DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The amendment filed 03/31/2026 has been entered. As directed, claims 1, 11-12 and 19 have
been amended, no claim have been canceled or added. Thus claims 1-22 remain pending in the application.
Response to Arguments
With respect to the Applicant’s argued rejection under 35 U.S.C 101 in “Applicant Arguments/Remarks Made in an Amendment”:
Applicant argues:
…
A. Step 2A, Prong One - The Claims Are Not Directed to a Judicial Exception
Under Step 2A, Prong One, the threshold inquiry is whether the claims recite a judicial exception, such as an abstract idea (e.g., mental processes or mathematical concepts).
The Examiner characterizes the claims as allegedly reciting abstract ideas related to "determining" or "calculating" information. That characterization does not withstand scrutiny when the claims are analyzed as written.
1. The Claims Do Not Recite a Mental Process
MPEP § 2106.04(a)(2)(III) makes clear that a claim does not recite a mental process when it includes limitations that cannot practically be performed in the human mind. The independent claims require, inter alia:
receiving near-range wellbore measurement data from physical subsurface sensors at a plurality of depths;
receiving reference data physically indicative of formation density at those depths;
deriving near-range earth models by inversion of sensor-derived data constrained by reference data;
receiving surface gravitational data from multiple surface locations; and
generating mid-range or far-range formation models used for geosteering a drill bit during drilling.
These steps require instrument-derived data, computational inversion, and model generation across multiple spatial scales, culminating in physical control of drilling equipment. Such operations cannot be practically performed mentally and therefore do not fall within the "mental process" grouping.
2. The Claims Do Not Recite a Mathematical Concept Standing Alone
While the claims involve computational techniques (e.g., inversion), MPEP § 2106.04(a)(2) distinguishes between claims that merely involve mathematics and claims that recite a mathematical concept as the focus of the claim. The pending claims do not recite a mathematical formula, equation, or abstract calculation in isolation. Instead, any mathematical processing is embedded as one step within a larger technical workflow for physically modeling subsurface formations and controlling drilling direction.
Accordingly, at most, the claims involve math as part of a technological process, which does not render them abstract under Prong One.
(see Response filed 03/31/2026 [pages 8-9]).
Applicant’s arguments regarding Section A have been fully considered but are not persuasive.
Applicant argues that “While the claims involve computational techniques (e.g., inversion), MPEP § 2106.04(a)(2) distinguishes between claims that merely involve mathematics and claims that recite a mathematical concept as the focus of the claim. The pending claims do not recite a mathematical formula, equation, or abstract calculation in isolation. Instead, any mathematical processing is embedded as one step within a larger technical workflow for physically modeling subsurface formations and controlling drilling direction.” However, independent claims 1 and 12 expressly recite “deriving … one or more near-range earth models … by inversion of the near-range wellbore measurement data constrained by the reference data” and “generating … at least one of a mid-range formation model or a far-range formation model … using the one or more near-range earth models … and the plurality of surface gravitational data.” The specification explains that the claimed inversion and formation model generation operations are performed using mathematical relationships, optimization techniques, curve fitting, forward modeling calculations, and gravitational modeling algorithms (see e.g., Spec. [0023], [0024], [0056] - [0060]). The specification further explains that surface gravitational data are used in inversion algorithms to model geological strata based on density related gravitational effects and calculated matches between modeled and measured data. Accordingly, under a broadest reasonable interpretation in light of the specification, the recited inversion based derivation of earth models and generation of formation models constitute mathematical relationships, mathematical calculations and mathematical modeling operations. As explained in MPEP 2106.04(a)(2)(I)(C), “That is, a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation. For example, a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.
Therefore, the claims recite a mathematical concept under MPEP 2106.04(a)(2)(I).
With respect to the Applicant’s argued rejection under 35 U.S.C 101 in “Applicant Arguments/Remarks Made in an Amendment”:
Applicant argues:
B. Step 2A, Prong Two - Any Alleged Abstract Idea Is Integrated Into a Practical Application
Even assuming, arguendo, that the claims recite an abstract idea at some level, the claims are not "directed to" that idea because they integrate it into a practical application, satisfying Step 2A, Prong Two (MPEP § 2106.04(d)).
1. The Claims Solve a Technical Problem in a Technical Field
The claims address a recognized technical problem in drilling operations: how to accurately model subsurface formation density across multiple spatial ranges and depths, and use that model to guide real-time geosteering of a drill bit.
The claimed solution is technical and specific:
combining near-range wellbore sensor data with independent density reference data;
performing constrained inversion to generate depth-resolved near-range earth models;
integrating those models with surface gravity measurements to generate mid-range or far-range formation models; and
using the resulting formation models to geosteer a drill bit.
This is not a generic data analysis or result-based claim. It recites a concrete technical process that improves subsurface formation modeling and geosteering control of drilling operations.
2. The Claimed Solution Improves the Functionality of Subsurface Modeling and Drilling Control Technology
Under the USPTO Subject Matter Eligibility Guidance, claims are patent eligible at Step 2A when they recite a solution that improves the functioning of a computer or another technical field, rather than merely using computers as tools to perform an abstract task. See MPEP § 2106.04(d)(1). Applicant respectfully submits that the pending claims satisfy this standard because they recite specific architectural and operational improvements to subsurface formation modeling and geosteered drilling systems themselves.
The claims do not merely apply known data processing techniques to achieve a desired result. Instead, they define a new way in which subsurface formation models are constructed and used, thereby improving how drilling systems operate in complex geological environments.
The technological improvement arises from how the system generates formation models, not simply from what the system does with those models. In particular, the claims recite:
Deriving near-range earth models by constrained inversion of near-range wellbore measurement data using independently obtained reference density data.
This improves formation modeling technology by stabilizing and physically grounding inversion results, improving model accuracy and robustness relative to unconstrained or single-source models.
Generating mid-range or far-range formation models using the derived near-range earth models as inputs together with surface gravitational data.
This hierarchical, multiscale modeling architecture improves the modeling technology itself by enabling cross-scale consistency between localized and broader formation representations, which is not achievable using conventional isolated modeling techniques.
Using the improved formation models to control geosteering of a drill bit.
This is not a mere downstream use of information; it reflects an improvement in the operational control mechanism of drilling systems, allowing real-time trajectory adjustments based on physically improved subsurface representations.
Collectively, these features form a technological modeling and control pipeline that improves how subsurface data is transformed into actionable control signals for drilling operations.
Importantly, the claimed improvement is not simply that drilling decisions are better informed. Rather, the claims improve:
formation modeling technology, by defining a constrained, multiscale inversion architecture that produces physically consistent density models; and
drilling system operation, by integrating those improved models directly into geosteering control.
Under USPTO guidance, improvements of this kind-where claimed elements change how data is generated, structured, and used within a technical system-constitute technological improvements even if conventional sensors or processors are employed. See MPEP § 2106.04(d)(1) (improvements to "another technology or technical field").
The Examiner's rejection appears to treat the claims as merely "using" data processing to accomplish a drilling task. That framing is incorrect. The claims redefine the internal modeling workflow of the system, including:
the relationship between near-range and mid-/far-range formation models,
the role of physical reference density constraints in inversion, and
the integration of multiscale models into drilling control.
This is precisely the type of technological improvement recognized by the USPTO as patent eligible, as opposed to claims that simply instruct a computer to analyze data or present results.
Because the pending claims recite a solution that improves subsurface formation modeling and drilling control technology itself, any alleged abstract idea is integrated into a practical application under Step 2A, Prong Two. Accordingly, the claims are not directed to an abstract idea, and the § 101 inquiry should end at Step 2A.
3. Specific Claim Elements That Integrate the Alleged Abstract Idea
The following claim elements impose meaningful limits and integrate any alleged abstract idea into a practical application:
"derive near-range earth models ... by inversion of near-range wellbore measurement data constrained by reference data"
- ties computation to physical measurements and constrained modeling, not abstract calculation.
"generate ... mid-range or far-range formation model ... using the near-range earth models and the plurality of surface gravitational data"
- reflects hierarchical, multiscale formation modeling tied to real-world sensing inputs.
"provide the ... formation model to a well driller ... for geosteering a drill bit" / "geosteering ... a drill bit ... based on the formation model"
- expressly links the computational output to physical control of drilling equipment.
4. Claims 11 and 22 Are Integrated Into a Practical Application (Step 2A, Prong Two)
Additionally, claims 11 and 22 expressly recite directing and geosteering a drill bit within a subterranean earth formation, which is a physical action performed by a computer system to control industrial equipment. Under MPEP § 2106.04(d)(1), claims that apply information processing to control a physical process or machine are integrated into a practical application and are not directed to an abstract idea. Further, the physical steering of the drill bit in claims 11 and 22 is not insignificant extra-solution activity. Rather, it is the primary technical purpose of the claimed invention. The claims do not merely output information for review; instead, the claimed formation models are used to actively control the trajectory and orientation of a drill bit during drilling operations. As set forth in MPEP § 2106.05(g), steps that are central to achieving a technical improvement cannot be dismissed as post-solution activity. Claims 11 and 22 further constitute an improvement in the technical field of subsurface drilling operations. Specifically, the claimed system and method improve how drilling equipment is controlled based on formation modeling derived from physical sensor data, including near-range wellbore sensors and surface gravitational measurements. Under MPEP § 2106.04(d)(1), claims that improve the operation of a technical process or system-here, the operation of a geosteered drilling assembly-are integrated into a practical application and satisfy Step 2A, Prong Two. Further, steering or directing the depth or orientation of a drill bit within a subterranean formation is a physical actuation of industrial machinery that cannot practically be performed in the human mind. MPEP § 2106.04(a)(2)(III) expressly provides that claim limitations that cannot practically be performed mentally do not fall within the mental process category of abstract ideas.
Under MPEP § 2106.04(d)(1), claims that apply alleged abstractions to control or improve a physical process are integrated into a practical application. That is precisely the case here.
