DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The amendment filed 08/20/2026 has been entered. As directed, claims 1, 7 and 19-21 have
been amended, claims 9, 11-13 and 22 have been canceled and no claim has been added. Thus, claims 1-8, 10, and 14-21 remain pending in the application.
In the prior Office Action, the Examiner indicated allowable subject matter in dependent claim 22. At that time, claim 22 depended from claim 21, which in turn depended from claim 1. Thus, the subject matter of claim 22 was previously presented and examined in combination with the limitations of both claims 1 and 21. During the subsequent interview, Applicant proposed incorporating subject matter of claim 22 into the independent claims while omitting the intervening subject matter of claim 21. The Examiner indicated that the proposed amendment appeared to overcome the prior rejection under 35 U.S.C. § 103, while also identifying potential issues under 35 U.S.C. § 112(b) and indicating that further consideration and search would be required upon submission.
Upon review of the amendment as actually filed, the Examiner notes that the amended independent claims do not merely reproduce the previously examined dependent claim combination. Applicant incorporated subject matter previously recited in claim 22 while omitting the intervening subject matter of claim 21 and further changed the functional relationships among the modeled loads, the plurality of friction factor values, and the friction factor track. In particular, the amended claims no longer recite that the plurality of modeled loads corresponds to a plurality of different friction factor values and now recite that generating the friction factor track comprises generating the slackoff, pickup, and torque friction factor values based upon comparisons between respective drillstring load values and one or more modeled loads, and the subsequently recited automatic determination is now based upon a friction factor track comprising friction factor values generated from the recited comparisons. Accordingly, the amendment materially changes the scope and ordered relationship of the claimed operations. Because the prior subject matter eligibility determination was based upon the prior claim structure and ordered combination, Applicant’s amendment necessitates a renewed eligibility analysis of the presently claimed combination. The presently amended claims have accordingly been reevaluated as a whole, and a new rejection under 35 U.S.C. § 101 is set forth below.
Furthermore, the same amendments present a materially different combination for purposes of prior art examination. The subject matter of claim 22 was previously examined only in combination with the limitations of claims 1 and 21, whereas the presently amended independent claims omit the intervening limitations of claim 21 and include the modified relationships identified above. Further consideration and search of this newly presented combination resulted in identification of additional prior art not relied upon in the prior rejection. Accordingly, a new ground of rejection under 35 U.S.C. § 103 based on the newly applied prior art is set forth below.
Furthermore, the amendment changes the relationship between the plurality of friction factor values now recited in claim 1 and the friction factor values further recited in claim 21. This amended relationship presents new issues under 35 U.S.C. § 112(b), which are addressed below.
Response to Arguments
Applicant’s arguments, see “Applicant Arguments/Remarks Made in an Amendment”, filed
08/20/2026, with respect to the rejection(s) of claim(s) 1, 19 and 20 under 35 U.S.C. § 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of the newly found prior art reference(s).
As explained above under Response to Amendment, the amendment presents a materially different claimed combination and changes the relationships among the modeled loads, generated friction factor values, and friction factor track. Further consideration and search of the calms as presently amended resulted in the identification of additional prior art and a new ground of rejection. The present rejection under 35 U.S.C. § 103 does not rely on the prior art combination challenged by Applicant and instead is based on the newly applied references set forth below.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-8, 10, and 14-21 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second
paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites “… automatically determining a friction factor value of the slackoff no rotation run in hole friction factor value, the slackoff no rotation drilling friction factor value, the pickup no rotation drilling friction factor value, the pickup no rotation pull out of hole friction factor value, and the torque friction factor value …” which is indefinite because it is unclear if the limitation refers to determining one of the five friction factor values, each of the five friction factor values, or another friction factor value derived from or associated with the five recited friction factor values. For the purposes of examination, it is interpreted as at least one of friction factor value associated with the five recited friction factor values based upon the friction factor track.
Claims 19 and 20 also recite “a friction factor of,” and are rejected for the same reason.
