DETAILED ACTION
Claims 1-20 have been examined and are pending.
Claims 1-20 are rejected (Non-Final Rejection).
Notice of 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 .
Information Disclosure Statement
The information disclosure statements (IDSs) submitted on 24 July 2023 and 5 June 2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the IDSs have been considered by the examiner.
Claim Objections
Claims 2, 12, 16 and 17 are objected to because of the following informalities:
Claim 2 recites “the independent contributions to output of each identified parameter” (emphasis added), which appears to be an artifact of Applicant’s editing process. Examiner suggests removing “to output”. Appropriate correction is required.
Claim 12 recites “calculate a direction and amount by with the parameters need to change to …” (emphasis added), which appears to be an artifact of Applicant’s editing process. Examiner suggests replacing “by with” with “by which”. Appropriate correction is required.
Claim 16 recites “nonvolatile”, which is being interpreted as “non-transitory”. Examiner believes the intent was to cover “non-transitory”, which covers the eligible media type(s). Appropriate correction is required. Examiner suggests replacing “nonvolatile” with “non-transitory” in claim 16 and adding “non-transitory” in claim 17, which depends from claim 16.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 20 is objected to under 35 U.S.C. §112(d) as being an improper dependent claim because it fails to further limit the subject matter of claim 18 from which it depends. Claim 18 recites “a regression model with hyperparameter tuning”. Therefore, the “hyperparameter tuning” limitation recited in claim 20 does not further limit claim 18. Appropriate correction is required.
Claim Rejections - 35 U.S.C. § 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 following is an analysis based on the 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG).
To determine if a claim is directed to patent ineligible subject matter, the Court has guided the Office to apply the Alice/Mayo test, which requires:
1. Determining if the claim falls within a statutory category;
2A. Determining if the claim is directed to a patent ineligible judicial exception consisting of a law of nature, a natural phenomenon, or abstract idea; and
2B. If the claim is directed to a judicial exception, determining if the claim recites limitations or elements that amount to significantly more than the judicial exception.
(See MPEP 2106).
Claims 1-20 Step 1, Statutory Category?:
Yes: Claims 1-15 and 18-20 are directed to the statutory category of a process. See MPEP § 2106.03.
Yes: Claims 16 and 17 are directed to the statutory category of a manufacture. See MPEP § 2106.03.
Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed inventions are directed to an abstract idea without significantly more. The claim(s) recite a mental process and a mathematical calculation. See MPEP § 2106.04(a)(2)(I) and MPEP § 2106.04(a)(2)(III).
Step 2A:
Step 2A is a two-prong inquiry. See MPEP § 2106.04(II)(A). Under the first prong, examiners evaluate whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. Abstract ideas include mathematical concepts, certain methods of organizing human activity, and mental processes. See MPEP § 2106.04(a)(2). The second prong is an inquiry into whether the claim integrates a judicial exception into a practical application. See MPEP § 2106.04(d).
Claim 1 Step 2A Prong One: Does the Claim Recite a Judicial Exception?
For the sake of identifying the abstract ideas, a copy of the claim is provided below. The limitations of the claims that describe abstract ideas are bolded.
A method of steering a drill string when forming a wellbore in a subterranean formation, the method comprising:
identifying two or more parameters associated with steering the drill string in a subject well;
determining, via a statistical model, individual contributions to a tool yield model by each of the identified parameters; and
suggesting, based on the statistical model and on current values of the identified parameters, one or more changes in the identified parameters, the changes sufficient to alter a trajectory of the drill string in the subject well.
The limitations “identifying two or more parameters associated with steering the drill string in a subject well” and “suggesting, based on the statistical model and on current values of the identified parameters, one or more changes in the identified parameters, the changes sufficient to alter a trajectory of the drill string in the subject well” are abstract ideas because they are directed to mental processes, observations, evaluations, judgments, and/or opinions. The limitations, as drafted and under broadest reasonable interpretation, “can be performed in the human mind or by a human using a pen and paper”. See MPEP 2106.04(a)(2)(III). For example, a human could identify drill string steering parameters (e.g., WOB, RPM, flow rate) and suggest, based on the individual contributions/statistical model and current values of the identified parameters, a suggestion/recommendation regarding the steering parameters. In addition, the limitation of “determining, via a statistical model, individual contributions to a tool yield model by each of the identified parameters” can be performed using mathematical calculations/equations and therefore encompass mathematical concepts. See MPEP 2106.04(a)(2)(I). The broadest reasonable interpretation, in light of the specification, of the “determining, via a statistical model, individual contributions to a tool yield model” requires mathematical calculations. For example, Para. [0038] of the specification indicates the “statistical analysis” is performed on the model to obtain mathematical models that describe relationship of each individual input with the output and symbolic regression is performed on the dependence data to obtain a data-driven model. Thus, claim 1 recites an abstract idea(s).
Claim 1 Step 2A Prong Two: Does the claim recite additional elements that integrate the judicial exception/Abstract idea into practical application?
Under Step 2A Prong Two, this judicial exception is not integrated into a practical application because the additional claim limitations outside of the abstract idea only present mere instructions to apply an exception, generally link the use of the judicial exception to the technological environment, or insignificant extra-solution activity. In particular, the claim recites the additional limitations of:
• “of steering a drill string when forming a wellbore in a subterranean formation” (general field of use or technological environment – see MPEP 2106.04(d) referencing MPEP 2106.05(h); these limitations can be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of an oil rig/wellsite (see MPEP 2106.05(h)). Moreover, when reading the preamble in the context of the entire claim, the recitation is not limiting because the body of the claim describes a complete invention and the language recited solely in the preamble does not provide any distinct definition of any of the claimed invention’s limitations. Thus, the preamble of the claim(s) is not considered a limitation and is of no significance to claim construction. See Pitney Bowes, Inc. v. Hewlett-Packard Co., 182 F.3d 1298, 1305, 51 USPQ2d 1161, 1165 (Fed. Cir. 1999). See MPEP § 2111.02.
Claim 1 Step 2B: Do the additional elements, considered individually and in combination, amount to significantly more than the judicial exception?
The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As explained above, there is one type of additional element. The first type of additional element is “of steering a drill string when forming a wellbore in a subterranean formation”, which is at best viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of an oil rig/wellsite environment. For the claim limitations that generally link the use of the judicial exception to a particular technological environment or field of use, the claim limitations do not meaningfully limit the claim because the claim limitations employ generic computer functions to execute an abstract idea, even when limiting the use of the idea to one particular environment, and does not add significantly more, similar to how limiting the abstract idea in Flook to petrochemical and oil-refining industries was insufficient. See MPEP 2106.05(h). Moreover, as discussed above, the preamble of the claim(s) is not considered a limitation and is of no significance to claim construction. See Pitney Bowes, Inc. v. Hewlett-Packard Co., 182 F.3d 1298, 1305, 51 USPQ2d 1161, 1165 (Fed. Cir. 1999). See MPEP § 2111.02.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and/or data gathering, which do not provide an inventive concept. The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception. See MPEP 2106.05(f).
Considering the claim limitations as an ordered combination, claim 1 does not include significantly more than the abstract idea. The claim 1 is not patent subject matter eligible. Dependent claims 2-15 are further addressed below after addressing each independent claim.
Claim 16 Step 2A Prong One: Does the Claim Recite a Judicial Exception?
For the sake of identifying the abstract ideas, a copy of the claim is provided below. The limitations of the claims that describe abstract ideas are bolded.
A nonvolatile computer readable medium having instructions that, when executed by a processor:
identify two or more parameters associated with steering a drill string in a subject well;
determine, via a statistical model, individual contributions to a tool yield model by each of the identified parameters; and
suggest, based on the statistical model and on current values of the identified parameters, one or more changes in the identified parameters, the changes sufficient to alter a trajectory of the drill string in the subject well.