(see Response filed 03/31/2025 [pages 10-14]).
Applicant’s arguments regarding Section B have been fully considered but are not persuasive.
In order to determine if additional element is integrating the abstract idea into a practical application, See MPEP 2106.04(d)(1), “first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. Second, if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. That is, the claim includes the components or steps of the invention that provide the improvement described in the specification. The claim itself does not need to explicitly recite the improvement described in the specification (e.g., "thereby increasing the bandwidth of the channel").” In other words, the specification should describe the improvement over the background invention or existing technology, and the improvement should be reflected at least in the additional elements (emphasis added) by specifying how the improvement perform the additional element different from existing technology, functioning of a computer or existing technical field.
Applicant argues that the claims solve a technical problem in a technical field. However, merely identifying a technical field or a technical problem does not establish integration into a practical application. The claims must recite a technical solution that applies or uses the identified abstract idea in a meaningful way. The additional limitations recite receiving measurement data, receiving reference data, receiving surface gravitational data, and providing or using the resulting formation model for drilling or geosteering. These limitations provide input data to the mathematical modeling operations and apply the resulting model information in the drilling environment recited at high level of generality, but do not recite a particular improvement to a sensor, processor, drilling tool, or geosteering control mechanism. Accordingly, the clams do not integrate the abstract idea into a practical application under Step 2A, Prong Two.
Applicant further arguers that the claim improve subsurface formation modeling and drilling control technology though constrained inversion, multiscale modeling and geosteering operations. However, the alleged improvement arises from the mathematical modeling itself. As explained in MPEP 2106.05(a), II.: "it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology." (emphasis added). The claims do not recite any improvement to computer functionality, sensor technology, inversion technology, geosteering hardware, drilling equipment, or any other technical system. Rather, the claims recite using mathematical calculations to generate formation models and then using the resulting models for drilling decisions. The additional limitations merely gather data for use by the mathematical model and apply the result of the mathematical modeling to a user and recite subsequent use of that result by the user in making a drilling or geosteering decision. Such limitations do not integrate the judicial exception into a practical application. See MPEP §2106.04(d).
Applicant further argues that deriving near-range earth models using reference data, generating mid-range or far-range formation models using gravitational data, and geosteering a drill bit based on the resulting formation models integrate the alleged abstract idea into a practical application. However, providing the resulting formation model to a well driller and geosteering a drill bit based on the generated model merely use the results of the mathematical calculations. The claims do not recite any particular machine control technique, particular geosteering algorithm, or specific drilling control mechanism. Accordingly, the additional limitations merely apply the result of the mathematical modeling to a user and recite subsequent use of that result by the user in making a drilling or geosteering decision and do not integrate the judicial exception into a practical application.
Applicant further argues that claims 11 and claim 22 are integrated into a practical application because they recite directing or geosteering a drill bit whin ta subterranean earth formation. However, the recited geosteering limitation merely uses the formation model generated by the claimed mathematical modeling operations. The claims do not recite any specific technique for controlling the drill bit, any particular modification to drilling equipment, or any improvement geosteering technology itself. Rather the claim broadly recite using the result of the mathematical modeling to direct drilling operations. Accordingly, the limitation merely applies the results of the mathematical modeling in a generic drilling system in its ordinary capacity for directing or geosteering the drill bit into the subterranean, does not integrate the judicial exception into a practical application.
With respect to the Applicant’s argued rejection under 35 U.S.C 101 in “Applicant Arguments/Remarks Made in an Amendment”:
Applicant argues:
C. USPTO Eligibility Example Analogy
The claims are analogous to USPTO examples deemed eligible where sensor data is processed to control or improve a physical system (e.g., signal processing or industrial control examples in which mathematical processing is embedded in a technological workflow). The claims are not analogous to ineligible examples that merely organize, analyze, or display information without a physical application.
For example, in Example 39, the USPTO determined that claims reciting sensor-based data processing and model generation operations that cannot practically be performed in the human mind do not recite a judicial exception under Step 2A, Prong One. Similarly, in Example 47, claims applying algorithmic processing to physical input data in a technical workflow were found to be integrated into a practical application under Step 2A, Prong Two. Like those examples-and unlike ineligible data-analysis claims-the pending claims process physical subsurface measurement data to generate formation models that are used to geosteer a drill bit in real time, which constitutes a concrete industrial application.
Here, the end result is not information for its own sake, but operational guidance used to steer a drill bit in the earth. This places the claims squarely on the eligible side of the Guidance.
D. Examiner Error in Applying Step 2A
1. Conclusory Identification of an Abstract Idea
The rejection treats the verb "determine" or "derive" as dispositive, without addressing the full claim limitations requiring specific sensor inputs, constrained inversion, multiscale modeling, and geosteering. This is inconsistent with MPEP § 2106.04, which requires analysis of the claim as a whole.
2. Failure to Address Prong Two Integration
The Examiner fails to meaningfully analyze whether the claims integrate any alleged abstract idea into a practical application. In particular, the rejection:
dismisses physical modeling and drilling control as "post-solution activity,"
and
does not explain how geosteering a drill bit based on derived formation models is merely abstract.
This omission is a legal and procedural error under Step 2A, Prong Two.
E. Step 2B - The Claims Recite Significantly More
Even if Step 2B were reached, the claims recite additional elements in an ordered combination that amount to significantly more than any alleged abstract idea (MPEP § 2106.05).
The ordered combination includes:
specific sensor-based inputs at defined spatial depths,
constrained inversion to generate layered density models,
integration of surface gravity measurements with downhole models, and
physical geosteering of drilling equipment based on those models.
This ordered combination reflects specialized subsurface modeling architecture, not routine or conventional computer activity, and therefore constitutes an inventive concept.
Therefore, under the USPTO Subject Matter Eligibility Guidance:
the claims do not recite a judicial exception under Step 2A, Prong One;
even if an abstract idea were alleged, it is integrated into a practical application under Step 2A, Prong Two; and
in any event, the claims recite significantly more under Step 2B.
Accordingly, claims 1-22 are directed to patent-eligible subject matter and the § 101 rejection should be withdrawn.
(see Response filed 03/31/2025 [pages 14-16]).
Applicant’s arguments regarding Section C, D and E have been fully considered but are not persuasive.
Applicant’s arguments regarding Section C have been fully considered but are not persuasive.
Applicant argues that the claims are analogous to USPTO eligible examples because pending claims process physical subsurface measurement data to generate formation models that are used to geosteer a drill bit in real time, which constitutes a concrete industrial application. However, the present claims are distinguishable from those examples because the additional limitations do not recite a particular improvement to sensor operation, signal processing, drilling equipment, or geosteering control. Instead, the claims merely use sensor data as inputs to mathematical modeling operations, and use the resulting formation model in the drilling field. Thus, the present clams are not analogous to examples where the claim improves a physical system or technical process itself.
Applicant’s arguments regarding Section D have been fully considered but are not persuasive.
Applicant argues that the rejection identifies the abstract idea in a conclusory manner and fails to address Step 2A, Prong Two. This argument is not persuasive because the present rejection identifies the mathematical concept as the inversion based derivation of near-range earth models and generation of mid-range or far-range formation models using near-range earth models and surface gravitational data. The rejection also considers the additional limitations, including the sensor data, reference data, surface gravitational data, processor, memory, providing the model toa well driller, and geosteering limitations. These additional limitations do not integrate the mathematical concept into a practical application because they merely provide data to the mathematical modeling operations and apply the result of the mathematical modeling to a user and recite subsequent use of that result by the user in making a drilling or geosteering decision.
Applicant’s arguments regarding Section E have been fully considered but are not persuasive.
Applicant argues that the ordered combination recites significantly more. This argument is not persuasive because the ordered combination uses generic sensor, processor, memory, and drilling related components in their ordinary capacities to obtain data, perform mathematical modeling and use the resulting model information. The claims do not recite an unconventional arrangement of components, an improved computer, an improved sensor, or a specific technical control mechanism for geosteering. Accordingly, when consider individually and in combination, the additional limitations do not amount to significantly more than the identified abstract idea.
Therefore, the rejection for independent claims 1 and 12, and the claims dependent thereon, under 35 U.S.C. 101 is maintained.
Applicant's arguments filed “Applicant Arguments/Remarks Made in an Amendment,” on
03/31/2026, pages 16-23, have been fully considered but they are not persuasive.
With respect to Applicant’s arguments for claims 1-6, 10-16, and 20-22 have been considered but are not persuasive.
The present rejection has been revised in view of the amended claim scope. The Office no longer relies on Miles for the limitation directed to deriving the one or more near-range earth models by inversion. Instead, the present rejection relies on Shetty to teach deriving layered density-based formation models by inversion of measurement data and using previously determined layer information in the inversion model. Accordingly, Applicant’s arguments directed to alleged deficiencies of Miles do not overcome the present rejection.
Applicant argues that the independent claims require deriving near-range earth models by inversion of near-range wellbore measurement data constrained by reference data “physically indicative of formation density.” However, the independent claim does not recite the reference data that are physically indicative of formation density. Rather, claim 1 recites receiving reference data related to a density measurement of the subterranean earth formation and deriving the one or more near-range earth models by inversion of near-range wellbore measurement data constrained by the reference data. The requirement that the reference data comprise data physically or directly indicative of the density of the subterranean earth formation at each of the plurality of depths along the wellbore is recited in dependent claim 4, not the independent claims 1 and 12. Accordingly, Applicant’s argument is not commensurate in scope with the limitations of claims 1 and 12.
Applicant further argues that the references do not teach generating a mid-range or far-range formation model using per-depth near-range density models as input constraints together with surface gravitational data. This argument is also not commensurate with the claim language. The generate step recites generating the mid-range or far-range formation model using the one or more near-range earth models and the plurality of surface gravitational data. The claim does not require the near-range earth models to be imposed as “input constraints,” and does not require constraining permissible solutions when generating the mid-range or far-range formation model.