Claim 21 recites “dynamically adjusting one or more friction factor values of the plurality of different friction factor values that correspond to a respective modeled load of the plurality of modeled loads to generate dynamically adjusted friction factor values at a time increment or time increments basis behind real-time, wherein dynamically adjusting the one or more friction factor values is performed utilizing a statistical approach considering deviations about a mean to provide for more accurate estimates of the one or more friction factor values,” which is indefinite because it is unclear how the recited dynamically adjusted friction factor values relate to the friction factor values generated in the friction factor track and whether the dynamically adjusted values replace or update those friction factor values in the friction factor track. It is also unclear how the dynamically adjusted friction factor values relate to the friction factor value subsequently automatically determined based on the friction factor track in claim 1. For the purposes of examination, the limitation is interpreted as dynamically adjusting one or more of the plurality of different friction factor values recited in claim 1 according to the recited statistical approach to generate dynamically adjusted friction factor values corresponding to respective modeled loads.
The remaining claims are dependent upon one of the claims listed above and are rejected for the same reason.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
The claim(s) 1-8, 10, and 14-21 are rejected under 35 USC § 101 because the claimed invention is
directed to judicial exception an abstract idea, it has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception. Examiner has evaluated the claims under the framework provided in the 2019 Patent Eligibility Guidance published in the Federal Register 01/07/2019 and has provided such analysis below.
Step 1: Are the claims to a process, machine, manufacture or composition of matter?"
Yes, Claims 1-8, 10, and 14-18 and 21 are directed to method and fall within the statutory category of processes;
Yes, Claim 19 is directed to system and falls within the statutory category of machine;
Yes, Claim 20 is directed to non-transitory computer-readable medium and falls within the statutory category of article of manufactures.
In order to evaluate the Step 2A inquiry "Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?" we must determine, at Step 2A Prong 1, whether the claim recites a law of nature, a natural phenomenon or an abstract idea and further whether the claim recites additional elements that integrate the judicial exception into a practical application.
Step 2A Prong 1: The claim 1 does recite a mental process.
As explained in MPEP 2106.04(a)(2)(III): Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer").
Further, as explain in MPEP 2106.04(a)(2)(III)(A): In contrast, claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include: • a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016); …
Further, as explain in MPEP 2106.04(a)(2)(III)(C): 1. Performing a mental process on a generic computer. An example of a case identifying a mental process performed on a generic computer as an abstract idea is Voter Verified, Inc. v. Election Systems & Software, LLC, 887 F.3d 1376, 1385, 126 USPQ2d 1498, 1504 (Fed. Cir. 2018) … 2. Performing a mental process in a computer environment. An example of a case identifying a mental process performed in a computer environment as an abstract idea is Symantec Corp., 838 F.3d at 1316-18, 120 USPQ2d at 1360 … 3. Using a computer as a tool to perform a mental process. An example of a case in which a computer was used as a tool to perform a mental process is Mortgage Grader, 811 F.3d. at 1324, 117 USPQ2d at 1699.
Claim 1: the limitations of “determining a drillstring load based on at least a portion of the data; comparing the drillstring load to a plurality of modeled loads, wherein the plurality of modeled loads depend on the specified drillstring, the specified borehole, and at least a portion of the survey data;,” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation (BRI) in light of specification, covers performance of the limitation in the human mind.
For example, a person is capable of observing rig operational information, identifying or deriving from that information a drillstring load value, and comparing the identified drillstring load value with multiple reference load values associated with the particular drillstring and borehole and at least in part on the survey information. The steps include observation, evaluation, judgment, and reasoning processes that can be performed mentally or with the aid of pen and paper. (The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).).
Examiner note: The claimed limitation is broadly recited and does not require any particular computer implementation or degree of processing complexity that would prevent the limitation from being performed in the human mind. See MPEP 2106.04(a)(2)(III).
