If the FORS depth measurements are designated as c₁(l_i) and the GR depth measurements are designated as c₂(l_i) in Equation 2 when calculating combined category scores for the lithologies in the category table 600, some of the respective values (e.g., amplitudes) of the combined category scores change. For example, the combined category score for coal-lignite remains zero, the combined category score for dolomite changes from nine to twenty-one, the combined category score for fine sand changes from seven to eleven, the combined category score for silt changes from thirteen to seventeen, and the combined category score for clay-shale changes from sixteen to eight. Notably, however, even with the reversed order of the GR and FORS depth measurements, none of the lithologies have equivalent combined category scores. In that regard, combined category scores are still effective in discriminating between lithologies regardless of the order in which measurement types of considered and/or weighted when calculating combined category scores.

As described herein, the interpreted lithology application 432 can use category tables of lithological properties (e.g., category table 600, combined category score table 700, etc.) to determine respective lithologies of the geological layers encountered during drilling. For example, the interpreted lithology application 432 can use the information contained within a category table and/or a combined category score table to analyze measurement logs when determining respective lithologies of the geological layers encountered during drilling. As used herein, the term “measurement log” refers to a log of measurements collected and/or determined during drilling within a particular depth range of in the subterranean formation 114 during drilling.

FIG. 8 illustrates example gamma ray and formation strength measurement logs, according to the various embodiments. For example, FIG. 8 illustrates an example GR log 800 that comprises GR measurements generated during drilling at depths between 11910-1970 feet in the subterranean formation 114. The GR measurements included in the GR log 800 can be, for example, generated by the LWD module 304, the MWD module 306, and/or one or more other downhole tools during drilling. Furthermore, FIG. 8 illustrates an example FORS log 802 that comprises FORS measurements generated and/or determined during drilling at depths between 11910-11970 feet in the subterranean formation 114. The FORS measurements included in the FORS log 802 can be, for example, determined based one or more drilling parameters (e.g., rate of penetration, rotary speed, weight on bit, etc.) of the drill string 102 and/or the drill bit 106 during drilling. Drilling parameter measurements can be, for example, generated by one or more of the telemetry equipment 302, the LWD module 304, the MWD module 306, sensors at the surface, and/or one or more other downhole or uphole tools. For illustrative purposes, the GR and FORS logs 800, 802 are displayed alongside the example lithology quantification 500 in FIG. 8.

Similar to how combined category scores can be determined from lithology measurement values described in a category table, a combined measurement value can be determined based on two or more different types of measurement values. For example, a combined measurement for a particular depth in the subterranean formation 114 can be determined based on two or more measurement types (e.g., GR, FORS, etc.) generated during drilling at the particular depth in the subterranean formation 114. In some examples, the interpreted lithology application 432 can determine combined measurement values based on two or more different types of measurement values. For example, the interpreted lithology application 432 can determine respective combined measurement values for depths between 11910-11970 feet in the subterranean formation 114 based in part on the measurements included in GR log 800 and the FORS log 802. In some examples, the interpreted lithology application 432 can generate a combined measurement log that comprises combined measurement values for respective depths within a specified depth range of the subterranean formation 114.

In some examples, a combined measurement can be determined as a function of two or more different measurement types generated during drilling. For example, Equation 4 below denotes a generic function ƒ_M for determining a combined measurement, where

measurement m d

is the m^th measurement at the depth d. In some examples, the function ƒ_M for determining a combined measurement at a particular depth d is a linear function. In other examples, the function ƒ_M for determining a combined measurement at a particular depth d is non-linear.

Combined ⁢ Measurement d = f M ( measurement 1 d , … , measurement M d ) Equation ⁢ 4

In some examples, the function ƒ_M for determining a combined measurement at a particular depth d can be a weighted sum that more heavily weights measurements of a first type than measurements of other types. For example, assuming that each type of measurement is discretized by B bits, which without generality can be assumed to have values between 0 and 2^B−1, Equation 5 below denotes a weighted sum function for determining a combined measurement

measurement Combined d

at a particular depth d.

measurement Combined d = ∑ m = 1 M ( 2 B ) m - 1 × measurement m d Equation ⁢ 5

With respect to the illustrated examples of FIGS. 5-8 in which there are only two types of measurements (e.g., GR and FORS), M is two. However, as described herein, more than two types of measurements can be used when determining respective lithologies of geological layers encountered during drilling in the subterranean formation 114. In that regard, in some examples, a combined measurement is determined based on more than two types of measurements generated during drilling.