The limitations “identify two or more parameters associated with steering a drill string in a subject well” and “suggest, based on the statistical model and on current values of the identified parameters, one or more changes in the identified parameters, the changes sufficient to alter a trajectory of the drill string in the subject well” are abstract ideas because they are directed to mental processes, observations, evaluations, judgments, and/or opinions. The limitations, as drafted and under broadest reasonable interpretation, “can be performed in the human mind or by a human using a pen and paper”. See MPEP 2106.04(a)(2)(III). For example, a human could identify drill string steering parameters (e.g., WOB, RPM, flow rate) and suggest, based on the individual contributions/statistical model and current values of the identified parameters, a suggestion/recommendation regarding the steering parameters. In addition, the limitation of “determine, via a statistical model, individual contributions to a tool yield model by each of the identified parameters” can be performed using mathematical calculations/equations and therefore encompass mathematical concepts. See MPEP 2106.04(a)(2)(I). The broadest reasonable interpretation, in light of the specification, of the “determining, via a statistical model, individual contributions to a tool yield model” requires mathematical calculations. For example, Para. [0038] of the specification indicates the “statistical analysis” is performed on the model to obtain mathematical models that describe relationship of each individual input with the output and symbolic regression is performed on the dependence data to obtain a data-driven model. Thus, claim 1 recites an abstract idea(s).
Claim 16 Step 2A Prong Two: Does the claim recite additional elements that integrate the judicial exception/Abstract idea into practical application?
Under Step 2A Prong Two, this judicial exception is not integrated into a practical application because the additional claim limitations outside of the abstract idea only present mere instructions to apply an exception, generally link the use of the judicial exception to the technological environment, or insignificant extra-solution activity. In particular, the claim recites the additional limitations of:
• “nonvolatile computer readable medium having instructions that, when executed by a processor” (mere instructions to apply an exception to a computer – see MPEP 2106.04(d) referencing MPEP 2106.05(f); these limitations can be viewed as nothing more than high level recitations of generic computer components or computer elements used as a tool, and represent mere instructions to apply the abstract idea on a generic computer (see MPEP 2106.05(f)).
Claim 16 Step 2B: Do the additional elements, considered individually and in combination, amount to significantly more than the judicial exception?
The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As explained above, there is one type of additional element. The first type of additional element is the generic computer components (“nonvolatile computer readable medium”), which are high level recitations of generic computer component(s) or computer elements used as a tool, and represent mere instructions to apply the abstract idea on a computer. See MPEP § 2106.05(f). Implementing an abstract idea on a generic computer, does not integrate the abstract idea into a practical application in Step 2A Prong Two or add significantly more in Step 2B, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer. See MPEP § 2106.05(f).
Even when considered in combination, these additional elements represent mere instructions to apply an exception and/or data gathering, which do not provide an inventive concept. The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception. See MPEP 2106.05(f).
Considering the claim limitations as an ordered combination, claim 16 does not include significantly more than the abstract idea. The claim 16 is not patent subject matter eligible. Dependent claim 17 is further addressed below after addressing each independent claim.
Claim 18 Step 2A Prong One: Does the Claim Recite a Judicial Exception?
For the sake of identifying the abstract ideas, a copy of the claim is provided below. The limitations of the claims that describe abstract ideas are bolded.
A method of determining tool yield as a function of dogleg severity (DLS) for a drill string in a subject well, the method comprising:
querying a database to obtain drilling information associated with different wells;
filtering the drilling information to identify wells from the database that are similar to the subject well and that are within a radius R of the subject well;
calculating a similarity score for each identified well;
if the similarity score is less than a threshold value, labeling the well as an offset well; and
applying a regression model with hyperparameter tuning to the drilling information of sections of the offset well that curve.
The limitations “calculating a similarity score for each identified well” and “applying a regression model with hyperparameter tuning to the drilling information of sections of the offset well that curve” can be performed using mathematical calculations/equations and therefore encompass mathematical concepts. See MPEP 2106.04(a)(2)(I). The broadest reasonable interpretation, in light of the specification, of the “calculating a similarity score” and “applying a regression model” require mathematical calculations. In addition, the limitation of “if the similarity score is less than a threshold value, labeling the well as an offset well” are abstract ideas because they are directed to mental processes, observations, evaluations, judgments, and/or opinions. The limitations, as drafted and under broadest reasonable interpretation, “can be performed in the human mind or by a human using a pen and paper”. See MPEP 2106.04(a)(2)(III). For example, a human could determine whether a score is less than a value, and based on such, create a well label. Thus, claim 18 recites an abstract idea(s).
Claim 18 Step 2A Prong Two: Does the claim recite additional elements that integrate the judicial exception/Abstract idea into practical application?
Under Step 2A Prong Two, this judicial exception is not integrated into a practical application because the additional claim limitations outside of the abstract idea only present mere instructions to apply an exception, generally link the use of the judicial exception to the technological environment, or insignificant extra-solution activity. In particular, the claim recites the additional limitations of:
• “of determining tool yield as a function of dogleg severity (DLS) for a drill string in a subject well” (general field of use or technological environment – see MPEP 2106.04(d) referencing MPEP 2106.05(h); these limitations can be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of an oil rig/wellsite (see MPEP 2106.05(h)). Moreover, when reading the preamble in the context of the entire claim, the recitation is not limiting because the body of the claim describes a complete invention and the language recited solely in the preamble does not provide any distinct definition of any of the claimed invention’s limitations. Thus, the preamble of the claim(s) is not considered a limitation and is of no significance to claim construction. See Pitney Bowes, Inc. v. Hewlett-Packard Co., 182 F.3d 1298, 1305, 51 USPQ2d 1161, 1165 (Fed. Cir. 1999). See MPEP § 2111.02.
• “querying a database to obtain drilling information associated with different wells” and “filtering the drilling information to identify wells from the database that are similar to the subject well and that are within a radius R of the subject well” (insignificant extra-solution activity – mere data gathering/inputting – see MPEP 2106.04(d) referencing MPEP 2106.05(g); this limitation can be viewed as nothing more than mere data gathering/inputting in conjunction with the abstract idea (see MPEP § 2106.05(g)).
Claim 18 Step 2B: Do the additional elements, considered individually and in combination, amount to significantly more than the judicial exception?
The Examiner must consider whether each claim limitation individually or as an ordered combination amount to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As explained above, there are two types of additional element. The first type of additional element is “of determining tool yield as a function of dogleg severity (DLS) for a drill string in a subject well”, which is at best viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of an oil rig/wellsite environment. For the claim limitations that generally link the use of the judicial exception to a particular technological environment or field of use, the claim limitations do not meaningfully limit the claim because the claim limitations employ generic computer functions to execute an abstract idea, even when limiting the use of the idea to one particular environment, and does not add significantly more, similar to how limiting the abstract idea in Flook to petrochemical and oil-refining industries was insufficient. See MPEP 2106.05(h). Moreover, as discussed above, the preamble of the claim(s) is not considered a limitation and is of no significance to claim construction. See Pitney Bowes, Inc. v. Hewlett-Packard Co., 182 F.3d 1298, 1305, 51 USPQ2d 1161, 1165 (Fed. Cir. 1999). See MPEP § 2111.02.
The second type of additional element (“obtaining … [and] filtering drilling information”), as explained previously, are insignificant extra-solution activity (mere data inputting/gathering and/or data outputting). These recitations are recited at a high level of generality, and are also well-known. These limitations therefore remain insignificant extra-solution activity even upon reconsideration. Thus, these limitations do not amount to significantly more.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and/or data gathering, which do not provide an inventive concept. The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception. See MPEP 2106.05(f).
Considering the claim limitations as an ordered combination, claim 18 does not include significantly more than the abstract idea. The claim 18 is not patent subject matter eligible. Dependent claims 19 and 20 are further addressed below after addressing each independent claim.