Further, Claim 1: the limitations of “generating a friction factor track derived from the plurality of modeled loads in real-time responsive to the data acquired during the rig operations to account for changes in one or more rig parameters or changes in mud weight or string conditions in conjunction with the rig operations, wherein the friction factor track comprises a plurality of different friction factor values generated with respect to a time domain or a depth domain related to a depth of a drill bit, wherein the plurality of different friction factor values comprises a slackoff no rotation run in hole friction factor value, a slackoff no rotation drilling friction factor value, a pickup no rotation drilling friction factor value, a pickup no rotation pull out of hole friction factor value, and a torque friction factor value, and wherein generating the friction factor track comprises:
generating the slackoff no rotation run in hole friction factor value and the slackoff no rotation drilling friction factor value based upon a comparison of a hook load slackoff value as the drillstring load with at least one modeled load of the plurality of modeled loads;
generating the pickup no rotation drilling friction factor value and the pickup no rotation pull out of hole friction factor value based upon a comparison of a hook load pickup value as the drillstring load with at least one modeled load of the plurality of modeled loads; and
generating the torque friction factor value based upon a comparison of a torque loss value as the drillstring load with at least one modeled load of the plurality of modeled loads,” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation (BRI) in light of specification, covers performance of the limitation in the human mind.
For example, a person is capable of reviewing multiple reference load values and, as rig operations proceed and new operational information becomes available, observing changes in rig parameters, mud weight or drillstring conditions, comparing observed slackoff hook load , pickup hook load, and torque loss values with one or more of the reference load values, identifying from those comparisons corresponding friction factor values, and recording the identified friction factor values in a continuing written record according to time or drill bit related depth. The steps include observation, evaluation, judgment, and reasoning processes that can be performed mentally or with the aid of pen and paper. (The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).).
Examiner note: The claimed limitation is broadly recited and does not require any particular computer implementation or degree of processing complexity that would prevent the limitation from being performed in the human mind. See MPEP 2106.04(a)(2)(III). Although the limitation recites generating the friction factor track “in real-time responsive to the data acquired during the rig operations,” the claim does not require any particular processing speed, update frequency, data volume, or other machine specific implementation that would preclude the mental performance.
Further, Claim 1: the limitations of “automatically determining a friction factor value of the slackoff no rotation run in hole friction factor value, the slackoff no rotation drilling friction factor value, the pickup no rotation drilling friction factor value, the pickup no rotation pull out of hole friction factor value, and the torque friction factor value that corresponds to the drillstring load in a time responsive to the data acquired during the rig operations based upon the friction factor track in place of a broomstick plot,” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation (BRI) in light of specification, covers performance of the limitation in the human mind.
For example, a person is capable of reviewing the friction factor values recorded for the slackoff, pickup, and torque conditions as rig operational information becomes available, observing the drillstring load at a particular time, identifying from the recorded friction factor values a friction factor value that corresponds to the drillstring load value at the particular time, rather than a broomstick plot. The steps include observation, evaluation, judgment, and reasoning processes that can be performed mentally or with the aid of pen and paper. (The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011).).
Examiner note: The claimed limitation is broadly recited and does not require any particular computer implementation or degree of processing complexity that would prevent the limitation from being performed in the human mind. See MPEP 2106.04(a)(2)(III). Although the limitation recites determining a friction factor value “automatically,” this merely requires computer implementation of the recited determination and does not require any particular processing speed, update frequency, data volume, or other machine specific implementation that would preclude the mental performance.
Claims 19 and 20 recite the similar elements as claim 1, and are rejected for the same reasons under 35 U.S.C. 101.
Therefore, claims 1, 19 and 20 recite judicial exceptions. The claims have been identified to recite judicial exceptions, Step 2A Prong 2 will evaluate whether the claims as a whole integrates the exception into a practical application of that exception.
Step 2A Prong 2: Claims 1, 19 and 20: The judicial exception is not integrated into a practical application.
