SUBSURFACE FORMATION BED BOUNDARY INTERPRETATION WITH DEPTH AND DIP INFORMATION FOR WELL SYSTEMS

Description

TECHNICAL FIELD

The present invention relates generally to oil and gas systems and services, and more specifically to determining a subsurface formation bed boundary interpretation using depth and dip information for well systems.

BACKGROUND

In real-time geosteering operations, subsurface formation boundaries may be interpreted from different logging-while-drilling (LWD) logs. Since different LWD sensors may be configured with different depths of investigation (DOI), geosteering engineers may have different confidences in interpretations made from the different LWD sensors. Therefore, it is challenging to generate a fusion of different interpretations based on their confidence. Today, geosteering engineers may fuse the different interpretations manually using their knowledge and experience to generate a combined interpretation of the bed boundaries. The quality of the fusion highly depends on the engineer's understanding of geology and logs, and extra errors may be introduced to the interpretation due to the understanding bias. Furthermore, the engineer's confidence in the fusion of the interpretations is also empirical.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example well system, according to some implementations.

FIG. 2 is a flowchart of example operations for determining subsurface formation boundary information for drilling a wellbore using a well system, according to some implementations.

FIG. 3 depicts an example plot of the formation bed boundary determined from the corrected boundary interpretation versus the ground truth, according to some implementations.

FIG. 4 depicts another example plot of the formation bed boundary including confidence intervals determined from the corrected boundary information, according to some implementations.

FIG. 5 is a flowchart of example operations for determining subsurface formation boundary information for drilling a wellbore using a well drilling system, according to some implementations.

FIG. 6 depicts an example computer system that can be implemented in surface equipment of a well system for determining subsurface formation boundary information for drilling a wellbore, according to some implementations.

DESCRIPTION

The description that follows includes example systems, methods, techniques, and program flows that describe aspects of the disclosure. However, it is understood that this disclosure may be practiced without these specific details. For instance, this disclosure refers to certain well systems, devices, or tools in illustrative examples. Aspects of this disclosure can be instead applied to other types of well systems, devices, and tools. In other instances, well-known instruction instances, protocols, structures, and techniques have not been shown in detail to avoid confusion.

FIG. 1 depicts an example well system, according to some implementations. In particular, FIG. 1 is a schematic diagram of a well system 100 that includes a drill string 180 having a drill bit 112 disposed in a wellbore 106 for drilling the wellbore 106 in the subsurface formation 108. The well system 100 may also be referred to as a well drilling system. While depicted for a land-based well system, example implementations may be used in subsea operations that employ floating or sea-based platforms and rigs.

The well system 100 may further include a drilling platform 110 that supports a derrick 152 having a traveling block 114 for raising and lowering the drill string 180. The drill string 180 may include, but is not limited to, drill pipe, drill collars, and drilling assembly 116. The drilling assembly 116 may comprise any of a number of different types of tools including a rotary steerable system (RSS), measurement while drilling (MWD) tools, logging while drilling (LWD) tools, mud motors, etc. A kelly 115 may support the drill string 180 as it may be lowered through a rotary table 118. The drill bit 112 may include roller cone bits, polycrystalline diamond compact (PDC) bits, natural diamond bits, any hole openers, reamers, coring bits, and the like. Drilling parameters (or drilling attributes) of drilling the wellbore 106 may be adjusted to increase, decrease, and/or maintain the rate of penetration (ROP) of the drill bit 112 through the subsurface formation 108 and, additionally, steer the drill bit 112 through the subsurface formation 108. The subsurface formation 108 may include multiple formations such as formations 130, 132. The interface between the formations 130, 132 may be the formation bed boundary 111. The drilling parameters may assist in steering the wellbore 106 to avoid contact and/or penetration of the formation bed boundary 111. Drilling parameters may include weight-on-bit (WOB) and rotations-per-minute (RPM) of the drill string 180. A pump 122 may circulate drilling fluid through a feed pipe 124 to the kelly 115, downhole through interior of the drill string 180, through orifices in the drill bit 112, back to the surface 120 via an annulus surrounding the drill string 180, and into a retention pit 128.

In some implementations, various sections of the wellbore 106 such as the vertical, tangent, curve, and horizontal section may require directional drilling to steer the drill bit 112 on a planned well path and/or keep the wellbore 106 in a target formation. Sensors on the drilling assembly 116, such as gamma ray sensors, porosity sensors, resistivity sensors, etc., may log respective measurements while drilling the wellbore 106. The measurement logs may be obtained from the sensors on the drilling assembly 116 and uplinked to the surface 120. In some implementations, the measurements may be communicated to tools on the drilling assembly 116 for processing. The measurements may be processed and utilized to determine the location of the formation bed boundary 111. Steering decisions may be determined based on the wellbore 106 location relative to the formation bed boundary 111 and may be communicated back to the drilling assembly 116 for implementation to maintain the planned well path and/or remain in the target formation. For example, a target formation of the wellbore 106 may be formation 132. Steering decisions may be implemented such that the wellbore 106 may not be drilled through the formation bed boundary 111 and into formation 130.