Dependent Claims 2-15, 17, 19 and 20
Regarding claims 2-15, 17, 19 and 20, claim 2 depends from claim 1 and further recites: “wherein determining individual contributions includes: obtaining the tool yield model, wherein the tool yield model is a regression model of drilling information from similar wells; performing statistical modeling of the tool yield model to identify independent contributions to output as a linear combination of the independent contributions to output of each identified parameter; and performing regression analysis of each parameter/output pair”, claim 3 depends from claim 1 and further recites: “wherein the tool yield model is a regression model of drilling information for curved sections of boreholes of similar wells, the regression model including hyperparameter tuning”, claim 4 depends from claim 1 and further recites: “wherein determining individual contributions to a tool yield model by each of the identified parameters includes retrieving drilling information obtained from offset wells”, claim 5 depends from claim 4 and further recites: “wherein retrieving drilling information obtained from offset wells includes identifying, as offset wells, wells with characteristics like the subject well that are within a radius, R, of the subject well”, claim 6 depends from claim 5 and further recites: “wherein identifying wells with characteristics like the subject well includes calculating a similarity score for each well and, if the similarity score is less than a threshold value, identifying the well as an offset well”, claim 7 depends from claim 5 and further recites: “wherein identifying wells with characteristics like the subject well includes: querying a database to obtain drilling information associated with different wells; and filtering the drilling information to identify wells that used a similar bit type, size, and design as the subject well”, claim 8 depends from claim 5 and further recites: “wherein identifying wells with characteristics like the subject well includes: querying a database to obtain drilling information associated with different wells; and filtering the drilling information to identify wells that used a similar tool size, type, and design as the subject well”, claim 9 depends from claim 5 and further recites: “wherein identifying wells with characteristics like the subject well includes: querying a database to obtain drilling information associated with different wells; and filtering the drilling information to identify wells that used a similar borehole apparatus (BHA) as the subject well”, claim 10 depends from claim 1 and further recites: “wherein the tool yield model is a regression model of drilling information of similar wells and wherein identifying wells like the subject well includes: querying a database to obtain the drilling information associated with different wells; filtering the drilling information to identify wells that are within a radius R of the subject well and that used: a similar bit type, size, and design as the subject well; a similar tool size, type, and design as the subject well; and a similar borehole apparatus (BHA) as the subject well; calculating a similarity score for each identified well; and if the similarity score is less than a threshold value, labeling the well as an offset well”, claim 11 depends from claim 10 and further recites: “wherein the method further comprises: applying a regression model to the drilling information of sections of the offset well that curve to determine the tool yield model”, claim 12 depends from claim 1 and further recites: “wherein suggesting a change in one of the identified parameters includes: calculating a dogleg severity (DLS) required to meet a well plan for the subject well; calculating a current DLS; and if the current DLS is less than the required DLS, applying current parameter values, limits and the statistical model to calculate a direction and amount by with the parameters need to change to obtain the required DLS”, claim 13 depends from claim 1 and further recites: “wherein suggesting one or more changes in the identified parameters includes: calculating a dogleg severity (DLS) required to meet a well plan for the subject well; calculating a current DLS; and if the current DLS is less than the required DLS, determining changes in the parameters that maximize rate of penetration (ROP) or achieves a ROP within certain constrained limits at the required DLS”, claim 14 depends from claim 13 and further recites: “wherein determining changes in the parameters that maximize rate of penetration (ROP) at the required DLS includes solving an optimization problem using an ROP model and the tool yield model”, claim 15 depends from claim 1 and further recites: “wherein the method further comprises: incorporating the suggested changes in the identified parameters in the drilling system of the subject well; receiving feedback from the drilling system after incorporating the suggested changes, wherein the feedback includes new values for one or more of the identified parameters; updating the current values to reflect the new values; and suggesting, based on the statistical model and on the updated current values of the identified parameters, one or more changes in the identified parameters”, claim 17 depends from claim 16 and further recites: “wherein the instructions that, when executed by the processor, suggest one or more changes in the identified parameters include instructions that, when executed by the processor: calculate a dogleg severity (DLS) required to meet a well plan for the subject well; determine a current DLS; and if the current DLS is less than the required DLS, determine changes in the identified parameters needed to obtain the required DLS”, claim 19 depends from claim 18 and further recites: “wherein filtering the drilling information to identify wells from the database that are like the subject well includes filtering the identified wells to find wells that have one or more of: a similar bit type, size, and design as the subject well; a similar tool size , type, and design as the subject well; a similar borehole apparatus (BHA) as the subject well; a similar rotary steering system (RSS) as the subject well; a similar inclination as the planned inclination with respect to measured depth of the drill string; and a similar true vertical depth (TVD) as the planned TVD with respect to measured depth of the subject well” and claim 20 depends from claim 18 and further recites: “wherein the regression model includes hyperparameter tuning”. These features have been considered in combination with the features required by the claim(s) from which these claims depend. The bolded portion of the additional features are considered to further clarify the details of the mathematical concepts and/or the human’s mental activity (e.g., with pen and paper). See MPEP §§ 2106.04(a)(2)(I) and (III). In addition, the not bolded features of claims 4, 5, 7-10, 15 and 19 are considered to be insignificant extra-solution activity of data gathering/inputting, which cannot provide an inventive concept, and is well-understood, routine and conventional. See MPEP 2106.05(g); See also MPEP § 2106.05(d)(II) (“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, e.g., using the Internet to gather data”)). Therefore, these features are considered to be drawn to the abstract idea without adding significantly more, and hence claims 2-15are considered to be ineligible under 35 U.S.C. § 101.
For the foregoing reasons, claims 1-20 are rejected under 35 U.S.C. § 101 as being directed to patent ineligible subject matter.
Claim Rejections - 35 U.S.C. § 103
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.
Claims 1, 2, 4 and 12-17 are rejected under 35 U.S.C. § 103 as being unpatentable over WEIDEMAN et al. (U.S. Patent Application Publication No. 2023/0151696 A1) in view of WESTON et al. (U.S. Patent Application Publication No. 2021/0026037 A1).
Regarding claim 1, WEIDMAN discloses a method of steering a drill string when forming a wellbore in a subterranean formation (sliding, also called steering, uses a downhole mud motor with an adjustable bent housing, and does not rotate the drill string … instead, sliding uses hydraulic power to drive the downhole motor and bit … sliding is used in order to control well direction, Para. [0111] of WEIDEMAN), the method comprising: identifying two or more parameters associated with steering the drill string in a subject well (control parameters may define the settings for various drilling operations that are to be executed by the drilling rig 110 to form the borehole, such as WOB, flow rate of mud, toolface orientation, and similar settings, Para. [0158] of WEIDEMAN; [Examiner’s Note: Para. [0015]-[0016] of Applicant’s specification indicate WOB, RPM and flowrate are operational parameters adjusted to steer a drill string]); determining(the automated slide drilling system may be programmed to select a control data set based on one or more algorithms, such as linear or polynomial regression based on one or more parameters of the data sets in the database, Para. [0391] of WEIDEMAN; [Examiner’s Note: Applicant’s claim 2 indicates that tool yield model may be a regression model]; See also a toolface control evaluator 3972 that is responsible for evaluating all factors impacting toolface control and whether adjustments need to be projected … a top drive adjustment calculator 3974 that is responsible for calculating top drive adjustments resultant to toolface projections; an oscillator adjustment calculator 3976 that is responsible for calculating oscillator adjustments resultant to toolface projections; and an auto driller adjustment calculator 3978 that is responsible for calculating auto driller adjustments resultant to toolface projections, Para. [0374] of WEIDEMAN; See also determine that the ideal adjustment is to simultaneously increase the WOB and differential pressure targets, adjust the oscillator bias to the right by 0.83 wraps, and adjust the flowrate up by 10% … all of the adjustments can be made simultaneously … the net result is a faster acquisition of the toolface target, an increase in drilling performance and less unnecessary deviation of the well … the ability to make these simultaneous optimal adjustments is assisted by modeling the borehole and being able to simultaneously consider numerous variables, including the BHA, drill string, precise well path, historical trends, surface torque, reactive torque produced by the mud motor, and friction of the borehole from past evaluation, Para. [0400] of WEIDEMAN; See also adjustments, in some embodiments, can be made to various operating parameters, such as an angular displacement, a weight on the bit, toolface orientation, spindle position, or a differential pressure, Para. [0555] of WEIDEMAN; See also model error can be an error value that is calculated based on the determined adjustment … the model error can be calculated without deploying the determined adjustment, Para. [0556] of WEIDEMAN); and suggesting, based on the (automated slide-drilling controller offers a restricted set of alternatives and suggests one, but the human operator still makes and implements final decision, Paras. [0266] & [0267] of WEIDEMAN; See also at least one of the control parameters is changed to modify the drilling operation, although the target MSE or ROP should be maintained, Paras. [0195] & [0196] of WEIDEMAN; See also the authorizations used to approve changes in the drilling process, Para. [0137] of WEIDEMAN; [WEIDEMAN discusses changes that are/should be implemented (e.g., Paras. [0195] & [0196]) but also explains these changes can require user approval (Para. [0137], which means the change is a suggestion]), the changes sufficient to alter a trajectory of the drill string in the subject well (directional drilling may involve multiple vertical adjustments that complicate the path of the borehole, Para. [0108] of WEIDEMAN; See also in order to reach an ideal ROP and still maintain appropriate control over a slide, it may be important to adjust various drilling parameters … for example, if it is desired to increase ROP while sliding, an operator or the automated slide system described above can increase WOB and/or differential pressure … the operator or automated slide drilling system can also make appropriate adjustments to the wraps in the appropriate direction in order to maintain toolface orientation and avoid destabilizing the toolface, such as by sending one or more control signals to the rig's auto driller, Para. [0388] of WEIDEMAN).