In particular, the claims recite the following additional limitations, “A system comprising: a processor; memory accessible by the processor; processor-executable instructions stored in the memory and executable to instruct the system to: ” and " One or more non-transitory computer-readable storage media comprising processor-executable instructions to instruct a computing system to:,” which are merely recitations of instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to implement the judicial exception, which does not integrate judicial exception into a practical application (see MPEP § 2106.05(f)). As explained in MPEP § 2106.05(f)(2): Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.
Further, the following additional limitation, “acquiring data during rig operations for a specified drillstring for drilling a specified borehole in a geologic environment, wherein the data comprise downhole survey data,” are merely a recitation of insignificant extra-solution activity such as data gathering (i.e., collecting data), which does not integrate a judicial exception into practical application. See MPEP § 2106.05(g).
Further, the limitation “automatically issuing a control signal to alter operation of at least one subsystem of a drilling rig performing the rig operations when the friction factor value exceeds a threshold to reduce a risk of the drill bit becoming stuck, damage to the specified borehole, or damage to the specified drillstring.”
The limitation is merely adding the words "apply it" (or an equivalent) with the judicial exception, or instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). The limitation merely recites, at a high level of generality, automatically issuing a control signal to perform an unspecified alteration of a drilling rig subsystem when the recited threshold condition is satisfied. The claim does not recite any particular physical operation of the drilling rig actually be performed in response to the control signal, or any particular technical manner in which the control signal causes a physical alteration of the drilling operation to reduce the recited risk. Thus, the limitation merely apply a generic computer or computing components to issue a control signal for the subsystem and does not impose a meaningful limit on the judicial exception or otherwise integrated the judicial exception into a practical application.
Therefore, "Do the claims recite additional elements that integrate the judicial exception into a practical application? No, these additional elements do not integrate the abstract idea into a practical application and they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
After having evaluated the inquiries set forth in Steps 2A Prong 1 and 2, it has been concluded that claims 1, 19 and 20 not only recite a judicial exception but that the claims are directed to the judicial exception as the judicial exception has not been integrated into practical application.
Step 2B: Claims 1, 19 and 20: The claims do not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than generic computing components which do not amount to significantly more than the abstract idea. Limitations that the courts have found not to be enough to qualify as "significantly more" when recited in a claim with a judicial exception include:
i. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
iii. Adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) (see MPEP § 2106.05(g)); or
iv. Generally linking the use of the judicial exception to a particular technological environment or field of use, e.g., a claim describing how the abstract idea of hedging could be used in the commodities and energy markets, as discussed in Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1010 (2010) or a claim limiting the use of a mathematical formula to the petrochemical and oil-refining fields, as discussed in Parker v. Flook, 437 U.S. 584, 588-90, 198 USPQ 193, 197-98 (1978) (MPEP § 2106.05(h)).
Further, 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, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); … ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); …; iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log); iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; v. Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d 1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir. 2014) (optical character recognition); …
In particular, the additional limitations, when considered individually and in combination, do not amount to significantly more than the judicial expectation. The data acquisition and generic computer limitations merely collect information and computer implementation for performing the recited mental processes. The control signal limitation is recited at a high level of generality and does not require any particular physical alteration of the drilling operation or specific technical manner of control. Accordingly, the addition limitations do not provide an inventive concept sufficient to transform the judicial exception into patent eligible subject matter.
Therefore, "Do the claims recite additional elements that amount to significantly more than the judicial exception? No, these additional elements, alone or in combination, do not amount to significantly more than the judicial exception. Having concluded analysis within the provided framework, claims 1, 19 and 20 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Dependent claims 2-8, 10, 14-18, and 21 are also similar rejected under same rationale as cited above wherein these claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. These claims are merely further elaborate the mental process itself (and/or mathematical operations) or providing additional definition of process which does not impose any meaningful limits on practicing the abstract idea. Claims 2-8, 10, 14-18, and 21 are also rejected for incorporating the deficiency of their independent claim 1.
Claim 2 recites “The method of claim 1, wherein the drillstring load comprises a directional load.”
The limitation further defines the drillstring load as including a directional load and thus merely further specifies the information evaluated in the mental process recited in claim 1. Therefore, the office finds that the claim 2 is ineligible under 35 U.S.C. § 101.