In the present rejection, Bartetzko teaches the wellbore formation characterization environment, including wellbore measurement data and reference data. Shetty teaches deriving layered density based formation models by inversion of measurement data. Wang teaches obtaining surface gravitational data from a plurality of surface sampling locations. Priezzhev teaches generating a broader volumetric subsurface formation model using borehole derived information and surface gravity data through forward modeling and inversion. Thus, the cited references collectively teach or suggest generating a mid-range or far-range formation model using near-range formation information and surface gravitational data as claimed.
Applicant’s argument regarding structural incompatibility and hindsight is likewise not persuasive. The rejection applies the express teachings of the references in a predictable manner. Bartetzko provides the drilling and formation-characterization context, Shetty provides inversion based density model derivation, Wang provides surface gravitational data, and Priezzhev provides integration of borehole derived information and surface gravity data to generate a broader volumetric subsurface model. The combination is supported by the recognized benefit of improving subsurface formation characterization by integrating local wellbore derived formation information with broader surface gravity measurements.
Applicant also argues that the dependent claims recite limitations involving particular sensor types, survey measurement data, and constraining of formation models. These arguments are not persuasive because the rejection addresses the limitations of the dependent claims with the corresponding applied references. Moreover, Applicant’s arguments largely rely on the same alleged deficiencies asserted against the independent claims. Because the present rejection establishes that the independent claim limitations are taught or suggested by the applied combination, and because the dependent claim limitations are separately addressed in the rejection, Applicant’s arguments do not overcome the rejection of claims 1-6, 10-16, and 20-22.
With respect to Applicant’s arguments regarding claims 7, 8, 17, and 18 have been considered but are not persuasive.
Applicant argues that Wu is directed to quantum gravimetry instrumentation and does not disclose the full multiscale formation modeling framework of the independent claims. However, Wu is not relied upon to teach the full formation modeling workflow. Wu is relied upon for the additional dependent claim limitations directed to the manner in which surface gravitational data are obtained.
For claim 7, Wu teaches operating an atomic gravimeter inside a vehicle and measuring gravity at six field locations, with the gravimeter being set up at each location before taking the measurement. Thus, Wu teaches a mobile surface gravity sensor used at multiple surface locations. A person of ordinary skill in the art would have understood that using the same mobile gravimeter at multiple field locations requires the sensor to be located sequentially at the respective locations during the gravity survey. Therefore, Wu teaches or suggests the limitation of claim 7.
For claim 8, Wu teaches an atomic gravimeter used to measure absolute gravity in a field survey. An atomic gravimeter is a quantum gravity sensor because it measures gravity using atom interferometry. Thus, Wu teaches obtaining surface gravitational data from one or more quantum gravity sensors as recited in claim 8.
Applicant’s argument that Wu does not disclose interaction with near-range density models or the overall hierarchical modeling architecture is not persuasive because claims 7 and 8 do not separately require Wu to teach those features. The combination teaches the independent claim limitations, and Wu is applied only for the additional sensor configuration limitations of the dependent claims.
Applicant’s hindsight argument is also not persuasive. The rationale for incorporating Wu is based on Wu’s express teaching of using a mobile atomic gravimeter to obtain gravity measurements at multiple field locations, together with the recognized benefit of obtaining accurate and reliable surface gravity measurements for subsurface formation characterization. Thus, the use of Wu’s gravity sensor technology in the surface gravity acquisition portion of the combined system would have been a predictable use of known sensor technology for its known purpose.
With respect to Applicant’s arguments regarding claims 9 and 19 have been considered but are not persuasive.
Applicant argues that Xu does not teach correlating formation models at different depths along a wellbore to determine layer density inhomogeneities. However, Xu is not relied upon to teach the entire wellbore based formation modeling workflow. Rather, Bartetzko, Shetty, Wang, and Priezzhev provide the formation modeling framework, including the generated mid-range or far-range formation model. Xu is relied upon for the additional analysis of density structures at different depths and the determination of density inhomogeneities within subsurface layers.
Xu teaches decomposing Bouguer gravity anomalies to reveal refined subsurface density structure at different depths, dividing the subsurface into multiple layers, determining multilayer densities, and identifying strong lateral density inhomogeneity within layers. Xu further teaches strong correlations between decomposed gravity anomalies and tectonic features at different depths. Thus, Xu teaches or suggests analyzing density related model information at different depths and determining layer density inhomogeneities.
Applicant’s argument improperly requires Xu alone to disclose the full claimed multiscale wellbore modeling architecture. The rejection does not rely on Xu for that purpose. Instead, Xu is combined with the combined references for its teaching of multilayer density analysis and density inhomogeneity determination. Applying Xu’s depth dependent density analysis to the generated formation model of the combination would have predictably improved subsurface interpretation by identifying density variations within layers of the model.
Therefore, for the reasons discussed above, Applicant’s arguments do not overcome the rejection of claims 1-22. Therefore, the rejection of independent claims 1 and 12, and the claims dependent thereon, under 35 U.S.C. 103 is maintained.
Claim Objections
Claims 1 and 12 are objected to because of the following informalities:
Claim 1 recites “derive, for each of the plurality of depths along the wellbore, one or more near-range earth models of the subterranean earth formation each comprising a density model of a layer at a respective depth by inversion of the near-range wellbore measurement data constrained by the reference data, wherein each of the one or more near-range earth models comprises a density model of a layer of the subterranean earth formation,” which should read “derive, for each of the plurality of depths along the wellbore, one or more near-range earth models of the subterranean earth formation each comprising a density model of a layer at a respective depth by inversion of the near-range wellbore measurement data constrained by the reference data”. Examiner note: the highlighted limitation merely restates that each near-range earth model comprise a density model of a layer, and does not further limit the claim.
Claims 12 recites the same limitations, and are objected to for the same reason.
Claim 12 recites “geosteering, by the well driller, a drill bit into …” which should read “geosteering, by a well driller, a drill bit into …”.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
The claim(s) 1-22 are rejected under 35 USC § 101 because the claimed invention is directed
to judicial exception an abstract idea, it has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception. Examiner has evaluated
the claims under the framework provided in the 2019 Revised Patent Subject Matter Eligibility Guidance
published in the Federal Register 01/07/2019, as well as subsequent USPTO eligibility guidance updates,
and has provided such analysis below.
Step 1: Are the claims to a process, machine, manufacture or composition of matter?"
Yes, Claims 1-11 are directed to system and fall within the statutory category of machine;
Yes, Claims 12-22 are directed to method and fall within the statutory category of process.
In order to evaluate the Step 2A inquiry "Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?" we must determine, at Step 2A Prong 1, whether the claim recites a law of nature, a natural phenomenon or an abstract idea and further whether the claim recites additional elements that integrate the judicial exception into a practical application.
Step 2A Prong 1:
The claim 1 does recite a mathematical concepts.
MPEP 2106.4(a)(2)(I): “The mathematical concepts grouping is defined as mathematical
relationships, mathematical formulas or equations, and mathematical calculations”.
MPEP 2106.04(a)(2)(I)(A), “A mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words or using mathematical symbols.”
MPEP 2106.4(a)(2)(I)(C): “a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation. For example, a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.
Claim 1: The limitations of “derive, for each of the plurality of depths along the wellbore, one or more near-range earth models of the subterranean earth formation each comprising a density model of a layer at a respective depth by inversion of the near-range wellbore measurement data constrained by the reference data … generate at least one of a mid-range formation model or a far-range formation model at each of the plurality of depths along the wellbore using the one or more near-range earth models and the plurality of surface gravitational data,” as drafted, under its broadest reasonable interpretation (BRI) in light of specification, can be reasonably considered to recite a mathematical concept, as recites in the specification: [0023], “An inversion algorithm may start with an initial estimated model of a subterranean formation to describe the subterranean formation … The initial model may be used with governing equations generate simulation measurements to relate the model to the indirect layer density characterizations from the wellbore measurement data.” [0024] “In some non-limiting aspects, the inversion algorithm may, for example, successively modify the initial model based on a gradient search technique, such as a Gauss-Newton search method. Typically, an inversion algorithm solution may be a one dimensional solution curve of wellbore measurement data versus measurement depth. In some non-limiting aspects, the inversion algorithm may also generate a two dimensional solution of wellbore measurement data versus measurement depth and angular position about the wellbore. The model produced by the inversion algorithm may include, for example, modeled wellbore measurement data over distance or distance and angular position. The modeled wellbore measurement data may be produced by a specific model of the formation defined over a measurement depth. In some aspects, the modeled wellbore measurement data may be compared to the measured wellbore measurement data obtained from measured wellbore data using a least-squares algorithm.” [0056], “… the inversion algorithms may start with a near-range measurement of strata properties at each of a variety of depths of the wellbore. Reference data taken at each depth are also acquired. The inversion algorithms then generate an initial model of the strata next to the wellbore at each depth … At this point, the near-range models of the strata are determined at each of the variety of depths that are probed.” [0057], “Surface gravimetric data may be used to extend the near-range models into the mid-range and even far-range areas.” [0058], “Because the gravitational data have such fine spatial resolution, they can be used by inversion algorithms based on density measurements—or measurements correlated with strata density—to model strata formations up to about 200 ft into the formation from the wellbore.” [0059], “The force of gravity at the surface is measured at a location j … using the expression Fgi = G(mi × mj)/r2 were r is the distance between layer i and surface location j … It is well understood that mass=volume × density … Thus, each mass element occupying a volume may be used to calculate the effect at surface location j … ”. [0060], “In this fashion, a distance from the various density elements comprising each stratum layer may be calculated at the various surface positions … positions of the model layers and their thicknesses may be iteratively estimated by trading cells across bed boundaries in order to forward model the best Fgi match at the various locations along the surface.” Examiner note: the specification explains that the claimed inversion process generates and fits earth models using governing equations, solution curves and least-squares algorithms. The specification further explains that surface gravimetric data are used to extend the near-range models into the mid-range or far-range areas, and that the gravitational data are used by inversion algorithms to model strata formations and that such modeling employs mathematical calculations and mathematical relationships including Fgi = G(mi × mj)/r2, mass =volume x density, calculating the effect at surface location j, distance calculations and forward modeling to obtain the best Fgi match. Accordingly, under a broadest reasonable interpretation in light of the specification, the claimed deriving and generating operations are performed through mathematical relationships, mathematical calculations and mathematical modeling of geological formations. See MPEP 2106.04(a)(2)(I).