In some examples, the interpreted lithology application 432 uses Equation 5 to determine respective combined measurement values for the depths d included within a specified depth range of the subterranean formation 114 at which drilling is occurring. For example, the interpreted lithology application 432 uses Equation 5 to determine combined measurement values for the depths d between 11910-11970 feet in the subterranean formation 114. In some examples, the interpreted lithology application 432 can further assemble the determined combined measurement values for various depths d into a combined measurement log.

FIG. 9 illustrates an example combined measurement log, according to the various embodiments. For example, FIG. 9 illustrates a combined GR/FORS log 900 that is a combination of the GR and FORS logs 800, 802 described herein and shown in FIG. 8. In that regard, the combined GR/FORS log 900 comprises respective combined measurement values for depths between 11910-11970 feet in the subterranean formation 114. In some examples, the interpreted lithology application 432 uses Equation 5 to generate the combined GR/FORS log 900 based on the measurements included in the GR and FORS depth logs 800, 802. In other examples, the interpreted lithology application 432 can use one or more different equations and/or algorithms to generate the combined GR/FORS log 900 based on the measurements included in the GR and FORS depth logs 800, 802. For illustrative purposes, the combined GR/FORS log 900 is displayed alongside the lithology quantification 500, the GR log 800, and the FORS log 802 in FIG. 9.

In some examples, the measurements that are included in a measurement log and used to determine a combined measurement value for a particular depth d can be discretized at varying bit resolutions and/or normalized with respect the maximum value of the measurement log. FIG. 10 illustrates example measurement plots that are discretized with varying bit resolutions and normalized with respect to maximum measurement values, according to various embodiments. For example, FIG. 10 illustrates a first GR measurement plot 1000A that is normalized with respect to a maximum GR measurement, a second GR measurement 1000B that is discretized with sixteen bits and normalized with respect to a maximum GR measurement, a third GR measurement 1000C that is discretized with eight bits and normalized with respect to a maximum GR measurement, a fourth GR measurement 1000D that is discretized with four bits and normalized with respect to a maximum GR measurement, and a fifth GR measurement 1000E that is discretized with two bits and normalized with respect to a maximum GR measurement. Moreover, FIG. 10 illustrates a first FORS measurement plot 1002A that is normalized with respect to a maximum FORS measurement, a second FORS measurement 1002B that is discretized with sixteen bits and normalized with respect to a maximum FORS measurement, a third FORS measurement 1002C that is discretized with eight bits and normalized with respect to a maximum FORS measurement, a fourth FORS measurement 1002D that is discretized with four bits and normalized with respect to a maximum FORS measurement, and a fifth FORS measurement 1002E that is discretized with two bits and normalized with respect to a maximum FORS measurement.

For an example in which GR and FORS measurement logs are normalized with respect maximum GR and FORS measurement values, Equation 6 below denotes a modified version of Equation 5 that can be used to determine a combined measurement

measurement Combined d

at a particular depth d.

measurement Combined d = 2 B * GR norm + 1 * ( FORS norm ) Equation ⁢ 6

As shown, Equation 6 includes use of a normalized GR measurement GR_norm and a normalized FORS measurement FORS_norm, which can respectively be determined using Equations 7 and 8 below.

R norm = GR - GR min GR max × 2 B ∈ ℤ + Equation ⁢ 7 FORS n ⁢ o ⁢ r ⁢ m = FORS - FORS min FORS max × 2 B ∈ ℤ + Equation ⁢ 8

In some examples, combined measurements can be stored using extended precision arithmetic. In other examples, fixed precision arithmetic can be utilized for individual measurements to compute the combined measurement within a given precision. In such examples, computed individual normalized measurements can be projected to the integer grid. Similar approaches can be taken with combined measurement calculations. While extended precision can ensure that there will be a bijection from combined measurement to individual measurement (i.e., preserving the information of all measurements in the combined measurement), extended precision arithmetic can be considered as a lossy transformation of the individual measurements. In other examples, other methods/strategies can be utilized to represent the individual or combined measurements to favor the computational/storage limitations of a computing system (e.g., computing device 400).