The well system 100 may include a computer 170 that may be communicatively coupled to other parts of the well system 100. The computer 170 may be local or remote to the drilling platform 110. A processor of the computer 170 may perform simulations (as further described below). In some implementations, the processor of the computer 170 may control drilling operations of the well system 100 or subsequent drilling operations of other wellbores. For instance, the processor of the computer 170 may determine the formation bed boundary 111 and determine steering inputs to avoid contacting the formation bed boundary 111. An example of the computer 170 is depicted in FIG. 6, which is further described below.

FIG. 2 is a flowchart 200 of example operations for determining subsurface formation boundary information for drilling a wellbore using a well system, according to some implementations. In some implementations, the well system (e.g., such as the well system 100 of FIG. 1) may obtain primary measurements from one or more sensors of the well system (block 202). For example, the one or more sensors may include downhole sensors that are part of the drill string of the well system (e.g., located in the drilling assembly of the drill string) and/or may include surface sensors that are part of the surface equipment of the well system. The one or more sensors may include, for example, one or more of a gamma ray sensor, a porosity sensor, a resistivity sensor, a nuclear magnetic resonance sensor, a density sensor, and an acoustic sensor, among others. In some implementations, the primary measurements may include depth measurements, dip measurements, or both depth and dip measurements. The primary measurements may also be referred to as primary measurement data or primary measurement information.

In some implementations, the well system may determine a primary boundary interpretation for a formation bed boundary of the subsurface formation based on the primary measurements (block 204). The primary boundary interpretation may also be referred to as primary boundary information. As noted above, the primary measurements may include depth measurements, dip measurements, or both depth and dip measurements. In one non-limiting example, as shown in Equation 1, the primary boundary interpretation may be determined by using both depth and dip measurements and using a linear projection. In Equation 1,

represents the primary boundary interpretation, TVDss_k may represent the depth measurements, such as true vertical depth (TVD) measurements, dip_k may represent the dip measurements, and ΔHorizontalDeparture may represent the horizontal departure from an initial well trajectory having a vertical drilling plane, or how far the drilling moves in a horizontal direction from the initial vertical drilling plane. For example, the ΔHorizontalDeparture in a perfectly horizontal part of the well will be the increase in measured depth. In some implementations, the measurements used in Equation 1 may be obtained from multiple sensor sources and multiple sensor readings, e.g., dip_k may be obtained from multiple logging while drilling (LWD) sources.

TV = TVDss k + dip k · Δ ⁢ HorizontalDeparture ( Equation ⁢ 1 )

In another non-limiting example, after determining the primary boundary interpretation (or primary boundary information) using Equation 1, the variance for the primary boundary interpretation may be projected or estimated using Equation 2. It is noted that the variance may be other types of uncertainty, such as a confidence interval, percentile, or standard deviation. In Equation 2, may represent the projected or estimated variance (or uncertainty) for the primary boundary interpretation, Var_TVDss,k may represent the projected or estimated variance (or uncertainty) for the TVD measurements, Var_dipk may represent the projected or estimated variance (or uncertainty) for the dip measurements, and ΔHorizontalDeparture² may represent another horizontal departure measurement, similarly as described in Equation 1.

= Var T ⁢ V ⁢ D ⁢ s ⁢ s , k + Var d ⁢ i ⁢ p k · Δ ⁢ HorizontalDeparture 2 ( Equation ⁢ 2 )

In some implementations, the well system may obtain secondary measurements from one or more sensors of the well system (block 206). In some implementations, the secondary measurements may be obtained from different sensors (e.g., different sensors of the same type or different types of sensors) than the primary measurements, the secondary measurements may be obtained from different locations than the primary measurements, or the secondary measurements may be taken or read at different times than the primary measurements. In other words, the secondary measurements may be different than the primary measurement in some way. When the same sensors are used, then the location or time of the readings may be different. When different sensors are used (e.g., different sensors of the same type or different types of sensors), then the location or time of the readings may be the same or different. In some implementations, the secondary measurements may include depth measurements, dip measurements, or both depth and dip measurements. The secondary measurements may also be referred to as secondary measurement data or secondary measurement information. In some implementations, the depth measurements may be TVD measurements of the formation bed boundary, and the dip measurements may be a change in the trend of the formation bed boundary (c.g., a change in angle or degrec). In some non-limiting examples, the TVD measurements may be obtained from LWD logs and/or seismic inversion information. In some non-limiting examples, the dip measurements may be obtained from dip picks in azimuthal images, from a trend inferred from a continuous boundary detected from an inversion image, from a trend inferred from discrete lithological correlation points, and/or from a trend observed from the seismic surface information. In some implementations, one or both of the first measurements and the second measurements may be taken during the drilling of the wellbore, i.c., while the drilling operation is ongoing.