The elements of claim 12 is substantially the same as those of claim 1. Therefore, the elements of claim 12 is rejected due to the same reasons as outlined above for claim 1.
Therefore, claims 1 and 12 recite judicial exceptions. The claims have been identified to recite judicial exceptions, Step 2A Prong 2 will evaluate whether the claim as a whole integrates the exception into a practical application of that exception.
Step 2A Prong 2: Claims 1 and 12: The judicial exception is not integrated into a practical application.
In particular, the claims recite the following additional elements – “A system for drilling a wellbore into a subterranean earth formation comprising: a logging tool operable to measure formation data and locatable in the wellbore, wherein the logging tool comprises at least one near-range measurement sensor; and a processor and a non-transitory memory device in data communication with the logging tool, wherein the non-transitory memory device comprises instructions that, when executed by the processor, cause the processor to:" and “by a processor,” which are merely recitations of instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to implement the judicial exception with the broad reasonable interpretation in light of specification, which does not integrate judicial exception into a practical application (see MPEP § 2106.05(f)).
Further, the following additional element – “receive, from the at least one near-range measurement sensor, near-range wellbore measurement data at each of a plurality of depths along the wellbore; receive reference data related to a density measurement of the subterranean earth formation at each of the plurality of depths along the wellbore” and “receive a plurality of surface gravitational data, wherein each of the plurality of surface gravitational data is obtained at each of a plurality of surface locations proximate to the wellbore,” which are merely adding a recitation of insignificant extra-solution activities such as data gathering (i.e., receiving measurement data), which does not integrate a judicial exception into practical application (see MPEP 2106.05(g)).
Further, the following additional element – “provide the at least one of the mid-range formation model or the far-range formation model to a well driller, wherein the well driller uses the at least one of the mid-range formation model or the far-range formation model for geosteering a drill bit into the subterranean earth formation” and “geosteering, by the well driller, a drill bit into the subterranean earth formation based on the at least one of the mid-range formation model or the far-range formation model,” which are merely a recitation of insignificant extra-solution activity: Insignificant application (i.e., a well driller uses the generated range formation model when making a geosteering decision) which does not integrate a judicial exception into practical application (see MPEP § 2106.05(g)). See also In re Brown, 645 Fed. App'x 1014, 1016-1017 (Fed. Cir. 2016) (non-precedential).
Examiner note: these limitations merely use the result of the mathematical modeling as information for consideration by a well driller. In claim 1, the generated range formation model is merely provided to the well driller. In claim 12, the well driller merely geosteers a drill bit based on the generated range formation model. Thus, the claims merely present the result of the mathematical modeling to the well driller and recite subsequent use of that result by the well driller in making a drilling or geosteering decision. Such subsequent use of the generated model by the well driller, after the mathematical modeling has been performed, does not impose any meaningful limit on the abstract idea, and therefore amounts to insignificant extra-solution activity.
Therefore, "Do the claims recite additional elements that integrate the judicial exception into a practical application? No, these additional elements do not integrate the abstract idea into a practical application and they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
After having evaluated the inquires set forth in Steps 2A Prong 1 and 2, it has been concluded that claims 1 and 12 not only recite a judicial exception but that the claims are directed to the judicial exception as the judicial exception has not been integrated into practical application.
Step 2B: Claims 1 and 12: The claim does not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than generic computing components which do not amount to significantly more than the abstract idea. Limitations that the courts have found not to be enough to qualify as "significantly more" when recited in a claim with a judicial exception include: i. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)); ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)); iii. Adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) (see MPEP § 2106.05(g)); …
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, …; ii. Performing repetitive calculations, … iii. Electronic recordkeeping, … (updating an activity log). iv. Storing and retrieving information in memory,…
In particular, the logging tool, near-range measurement sensor, processor, non-transitory memory device, and wellbore drilling geosteering components are recited only at a generic functional level and are used in their ordinary capacities to obtain formation data, process/model data, and provide or use the resulting calculated formation model. The claims do not recite any unconventional arrangement of these components, any particular technical implementation, or any specific control technique for carrying out geosteering based on the generated range formation model. Rather, the combination merely places conventional data gathering, computer modeling, and drilling/geosteering components around the abstract mathematical modeling workflow. Therefore, the additional limitations, considered individually and in combination, do not amount to significantly more than the judicial exception.
Therefore, "Do the claims recite additional elements that amount to significantly more than the judicial exception? No, these additional elements, alone or in combination, do not amount to significantly more than the judicial exception. Having concluded analysis within the provided framework, claims 1 and 12 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Dependent claims 2-11 and 13-22 are also similar rejected under same rationale as cited above wherein these claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. These claims are merely further elaborate the mental process and/or mathematical concepts, or providing additional definition of process which does not impose any meaningful limits on practicing the abstract idea. Claims 2-11 and 13-22 are also rejected for incorporating the deficiency of their independent claims 1 and 12.
Claim 2 recites “The system of claim 1, wherein the at least one near-range measurement sensor comprises one or more of a wellbore acoustic sensor, a wellbore NMR sensor, a wellbore resistivity sensor, a wellbore gravimetric sensor, a pulse neutron sensor, a gamma ray source/gamma ray sensor, and a passive gamma detection sensor.”
The limitation further defines near-range measurement sensor for receive data recited in claim 1 by specifying it includes one or more different types of wellbore sensors; therefore, it merely adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to implement the judicial exception (see MPEP § 2106.05(f)), and alternatively, it merely an insignificant extra-solution activity such as data gathering (i.e., receiving measurement data by using different types of wellbore sensor), which does not integrate a judicial exception into practical application (see MPEP 2106.05(g)), with the broad reasonable interpretation in light of specification, which does not integrate judicial exception into a practical application. Therefore, the office finds that the claim 2 is ineligible under 35 USC 101.
Claim 3 recites “The system of claim 1, wherein the near-range wellbore measurement data comprise one or more of wellbore acoustic data, wellbore NMR data, wellbore resistivity data, neutron data, and gamma ray data.”
The limitation further defines near-range wellbore measurement data is received from the near-range measurement sensor recited in claim 1 by specifying it includes one or more particular types of wellbore data; therefore, it merely an insignificant extra-solution activity such as data gathering (i.e., receiving different types of measurement data) to the judicial exception (MPEP § 2106.05(g)), with the broad reasonable interpretation in light of specification, which does not integrate judicial exception into a practical application. Therefore, the office finds that the claim 3 is ineligible under 35 USC 101.
Claim 4 recites “The system of claim 1, wherein the reference data comprise data physically or directly indicative of the density of the subterranean earth formation at each of the plurality of depths along the wellbore.”
The limitation further defines reference data is received recited in claim 1 by specifying it physically or directly indicative of the density of the subterranean earth formation at each of the plurality of depths along the wellbore; therefore, it merely an insignificant extra-solution activity such as data gathering (i.e., receiving reference data physically or directly indicative of density at different depth) to the judicial exception (MPEP § 2106.05(g)), with the broad reasonable interpretation in light of specification, which does not integrate judicial exception into a practical application. Therefore, the office finds that the claim 4 is ineligible under 35 USC 101.
Claim 5 recites “The system of claim 4, wherein the reference data comprise one or more of a bulk density measurement of the subterranean earth formation, gamma ray source/gamma ray data, neutron density data, acoustic density data, photometric data, core sample data, cutting sample data, a formation fluid data, and down well composition data.”
The limitation further defines reference data is received recited in claims 1 and 4 by specifying it includes one or more particular types of data; therefore, it merely an insignificant extra-solution activity such as data gathering (i.e., receiving different types of reference data) to the judicial exception (MPEP § 2106.05(g)), with the broad reasonable interpretation in light of specification, which does not integrate judicial exception into a practical application. Therefore, the office finds that the claim 5 is ineligible under 35 USC 101.
Claim 6 recites “The system of claim 1, wherein the plurality of surface gravitational data are obtained from a plurality of surface gravity sensors, wherein each of the plurality of surface gravity sensors is located at each of the plurality of surface locations proximate to the wellbore.”
The limitation specifies surface gravitational data is received from gravity sensors, and the surface gravity sensors is located at each of the plurality of surface locations proximate to the wellbore; therefore, it merely adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to implement the judicial exception (see MPEP § 2106.05(f)) and merely an insignificant extra-solution data gathering (i.e., obtaining gravitational data) activity to the judicial exception (MPEP § 2106.05(g)), with the broad reasonable interpretation in light of specification, which does not integrate judicial exception into a practical application. Therefore, the office finds that the claim 6 is ineligible under 35 USC 101.
Claim 7 recites “The system of claim 1, wherein the plurality of surface gravitational data are obtained from at least one surface gravity sensor located sequentially at each of the plurality of surface locations proximate to the wellbore.”
The limitation specifies surface gravitational data is received from gravity sensors, and the surface gravity sensors is located sequentially at each of the plurality of surface locations proximate to the wellbore; therefore, it merely adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to implement the judicial exception (see MPEP § 2106.05(f)) and merely an insignificant extra-solution activity such as data gathering (i.e., obtaining gravitational data) to the judicial exception (MPEP § 2106.05(g)), with the broad reasonable interpretation in light of specification, which does not integrate judicial exception into a practical application. Therefore, the office finds that the claim 7 is ineligible under 35 USC 101.