FIG. 11 illustrates example histograms of bin size fifty for gamma ray measurements, formation strength measurements, and combined measurements. For example, FIG. 11 illustrates a first histogram 1100A of bin size fifty, a second histogram 1100B of bin size fifty, a third histogram 1100C of bin size fifty, and a fourth histogram 1100D of bin size fifty. The first histogram 1100A represents individual FORS measurements, the second histogram 1100B represents individual GR measurements, the third histogram 1100C represents a combination of GR and FORS measurements in which the FORS measurements are more heavily weighted, and the fourth histogram 1100D represents a combination of GR and FORS measurements in which the GR measurements are more heavily weighted.

FIG. 12 illustrates example histograms of bin size one hundred for gamma ray measurements, formation strength measurements, and combined measurements. For example, FIG. 12 illustrates a first histogram 1200A of bin size one hundred, a second histogram 1200B of bin size one hundred, a third histogram 1200C of bin size one hundred, and a fourth histogram 1200D of bin size one hundred. The first histogram 1200A represents individual FORS measurements, the second histogram 1200B represents individual GR measurements, the third histogram 1200C represents a combination of GR and FORS measurements in which the FORS measurements are more heavily weighted, and the fourth histogram 1200D represents a combination of GR and FORS measurements in which the GR measurements are more heavily weighted.

After determining combined measurements values based on the two more measurement logs, the interpreted lithology application 432 can determine the respective lithologies of geological layers in the subterranean formation 114 encountered during drilling. For example, the interpreted lithology application 432 can determine respective lithologies of the geological layers encountered during drilling at depths between 11910-11970 feet in the subterranean formation 114 based on (i) the lithology quantification 500 that was determined based on drill bit cuttings 200 formed during the drilling, (ii) the combined category score table 700 that describes respective combined category scores and numbers for each possible lithology that could be encountered during the drilling, and (iii) the combined measurement log 900 that was determined, based in part on GR and FORS logs 800, 802, using Equations 5 and/or 6.

As described herein, the combined category score table 700 indicates that the combined category score for coal-lignite is less than the combined category score for fine sand, which is less than the combined category score for clay-shale. Stated another way, the combined category score table 700 indicates that s_coal-lignite<s_{fine sand}<s_clay-shale. In that regard, the interpreted lithology application 432 can determine from the combined category score table 700 that depths between 11910-11970 feet having the highest amplitude combined measurements correspond to clay-shale, depths between 11910-11970 feet having the lowest amplitude combined measurements correspond to coal-lignite, and the remaining depths between 11910-11970 feet having intermediate amplitude combined measurements correspond to fine sand.

Furthermore, as described herein, the lithology quantification 500 indicates that percentage of coal-lignite (e.g., 10%) between depths of 11910-11970 feet in the subterranean formation 114 is less than the percentage of clay-shale (e.g., 30%) between depths of 11910-11970 feet in the subterranean formation 114, which is less than the percentage (e.g., 60%) of fine sand between depths of 11910-11970 feet in the subterranean formation 114. Stated another way, between depths of 11910-11970 in the subterranean formation 114, q_coal-lignite (e.g., 10%)<q_clay-shale (e.g., 30%)<q_{fine sand} (e.g., 60%). In that regard, the interpreted lithology application 432 can determine that the highest q_clay-shale percentage (e.g., 30%) of the amplitudes in the combined measurement log 900 are associated with clay-shale, the second highest q_{fine sand} percentage (e.g., 60%) of the amplitudes in the combined measurement log 900 are associated with fine sand, and the remaining q_coal-lignite percentage (e.g., 10%) of the amplitudes in the combined measurement log 900 are associated with coal-lignite.