In some implementations, the well system performs a correction on the primary boundary interpretation using the secondary measurements (block 208). In some implementations, the well system may determine a secondary boundary interpretation for the formation bed boundary of the subsurface formation based on the secondary measurements, and the secondary boundary interpretation may be used to correct the primary boundary interpretation. The secondary boundary interpretation may also be referred to as secondary boundary information. The secondary boundary interpretation may be determined based on the secondary measurements using the Equation 1, and the variance or uncertainty for the secondary boundary interpretation may similarly be determined using Equation 2. In some implementations, the correction may be made using a weighted average of the primary and secondary boundary interpretations and/or using a data-driven method, such as machine learning and deep learning techniques.

In some implementations, the correction that is performed on the primary boundary interpretation using the secondary measurements may be used to determine a corrected boundary interpretation (block 210). The corrected boundary interpretation may also be referred to as the corrected boundary information. In some implementations, the primary boundary interpretation may be corrected using the secondary boundary interpretation (e.g., derived from the secondary measurements) to determine the corrected boundary interpretation. The secondary boundary interpretation may be determined based on the secondary measurements using the Equation 1. The corrected boundary interpretation may indicate the location of the formation bed boundary in the already drilled section of the wellbore and also project or estimate the location of the formation bed boundary in the section ahead of the drill bit (as shown below in FIGS. 3-4). In some non-limiting examples, the secondary measurements may be derived using kriging techniques, and the secondary boundary interpretation, such as TVDSS_kriging, may be determined based on the secondary measurements (e.g., kriging measurements) using the Equation 1. Although the examples herein uses kriging techniques, it is noted that other fusion methods may be utilized. After determining the secondary boundary interpretation (c.g., TVDss_kriging), the corrected boundary interpretation may be determined using Equation 3a, which uses both the primary boundary interpretation and the secondary boundary interpretation. Equation 3a uses a weight K to implement a weighted average of the primary and secondary boundary interpretations and derive the corrected boundary interpretation . The weight K can be selected to minimize the estimation uncertainty. Equation 3a can be further simplified into Equation 3b, which shows how the weights K and 1−K are applied to the secondary measurements and the primary measurements, respectively, to calculate the corrected boundary interpretation ().

= + K · ( TVDss k ⁢ r ⁢ i ⁢ g ⁢ i ⁢ n ⁢ g - ) ( Equation ⁢ 3 ⁢ a ) = ( 1 - K ) + K · TVDss k ⁢ r ⁢ i ⁢ g ⁢ i ⁢ n ⁢ g ( Equation ⁢ 3 ⁢ b )

The corrected boundary interpretation (or corrected boundary information) may be referred to as a combination or combined formation boundary interpretation or a fusion of formation boundary interpretations because the correction process described above combines or fuses the primary boundary interpretation (e.g., derived from the primary measurement data) and the secondary boundary interpretation (e.g., derived from the secondary measurement data). In some implementations, the corrected boundary interpretation is also a combination or fusion of depth measurement data and dip measurement data when the depth and dip measurements are used to determine the primary and secondary boundary interpretations. In some implementations, at least one of depth measurement data or dip measurement data may be used at each location in the wellbore. As described above, depth and dip measurement data may be used from the same location in the wellbore or different location in the wellbore. Also, for locations that have depth measurement data, dip measurement data may not be used for that location (but instead may be used from other locations), and for locations that have dip measurement data, depth measurement data may not be used for that location (but instead may be used from other locations). In some implementations, in some locations with limited depth measurement data, the dip information may be extracted from the depth differences in the depth information.