WEIDEMAN does not appear to explicitly disclose a statistical model used for determining individual contributions to a tool yield model by each of the identified parameters; and suggesting, based on the statistical model and on current values of the identified parameters, one or more changes in the identified parameters, the changes sufficient to alter a trajectory of the drill string in the subject well.
WESTON, however, is in the field of wellbore survey tools (Para. [0004] of WESTON) and teaches determining, via a statistical model, individual contributions to a tool yield model by each of the identified parameters (remove or reduce measurement biases in the measurements from a CVG sensor, one or more statistical estimation processes may be used … in such an implementation, a statistical estimation process for the calculation of the measurement bias contributions may be constructed based on a mathematical model of the system that yields estimates of the gyroscopic measurement errors, Para. [0073] of WESTON; See also FIGS. 6 & 7 of WESTON); and suggesting, based on the statistical model and on current values of the identified parameters, one or more changes in the identified parameters, the changes sufficient to alter a trajectory of the drill string in the subject well (the bias corrected measurements of the Earth's rotation rate about the x-axis, the y-axis, and the z-axis of the survey tool may be used to determine an azimuth of the survey tool and, hence, an azimuth of the wellbore. In turn, for some implementations, the survey tool may perform drilling operations based on this determined azimuth, such as to maintain or change a trajectory of the tool, Para. [0103] of WESTON; See also FIGS. 6 & 7 of WESTON).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to modify the method of optimizing steering of a drill string in a borehole of WEIDEMAN with the statistical modeling that provides a suggested trajectory change as in WESTON for the purpose of improving the accuracy of sensor measurements and/or drilling survey tools (Para. [0072] of WESTON).
Regarding claim 2, WEIDEMAN as modified by WESTON discloses the method of claim 1 (as shown above), wherein determining individual contributions includes: obtaining the tool yield model, wherein the tool yield model is a regression model of drilling information from similar wells (the automated slide drilling system may be programmed to select a control data set based on one or more algorithms, such as linear or polynomial regression based on one or more parameters of the data sets in the database, Para. [0391] of WEIDEMAN; See also Para. [0103] & FIGS. 6 & 7 of WESTON); performing statistical modeling of the tool yield model to identify independent contributions to output as a linear combination of the independent contributions to output of each identified parameter (analyses in steps 3628 and 3630 may be performed using a mathematical model indicative of the physical drill string using an expected transfer function to model the mechanical behavior of the drill string, as well as formation characteristics. In another example, historical reference data for similar drill string configurations and well plans, if available or accessible, including data from the same well bore, may be used instead of, or together with, mathematical models, Para. [0364] of WEIDEMAN; See also Para. [0103] & FIGS. 6 & 7 of WESTON); and performing regression analysis of each parameter/output pair (an error between the target value and the measured value is calculated … in some embodiments, the error may be measured across desired operational parameters … for example, the error may be calculated by the difference between a generated value using a model and the measured value of an operational parameter, by one or more sensors … based on the received data from the one or more sensors, the error may be measured by a linear regression model, Para. [0554] of WEIDEMAN; See also Para. [0103] & FIGS. 6 & 7 of WESTON).
Regarding claim 4, WEIDEMAN as modified by WESTON discloses the method of claim 1 (as shown above), wherein determining individual contributions to a tool yield model by each of the identified parameters includes retrieving drilling information obtained from offset wells (each well 102, 104, 106, and 108 has corresponding collected data 120, 122, 124 and 126, Para. [0105] of WEIDEMAN; [at least well 102 and 104 are considered to be offset wells of each other]; See also the wells 102 and 104 are located in a region 112, Para. [0101] of WEIDEMAN).
Regarding claim 12, WEIDEMAN as modified by WESTON discloses the method of claim 1 (as shown above), wherein suggesting a change in one of the identified parameters includes: calculating a dogleg severity (DLS) required to meet a well plan for the subject well (the path 744 may be rejected for an engineering reason (e.g., the path would require a dogleg of greater than allowed severity, Para. [0183] of WEIDEMAN; See also the optimization process may be applied to production by optimizing well smoothness and other factors affecting production … for example, by minimizing dogleg severity, production may be increased for the lifetime of the well, Para. [0194] of WEIDEMAN); calculating a current DLS (obtain, monitor, and consider the effects of information regarding the borehole, such as its measured depth, its true vertical depth, the tortuosity of one or more portions of the borehole (existing or planned), the severity of doglegs, Para. [0396] of WEIDEMAN); and if the current DLS is less than the required DLS, applying current parameter values, limits and the statistical model to calculate a direction and amount by with the parameters need to change to obtain the required DLS (MPEP 2111.04(II) recites: “[t]he broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met. For example, assume a method claim requires step A if a first condition happens and step B if a second condition happens. If the claimed invention may be practiced without either the first or second condition happening, then neither step A or B is required by the broadest reasonable interpretation of the claim”; [To avoid the contingent limitation interpretation, Examiner suggests replacing “if” (not required to occur) with “when” or “in response to” (required to occur at least once); See also the path 744 may be rejected for an engineering reason (e.g., the path would require a dogleg of greater than allowed severity, Para. [0183] of WEIDEMAN; See also the optimization process may be applied to production by optimizing well smoothness and other factors affecting production … for example, by minimizing dogleg severity, production may be increased for the lifetime of the well, Para. [0194] of WEIDEMAN).
Regarding claim 13, WEIDEMAN as modified by WESTON discloses the method of claim 1 (as shown above), wherein suggesting one or more changes in the identified parameters includes: calculating a dogleg severity (DLS) required to meet a well plan for the subject well (the path 744 may be rejected for an engineering reason (e.g., the path would require a dogleg of greater than allowed severity, Para. [0183] of WEIDEMAN; See also the optimization process may be applied to production by optimizing well smoothness and other factors affecting production … for example, by minimizing dogleg severity, production may be increased for the lifetime of the well, Para. [0194] of WEIDEMAN); calculating a current DLS (obtain, monitor, and consider the effects of information regarding the borehole, such as its measured depth, its true vertical depth, the tortuosity of one or more portions of the borehole (existing or planned), the severity of doglegs, Para. [0396] of WEIDEMAN); and if the current DLS is less than the required DLS, determining changes in the parameters that maximize rate of penetration (ROP) or achieves a ROP within certain constrained limits at the required DLS (MPEP 2111.04(II) recites: “[t]he broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met. For example, assume a method claim requires step A if a first condition happens and step B if a second condition happens. If the claimed invention may be practiced without either the first or second condition happening, then neither step A or B is required by the broadest reasonable interpretation of the claim”; [To avoid the contingent limitation interpretation, Examiner suggests replacing “if” (not required to occur) with “when” or “in response to” (required to occur at least once); See also the path 744 may be rejected for an engineering reason (e.g., the path would require a dogleg of greater than allowed severity, Para. [0183] of WEIDEMAN; See also the optimization process may be applied to production by optimizing well smoothness and other factors affecting production … for example, by minimizing dogleg severity, production may be increased for the lifetime of the well, Para. [0194] of WEIDEMAN).