FIG. 13 illustrates an example interpreted lithology 1300 of geological layers in a subterranean formation, according to the various embodiments. For example, FIG. 13 illustrates an interpreted lithology 1300 that is a repartition of the lithologies identified in the lithology quantification 500. As shown in FIG. 13, the interpreted lithology 1300 defines the respective lithologies of discrete geological layers 1302A-1302H formed in the subterranean formation 114 between depths of 11910-11970 feet. For example, the interpreted lithology 1300 defines (i) a first geological layer 1302A that comprises fine sand and spans between depths of approximately 11910-11916 feet, (ii) a second geological layer 1302B that comprises coal-lignite and spans between depths of approximately 11916-11918 feet, (iii) a third geological layer 1302C that comprises fine sand and spans between depths of approximately 11918-11920 feet, (iv) a fourth geological layer 1302D that comprises coal-lignite and spans between depths of approximately 11920-11924 feet, (v) a fifth geological layer 1302E that comprises fine sand and spans between depths of approximately 11924-11949 feet, (vi) a sixth geological layer 1302F that comprises clay-shale and spans between depths of approximately 11949-11964, (vii) a seventh geological layer 1302G that comprises fine sand and spans between depths of approximately 11964-11967 feet, and (viii) an eighth geological layer 1302H that comprises clay-shale and spans between depths of approximately 11967-11970 feet.

As described herein, in some examples, the interpreted lithology application 432 determines and/or generates the interpreted lithology 1300 based in part on the lithology quantification 500, the combined category score table 700, and the combined GR/FORS log 900. For example, the interpreted lithology application 432 uses the lithologies identified in the lithology quantification 500 and the corresponding combined category scores for the lithologies described in the combined category score table 700 to associate respective ones of the lithologies with corresponding amplitudes of the combined GR/FORS log 900. In that regard, the interpreted lithology application 432 associates coal-lignite, which is quantified at 10% of the depth range between 11910-11970 feet in the subterranean formation 114, with the depths that have the smallest 10% of the amplitudes in the combined GR/FORS log 900. Similarly, the interpreted lithology application 432 associates the fine sand, which is quantified at 60% of the depth range between 11910-11970 feet in the subterranean formation 114, with the depths that have amplitudes in the combined GR/FORS log 900 between the smallest 10% of amplitudes and the smallest 70% of amplitudes. Moreover, the interpreted lithology application 432 associates clay-shale, which is quantified 30% of the depth range between 11910-11970 feet in the subterranean formation 114, with the remaining depths (e.g., the largest 30% of the amplitudes in the combined GR/FORS log 900).

In some examples, the interpreted lithology application 432 uses a clustering algorithm, such as K-means clustering, to associate respective lithologies with depths in the subterranean formation 114. By using a clustering algorithm, the interpreted lithology application 432 can avoid sticking to exact quantification values defined in the lithology quantification 500. Rather, by implementing a clustering algorithm, the interpreted lithology application 432 perform clustering (e.g., identify discrete geological layers) based on similarities in the data contained in the combined GR/FORS log 900.

In some examples, the interpreted lithology application 432 presents the interpreted lithology 1300 to an operator. For example, the interpreted lithology application 432 renders and displays the interpreted lithology 1300 on the display device 416 of the computing device 400. In some examples, the interpreted lithology application 432 stores the interpreted lithology 1300 in the system disk 414 of the computing device 400 and/or in a remote storage database.

In some examples, the drilling control application 430 modifies a drilling plan based on the interpreted lithology 1300. Modifying a drilling plan can include, for example, changing one or more drilling parameters (e.g., rate of penetration, rotary speed, weight on bit, etc.) based on the determined lithologies of the geological layers encountered during drilling. In some examples, when the drill bit 106 is drilling at a particular depth, the drilling control application 430 can modify, via the telemetry equipment 302 or RSS 308, a drilling parameter of the drill bit 106 in accordance with the identified lithology of the depth at which the drill bit 106 is drilling. By adjusting drilling parameters in accordance with determined lithologies of the depths being drilled at, risk during drilling can be mitigated and operating efficiency can be greatly improved.

FIG. 14 is a flow diagram of method steps for automated interpreted lithology, according to various embodiments. Although the method steps are described in conjunction with the systems of FIGS. 1-13, persons skilled in the art will understand that any system configured to perform the method steps, in any order, is within the scope of the present disclosure.