After determining the corrected boundary interpretation using Equation 3a, the well system may perform additional analysis to determine the uncertainty associated with the corrected boundary interpretation (block 212). The uncertainty may be one or more confidence intervals, one or more variances, one or more percentiles, or one or more standard deviations. The uncertainty may also be referred to as uncertainty information. In a non-limiting example, after determining the corrected boundary interpretation using Equation 3a, the variance for the corrected boundary interpretation may be projected or estimated using Equation 4. Although Equation 4 shows a variance, it is noted that any time of uncertainty for the corrected boundary interpretation may be determined, such as one or more confidence intervals, one or more percentiles, or one or more standard deviation. In some implementations, the variance or uncertainty for the corrected boundary interpretation may be determined based on the variance or uncertainty that was determined for the primary boundary interpretation and the secondary boundary interpretation. In Equation 4, may represent the projected or estimated variance or uncertainty or confidence interval after correction for the corrected boundary interpretation. may represent the projected or estimated variance or uncertainty or confidence interval for the primary boundary interpretation, Var_Kriging may represent the projected or estimated variance or uncertainty or confidence interval for the secondary boundary interpretation (e.g., in the example above that uses kriging), and K is the weight described above in Equations 3a and 3b.

= K 2 · Var K ⁢ r ⁢ i ⁢ g ⁢ i ⁢ n ⁢ g + ( 1 - K ) 2 · ( Equation ⁢ 4 )

In some implementations, the variance may be minimized by solving Equation 5a and obtaining the optimal weight K, as shown in Equation 5b.

∂ Var ∂ K = 2 ⁢ K · Var Kriging - 2 ⁢ ( 1 - K ) · = 0 ( Equation ⁢ 5 ⁢ a ) K = ( Equation ⁢ 5 ⁢ b )

In some implementations, the uncertainty (e.g., variance or confidence interval) for the corrected boundary interpretation may be determined by statistics and/or by using a data-driven method, such as machine learning and deep learning techniques. In some implementations, in addition to the correction terms representing the primary and secondary boundary interpretations that are shown in Equation 3a, one or more additional correction terms may be added, such as a correction term for an original seismic surface interpretation, as shown in Equation 6. Equation 6 is similar to Equation 3a, except that a new correction term has been added, and thus the gain and correction weights now form a vector. In Equation 6, TVDss_Original is the new correction term that represents the original seismic surface interpretation, K₁ may be the same weight K shown in Equation 3a, and K₂ may be an additional weight for the new correction term.

= + ( K 1 ⁢ K 2 ) · ( TVDss kriging - TVss Original - ) ( Equation ⁢ 6 )

In some implementations, the drilling operation is performed based on the corrected boundary interpretation (block 214). For example, as described in FIG. 1, drilling parameters (or drilling attributes) may be modified based on the corrected boundary interpretation to make steering decisions in the drilling of the wellbore to avoid contact and/or penetration of the formation bed boundary. As shown in FIGS. 3 and 4, the corrected boundary interpretation can be visualized by generating a curve that shows the formation bed boundary of the subsurface formation. The drilling system (c.g., the drill string, drilling assembly, drill bit, etc.) of the well system may utilize the formation bed boundary indicated by the corrected boundary interpretation (or corrected boundary information) to make drilling decisions for drilling the remainder of the wellbore, c.g., by avoiding crossing the formation bed boundary. In some implementations, the determination of the primary measurement data, the primary boundary interpretation, the secondary measurement data, the secondary boundary interpretation, the corrected boundary interpretation, the corresponding one or more uncertainties (c.g., confidence intervals) and modifying a drilling operation (or drilling parameter/attribute) may be automated or be performed autonomously using the features and processes described herein in FIGS. 1-4. In some implementations, the corrected boundary interpretation (or corrected boundary information) and uncertainty may provide a boundary interpretation curve with uncertainty information (c.g., one or more confidence intervals) for a drilled section of the wellbore, and/or a projection curve of the formation bed boundary ahead of a drilling bit of the well drilling system during a drilling operation with uncertainty information. Furthermore, the corrected boundary interpretation (or corrected boundary information) and the uncertainty may provide quality control information if conflicting boundary information is found for the wellbore during the drilling operations. In some implementations, a projection curve of the formation bed boundary may be determined based on both the primary and secondary boundary interpretations with uncertainty information, or based on only a primary boundary interpretation curve with uncertainty information.

In some implementations, a downhole operation or attribute or parameters in the wellbore (e.g., drilling operation or drilling parameters or attributes) may be modified or updated based on the determined or projected formation bed boundary, such as the corrected boundary interpretation or corrected boundary information. For example, an operation (at the surface and/or downhole) associated with drilling the wellbore may be performed and/or directed to be performed to change a downhole operation or attribute or parameter (c.g., drilling operation or drilling parameters or attributes) based on the corrected boundary information. For example, attributes or parameters of a drilling operation in the wellbore may be set based on the corrected boundary information. For example, drilling attributes or parameters may steer the drilling operation to avoid crossing the formation bed boundary indicated or projected by the corrected boundary information. The corrected boundary information may provide an accurate boundary projection ahead of the bit. For applications such as geosteering and well target planning, an accurate boundary projection can minimize risks involved in geosteering steering decisions. Furthermore, the feature and operations described herein in FIGS. 1-4 may remove inconsistency due to human boundary interpretation, improve interpretation quality and accuracy, and provide an accurate estimation of uncertainty (e.g., one or more confidence intervals) in the interpretations.