Claim 3 recites “The method of claim 2, wherein the directional load comprises a pickup direction load.”
The limitation further defines the directional load as including a pickup direction load and thus merely further specifies the information evaluated in the mental process recited in claim 1. Therefore, the office finds that the claim 3 is ineligible under 35 U.S.C. § 101.
Claim 4 recites “The method of claim 2, wherein the directional load comprises a slackoff direction load.”
The limitation further defines the directional load as including a slackoff direction load and thus merely further specifies the information evaluated in the mental process recited in claim 1. Therefore, the office finds that the claim 4 is ineligible under 35 U.S.C. § 101.
Claim 5 recites “The method of claim 1, wherein the drillstring load comprises a rotational load.”
The limitation further defines the drillstring load as including rotational load and thus merely further specifies the information evaluated in the mental process recited in claim 1.Therefore, the office finds that the claim 5 is ineligible under 35 U.S.C. § 101.
Claim 6 recites “The method of claim 1, wherein the drillstring load corresponds to a stand of the specified drillstring.”
The limitation further specifies the informational relationship of the drillstring load evaluated in claim 1 by associating the load with a particular stand of the drillstring and thus merely further specifies the information evaluated in the mental process recited in claim 1. Therefore, the office finds that the claim 6 is ineligible under 35 U.S.C. § 101.
Claim 7 recites “The method of claim 1, comprising repeating the acquiring, determining, comparing, and automatically determining on a stand-by-stand basis for stands of the specified drillstring.”
The limitation merely requires repeating the data gather and mental process steps recited in claim 1 on a stand-by stand basis. The stand-by-stand requirement only specifies the basis on which the same activities are repeated and does not add a separate technological operation. Therefore, the office finds that the claim 7 is ineligible under 35 U.S.C. § 101.
Claim 8 recites “The method of claim 1, comprising detecting an activity state based on the at least a portion of the data, wherein the activity state comprises a pickup state or a slackoff state.”
The limitation merely specifies evaluating at least a portion of the acquired information to identify whether the drilling activity corresponds to a pickup state or slackoff state. It is merely an extensional mental process (e.g., identifying a state based on rig operation information). See MPEP 2106.04(a)(2)(III). Therefore, the office finds that the claim 8 is ineligible under 35 U.S.C. § 101.
Claim 10 recites “The method of claim 1, comprising rendering the friction factor value to a display with respect to time or with respect to depth.”
The limitation specifies displaying or outputting data to a generic display device. Thus, it merely a recitation of insignificant extra-solution activity such as data outputting or insignificant application (i.e., displaying data with respect to time or depth), which does not integrate a judicial exception into practical application. See MPEP § 2106.05(g). Therefore, the office finds that the claim 10 is ineligible under 35 U.S.C. § 101.
Claim 14 recites “The method of claim 1, comprising determining a model-based free rotate load.”
The limitation merely further specifies determining a model-based free rotate load. It is merely an extension of mental process (e.g., identifying a free rotate load value). See MPEP 2106.04(a)(2)(III). Therefore, the office finds that the claim 14 is ineligible under 35 U.S.C. § 101.
Claim 15 recites “The method of claim 14, wherein the data comprises a sensed free rotate load.”
The limitation merely further specifies that the acquired data include a sensed free rotate load. Thus, it merely a recitation of insignificant extra-solution activity such as data gathering (i.e., collected data include sensed free rotate load), which does not integrate a judicial exception into practical application. See MPEP § 2106.05(g). Therefore, the office finds that the claim 15 is ineligible under 35 U.S.C. § 101.
Claim 16 recites “The method of claim 15, comprising rendering a representation of the model-based free rotate load and the sensed free rotate load to a display.”
The limitation merely further specifies rendering representations of the model-based free rotate load and the sensed free rotated load to a display. Thus, it merely a recitation of insignificant extra-solution activity such as data outputting or insignificant application (i.e., displaying data) which do not integrate a judicial exception into practical application. See MPEP § 2106.05(g). Therefore, the office finds that the claim 16 is ineligible under 35 U.S.C. § 101.