Regarding claim 14, WEIDEMAN as modified by WESTON discloses the method of claim 13 (as shown above), wherein determining changes in the parameters that maximize rate of penetration (ROP) at the required DLS (in prioritizing speed, a goal can be to achieve the highest possible penetration rate accurately along the planned path within equipment and formation limitations … optimizing rate of penetration can be achieved through the lowest possible tortuosity and lowest possible toque and drag on the drill string, Para. [0434] of WEIDEMAN; See also the path 744 may be rejected for an engineering reason (e.g., the path would require a dogleg of greater than allowed severity, Para. [0183] of WEIDEMAN; See also the optimization process may be applied to production by optimizing well smoothness and other factors affecting production … for example, by minimizing dogleg severity, production may be increased for the lifetime of the well, Para. [0194] of WEIDEMAN) includes solving an optimization problem using an ROP model and the tool yield model (automated slide drilling system may determine the optimal control settings to adjust the drilling operations to maintain the toolface orientation at 3514 and optimize ROP, Para. [0343] of WEIDEMAN; See also an ROP impact model 3962 that is responsible for modeling the effect on the toolface control of a change in ROP or a corresponding set point, Para. [0374] of WEIDEMAN; See also selecting an optimal solution vector based on a set of target parameters, which may include one or more of a financial cost, a time cost, a reliability cost, and/or any other factors, such as an engineering cost like dogleg severity, that may be used to narrow the set of solution vectors to the optimal solution vector, Para. [0184] of WEIDEMAN).
Regarding claim 15, WEIDEMAN as modified by WESTON discloses the method of claim 1 (as shown above), wherein the method further comprises: incorporating the suggested changes in the identified parameters in the drilling system of the subject well (the authorizations used to approve changes in the drilling process, Para. [0137] of WEIDEMAN); receiving feedback from the drilling system after incorporating the suggested changes, wherein the feedback includes new values for one or more of the identified parameters (feedback information received from the drilling rig 110 (e.g., from one or more of the control systems 208, 210, and 212 and/or sensor system 214) is processed, Para. [0160] of WEIDEMAN); updating the current values to reflect the new values (update a database query and update engine/diagnostic logger 1022, Para. [0208] of WEIDEMAN); and suggesting, based on the statistical model and on the updated current values of the identified parameters, one or more changes in the identified parameters (automated slide-drilling controller offers a restricted set of alternatives and suggests one, but the human operator still makes and implements final decision, Paras. [0266] & [0267] of WEIDEMAN; See also at least one of the control parameters is changed to modify the drilling operation, although the target MSE or ROP should be maintained, Paras. [0195] & [0196] of WEIDEMAN).
Claim 16 is a nonvolatile computer readable medium and has substantially the same technical features as claim 1, differing only in the category of invention. Thus, the same reasoning as in claim 1 applies to claim 16. Additionally, WEIDEMAN teaches a nonvolatile computer readable medium having instructions that, executed by a processor (non-transitory, computer-readable medium comprising instructions that when executed by a processor, causes the processor to, Claim 22 of WEIDEMAN).
Regarding claim 17, WEIDEMAN as modified by WESTON discloses the computer readable medium of claim 16 (as shown above), wherein the instructions that, when executed by the processor, suggest one or more changes in the identified parameters include instructions that, when executed by the processor: calculate a dogleg severity (DLS) required to meet a well plan for the subject well (the path 744 may be rejected for an engineering reason (e.g., the path would require a dogleg of greater than allowed severity, Para. [0183] of WEIDEMAN; See also the optimization process may be applied to production by optimizing well smoothness and other factors affecting production … for example, by minimizing dogleg severity, production may be increased for the lifetime of the well, Para. [0194] of WEIDEMAN); determine a current DLS (obtain, monitor, and consider the effects of information regarding the borehole, such as its measured depth, its true vertical depth, the tortuosity of one or more portions of the borehole (existing or planned), the severity of doglegs, Para. [0396] of WEIDEMAN); and if the current DLS is less than the required DLS, determine changes in the identified parameters needed to obtain the required DLS (MPEP 2111.04(II) recites: “[t]he broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met. For example, assume a method claim requires step A if a first condition happens and step B if a second condition happens. If the claimed invention may be practiced without either the first or second condition happening, then neither step A or B is required by the broadest reasonable interpretation of the claim”; [To avoid the contingent limitation interpretation, Examiner suggests replacing “if” (not required to occur) with “when” or “in response to” (required to occur at least once); See also the path 744 may be rejected for an engineering reason (e.g., the path would require a dogleg of greater than allowed severity), Para. [0183] of WEIDEMAN; See also the optimization process may be applied to production by optimizing well smoothness and other factors affecting production … for example, by minimizing dogleg severity, production may be increased for the lifetime of the well, Para. [0194] of WEIDEMAN).
Claim 3 is rejected under 35 U.S.C. § 103 as being unpatentable over WEIDEMAN et al. (U.S. Patent Application Publication No. 2023/0151696 A1) in view of WESTON et al. (U.S. Patent Application Publication No. 2021/0026037 A1), and further in view of MAUS et al. (U.S. Patent Application Publication No. 2021/0381361 A1).
Regarding claim 3, WEIDEMAN as modified by WESTON discloses the method of claim 1 (as shown above), wherein the tool yield model is a regression model of drilling information for curved sections of boreholes of similar wells (in equipment comparison, data from different drilling operations (e.g., from drilling the wells 102, 104, 106, and 108) may be normalized and used to compare equipment wear, performance, and similar factors … for example, the same bit may have been used to drill the wells 102 and 106, but the drilling may have been accomplished using different parameters (e.g., rotation speed and WOB) … by normalizing the data, the two bits can be compared more effectively, Para. [0154] of WEIDEMAN; [at least wells 102 and 104 are located in a same region, which means they have that in common/similar wells]; See also in a curved section of the well, where the build rate may be a higher priority to achieve, it might make sense to orient off-bottom to ensure an ideal toolface while sliding, Para. [0303] of WEIDEMAN; See also FIGS. 1B & 1C of WEIDEMAN), the regression model including (model 4710 estimates can be “tuned” to match observed drill parameters received from the drill rig in the field … the model 4710 can provide the driller pro-active control rather than a reactive control over the rig, Para. [0436] of WEIDEMAN; See also fine-tuning can be accomplished using an artificial intelligence feedback loop where the model input can define the propagation functions, TCT number, and the three multipliers (M1, M2, and M3) before beginning a slide … as the slide progresses the drill controller can scale these appropriately based on sensor data feedback using an empirical model … the drilling controller in conjunction with the model and simulator can be used to tune the estimates in conjunction with feedback from the empirical model, Para. [0476] of WEIDEMAN; [model tuning is interpreted as corresponding to hyperparameter model tuning]) but appears to fail to explicitly disclose the term hyperparameter.
MAUS, however, is in the same field of data processing for optimizing the drilling process (Para. [0002] of MAUS) and teaches the model including hyperparameter (model may be described by physical parameters and hyperparameters, including parameters that characterize the frictional profiles of the system, Para. [0091] of MAUS; See also FIG. 8 of MAUS).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to modify the method of regression modeling tuning for drilling survey/optimization of WEIDEMAN as modified by WESTON with the hyperparameter modeling of MAUS [to arrive at the claimed features] for the purpose of optimizing the drilling process (Para. [0002] of MAUS).
Claims 5-11 are rejected under 35 U.S.C. § 103 as being unpatentable over WEIDEMAN et al. (U.S. Patent Application Publication No. 2023/0151696 A1) in view of WESTON et al. (U.S. Patent Application Publication No. 2021/0026037 A1), and further in view of PATINO VIRANO et al. (U.S. Patent Application Publication No. 2021/0081857 A1).
Regarding claim 5, WEIDEMAN as modified by WESTON discloses the method of claim 4 (as shown above) but appears to fail to explicitly disclose wherein retrieving drilling information obtained from offset wells includes identifying, as offset wells, wells with characteristics like the subject well that are within a radius, R, of the subject well.