FIG. 3 depicts an example plot 300 of the formation bed boundary determined from the corrected boundary interpretation versus the ground truth, according to some implementations. In some implementations, the corrected boundary interpretation (which may be referred to as the corrected boundary information) may be derived as previously described in FIG. 2. The ground truth may be the true formation bed boundary that may be used for simulation and testing purposes to compare to the corrected boundary interpretation. In the plot 300 of FIG. 3, the curve 302 for the corrected boundary interpretation is shown by the solid line, and the curve 304 for the ground truth is shown by the dashed line. Also, in FIG. 3, the vertical solid lines represent the true vertical depth (TVD) measurements 306 and the vertical dashed lines represent the dip measurements 308 that were used to determine the corrected boundary interpretation, c.g., using the techniques described in FIG. 2. As shown in FIG. 3, the corrected boundary interpretation curve for the foundation bed boundary accurately estimates the ground truth curve for the foundation bed boundary.

FIG. 4 depicts another example plot 400 of the formation bed boundary including confidence intervals determined from the corrected boundary information, according to some implementations. In some implementations, the corrected boundary interpretation (which may be referred to as the corrected boundary information) may be derived as previously described in FIG. 2. The ground truth may be the true formation bed boundary that may be used for simulation and testing purposes to compare to the corrected boundary interpretation. In the plot 400 of FIG. 4, the curve 402 for the corrected boundary interpretation is shown by the solid line, and the curve 404 for the ground truth is shown by the dashed line. Also, in FIG. 4, the solid vertical line 410 shows the location of the drill bit, the part of the curves that represent the formation bed boundary information behind the drilling bit are shown by section 420, and the part of the curves that represent the formation bed boundary projection information ahead of the drill bit are shown by section 430. Additionally, the curve 406 formed by the outer lighter dotted line represents a first confidence interval (or variance or uncertainty) that can be derived for the corrected boundary interpretation. The curve 408 formed by the inner thicker dotted line represents a second confidence interval (or variance or uncertainty) that can be derived for the corrected boundary interpretation. The curve 408 is not shown in section 420 (behind the drill bit) for clarity. As shown in FIG. 4, the corrected boundary interpretation curve for the foundation bed boundary accurately estimates the ground truth curve for the foundation bed boundary. Also, as shown in section 430 for the ahead of the bit projection, most of the ground truth curve is within the second (narrower) confidence interval, and all of the ground truth curve is within the first (wider) confidence interval, which further shows the accuracy of the corrected boundary interpretation curve.

In some implementations, the well system may use a learning machine (such as a machine learning model, a machine learning neural network, or other suitable particularized machine) to perform a correction on the primary boundary interpretation using the secondary measurements (e.g., using the secondary boundary interpretation derived from the secondary measurements) in order to derive the corrected boundary interpretation or information. In some implementations, the well system may also use a learning machine (such as a machine learning model, a machine learning neural network, or other suitable particularized machine) to determine the uncertainty (e.g., variance or confidence interval) for the corrected boundary interpretation. In some implementations, the operations described above in FIGS. 1-4 may be performed by a learning machine (or some combination of mathematical models and a learning machine) to determine the corrected boundary interpretation and/or the uncertainty. For example, the training data set or inputs for the learning machine may include one or more of the followings: the primary measurements, the primary boundary interpretation, the secondary measurements, and the secondary boundary interpretation that are described above in FIGS. 1-4. In some implementations, the learning machine or the machine learning model may include computer code and/or a neural network and be implemented on a non-transitory computer readable medium, circuitry, and/or any other logic components configured to perform the operations described herein.

FIG. 5 is a flowchart 500 of example operations for determining subsurface formation boundary information for drilling a wellbore using a well drilling system, according to some implementations. In some implementations, primary boundary information for a formation bed boundary of a subsurface formation may be determined based on primary measurement data (block 502). In some implementations, secondary measurement data may be obtained from one or more sensors of the well drilling system (block 504). In some implementations, the primary boundary information may be corrected using the secondary measurement data to determine corrected boundary information for the formation bed boundary of the subsurface formation (block 506). In some implementations, an uncertainty may be determined for the corrected boundary information (block 508). In some implementations, at least one of a drilling operation or a drilling attribute in the wellbore may be modified based on the corrected boundary information and the uncertainty.