Claim 8 recites “The system of claim 1, wherein the plurality of surface gravitational data are obtained from one or more quantum gravity sensors.”
The limitation specifies reference data are obtained from one or more quantum gravity sensors; therefore, it merely an insignificant extra-solution data activity such as data gathering (i.e., obtaining gravitational data by using quantum gravity sensors) to the judicial exception (MPEP § 2106.05(g)), with the broad reasonable interpretation in light of specification, which does not integrate judicial exception into a practical application. Therefore, the office finds that the claim 8 is ineligible under 35 USC 101.
Claim 9 recites “The system of claim 1, wherein the non-transitory memory device comprises instructions that, when executed by the processor, further cause the processor to correlate the at least one of the mid-range formation model or the far-range formation model at a first of the plurality of depths along the wellbore with the at least one of the mid-range formation model or the far-range formation model at a second of the plurality of depths along the wellbore, to determine one or more layer density inhomogeneities within one or more layers of the at least one of the mid-range formation model or the far-range formation model.”
The limitation specifies range formation model at different depths along the wellbore, and layer density inhomogeneities is determined or estimated; therefore, it merely recites mental process (e.g., observing formation data from two depths, compare differences in density values, and identify areas showing uneven density distribution between layers) and merely recitations of instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to implement the judicial exception (see MPEP § 2106.05(f)), which does not integrate judicial exception into a practical application. Therefore, the office finds that the claim 9 is ineligible under 35 USC 101.
Claim 10 recites “The system of claim 1, wherein the non-transitory memory device comprises instructions that, when executed by the processor, further cause the processor to constrain, the at least one of the mid-range formation model or the far-range formation model at each of the plurality of depths along the wellbore based on survey data.”
The limitation specifies range formation model is determined/constrained based on survey data as input; therefore, it merely an insignificant extra-solution activity such as data gathering (i.e., provide survey data is used for constraining or refining the previously recited mathematical formation model) to the judicial exception (MPEP § 2106.05(g)), with the broad reasonable interpretation in light of specification, which does not integrate judicial exception into a practical application. Therefore, the office finds that the claim 10 is ineligible under 35 USC 101.
Claim 11 recites “The system of claim 1, wherein the non-transitory memory device comprises instructions that, when executed by the processor, further cause the processor to direct one or more of a depth or an orientation of the drill bit into the subterranean earth formation”
The limitation specifies that the processor executes instructions to direct one or more of a depth or an orientation of the drill bit into the subterranean earth formation; therefore, it merely recitations of instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to implement the judicial exception (see MPEP § 2106.05(f)), which does not integrate judicial exception into a practical application. Therefore, the office finds that the claim 11 is ineligible under 35 USC 101. Examiner note: although claim 11 recites directing a depth or orientation of the drill bit, the claim does not recite any particular technological manner for directing the drill bit, any specific control algorithm, any particular drilling parameter that is modified, or any specific interaction between he processor and the drilling equipment. Rather, the limitation broadly recites using the processor to direct the drill bit based on the results of the previously recited mathematical modeling. Accordingly, the limitation merely applies the results of the mathematical modeling in a generic drilling context, does not integrate the judicial exception into a practical application, and does not amount to significantly more than judicial exception.
Claims 13-20 and 22 recite the similar elements as claims 3-11, and are rejected for the same reasons under 35 U.S.C. 101. Examiner note: for reasons similar to those discussed above with respect to claim 11, although claim 22 recites geosteering a drill bit by the processor based on the generated range formation model, the limitation still does not recite how the generated model is converted into a drilling command, what control logic is applied, what drilling parameter is adjusted, or what actuator operation is performed. Thus, claim 22 merely makes that the generated model is used as the basis for geosteering, but it still applies the result of the mathematical modeling, and recited at a high level of generality. Accordingly, claim 22 does not integrate the judicial exception into a practical application, and does not amounts to significantly more than judicial exception.
Claim 21 recites “The method of claim 20, wherein constraining the at least one of the mid-range formation model or the far-range formation model based on survey data comprises constraining the at least one of the mid-range formation model or the far-range formation model based on one or more of geological survey data, acoustic survey data, or magnetic survey data.”
The limitation further defines range formation model is constrained based on survey data as input recited in claim 20, and the survey data includes one or more different type of survey data; therefore, it merely an insignificant extra-solution activity such as data gathering (i.e., provide additional different type of survey data for constraining or refining the previously recited mathematical formation model) to the judicial exception (MPEP § 2106.05(g)), with the broad reasonable interpretation in light of specification, which does not integrate judicial exception into a practical application. Therefore, the office finds that the claim 21 is ineligible under 35 USC 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and
103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set
forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103
are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-6, 10-16 and 20-22 are rejected under 35 U.S.C. 103 as being unpatentable over
Bartetzko US20200333495A1 in view of Shetty US20180136362A1 and Wang US20200371268A1 and Priezzhev US20120232871A1.
Claim 1, Bartetzko teaches A system for drilling a wellbore into a subterranean earth formation (Abstract; [0022], “Referring to FIG. 1, an exemplary embodiment of a drilling and monitoring system 10 is shown. A drill string 14 is disposed in a borehole 12, which penetrates at least one earth formation 16, which may include one or more stratigraphic layers 18.”) comprising:
a logging tool operable to measure formation data and locatable in the wellbore, wherein the logging tool comprises at least one near-range measurement sensor ([0025], “Data and information regarding the formation 16 and/or stratigraphic layers 18 can be acquired by various measurement devices that may be included in the drilling assembly 20 and/or drill string 14, such as a downhole measurement tool 27 (e.g., a LWD tool). Exemplary devices include pulsed neutron tools, gamma ray measurement tools, neutron tools, resistivity tools, acoustic tools, nuclear magnetic resonance tools, density measurement tools, seismic data acquisition tools, acoustic impedance tools, formation pressure testing tools, fluid sampling and analysis tools, coring tools and/or any other type of sensor or device capable of providing information that can be used to identify or estimate formation features.” ); and
a processor and a non-transitory memory device in data communication with the logging tool, wherein the non-transitory memory device comprises instructions that, when executed by the processor ([0028], “The surface processing unit 28 is configured to receive, store and/or transmit data and signals, and includes processing components configured to analyze data and/or control operational parameters. In one embodiment, the surface processing unit 28 is configured to control the drilling assembly 20 and receive data from the measurement tool 27 and any other downhole and/or surface sensors. Operational parameters may be controlled or adjusted automatically by the surface processing unit 28 in response to sensor data, or controlled by a human driller or remote processing device. The surface processing unit 28 includes any number of suitable components, such as processors, memory, communication devices and power sources. For example, the surface processing unit 28 may include a processor 30 (e.g., a microprocessor), and a memory 32 storing software 34. In addition or as an alternative to surface processors, processing capability may be located downhole, for example, as downhole electronics 36, which may perform all or some of the functions described in conjunction with the surface processing unit 28.”), cause the processor to:
receive, from the at least one near-range measurement sensor, near-range wellbore measurement data at each of a plurality of depths along the wellbore ([0025], “… a downhole measurement tool 27 (e.g., a LWD tool). Exemplary devices include pulsed neutron tools, gamma ray measurement tools, neutron tools, resistivity tools, acoustic tools, nuclear magnetic resonance tools, density measurement tools, seismic data acquisition tools, acoustic impedance tools, formation pressure testing tools, fluid sampling and analysis tools, coring tools and/or any other type of sensor …” [0028], “… the surface processing unit 28 is configured to control the drilling assembly 20 and receive data from the measurement tool 27 and any other downhole and/or surface sensors …” Fig.10; [0074], “During drilling, a target well log 130 is monitored and a relative change log 132 and absolute change log 134 are calculated as measurement data is received. Similar changes or fingerprints and their corresponding depths are noted as A′, B′ and C′. The fingerprints from the reference and target logs are compared and depth shifts are calculated.”);
receive reference data related to a density measurement of the subterranean earth formation at each of the plurality of depths along the wellbore (Fig.9 and Fig.10 show different depth of reference data; [0041], “Reference data includes various types of data and information acquired from the one or more reference boreholes. Exemplary reference data discussed herein includes well logs such as gamma ray logs taken from a reference borehole. However, any suitable data or information that reflects changes in lithology or stratigraphy may be used. Examples of suitable data include well logs, such as resistivity, acoustic compressional or shear slowness, formation density, magnetic resonance, pulsed neutron, gamma ray, spontaneous potential, and neutron porosity logs, or a combination thereof.”);
provide the at least one of the ([0078], “A user or operator may thus utilize embodiments described herein to make proactive decisions during an operation, e.g., decisions regarding drilling parameters, completion equipment, downhole components, mud properties, and/or steering a well.” [0076], “… The comparison between the predicted and the monitored acoustic impedance can be used to update a seismic model during the drilling operation. This is extremely useful, for example, for landing a borehole during a reservoir navigation operation.” [0052], “the processor transmits and/or displays the predicted features and their corresponding depths or times (e.g., as an alert or alarm, or as a report) to allow an operator or user to adjust operational parameters …, weight on bit and/or rotational speed. Other changes may include changes in equipment, such as changing the drill bit or drill string components. In another embodiment, actions include making changes to reservoir navigation operations, e.g., by steering a drilling assembly to change the path of the borehole and/or updating the planning for landing of the well. Another action that may be performed is updating a stratigraphic model of the formation to correct the depth(s) of formation layers.).
However, Bartetzko fails to teach derive, for each of the plurality of depths along the wellbore, one or more near-range earth models of the subterranean earth formation each comprising a density model of a layer at a respective depth by inversion of the near-range wellbore measurement data constrained by the reference data, wherein each of the one or more near-range earth models comprises a density model of a layer of the subterranean earth formation.