As shown, a method 1400 begins at step 1402, at which a drill bit is used to drill within a specified depth range of a subterranean formation. For example, the drill bit 106 coupled to the lower end of the drill string 102 is rotated to drill within a specified depth range (e.g., between 11910-11970 feet) in the subterranean formation 114.

At step 1404, a first measurement log is generated during drilling within the specified depth range in the subterranean formation 114. For example, the GR log 800 is generated.

At step 1406, a second measurement log is generated during drilling within the specified depth range in the subterranean formation 114. For example, the FORS log 802 is generated.

At step 1408, N lithologies contained within the specified depth range in the subterranean formation 114 are identified based on drill bit cuttings formed during the drilling, where N>1. For example, the interpreted lithology application 432 identifies coal-lignite, fine sand, and clay-shale based on the drill bit cuttings 200. In some examples, step 1408 includes removing drill bit cuttings 200 from drilling fluid (e.g., mud 120) with a shale shaker 130.

At step 1410, a respective percentage of each of the N lithologies contained within the specified depth range of the subterranean formation is quantified based on the drill bit cuttings. For example, the interpreted lithology application 432 generates the lithology quantification 500, which identifies respective percentages of coal-lignite, fine sand, and clay-shale contained within the specified depth range in the subterranean formation 114.

At step 1412, a category table that defines a respective category score for each of the N lithologies identified at step 1408 is obtained. For example, the interpreted lithology application 432 obtains the category table 600 and/or the combined category score table 700. In some examples, step 1410 further includes determining the combined category score for each of the N lithologies identified at step 1408. For example, using one or more of Equations 1-3, the interpreted lithology application 432 can determine combined category scores for coal-lignite, fine sand, and clay-shale based on information included in the category table 600.

At step 1414, a plurality of combined measurements is determined based on the first and second measurement logs. For example, the interpreted lithology application 432 can use Equation 5 and/or Equation 6 to determine a plurality of combined measurement values based on the GR log 800 and the FORS log 802. In some examples, the interpreted lithology application 432 formats the plurality of combined measurements into a combined GR/FORS log 900.

At step 1416, each depth within the specified depth range is associated with a corresponding one of the N lithologies identified at step 1408. For example, the interpreted lithology application 432 can use one or more techniques described herein to associate each depth within the specified depth range with a corresponding one of the N lithologies based on the combined category scores for the N lithologies, the plurality of combined measurements (e.g., the combined GR/FORS log 900), and the respective percentages of each of the N lithologies contained within the specified depth range of the subterranean formation 114 (e.g., the lithology quantification 500). In some examples, at step 416, the interpreted lithology application 432 implements a clustering algorithm to associate depths within the specified depth range with corresponding lithologies.

At step 1418, a visual representation of the associations between the depths within the specified depth range and the corresponding ones of the N lithologies is generated. For example, the interpreted lithology application 432 generates a visual representation comprising the interpreted lithology 1300.

At step 1420, the visual representation is displayed on a display device. For example, the interpreted lithology application 432 displays the visual representation generated at step 1418 (e.g., the interpreted lithology 1300) on the display device 416.

In some examples, the method 1400 further includes modifying a drilling parameter (e.g., rate of penetration, rotary speed, or weight on the drill bit) during drilling at a particular depth based in part on the lithology associated with the particular depth at step 1416. For example, the drilling control application 430 adjusts a drilling parameter during drilling at a depth of 11930 feet within the subterranean formation 114 based on the association of fine sand with the depth of 11930 feet.

Although certain aspects have been described with reference to certain examples, variations and modifications exist within the spirit and scope of one or more independent aspects. Various features and aspects are set forth in the following claims.

Any and all combinations of any of the claim elements recited in any of the claims and/or any elements described in this application, in any fashion, fall within the contemplated scope of the present disclosure and protection. The descriptions of the various embodiments have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.

Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine.

The instructions, when executed via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such processors may be, without limitation, general purpose processors, special-purpose processors, application-specific processors, or field-programmable gate arrays.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

While the preceding is directed to embodiments of the present disclosure, other and further embodiments of the disclosure may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.