In some implementations, the correction of the primary boundary information using the secondary measurement data may include determining secondary boundary information for the formation bed boundary of the subsurface formation based on the secondary measurement data and correcting the primary boundary information using the secondary boundary information to determine the corrected boundary information. In some implementations, the correction of the primary boundary information using the secondary boundary information may include at least one of performing a weighted average of the primary boundary information and secondary boundary information to determine the corrected boundary information, or processing the primary boundary information and the secondary boundary information using a learning machine to determine the corrected boundary information. In some implementations, the determination of the uncertainty (c.g., one or more confidence intervals) for the corrected boundary information may include at least one of performing additional analysis on the primary boundary information and the secondary boundary information to determine the uncertainty for the corrected boundary information, or processing the primary boundary information and the secondary boundary information using a learning machine to determine the uncertainty for the corrected boundary information. In some implementations, the corrected boundary information and the uncertainty may provide at least one of a boundary interpretation curve with uncertainty information for a drilled section of the wellbore, a projection curve of the formation bed boundary ahead of a drilling bit of the well drilling system during a drilling operation with uncertainty information, or quality control information if conflicting boundary information is found for the wellbore during the drilling operation.

FIG. 6 depicts an example computer system that can be implemented in surface equipment of a well system for determining subsurface formation boundary information for drilling a wellbore, according to some implementations. The computer system 600 may be an example of a computer system that may be used during the operation of the well system, such as the computer system 170 shown in FIG. 1. For example, the computer system 600 may be a standalone computer system (such as a workstation, laptop, or desktop) or may be integrated into other surface equipment of the well system. The computer system 600 may include one or more processors 601 (possibly including multiple cores, multiple nodes, and/or implementing multi-threading, etc.). The computer system 600 may include memory 607. The memory 607 may be system memory or any type or implementation of machine or computer readable media having instructions that are executable by the one or more processors 601 to implement the operations described in FIGS. 1-5. The memory 607 may be system memory or any type or implementation of machine or computer readable and writable media having the ability to receive, process and/or store measurement data from well devices and tools (including those described in FIGS. 1-5). The computer system 600 also may include a bus 603 and a network interface 605. The computer system 600 also may include a communications module 608 that may control wired and wireless communications, such as communicating with downhole devices or tools and communicating with other surface equipment. The computer system 600 also may include at least a well system measurement unit 652 and a drilling control unit 654, among other processing units or modules that are used during the operation of the well drilling system and the well tools described herein. For example, the well system measurement unit 652 may control above ground and downhole equipment and tools to obtain measurement data (c.g., such as to obtain depth and dip measurements) and store other system metrics, and may process the measurements and system metrics as described in FIGS. 1-5 to determine the corrected boundary information (including uncertainty) for the formation bed boundary of the subsurface formation. The drilling control unit 654 may adjust or modify the drilling operation or a drilling parameter based on the corrected boundary information including the uncertainty (c.g., one or more confidence intervals), as described above in FIGS. 1-5. In some implementations, the well system measurement unit 652 (or the drilling control unit 654 or both the well system measurement unit 652 and the drilling control unit 654) may include a learning machine 653 to perform the operations described above with reference to FIGS. 1-5 for determining the corrected boundary information (including uncertainty) for the formation bed boundary of the subsurface formation. The functionality described herein may be implemented with an application-specific integrated circuit, in logic implemented in the processor(s) 601, in a co-processor on a peripheral device or card, etc. Further, implementations may include fewer or additional components not illustrated in FIG. 6. The processor(s) 601 and the network interface 605 may be coupled to the bus 603. Although illustrated as being coupled to the bus 603, the memory 607 may be coupled to the processor(s) 601.

Although an example well drilling system is shown in FIG. 1, it is noted that the operations and tools described in FIGS. 1-6 can be used in any type of well system.

As will be appreciated, aspects of the disclosure may be embodied as a system, method or program code/instructions stored in one or more machine-readable media. Accordingly, aspects may take the form of hardware, software (including firmware, resident software, micro-code, etc.), or a combination of software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” The functionality presented as individual modules/units in the example illustrations can be organized differently in accordance with any one of platform (operating system and/or hardware), application ecosystem, interfaces, programmer preferences, programming language, administrator preferences, etc.

Any combination of one or more machine-readable medium(s) may be utilized. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable storage medium may be, for example, but not limited to, a system, apparatus, or device, that employs any one of or combination of electronic, magnetic, optical, electromagnetic, infrared, or semiconductor technology to store program code. More specific examples (a non-exhaustive list) of the machine-readable storage medium would include the following: 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), 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 machine-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. A machine-readable storage medium is not a machine-readable signal medium.