Shetty teaches derive, for each of the plurality of depths along the wellbore, one or more near-range earth models of the subterranean earth formation each comprising a density model of a layer at a respective depth by inversion of the near-range wellbore measurement data constrained by the reference data, wherein each of the one or more near-range earth models comprises a density model of a layer of the subterranean earth formation ([0006], “… performing an inversion using apparent densities and volumetric photoelectric factor images to build a formation model …”. [0052], “This inversion is capable of processing density images in HA as well as HZ wells, solving for a 1D layered formation model …”. [0056], “defining the models in discrete trajectory segments … The result of the inversion is the accurate layer thicknesses, … layer densities, … in each segment.” [0064], “The density measurement is resolved into 16 azimuthal sectors each spanning 22.5°. The radial sensitivity extends radially approximately 6 inches into the formation …”. [0074], “… the trajectory can be discretized into segments such that the formation in each segment is 1D layering …”. [0075], “The free parameters for the segment are … each layer boundary, layer densities … and layer photoelectric factors …”. [0094], “The output from log-squaring and sinusoid extraction is used to define the number of layers, their properties and boundaries …”. [0096], “Gauss-Newton optimization with line search, adaptive regularization and parameter constraints is used to minimize the cost function …”. [0103], “The properties and thicknesses of the layers included from the previous segment are held fixed during the inversion.” Examiner note: the reference teaches near-wellbore nuclear density measurements having radial sensitivity extending into the formation, and it performs inversion using apparent density and volumetric photoelectric factor image data to build a formation model. The disclosed inversion solves for a 1D layered formation model in discrete trajectory segments along the wellbore, where the model includes layer boundaries, layer thicknesses, and layer densities in each segment. The reference further teaches that the inversion is guided or constrained by previously determined density related layer information because the initial model is defined from log-squaring and sinusoid extraction, the optimization uses parameter constraints and layer properties and thicknesses from adjacent segments may be held fixed during the inversion. Thus, the reference teaches deriving near-range earth models comprising density models of layers at respective depths by inversion of near-range wellbore measurement data constrained by density related reference or prior model information).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bartetzko to incorporate the teachings of Shetty, and apply inversion of density measurement data to build a layered formation model having layer densities and layer thicknesses, wherein the inversion is guided by previously determined layer information and model parameters, in order to improve characterization of formation layers from wellbore measurement data. In this case, Bartetzko teaches receiving wellbore measurement data and reference density data related to density measurements of a subterranean formation for formation characterization. Shetty teaches performing inversion of density measurement data to solve for a layered formation model having layer densities and layer thicknesses in discrete trajectory segments, and further teaches using previously determined layer information to define the inversion model and constrain the inversion process. The combination of teachings would predictably provide the benefit of deriving a more accurate density representation of formation layers from measured wellbore data.
However, Bartetzko and Shetty fail to teach receive a plurality of surface gravitational data, wherein each of the plurality of surface gravitational data is obtained at each of a plurality of surface locations proximate to the wellbore.
Wang teaches receive a plurality of surface gravitational data, wherein each of the plurality of surface gravitational data is obtained at each of a plurality of surface locations proximate to the wellbore ([0008], “obtaining a Bouguer gravity anomaly in a target region, wherein the Bouguer gravity anomaly comprises coordinates and field values of a plurality of sampling points in the target region; [0009], “determining a first pre-set range corresponding to each sampling point in the target region;” [0010], “obtaining a first regional field value of sampling points within the first pre-set range corresponding to each sampling point using a surface fitting method based on coordinates and field values of the sampling points;” [0096], “The Bouguer gravity anomaly comprises coordinates and field values of a plurality of sampling points in the target region.” – Examiner note: obtaining Bouguer gravity anomalies data that include field values of a plurality of sampling points in the targe region, and each sampling point corresponds to a distinct surface location, and a first regional field value is obtained for each point based on coordinates and field values are collected at a plurality of surface sampling points within the target region. A POSITA would understand that “sampling points” are physical surface observation stations distributed around a borehole or target region for subsurface modeling and anomaly prediction).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bartetzko and Shetty to incorporate the teachings of Wang, and apply surface gravitational data obtained from a plurality of surface3 sampling locations in order to improve subsurface formation characterization using additional geophysical information from a broader area surrounding the wellbore. In this case, Bartetzko teaches receiving wellbore measurement data and reference density data related to density measurements of a subterranean formation for formation characterization. Shetty teaches performing inversion of density measurement data to solve for a layered formation model having layer densities and layer thicknesses in discrete trajectory segments, and further teaches using previously determined layer information to define the inversion model and constrain the inversion process. Wang teaches obtaining Bouguer gravity anomaly data comprising gravity field values collected at a plurality of surface sampling locations in a target region. The combination of teachings would predictably provide the benefit of incorporating surface gravity measurements with wellbore derived formation information to improve formation characterization, increase model reliability, and provide additional geological information for subsurface modeling and drilling decisions.
However, Bartetzko and Shetty and Wang fail to teach generate at least one of a mid-range formation model or a far-range formation model at each of the plurality of depths along the wellbore using the one or more near-range earth models and the plurality of surface gravitational data, and provide the at least one of the mid-range formation model or the far-range formation model for further operation.
Priezzhev teaches generate at least one of a mid-range formation model or a far-range formation model at each of the plurality of depths along the wellbore using the one or more near-range earth models and the plurality of surface gravitational data and provide the at least one of the mid-range formation model or the far-range formation model for further operation ([0065], “…, shown at 12 is generating a three-dimensional (3-D) forward model in the wavenumber domain of a physical parameter having a potential field from a model of spatial distribution of the physical property. During this step, a volume (e.g., a cube) with the modeled physical parameter having a potential field will be created … If wellbores are specified within the modeled volume, then the potential field (e.g., gravity potential field) will be interpolated to include the data from any such wellbore …” – Examiner note: Priezzhev teaches generating 3D volumetric model (i.e., a formation model) in the wavenumber domain for a subsurface volume, and further teaches that, when wellbores are specified within the modeled volume, the gravity potential field is interpolated to include wellbore data. Thus, Priezzhev teaches generating a broader subsurface model that incorporates wellbore-related data within the modeled volume. [0069], “… shown at 20 is generating by inversion in the wavenumber domain a revised model of spatial distribution of the physical property (e.g., density) 32 from the revised model of spatial distribution of the potential field (e.g., gravity) 28.” – Examiner note: Priezzhev teaches generating, by inversion in the wavenumber domain, a revised model of spatial distribution of a physical property, such as density, from a revised gravity potential field model. Thus, Priezzhev teaches generating a revised density based formation model from gravity field modeling. [0072], “…, measured gravity data may be used in the present method. Gravity data may be obtained, for example, using a gravity sensor similar to the LaCoste and Romberg sensor shown schematically in FIG. 2. Such a sensor may be deployed proximate the Earth's surface at selected locations …” [0073], “A gravity sensor may also be deployed in any wellbore …”. – Examiner note: Priezzhev teaches obtaining measured gravity data using a gravity sensor deployed proximate the Earth’s surface at selected locations, which corresponds to obtaining surface gravitation data. [0095], “… interpretation of borehole gravity measurements in conjunction with surface gravity measurements. The fast Fourier transform permits applying this method to models with very large dimensions (tens of millions of cells). Sparse borehole gravity data can be interpolated to the entire volume of the subsurface being modeled, while taking into account surface gravity data. The result of this interpolation will determine the solution of the inversion problem, and it is this interpolation step along with the constraints provided by the initial density distribution that ensures a unique solution. A manageable solution to the inverse problem requires well controlled and powerful software such as PETREL software to interpolate the gravitational field from the borehole and surface data over the entire area of investigation.” - Examiner note: Priezzhev teaches interpreting borehole gravity measurements in conjunction with surface gravity measurements, and interpolating the gravitational field from borehole and surface data over the entire are of investigation. Thus, Priezzhev teaches using borehole related information together with surface gravitational data to generate an integrated volumetric subsurface model extending across a broader subsurface region. [0096], “When using gravity field data for geological interpretation one may use as much a priori information as is available to build the initial density model, such as borehole log data, the results of seismic data inversion, and geological and structural models. By finding a forward modeling solution maximum close to the initial model one can have high confidence that the solution is unique.” Examiner note: Priezzhev teaches using available a priori information, including borehole log data, seismic inversion results, and geological and structural models, to build the initial density model for gravity filed interpretation. Thus Priezzhev teaches using borehole derived formation information with gravity field data to generate a density based subsurface model. Collectively, Priezzhev teaches generating a larger density based subsurface formation model using borehole derived formation information and surface gravity measurement. Under BRI, the borehole derived formation information corresponds to the one or more near-range earth models, and the larger volumetric density based subsurface model corresponds to the mid-range or far-range formation model. Priezzhev further teaches that the generated model is used for geological interpretation of the subsurface, thereby, providing the generated model for further subsurface analysis or operation.).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bartetzko and Shetty and Wang to incorporate the teachings of Priezzhev, and apply generating a volumetric subsurface formation model using borehole derived formation information and surface gravitational data, refined through forward modeling and inversion, in order to generate a broader scale subsurface formation model for geological interpretation and operational planning. In this case, Bartetzko teaches receiving wellbore measurement data and reference density data related to density measurements of a subterranean formation for formation characterization. Shetty teaches performing inversion of density measurement data to solve for a layered formation model having layer densities and layer thicknesses in discrete trajectory segments, and further teaches using previously determined layer information to define the inversion model and constrain the inversion process. Wang teaches obtaining Bouguer gravity anomaly data comprising gravity field values collected at a plurality of surface sampling locations in a target region. Priezzhev teaches integrating borehole derived information and surface gravity measurements through forward modeling and inversion to generate a volumetric subsurface formation model extending across a broader subsurface region. The combination of teachings would predictably provide the benefit of generating a unified multi-scale subsurface formation model that integrates near-range formation information with surface gravitational measurements, thereby improving subsurface characterization geological interoperation, well placement planning, and drilling decision-making.