Claim 17 recites “The method of claim 15, comprising comparing the model-based free rotate load and the sensed free rotate load and issuing an alarm based at least in part on the comparing.”
The limitation merely further specifies comparing the model-based free rotate load with the sensed free rotate load and issuing alarm based on the result of comparison. Thus, it merely an extension of mental process and insignificant extra-solution activity such as data outputting (i.e., outputting/issuing a notification), which do not integrate a judicial exception into practical application. See MPEP § 2106.05(g). Therefore, the office finds that the claim 17 is ineligible under 35 U.S.C. § 101.
Claim 18 recites “The method of claim 1, wherein the drillstring load comprises a pickup load and a slackoff load, and comprising rendering a plurality of pickup loads and slackoff loads with respect to time and/or with respect to depth.”
The limitation merely further specifies the drillstring load as including pickup and slackoff load, and rending a plurality of the pickup and slackoff loads with respect to time and/or depth. Thus, it merely an extension of mental process and insignificant extra-solution activity such as data outputting (i.e., displaying data respect to time or depth), which do not integrate a judicial exception into practical application. See MPEP § 2106.05(g). Therefore, the office finds that the claim 18 is ineligible under 35 U.S.C. § 101.
Claim 21 recites “The method of claim 1, further comprising dynamically adjusting one or more friction factor values of the plurality of different friction factor values that correspond to a respective modeled load of the plurality of modeled loads to generate dynamically adjusted friction factor values at a time increment or time increments basis behind real-time, wherein dynamically adjusting the one or more friction factor values is performed utilizing a statistical approach considering deviations about a mean to provide for more accurate estimates of the one or more friction factor values.”
The limitation further specifies adjusting numerical friction factor values using a statistical approach that considers deviations about a mean to provide more accurate fraction factor estimates. Thus, the limitation recites a mathematical concept with statistical calculation and evaluation of numerical values. The limitation “dynamically adjusting …,” merely adding the words "apply it" (or an equivalent) with the judicial exception, or instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See MPEP 2106.05(f). Therefore, the office finds that the claim 21 is ineligible under 35 U.S.C. § 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and
103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set
forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-6, 8, 10, and 14-20 are rejected under 35 U.S.C. 103 as being unpatentable over
Forshaw US20210340856A1 in view of Ho US5044198A and Bimastianto (“Digital Twin Implementation on Current Development Drilling, Benefits and Way Forward,” published in 2020).
Claim 1, Forshaw teaches A method comprising:
acquiring data during rig operations for a specified drillstring for drilling a specified borehole in a geologic environment, ([0042] At block 304, the processing system 12 acquires measured torque and drag parameters during performing the upstream well construction operation. For example, as the BHA 13 moves along the borehole 2, the raw data is collected, for example by the measurement tools 11, and transmitted to the surface 3 or a measurement device at the surface for additional processing or display by the processing system 12. See also Figure.1; [0026]-[0027]);
determining a drillstring load based on at least a portion of the data ([0038] … To determine the torque and drag parameters, a three-step approach is applied: a) determine the features from the surface measurements, b) classify the current observation based on the features, c) quantify the torque and drag parameter for the certain classes … As an example, the quantification averages the hookload during the period the current observation is classified to be pick up drag in order to determine the torque and drag parameter “pick up weight measurement.” [0060] The pickup weight is the weight measured when the whole drillstring is moved up without rotation.);
comparing the drillstring load to a plurality of modeled loads, wherein the plurality of modeled loads depend on the specified drillstring, the specified borehole, and ([0050] Prior to drilling the borehole 2, torque and drag values can be modeled for different depths along the projected path of the borehole 2. In particular, the modeled values for indicated (i.e., what is seen at the surface 3) hookloads for torque and drag, using different friction factors for the openhole section, take into account the wellbore geometry (both diameters and trajectory) as well as basic physics pertaining to the buoyancy of the drill string within the drilling fluid. [0053] … This friction force (0.29) is determined by comparing the measured hookload at a particular sample time (i.e., 1200 hrs) to the expected (modeled) friction force curves as shown in FIGS. 5A, 5B, and 6.);