PATINO VIRANO, however, is in the same modeling oil rig/drilling operations (Para. [0002] of PATINO VIRANO) and teaches wherein retrieving drilling information obtained from offset wells includes identifying, as offset wells, wells with characteristics like the subject well that are within a radius, R, of the subject well (geographic location data is obtained regarding a desired geographic location for a drilling rig in accordance with one or more embodiments … for example, geographic location data may correspond to global positioning system (GPS) coordinates or other information identifying a geographic region of interest … the geographic location information may also include a radius defining a coverage area of the desired geographic location, e.g., as multiple drilling sites may be available for one or more drilling rigs … moreover, the desired geographic location may correspond to one or more potential drilling locations in a particular geological region, Para. [0038] of PATINO VIRANO).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to modify the method of modeling for drilling survey/optimization of WEIDEMAN as modified by WESTON with the radius-based data collection of PATINO VIRANO [to arrive at the claimed features] for the purpose of detailing/reporting details the amount of time, cost, and risks associated with building and/or operating one or more wells at the potential drilling location (Para. [0016] of PATINO VIRANO).
Regarding claim 6, WEIDEMAN as modified by WESTON and PATINO VIRANO discloses the method of claim 5 (as shown above), wherein retrieving drilling information obtained from offset wells includes identifying, as offset wells, wells with characteristics like the subject well that are within a radius, R, of the subject well (geographic location data is obtained regarding a desired geographic location for a drilling rig in accordance with one or more embodiments … for example, geographic location data may correspond to global positioning system (GPS) coordinates or other information identifying a geographic region of interest … the geographic location information may also include a radius defining a coverage area of the desired geographic location, e.g., as multiple drilling sites may be available for one or more drilling rigs … moreover, the desired geographic location may correspond to one or more potential drilling locations in a particular geological region, Para. [0038] of PATINO VIRANO).
Regarding claim 7, WEIDEMAN as modified by WESTON and PATINO VIRANO discloses the method of claim 5 (as shown above), wherein identifying wells with characteristics like the subject well includes: querying a database to obtain drilling information associated with different wells (querying a database by internal modules, Para. [0197] of WEIDEMAN; See also the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled, Para. [0390] of WEIDEMAN); and filtering the drilling information to identify wells that used a similar bit type, size, and design as the subject well (the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled … likewise, information relating to formation characteristics, the bore hole assembly, and other parameters with historic information can be used as part of the control data set, Para. [0390] of WEIDEMAN; [searching and selecting data from the database is interpreted as drilling information]; [Examiner’s Note: “to identify” limitation is not positively recited and not given patentable weight]; See also control parameters may define the settings for various drilling operations that are to be executed by the drilling rig 110 to form the borehole, such as WOB, flow rate of mud, toolface orientation, and similar settings … the control parameters may also define particular equipment selections, such as a particular bit, Para. [0158] of WEIDEMAN; See also ASDS 4210 can also obtain, monitor, and consider the potential effects of equipment information, such as the type and size of drill bit being used, the BHA type and configuration, the BHA stabilizers and their location, the bend in a mud motor, whether the tool is a push the bit or pull the bit type of tool, and so forth, Para. [0396] of WEIDEMAN).
Regarding claim 8, WEIDEMAN as modified by WESTON and PATINO VIRANO discloses the method of claim 5 (as shown above), wherein identifying wells with characteristics like the subject well includes: querying a database to obtain drilling information associated with different wells (querying a database by internal modules, Para. [0197] of WEIDEMAN; See also the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled, Para. [0390] of WEIDEMAN); and filtering the drilling information to identify wells that used a similar tool size, type, and design as the subject well (the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled … likewise, information relating to formation characteristics, the bore hole assembly, and other parameters with historic information can be used as part of the control data set, Para. [0390] of WEIDEMAN; [searching and selecting data from the database is interpreted as drilling information]; [Examiner’s Note: “to identify” limitation is not positively recited and not given patentable weight]; See also control parameters may define the settings for various drilling operations that are to be executed by the drilling rig 110 to form the borehole, such as WOB, flow rate of mud, toolface orientation, and similar settings … the control parameters may also define particular equipment selections, such as a particular bit, Para. [0158] of WEIDEMAN; See also ASDS 4210 can also obtain, monitor, and consider the potential effects of equipment information, such as the type and size of drill bit being used, the BHA type and configuration, the BHA stabilizers and their location, the bend in a mud motor, whether the tool is a push the bit or pull the bit type of tool, and so forth, Para. [0396] of WEIDEMAN).
Regarding claim 9, WEIDEMAN as modified by WESTON and PATINO VIRANO discloses the method of claim 5 (as shown above), wherein identifying wells with characteristics like the subject well includes: querying a database to obtain drilling information associated with different wells (querying a database by internal modules, Para. [0197] of WEIDEMAN; See also the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled, Para. [0390] of WEIDEMAN); and filtering the drilling information to identify wells that used a similar borehole apparatus (BHA) as the subject well (the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled … likewise, information relating to formation characteristics, the bore hole assembly, and other parameters with historic information can be used as part of the control data set, Para. [0390] of WEIDEMAN; See also control parameters may define the settings for various drilling operations that are to be executed by the drilling rig 110 to form the borehole, such as WOB, flow rate of mud, toolface orientation, and similar settings … the control parameters may also define particular equipment selections, such as a particular bit, Para. [0158] of WEIDEMAN).
Regarding claim 10, WEIDEMAN as modified by WESTON discloses the method of claim 1 (as shown above), wherein the tool yield model is a regression model of drilling information of similar wells (the automated slide drilling system may be programmed to select a control data set based on one or more algorithms, such as linear or polynomial regression based on one or more parameters of the data sets in the database, Para. [0391] of WEIDEMAN; See also Para. [0103] & FIGS. 6 & 7 of WESTON) and wherein identifying wells like the subject well includes: querying a database to obtain the drilling information associated with different wells (querying a database by internal modules, Para. [0197] of WEIDEMAN; See also the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled, Para. [0390] of WEIDEMAN); filtering the drilling information to identify wells that (the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled … likewise, information relating to formation characteristics, the bore hole assembly, and other parameters with historic information can be used as part of the control data set, Para. [0390] of WEIDEMAN; [searching and selecting data from the database is interpreted as drilling information]; [Examiner’s Note: “to identify” limitation is not positively recited and not given patentable weight]; See also control parameters may define the settings for various drilling operations that are to be executed by the drilling rig 110 to form the borehole, such as WOB, flow rate of mud, toolface orientation, and similar settings … the control parameters may also define particular equipment selections, such as a particular bit, Para. [0158] of WEIDEMAN; See also ASDS 4210 can also obtain, monitor, and consider the potential effects of equipment information, such as the type and size of drill bit being used, the BHA type and configuration, the BHA stabilizers and their location, the bend in a mud motor, whether the tool is a push the bit or pull the bit type of tool, and so forth, Para. [0396] of WEIDEMAN); a similar tool size, type, and design as the subject well (the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled … likewise, information relating to formation characteristics, the bore hole assembly, and other parameters with historic information can be used as part of the control data set, Para. [0390] of WEIDEMAN; [searching and selecting data from the database is interpreted as drilling information]; [Examiner’s Note: “to identify” limitation is not positively recited and not given patentable weight]; See also control parameters may define the settings for various drilling operations that are to be executed by the drilling rig 110 to form the borehole, such as WOB, flow rate of mud, toolface orientation, and similar settings … the control parameters may also define particular equipment selections, such as a particular bit, Para. [0158] of WEIDEMAN; See also ASDS 4210 can also obtain, monitor, and consider the potential effects of equipment information, such as the type and size of drill bit being used, the BHA type and configuration, the BHA stabilizers and their location, the bend in a mud motor, whether the tool is a push the bit or pull the bit type of tool, and so forth, Para. [0396] of WEIDEMAN); and a similar borehole apparatus (BHA) as the subject well (the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled … likewise, information relating to formation characteristics, the bore hole assembly, and other parameters with historic information can be used as part of the control data set, Para. [0390] of WEIDEMAN; See also control parameters may define the settings for various drilling operations that are to be executed by the drilling rig 110 to form the borehole, such as WOB, flow rate of mud, toolface orientation, and similar settings … the control parameters may also define particular equipment selections, such as a particular bit, Para. [0158] of WEIDEMAN).
Although WEIDEMAN (as modified by WESTON) teaches geographic areas of wells having similar geological formation characteristics (Para. [0101] of WEIDEMAN), WEIDEMAN as modified by WESTON appears to fail to explicitly disclose identify wells that are within a radius R of the subject well and calculating a similarity score for each identified well; and if the similarity score is less than a threshold value, labeling the well as an offset well.