Claim 2, Bartetzko further teaches The system of claim 1, wherein the at least one near-range measurement sensor comprises one or more of a wellbore acoustic sensor, a wellbore NMR sensor, a wellbore resistivity sensor, a wellbore gravimetric sensor, a pulse neutron sensor, a gamma ray source/gamma ray sensor, and a passive gamma detection sensor ([0025], “Data and information regarding the formation 16 and/or stratigraphic layers 18 can be acquired by various measurement devices that may be included in the drilling assembly 20 and/or drill string 14, such as a downhole measurement tool 27 (e.g., a LWD tool). Exemplary devices include pulsed neutron tools, gamma ray measurement tools, neutron tools, resistivity tools, acoustic tools, nuclear magnetic resonance tools, density measurement tools, seismic data acquisition tools, acoustic impedance tools, formation pressure testing tools, fluid sampling and analysis tools, coring tools and/or any other type of sensor or device capable of providing information that can be used to identify or estimate formation features.”).
Claim 3, Bartetzko further teaches The system of claim 1, wherein the near-range wellbore measurement data comprise one or more of wellbore acoustic data, wellbore NMR data, wellbore resistivity data, neutron data, and gamma ray data ([0025], “Data and information regarding the formation 16 and/or stratigraphic layers 18 can be acquired by various measurement devices that may be included in the drilling assembly 20 and/or drill string 14, such as a downhole measurement tool 27 (e.g., a LWD tool). Exemplary devices include pulsed neutron tools, gamma ray measurement tools, neutron tools, resistivity tools, acoustic tools, nuclear magnetic resonance tools, density measurement tools, seismic data acquisition tools, acoustic impedance tools, formation pressure testing tools, fluid sampling and analysis tools, coring tools and/or any other type of sensor or device capable of providing information that can be used to identify or estimate formation features.”).
Claim 4, Bartetzko further teaches The system of claim 1, wherein the reference data comprise data physically or directly indicative of the density of the subterranean earth formation at each of the plurality of depths along the wellbore ([0041], “Reference data includes various types of data and information acquired from the one or more reference boreholes. Exemplary reference data discussed herein includes well logs such as gamma ray logs taken from a reference borehole. However, any suitable data or information that reflects changes in lithology or stratigraphy may be used. Examples of suitable data include well logs, such as resistivity, acoustic compressional or shear slowness, formation density, magnetic resonance, pulsed neutron, gamma ray, spontaneous potential, and neutron porosity logs, or a combination thereof.”).
Claim 5, Bartetzko further teaches The system of claim 4, wherein the reference data comprise one or more of a bulk density measurement of the subterranean earth formation, gamma ray source/gamma ray data, neutron density data, acoustic density data, photometric data, core sample data, cutting sample data, a formation fluid data, and down well composition data ([0041], “Reference data includes various types of data and information acquired from the one or more reference boreholes. Exemplary reference data discussed herein includes well logs such as gamma ray logs taken from a reference borehole. However, any suitable data or information that reflects changes in lithology or stratigraphy may be used. Examples of suitable data include well logs, such as resistivity, acoustic compressional or shear slowness, formation density, magnetic resonance, pulsed neutron, gamma ray, spontaneous potential, and neutron porosity logs, or a combination thereof.”).
Claim 6, Bartetzko and Shetty fail to teach, but Wang teaches The system of claim 1, wherein the plurality of surface gravitational data are obtained from a plurality of surface gravity sensors, wherein each of the plurality of surface gravity sensors is located at each of the plurality of surface locations proximate to the wellbore ([0008], “obtaining a Bouguer gravity anomaly in a target region, wherein the Bouguer gravity anomaly comprises coordinates and field values of a plurality of sampling points in the target region;” [0010], “obtaining a first regional field value of sampling points within the first pre-set range corresponding to each sampling point using a surface fitting method based on coordinates and field values of the sampling points.” Examiner note: A POSITA would understand that the Bouguer gravity measurements are taken from a plurality of surface gravity sensors positioned at a plurality of surface locations proximate to the target wellbore).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bartetzko and Shetty to incorporate the teachings of Wang, and apply obtaining a first regional field value of sampling points within the first pre-set range corresponding to each sampling point using a surface fitting method based on coordinates and field values of the sampling points in order to determine and calibrate surface gravitation data collected from multiple surface gravity sensors positioned at different sampling locations proximate to the wellbore.
However, Bartetzko and Shetty and Wang fail to teaches obtaining gravitation data from gravity sensor.
Priezzhev teaches obtaining gravitation data from gravity sensor ([0072], “…, measured gravity data may be used in the present method. Gravity data may be obtained, for example, using a gravity sensor similar to the LaCoste and Romberg sensor shown schematically in FIG. 2. Such a sensor may be deployed proximate the Earth's surface at selected locations …”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bartetzko and Shetty and Wang to incorporate the teachings of Priezzhev, and apply gravity sensor to measure gravity data and deploy proximate Earth's surface at selected locations in order to improve the accuracy and density of surface gravitational measurements collected for subsurface modeling and anomaly detection.
Claim 10, Bartetzko and Shetty and Wang fail to teach, but Priezzhev teaches The system of claim 1, wherein the non-transitory memory device comprises instructions that, when executed by the processor, further cause the processor to constrain, the at least one of the mid-range formation model or the far-range formation model at each of the plurality of depths along the wellbore based on survey data ([0069], “…, shown at 20 is generating by inversion in the wavenumber domain a revised model of spatial distribution of the physical property (e.g., density) 32 from the revised model of spatial distribution of the potential field (e.g., gravity) 28.” – Examiner note: the inversion process constrains the formation model (density distribution) using survey-derived potential field (gravity) data, as the model is refined based on measured gravitational field information. [0072], “…, measured gravity data may be used in the present method. Gravity data may be obtained, for example, using a gravity sensor similar to the LaCoste and Romberg sensor shown schematically in FIG. 2. Such a sensor may be deployed proximate the Earth's surface at selected locations …” – Examiner note: the reference shows that gravity survey data acquired at surface locations are used to constrain and update the modeled gravitational field distribution. [0095], “… interpretation of borehole gravity measurements in conjunction with surface gravity measurements. The fast Fourier transform permits applying this method to models with very large dimensions (tens of millions of cells). Sparse borehole gravity data can be interpolated to the entire volume of the subsurface being modeled, while taking into account surface gravity data.” – Examiner note: the reference shows that survey-based gravity data from both borehole and surface measurements are integrated and interpolated to constrain the model solution during inversion, updating or limiting the mid-range or far-range formation model based on survey-derived gravity field data).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bartetzko and Shetty and Wang to incorporate the teachings of Priezzhev, and apply constrain, the at least one of the mid-range formation model or the far-range formation model at each of the plurality of depths along the wellbore based on survey data in order to refine and calibrate the predicted subsurface model using real world gravitational measurements obtained from both surface and borehole surveys.
Claim 11, Bartetzko further teaches The system of claim 1, wherein the non-transitory memory device comprises instructions that, when executed by the processor, further cause the processor to direct one or more of a depth or an orientation of the drill bit into the subterranean earth formation ([0053], “the processor automatically changes operational parameters at the appropriate time to react to the feature of interest. The alert and automatic adjustments may be performed in the alternative or together.” [0026], “Operational parameters may be controlled or adjusted automatically by the surface processing unit 28 in response to sensor data,…” [0035], “Knowing in time that this particular formation is being approached allows for adjustment and optimization of the completion scheme, mud type, and/or the navigation path of a drilling assembly.” [0069], “… the processor may send updates or alerts to a user regarding predicted features of interest, and/or perform automatic adjustments to the drilling operation is response to the predictions.”).
Claim 21, Bartetzko and Shetty and Wang fail to teach, but Priezzhev teaches The method of claim 20, wherein constraining the at least one of the mid-range formation model or the far-range formation model based on survey data comprises constraining the at least one of the mid-range formation model or the far-range formation model based on one or more of geological survey data, acoustic survey data, or magnetic survey data ([0096], “When using gravity field data for geological interpretation one may use as much a priori information as is available to build the initial density model, such as borehole log data, the results of seismic data inversion, and geological and structural models.” [0036], “One of the most widely used correlation curves used in the joint interpretation of seismic and gravity data was established by Gardner et al. … The investigators conducted a series of studies to determine an empirical relationship between the rock density and compressional wave velocity, …” – Examiner note: the model is constrained using seismic (acoustic) survey data within joint inversion).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bartetzko and Shetty and Wang to incorporate the teachings of Priezzhev, and apply constrain, the at least one of the mid-range formation model or the far-range formation model at each of the plurality of depths along the wellbore based on survey data in order to refine and calibrate the predicted subsurface model using real world gravitational measurements obtained from both surface and borehole surveys.
The elements of claims 12-16, 20 and 22 are substantially the same as those of claims 1, 3-6 and 10-11. Therefore, the elements of claims 12-16, 20 and 22 are rejected due to the same reasons as outlined above for claims 1, 3-6 and 10-11.
Claim(s) 7-8 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over
Bartetzko and Shetty and Wang and Priezzhev as applied to claims 1 and 12 above, and further in view of Wu (“Gravity surveys using a mobile atom interferometer,” published in 2019).