generating a friction factor track derived from the plurality of modeled loads in real-time responsive to the data acquired during the rig operations ([0043] … As described in more detail with reference to FIG. 6, the friction factors are interpolated between expected (modeled) curves generated during the modeling (block 302) and the measured torque and drag parameters that are sampled while performing the upstream well construction operation (block 304). [0036] … The techniques provided herein utilize real-time and/or near-real-time physics-based modeling in combination with real-time and/or near-real-time parameter sampling as described herein to interpolate those samples and produce a friction factor for each of the discrete samples. [0044] At block 308, the processing system 12 transposes the friction factors at the different sampling times for the measured torque and drag parameters to a time-based series.), wherein the friction factor track comprises a plurality of different friction factor values generated with respect to a time domain or a depth domain related to a depth of a drill bit ([0053] … For example, at sampling time 1200 hours, a pickup hookload is measured to be 36, and the friction force is interpolated to be 0.29. [0054] As another example, at sampling time 1300 hours, a pickup hookload is measured to be 37, and the friction force is interpolated to be 0.21. [0055] … The graph 700 depicts the friction factors interpolated in FIG. 6 as unit less values plotted versus sample time … the friction factors at the different sampling times for the measured torque and drag parameters are transposed to a time-based series depicted by the graph 700.),
wherein the plurality of different friction factor values comprises a slackoff no rotation ([0057] … The graph 820 plots friction forces including a pickup friction force (i.e., pickFF_num), a slackoff friction force (i.e., slackFF_num), a torque friction force (i.e., torqueFF_num), average friction force (i.e., avgFF_num), and friction force standard deviation e(i.e., ffSTD_num). [0060] The pickup weight is the weight measured when the whole drillstring is moved up without rotation. [0064] The slack off weight is the weight measured when the whole drillstring is moved down without rotation. See also [0043]), and wherein generating the friction factor track comprises:
generating the slackoff no rotation ([0064] The slack off weight is the weight measured when the whole drillstring is moved down without rotation. [0050] Examples of such torque and drag parameters as shown in FIG. 5A (and also FIG. 5B) are pickup 0.25 (friction factor), slack off 0.25 (friction factor), pickup 0.30 (friction factor), slack off 0.30 (friction factor), pickup 0.35 (friction factor), slack off 0.35 (friction factor), and rotation off bottom. [0051] FIG. 5B depicts an example plot 501, which plots actual (measured) hookload (kilo foot pounds) versus depth (feet) for actual slack off, actual rotation off bottom, and actual pickup, superimposed with the expected (modeled) hookload of FIG. 5A. [0043] For example, by comparing the measured torque and drag parameters to the expected (modeled) curves, as shown in FIG. 6, friction factors are interpolated. [0057] The graph 820 plots friction forces including a pickup friction force (i.e., pickFF_num), a slackoff friction force (i.e., slackFF_num), a torque friction force (i.e., torqueFF_num), average friction force (i.e., avgFF_num), and friction force standard deviation e(i.e., ffSTD_num) … Examiner note: the slack off weight is a hook load measured while the drillstring moves downward without rotation, and the measured slack off hookload is compared with modeled slack off hookloads corresponding to different friction factors to determine the slack off friction factor);