PATINO VIRANO, however, is in the same modeling oil rig/drilling operations (Para. [0002] of PATINO VIRANO) and teaches filtering the drilling information to identify wells that are within a radius R of the subject well (geographic location data is obtained regarding a desired geographic location for a drilling rig in accordance with one or more embodiments … for example, geographic location data may correspond to global positioning system (GPS) coordinates or other information identifying a geographic region of interest … the geographic location information may also include a radius defining a coverage area of the desired geographic location, e.g., as multiple drilling sites may be available for one or more drilling rigs … moreover, the desired geographic location may correspond to one or more potential drilling locations in a particular geological region, Para. [0038] of PATINO VIRANO) and calculating a similarity score for each identified well (synthetic rig operation data may be generated using one or more artificial intelligence algorithms with respect to a well profile and location using data from a similar well profile and location, Para. [0041] of PATINO VIRANO; See also FIGS. 4 & 5 of PATINO VIRANO); and if the similarity score is less than a threshold value, labeling the well as an offset well (MPEP 2111.04(II) recites: “[t]he broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met. For example, assume a method claim requires step A if a first condition happens and step B if a second condition happens. If the claimed invention may be practiced without either the first or second condition happening, then neither step A or B is required by the broadest reasonable interpretation of the claim”; [To avoid the contingent limitation interpretation, Examiner suggests replacing “if” (not required to occur) with “when” or “in response to” (required to occur at least once); See also synthetic rig operation data may be generated using one or more artificial intelligence algorithms with respect to a well profile and location using data from a similar well profile and location, Para. [0041] of PATINO VIRANO; See also FIGS. 4 & 5 of PATINO VIRANO).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to modify the method of modeling for drilling survey/optimization of WEIDEMAN as modified by WESTON with the radius-based data collection of PATINO VIRANO [to arrive at the claimed features] for the purpose of detailing/reporting details the amount of time, cost, and risks associated with building and/or operating one or more wells at the potential drilling location (Para. [0016] of PATINO VIRANO).
Regarding claim 11, WEIDEMAN as modified by WESTON and PATINO VIRANO discloses the method of claim 10 (as shown above), wherein the method further comprises: applying a regression model to the drilling information of sections of the offset well that curve to determine the tool yield model (programming to select a control data set based on polynomial regression based on one or more parameters of the data sets in the database, Para. [0391] of WEIDEMAN).
Claims 18-20 are rejected under 35 U.S.C. § 103 as being unpatentable over WEIDEMAN et al. (U.S. Patent Application Publication No. 2023/0151696 A1) in view of PATINO VIRANO et al. (U.S. Patent Application Publication No. 2021/0081857 A1), and further in view of MAUS et al. (U.S. Patent Application Publication No. 2021/0381361 A1).
Regarding claim 18, WEIDEMAN discloses a method of determining tool yield as a function of dogleg severity (DLS) for a drill string in a subject well (the path 744 may be rejected for an engineering reason (e.g., the path would require a dogleg of greater than allowed severity, Para. [0183] of WEIDEMAN; See also the optimization process may be applied to production by optimizing well smoothness and other factors affecting production … for example, by minimizing dogleg severity, production may be increased for the lifetime of the well, Para. [0194] of WEIDEMAN; See also obtain, monitor, and consider the effects of information regarding the borehole, such as its measured depth, its true vertical depth, the tortuosity of one or more portions of the borehole (existing or planned), the severity of doglegs, Para. [0396] of WEIDEMAN), the method comprising: querying a database to obtain drilling information associated with different wells (querying a database by internal modules, Para. [0197] of WEIDEMAN; See also the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled, Para. [0390] of WEIDEMAN); filtering the drilling information to identify wells from the database that are similar to the subject well (the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled … likewise, information relating to formation characteristics, the bore hole assembly, and other parameters with historic information can be used as part of the control data set, Para. [0390] of WEIDEMAN; [searching and selecting data from the database is interpreted as drilling information]; [Examiner’s Note: “to identify” limitation is not positively recited and not given patentable weight]; See also control parameters may define the settings for various drilling operations that are to be executed by the drilling rig 110 to form the borehole, such as WOB, flow rate of mud, toolface orientation, and similar settings … the control parameters may also define particular equipment selections, such as a particular bit, Para. [0158] of WEIDEMAN; See also ASDS 4210 can also obtain, monitor, and consider the potential effects of equipment information, such as the type and size of drill bit being used, the BHA type and configuration, the BHA stabilizers and their location, the bend in a mud motor, whether the tool is a push the bit or pull the bit type of tool, and so forth, Para. [0396] of WEIDEMAN); and applying a regression model (an error between the target value and the measured value is calculated … in some embodiments, the error may be measured across desired operational parameters … for example, the error may be calculated by the difference between a generated value using a model and the measured value of an operational parameter, by one or more sensors … based on the received data from the one or more sensors, the error may be measured by a linear regression model, Para. [0554] of WEIDEMAN; See also Para. [0103] & FIGS. 6 & 7 of WESTON; See also programming to select a control data set based on polynomial regression based on one or more parameters of the data sets in the database, Para. [0391] of WEIDEMAN) with (model 4710 estimates can be “tuned” to match observed drill parameters received from the drill rig in the field … the model 4710 can provide the driller pro-active control rather than a reactive control over the rig, Para. [0436] of WEIDEMAN; See also fine-tuning can be accomplished using an artificial intelligence feedback loop where the model input can define the propagation functions, TCT number, and the three multipliers (M1, M2, and M3) before beginning a slide … as the slide progresses the drill controller can scale these appropriately based on sensor data feedback using an empirical model … the drilling controller in conjunction with the model and simulator can be used to tune the estimates in conjunction with feedback from the empirical model, Para. [0476] of WEIDEMAN; [model tuning is interpreted as corresponding to hyperparameter model tuning]) to the drilling information of sections of the offset well that curve (in equipment comparison, data from different drilling operations (e.g., from drilling the wells 102, 104, 106, and 108) may be normalized and used to compare equipment wear, performance, and similar factors … for example, the same bit may have been used to drill the wells 102 and 106, but the drilling may have been accomplished using different parameters (e.g., rotation speed and WOB) … by normalizing the data, the two bits can be compared more effectively, Para. [0154] of WEIDEMAN; [at least wells 102 and 104 are located in a same region, which means they have that in common/similar wells]; See also in a curved section of the well, where the build rate may be a higher priority to achieve, it might make sense to orient off-bottom to ensure an ideal toolface while sliding, Para. [0303] of WEIDEMAN; See also FIGS. 1B & 1C of WEIDEMAN).
WEIDEMAN appears to fail to explicitly disclose identify wells that are within a radius R of the subject well and calculating a similarity score for each identified well; and if the similarity score is less than a threshold value, labeling the well as an offset well.
PATINO VIRANO, however, is in the same modeling oil rig/drilling operations (Para. [0002] of PATINO VIRANO) and teaches filtering the drilling information to identify wells that are within a radius R of the subject well (geographic location data is obtained regarding a desired geographic location for a drilling rig in accordance with one or more embodiments … for example, geographic location data may correspond to global positioning system (GPS) coordinates or other information identifying a geographic region of interest … the geographic location information may also include a radius defining a coverage area of the desired geographic location, e.g., as multiple drilling sites may be available for one or more drilling rigs … moreover, the desired geographic location may correspond to one or more potential drilling locations in a particular geological region, Para. [0038] of PATINO VIRANO) and calculating a similarity score for each identified well (synthetic rig operation data may be generated using one or more artificial intelligence algorithms with respect to a well profile and location using data from a similar well profile and location, Para. [0041] of PATINO VIRANO; See also FIGS. 4 & 5 of PATINO VIRANO); and if the similarity score is less than a threshold value, labeling the well as an offset well (MPEP 2111.04(II) recites: “[t]he broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met. For example, assume a method claim requires step A if a first condition happens and step B if a second condition happens. If the claimed invention may be practiced without either the first or second condition happening, then neither step A or B is required by the broadest reasonable interpretation of the claim”; [To avoid the contingent limitation interpretation, Examiner suggests replacing “if” (not required to occur) with “when” or “in response to” (required to occur at least once); See also synthetic rig operation data may be generated using one or more artificial intelligence algorithms with respect to a well profile and location using data from a similar well profile and location, Para. [0041] of PATINO VIRANO; See also FIGS. 4 & 5 of PATINO VIRANO).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to modify the method of modeling for drilling survey/optimization of WEIDEMAN with the radius-based data collection of PATINO VIRANO [to arrive at the claimed features] for the purpose of detailing/reporting details the amount of time, cost, and risks associated with building and/or operating one or more wells at the potential drilling location (Para. [0016] of PATINO VIRANO).