A machine-readable signal medium may include a propagated data signal with machine-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A machine-readable signal medium may be any machine-readable medium that is not a machine-readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a machine-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as the Java® programming language, C++ or the like; a dynamic programming language such as Python; a scripting language such as Perl programming language or PowerShell script language; and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on a stand-alone machine, may execute in a distributed manner across multiple machines, and may execute on one machine while providing results and or accepting input on another machine.

The program code/instructions may also be stored in a machine-readable medium that can direct a machine to function in a particular manner, such that the instructions stored in the machine-readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

None of the implementations described herein may be performed exclusively in the human mind nor exclusively using pencil and paper. None of the implementations described herein may be performed without computerized components such as those described herein. Some implementations may perform additional operations, fewer operations, operations in parallel or in a different order, and some operations differently.

While the aspects of the disclosure are described with reference to various implementations and exploitations, it will be understood that these aspects are illustrative and that the scope of the claims is not limited to them. In general, techniques for determining the corrected boundary information (including uncertainty) for the formation bed boundary of the subsurface formation as described herein may be implemented with facilities consistent with any hardware system or hardware systems. Many variations, modifications, additions, and improvements are possible.

Plural instances may be provided for components, operations or structures described herein as a single instance. Finally, boundaries between various components, operations, and data stores are somewhat arbitrary, and particular operations are illustrated in the context of specific illustrative configurations. Other allocations of functionality are envisioned and may fall within the scope of the disclosure. In general, structures and functionality presented as separate components in the example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements may fall within the scope of the disclosure.

As used herein, the term “or” is inclusive unless otherwise explicitly noted. Thus, the phrase “at least one of A, B, or C” is satisfied by any element from the set {A, B, C} or any combination thereof, including multiples of any element.

Furthermore, unless otherwise specified, use of the terms “up,” “upper,” “upward,” “uphole,” “upstream,” or other like terms shall be construed as generally away from the bottom, terminal end of a well; likewise, use of the terms “down,” “lower,” “downward,” “downhole,” or other like terms shall be construed as generally toward the bottom, terminal end of the well, regardless of the wellbore orientation. Use of any one or more of the foregoing terms shall not be construed as denoting positions along a perfectly vertical axis. In some instances, a part near the end of the well can be horizontal or even slightly directed upwards. Unless otherwise specified, use of the term “subterranean formation” shall be construed as encompassing both areas below exposed earth and areas below earth covered by water such as ocean or fresh water.

Example Embodiments

Example Embodiments can include the following:

Embodiments #1: A method for determining subsurface formation boundary information for a wellbore using a well drilling system, comprising: determining primary boundary information for a formation bed boundary of a subsurface formation based on primary measurement data; obtaining secondary measurement data from one or more sensors of the well drilling system; correcting the primary boundary information using the secondary measurement data to determine corrected boundary information for the formation bed boundary of the subsurface formation; and determining an uncertainty for the corrected boundary information.

Embodiments #2: The method of Embodiments #1, wherein at least one of a drilling operation or a drilling attribute in the wellbore is modified based on the corrected boundary information and the uncertainty.

Embodiments #3: The method of Embodiments #1, further comprising: directing an operation to modify at least one of a drilling operation or a drilling attribute based on the corrected boundary information and the uncertainty.

Embodiments #4: The method of Embodiments #1, further comprising: modifying at least one of a drilling operation or a drilling attribute based on the corrected boundary information and the uncertainty.

Embodiments #5: The method of Embodiments #1, wherein correcting the primary boundary information using the secondary measurement data includes: determining secondary boundary information for the formation bed boundary of the subsurface formation based on the secondary measurement data; and correcting the primary boundary information using the secondary boundary information to determine the corrected boundary information.

Embodiments #6: The method of Embodiments #5, wherein correcting the primary boundary information using the secondary boundary information includes at least one of: performing a weighted average of the primary boundary information and secondary boundary information to determine the corrected boundary information; or processing the primary boundary information and the secondary boundary information using a learning machine to determine the corrected boundary information.

Embodiments #7: The method of Embodiments #1, wherein the primary measurement data includes primary depth measurements, primary dip measurements, or both primary depth and dip measurements, and the secondary measurement data includes secondary depth measurements, secondary dip measurements, or both secondary depth and dip measurements.

Embodiments #8: The method of Embodiments #7, wherein the secondary measurement data includes at least one of: sensor measurements from different sensors compared to the primary measurement data; sensor measurements from different locations in the wellbore compared to the primary measurement data; or sensor measurements from different times compared to the primary measurement data.