Claim 7, Bartetzko and Shetty and Wang and Priezzhev fail to teach, but Wu teaches The system of claim 1, wherein the plurality of surface gravitational data are obtained from at least one surface gravity sensor located sequentially at each of the plurality of surface locations proximate to the wellbore (page.4, Gravity survey in Berkeley Hills, “… We operated the atomic gravimeter inside a vehicle using passive vibration isolation and measured gravity at six locations. At each location, it took about 15 min to set up the gravimeter, including powering up the instrument and aligning the interferometer beam to the gravity axis ...” Examiner note: Wu teaches operating a mobile atomic gravimeter and obtaining gravity measurements at six different field locations. Because the same gravimeter is transported between measurement locations and configured at each location before acquiring gravity data, A POSITA would understand that the atomic gravimeter (i.e., gravity sensor) can be located sequentially at each of the plurality of surface locations proximate to the wellbore”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bartetzko and Miles and Wang and Priezzhev to incorporate the teachings of Wu, and apply mobile atomic gravimeter for acquiring surface gravitational data at multiple surface survey locations in order to improve the accuracy and reliability of surface gravity measurements used for subsurface formation characterization. In this case, Bartetzko teaches receiving wellbore measurement data and reference density data related to density measurements of a subterranean formation for formation characterization. Shetty teaches performing inversion of density measurement data to solve for a layered formation model having layer densities and layer thicknesses in discrete trajectory segments, and further teaches using previously determined layer information to define the inversion model and constrain the inversion process. Wang teaches obtaining Bouguer gravity anomaly data comprising gravity field values collected at a plurality of surface sampling locations in a target region. Priezzhev teaches integrating borehole derived information and surface gravity measurements through forward modeling and inversion to generate a volumetric subsurface formation model extending across a broader subsurface region. Wu teaches operating a mobile atomic gravimeter in a vehicle to measure gravity at multipole field locations, wherein the gravimeter is set up at each location before acquiring gravity data. The combination of teachings would predictably provide the benefit of acquiring surface gravitational data at multiple surface locations using a mobile gravity sensor having improved accuracy and reliability for use in the integrated subsurface formation model workflow.
Claim 8, Bartetzko and Shetty and Wang and Priezzhev fail to teach, but Wu teaches The system of claim 1, wherein the plurality of surface gravitational data are obtained from one or more quantum gravity sensors (Page.4, Gravity survey in Berkeley Hills, “To demonstrate the use of the atomic gravimeter (examiner note: i.e., one type of quantum gravity sensors) in the field, we measured absolute gravity in the Berkeley Hills.”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bartetzko and Shetty and Wang and Priezzhev to incorporate the teachings of Wu, and apply a mobile atomic gravimeter as a quantum gravity sensor for obtaining surface gravitational data in order to measure absolute gravity using light-pulse atom interferometry, which exploits quantum interference of atomic matter wave to achieve more accurate and reliable surface gravitational data for detecting subsurface formation.
The elements of claims 17-18 are substantially the same as those of claims 7-8 . Therefore, the elements of claims 17-18 are rejected due to the same reasons as outlined above for claims 7-8.
Claim(s) 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over
Bartetzko and Shetty and Wang and Priezzhev as applied to claims 1 and 12 above, and further in view of Xu (“Multilayer densities using a wavelet-based gravity method and their tectonic implications beneath the Tibetan Plateau,” published in 2018).
Claim 9, Bartetzko and Shetty and Wang fail to teach, but Priezzhev teaches The system of claim 1, wherein the non-transitory memory device comprises instructions that, when executed by the processor, further cause the processor to correlate the at least one of the mid-range formation model or the far-range formation model at a first of the plurality of depths along the wellbore with the at least one of the mid-range formation model or the far-range formation model at a second of the plurality of depths along the wellbore, to determine one or more layer density inhomogeneities within one or more layers of the at least one of the mid-range formation model or the far-range formation model ([0065], “…, shown at 12 is generating a three-dimensional (3-D) forward model in the wavenumber domain of a physical parameter having a potential field from a model of spatial distribution of the physical property …” [0069], “… shown at 20 is generating by inversion in the wavenumber domain a revised model of spatial distribution of the physical property (e.g., density) 32 from the revised model of spatial distribution of the potential field (e.g., gravity) 28 …” [0095], “The model calculations according to the present invention demonstrate the use of the proposed method for interpretation of borehole gravity measurements … Sparse borehole gravity data can be interpolated to the entire volume of the subsurface being modeled, while taking into account surface gravity data. The result of this interpolation will determine the solution of the inversion problem, and it is this interpolation step along with the constraints provided by the initial density distribution that ensures a unique solution.” Examiner note: Priezzhev teaches generating a broader volumetric density based subsurface formation model using borehole gravity data and surface gravity data. Thus, Priezzhev teaches the underlying mid-range or far-range formation model).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bartetzko and Shetty and Wang to incorporate the teachings of Priezzhev, and apply generating a three-dimensional (3-D) forward model and inversion refinement using borehole derived information and surface gravity data in order to generate a broader volumetric formation model for improved subsurface representation. The combination of teachings would predictably provide the benefit of generating a broader subsurface formation model that integrates borehole derived information withy surface gravity measurement.
However, Bartetzko and Shetty and Wang and Priezzhev fail to teach correlation between models at two different depths and determining layer density inhomogeneities within a layer of the model.
Xu teaches correlation between models at two different depths (Page.2087, above 3 Method, “To reveal refined subsurface density structure at different depths, the Bouguer gravity anomalies should be decomposed further.” Page.2087 -2088, 3 Method, “In this study, the complete Bouguer gravity anomalies Δg (ϕ, λ) on the geoid (spherical approximation is assumed and the undulation of the geoid is neglected in this paper) are decomposed into wavelet approximation AS(ϕ, λ) and wavelet details Ds(ϕ, λ) using wavelet multiscale analysis … According to the solution to 2-D Laplace’s equation … can be obtained.” Page.2090, 4.2 Multilayer densities from decomposed gravity anomalies, “Based on the decomposed gravity anomalies … the crust and upper mantle of the TP are divided into S = 6 layers (see Table 2). The thicknesses rs (s = 1,2,··· ,6) of the six layers … Subsequently, each layer is … Lastly, multilayer densities ρs (s = 1,2,··· ,6) … are determined by eq. (17). Page.2093, 6 CONCLUSIONS, “… There are strong correlations between the decomposed gravity anomalies and the tectonic features at different depths in the crust and upper mantle.”) and determining one or more layer density inhomogeneities within one or more layers of the model (Page. 2090, last paragraph, “… Densities of Layer 1 and Layer 2 (see Figs 5a and b) primarily reflect material distributions of 0–6 km depth and 6–10 km depth in the upper crust, respectively. Densities of these two layers range from 2.52 to 2.67 g cm−3, indicating strong lateral density inhomogeneity existing in the upper crust (Yang et al. 2015) ...” Page 2093, last paragraph, “There are strong correlations between the decomposed gravity anomalies and the tectonic features at different depths in the crust and upper mantle … The fifth- and sixth-order wavelet details reflect the attenuating lateral density inhomogeneity in the lower lithosphere. Moreover, six-layer densities of the TP with the lateral spatial resolution of 0.5◦ × 0.5◦ are inverted based on the decomposed gravity anomalies. The inverted multilayer densities provide a clear 3-D model to further insight into the tectonic structure and development. Densities of Layer 1 and Layer 2 imply strong lateral density inhomogeneity existing in the upper crust. From Layer 3 to Layer 5, fold structure and possible channel flows can be identified. Layer 6 gives smooth density distribution at the bottom of lithosphere.” Examiner note: Xue teaches analyzing density related models or density distributions at different depth layers and determining density inhomogeneities within individual layers. Although Xue does not expressly use the terms “mid-range or far-range formation model”, Xue is relied upon for the correlation and density inhomogeneity analysis applied to the formation model taught by Priezzhev).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bartetzko and Shetty and Wang and Priezzhev to incorporate the teachings of Xu, and apply multilayer density analysis and density inhomogeneity determination techniques in order to identify density variation within different subsurface layers of the generated formation model. The combination of teachings would predictably provide the benefit of improving characterization of subsurface density variations within the generated formation model for more accurate subsurface interpretation.
The elements of claim 19 is substantially the same as those of claim 9. Therefore, the elements of claims 19 is rejected due to the same reasons as outlined above for claim 9.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Habashy US 20090164187 A1, discloses building a predictive or forward model adapted for
predicting the future evolution of a reservoir, comprising: integrating together a plurality of measurements thereby generating an integrated set of deep reading measurements, the integrated set of deep reading measurements being sufficiently deep to be able to probe the reservoir and being self-sufficient in order to enable the building of a reservoir model and its associated parameters; generating a reservoir model and associated parameters in response to the set of deep reading measurements; and receiving, by a reservoir simulator, the reservoir model and, responsive thereto, generating, by the reservoir simulator, the predictive or forward model.
Ander US 20040250614 A1, discloses Techniques for using gravity in applications such as drilling and logging. Techniques are present for (1) gravity well logging using gravity sensors arrays; (2) creating density pseudosections using gravity measurements; (3) performing Gravity Measurement While Drilling (GMWD) using single or multiple gravity sensors; and (4) geosteering using GMWD.
Vasilevskiy US 20100286967 A1, discloses estimating a property of an earth formation includes: a plurality of sensors configured to estimate at least one property, each of the plurality of sensors located at a known position relative to one another; and a processor in operable communication with the plurality of sensors and configured to estimate uncertainties of the location of the plurality of sensors over a period of time. A method and computer program product for estimating a property of an earth formation is also disclosed.
Green US 20110166840 A1, discloses electromagnetic subsurface mapping to derive information with respect to subsurface features whose sizes are near to or below the resolution of electromagnetic data characterizing the subsurface are shown. Embodiments operate to identify a region of interest (203) in a resistivity image generated (202) using electromagnetic data (201). One or more scenarios may be identified for the areas of interest, wherein the various scenarios comprise representations of features whose sizes are near to or below the resolution of the electromagnetic data (204). According to embodiments, the scenarios are evaluated (205), such as using forward or inverse modeling, to determine each scenarios' fit to the available data and further to determine their geologic reasonableness (206). Resulting scenarios may be utilized in a number of ways, such as to be substituted in a resistivity image for a corresponding region of anomalous resistivity for enhancing the resistivity image (207).
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/YI . HAO/
Examiner, Art Unit 2187
/EMERSON C PUENTE/Supervisory Patent Examiner, Art Unit 2187
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