In addition, WEIDEMAN as modified by PATINO VIRANO appears to fail to explicitly disclose the term hyperparameter.
MAUS, however, is in the same field of data processing for optimizing the drilling process (Para. [0002] of MAUS) and teaches the model including hyperparameter (model may be described by physical parameters and hyperparameters, including parameters that characterize the frictional profiles of the system, Para. [0091] of MAUS; See also FIG. 8 of MAUS).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to modify the method of regression modeling tuning for drilling survey/optimization of WEIDEMAN as modified by PATINO VIRANO with the hyperparameter modeling of MAUS [to arrive at the claimed features] for the purpose of optimizing the drilling process (Para. [0002] of MAUS).
Regarding claim 19, WEIDEMAN as modified by PATINO VIRANO and MAUS discloses the method of claim 18 (as shown above), wherein filtering the drilling information to identify wells from the database that are like the subject well includes filtering the identified wells to find wells that have one or more of: a similar bit type, size, and design as the subject well (the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled … likewise, information relating to formation characteristics, the bore hole assembly, and other parameters with historic information can be used as part of the control data set, Para. [0390] of WEIDEMAN; [searching and selecting data from the database is interpreted as drilling information]; [Examiner’s Note: “to identify” limitation is not positively recited and not given patentable weight]; See also control parameters may define the settings for various drilling operations that are to be executed by the drilling rig 110 to form the borehole, such as WOB, flow rate of mud, toolface orientation, and similar settings … the control parameters may also define particular equipment selections, such as a particular bit, Para. [0158] of WEIDEMAN; See also ASDS 4210 can also obtain, monitor, and consider the potential effects of equipment information, such as the type and size of drill bit being used, the BHA type and configuration, the BHA stabilizers and their location, the bend in a mud motor, whether the tool is a push the bit or pull the bit type of tool, and so forth, Para. [0396] of WEIDEMAN); a similar tool size , type, and design as the subject well (the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled … likewise, information relating to formation characteristics, the bore hole assembly, and other parameters with historic information can be used as part of the control data set, Para. [0390] of WEIDEMAN; [searching and selecting data from the database is interpreted as drilling information]; [Examiner’s Note: “to identify” limitation is not positively recited and not given patentable weight]; See also control parameters may define the settings for various drilling operations that are to be executed by the drilling rig 110 to form the borehole, such as WOB, flow rate of mud, toolface orientation, and similar settings … the control parameters may also define particular equipment selections, such as a particular bit, Para. [0158] of WEIDEMAN; See also ASDS 4210 can also obtain, monitor, and consider the potential effects of equipment information, such as the type and size of drill bit being used, the BHA type and configuration, the BHA stabilizers and their location, the bend in a mud motor, whether the tool is a push the bit or pull the bit type of tool, and so forth, Para. [0396] of WEIDEMAN); a similar borehole apparatus (BHA) as the subject well (the automated slide drilling system may be coupled to a database which may include historical data from other wells … data in the database may include … one or more control data elements … automated slide drilling system may be programmed to search the database and select the control data set for the entry at that measured depth with the same or substantially similar difference between the most recent toolface and the target toolface orientation as determined in the wellbore being drilled … likewise, information relating to formation characteristics, the bore hole assembly, and other parameters with historic information can be used as part of the control data set, Para. [0390] of WEIDEMAN; See also control parameters may define the settings for various drilling operations that are to be executed by the drilling rig 110 to form the borehole, such as WOB, flow rate of mud, toolface orientation, and similar settings … the control parameters may also define particular equipment selections, such as a particular bit, Para. [0158] of WEIDEMAN); a similar rotary steering system (RSS) as the subject well (equipment data 140 may include any equipment information, such as drilling rig configuration (e.g., rotary table or top drive), Para. [0106] of WEIDEMAN; See also class may be based on the following components and sub-models: a drill bit model, a borehole model, a rig surface gear model, a mud pump model, a WOB/differential pressure model, a positional/rotary model, Para. [0231] of WEIDEMAN); a similar inclination as the planned inclination with respect to measured depth of the drill string (drill bit trajectory may be specified as an inclination and an azimuth angle, Para. [0232] of WEIDEMAN; See also as shown in FIG. 20 , the inputs include formation hardness/USC 2010, formation structure 2012, inclination 2014, Para. [0296] of WEIDEMAN); and a similar true vertical depth (TVD) as the planned TVD with respect to measured depth of the subject well (ASDS 4210 can obtain, monitor, and consider the effects of information regarding the borehole, such as its measured depth, its true vertical depth, Para. [0396] of WEIDEMAN).
Regarding claim 20, WEIDEMAN as modified by WESTON and PATINO VIRANO discloses the method of claim 18 (as shown above), wherein the regression model (an error between the target value and the measured value is calculated … in some embodiments, the error may be measured across desired operational parameters … for example, the error may be calculated by the difference between a generated value using a model and the measured value of an operational parameter, by one or more sensors … based on the received data from the one or more sensors, the error may be measured by a linear regression model, Para. [0554] of WEIDEMAN; See also Para. [0103] & FIGS. 6 & 7 of WESTON; See also programming to select a control data set based on polynomial regression based on one or more parameters of the data sets in the database, Para. [0391] of WEIDEMAN) includes (model 4710 estimates can be “tuned” to match observed drill parameters received from the drill rig in the field … the model 4710 can provide the driller pro-active control rather than a reactive control over the rig, Para. [0436] of WEIDEMAN; See also fine-tuning can be accomplished using an artificial intelligence feedback loop where the model input can define the propagation functions, TCT number, and the three multipliers (M1, M2, and M3) before beginning a slide … as the slide progresses the drill controller can scale these appropriately based on sensor data feedback using an empirical model … the drilling controller in conjunction with the model and simulator can be used to tune the estimates in conjunction with feedback from the empirical model, Para. [0476] of WEIDEMAN; [model tuning is interpreted as corresponding to hyperparameter model tuning]). As noted in the mapping of claim 18, MAUS teaches the model including hyperparameter (model may be described by physical parameters and hyperparameters, including parameters that characterize the frictional profiles of the system, Para. [0091] of MAUS; See also FIG. 8 of MAUS).
Conclusion
The prior art previously made of record and not relied upon is considered pertinent to applicant's disclosure:
SAMUEL (U.S. Patent Application Publication No. 2018/0003031 A1) teaches, at Para. [0020], generates a display on interactive user interface 214 of the relevant information, e.g., measurement logs, borehole trajectory, drill string trajectory, or recommended drilling parameters to optimize a trajectory to limit estimated dogleg severity … commands may alter the settings of the steering mechanism 206.
SUMMERS et al. (U.S. Patent Application Publication No. 2017/0306702 A1) teaches, at Para. [0053], system may display suggested drilling operating parameters to the driller on a user interface (or execute the drilling operating parameters automatically) with higher-frequency toolface fluctuation (e.g., by varying WOB or by alternating between slide drilling and rotary drilling) to reduce dogleg severity.
SHEN et al. (U.S. Patent Application Publication No. 2018/0119535 A1) teaches, at Para. [0035], system may recommend a drilling parameter change based on high lateral/axial/torsional vibrations detected, poor borehole quality, challenging formation drilling (formation information based on LWD, mud logging, and the look-ahead detection of LWD), poor directional control, poor weight distribution between bit and reamer, an undesired neutral point depth, and mild drillstring buckling.
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/JOHN P HOCKER/Examiner, Art Unit 2189
/REHANA PERVEEN/Supervisory Patent Examiner, Art Unit 2189
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