Embodiments #9: The method of Embodiments #1, further comprising determining secondary boundary information for the formation bed boundary of the subsurface formation based on the secondary measurement data, wherein determining the uncertainty for the corrected boundary information includes at least one of: performing additional analysis on the primary boundary information and the secondary boundary information to determine the uncertainty for the corrected boundary information; or processing the primary boundary information and the secondary boundary information using a learning machine to determine the uncertainty for the corrected boundary information.

Embodiments #10: The method of Embodiments #1, wherein the corrected boundary information for the formation bed boundary of the subsurface formation includes a curve indicating a location of the formation bed boundary of the subsurface formation.

Embodiments #11: The method of Embodiments #1, wherein the corrected boundary information and the uncertainty provides at least one of: a boundary interpretation curve with the uncertainty for a drilled section of the wellbore; a projection curve of the formation bed boundary ahead of a drilling bit of the well drilling system during a drilling operation with the uncertainty; or quality control information if conflicting boundary information is found for the wellbore during the drilling operation.

Embodiments #12: The method of Embodiments #1, further comprising determining a projection curve of the formation bed boundary based, at least in part, on the primary boundary information with uncertainty information.

Embodiments #13: The method of Embodiments #1, wherein the uncertainty includes at least one of one or more confidence intervals, one or more variances, one or more percentiles, or one or more standard deviations.

Embodiments #14: A well drilling system, comprising: one or more processors; and a computer-readable storage medium having instructions stored thereon that are executable by the one or more processors to cause the well drilling system to: determine primary boundary information for a formation bed boundary of a subsurface formation based on primary measurement data; obtain secondary measurement data from one or more sensors of the well drilling system; correct the primary boundary information using the secondary measurement data to determine corrected boundary information for the formation bed boundary of the subsurface formation; and determine an uncertainty for the corrected boundary information.

Embodiments #15: The well drilling system of Embodiments #14, wherein the instructions that cause the well drilling system to correct the primary boundary information using the secondary measurement data include instructions that cause the well drilling system to: determine secondary boundary information for the formation bed boundary of the subsurface formation based on the secondary measurement data; and correct the primary boundary information using the secondary boundary information to determine the corrected boundary information.

Embodiments #16: The well drilling system of Embodiments #15, wherein the instructions that cause the well drilling system to correct the primary boundary information using the secondary measurement data include instructions that cause the well drilling system to perform at least one of: perform a weighted average of the primary boundary information and secondary boundary information to determine the corrected boundary information; or process the primary boundary information and the secondary boundary information using a learning machine to determine the corrected boundary information.

Embodiments #17: The well drilling system of Embodiments #14, wherein the primary measurement data includes primary depth measurements, primary dip measurements, or both primary depth and dip measurements, and the secondary measurement data includes secondary depth measurements, secondary dip measurements, or both secondary depth and dip measurements.

Embodiments #18: The well drilling system of Embodiments #17, wherein the secondary measurement data includes at least one of: sensor measurements from different sensors compared to the primary measurement data; sensor measurements from different locations in a wellbore compared to the primary measurement data; or sensor measurements from different times compared to the primary measurement data.

Embodiments #19: A non-transitory computer-readable storage medium having instructions stored thereon that are executable by one or more processors of a well drilling system, the instructions comprising: instructions for determining primary boundary information for a formation bed boundary of a subsurface formation based on primary measurement data; instructions for obtaining secondary measurement data from one or more sensors of the well drilling system; instructions for correcting the primary boundary information using the secondary measurement data to determine corrected boundary information for the formation bed boundary of the subsurface formation; and instructions for determining an uncertainty for the corrected boundary information.

Embodiments #20: The non-transitory computer-readable storage medium of Embodiments #19, wherein the instructions for correcting the primary boundary information using the secondary measurement data include: instructions for determining secondary boundary information for the formation bed boundary of the subsurface formation based on the secondary measurement data; and instructions for correcting the primary boundary information using the secondary boundary information to determine the corrected boundary information.

Embodiments #21: The non-transitory computer-readable storage medium of Embodiments #19, wherein the primary measurement data includes primary depth measurements, primary dip measurements, or both primary depth and dip measurements, and the secondary measurement data includes secondary depth measurements, secondary dip measurements, or both secondary depth and dip measurements.

Embodiments #22: The non-transitory computer-readable storage medium of Embodiments #21, wherein the secondary measurement data includes at least one of: sensor measurements from different sensors compared to the primary measurement data; sensor measurements from different locations in a wellbore compared to the primary measurement data; or sensor measurements from different times compared to the primary measurement data.