generating the pickup no rotation ([0060] The pickup weight is the weight measured when the whole drillstring is moved up without rotation. [0050] An example plot 500 is shown in FIG. 5A, which plots expected (modeled) hookload (kilo foot pounds) versus depth (feet) for various torque and drag parameters. Examples of such torque and drag parameters as shown in FIG. 5A (and also FIG. 5B) are pickup 0.25 (friction factor), slack off 0.25 (friction factor), pickup 0.30 (friction factor), slack off 0.30 (friction factor), pickup 0.35 (friction factor), slack off 0.35 (friction factor), and rotation off bottom. [0053] For example, at sampling time 1200 hours, a pickup hookload is measured to be 36, and the friction force is interpolated to be 0.29. This friction force (0.29) is determined by comparing the measured hookload at a particular sample time (i.e., 1200 hrs) to the expected (modeled) friction force curves as shown in FIGS. 5A, 5B, and 6. [0043] For example, by comparing the measured torque and drag parameters to the expected (modeled) curves, as shown in FIG. 6, friction factors are interpolated. [0057] The graph 820 plots friction forces including a pickup friction force (i.e., pickFF_num), a slackoff friction force (i.e., slackFF_num), a torque friction force (i.e., torqueFF_num), average friction force (i.e., avgFF_num), and friction force standard deviation e(i.e., ffSTD_num) … Examiner note: the pickup weight is a hook load measured while the drillstring moves upward without rotation, and the measured pickup hookload is compared with modeled pickup hookloads corresponding to different friction factors to determine the pickup friction factor); and
generating the torque friction factor value based upon a comparison of a torque loss value as the drillstring load with at least one modeled load of the plurality of modeled loads ([0038] For example, the torque and drag parameters can be discretely identified in real-time or near-real-time while drilling based on actual surface measurements to represent friction in the wellbore. [0067] The rotating off bottom torque is the torque measured when the drillstring is rotating constantly close to the drilling rotary speed … and the drill bit is off bottom. [0041] At block 302, the processing system 12 models torque and drag parameters for an upstream well construction operation (e.g., a drilling operation). Examples of the discrete torque and drag parameters include … rotating off bottom torque measurement … Modeling the torque and drag parameters can include generating expected (modeled) curves for the torque and drag parameters ... [0043] At block 306, the processing system 12 interpolates friction factors at different sampling times for the measured torque and drag parameters … by comparing the measured torque and drag parameters to the expected (modeled) curves, as shown in FIG. 6, friction factors are interpolated. [0057] The graph 820 plots friction forces including a pickup friction force (i.e., pickFF_num), a slackoff friction force (i.e., slackFF_num), a torque friction force (i.e., torqueFF_num), average friction force (i.e., avgFF_num), and friction force standard deviation e(i.e., ffSTD_num) … Examiner note: the reference teaches the torque and drag parameters are identified from actual surface measurements to represent friction in the wellbore, and identifies rotating off bottom torque as a torque and drag parameter and defines it as toque measured when the drillstring is rotating constantly close to the drilling rotary speed and the drill bit is off bottom. Under the BRI in light of specification, the rotating off bottom torque corresponds to the torque loss value because the torque is measured during rotation with the bit off bottom and represents friction in the wellbore. The reference further teaches generating expected modeled curves for the toque and drag parameters, comparing the measured toque and drag parameters with the expected modeled curves, and interpolating fiction factors from the comparison.);
automatically determining a friction factor value of the slackoff no rotation run in hole friction factor value, the slackoff no rotation drilling friction factor value, the pickup no rotation drilling friction factor value, the pickup no rotation pull out of hole friction factor value, and the torque friction factor value that corresponds to the drillstring load in a time responsive to the data acquired during the rig operations based upon the friction factor track in place of a broomstick plot ([0043] At block 306, the processing system 12 interpolates friction factors at different sampling times for the measured torque and drag parameters. As described in more detail with reference to FIG. 6, the friction factors are interpolated between expected (modeled) curves generated during the modeling (block 302) and the measured torque and drag parameters that are sampled while performing the upstream well construction operation (block 304). For example, by comparing the measured torque and drag parameters to the expected (modeled) curves, as shown in FIG. 6, friction factors are interpolated. [0044] At block 308, the processing system 12 transposes the friction factors at the different sampling times for the measured torque and drag parameters to a time-based series. [0054] … These depth-based samples for measured torque and drag parameters are transposed, in the context of the modeled data, into a simple time-based series that in-experienced humans, and more importantly simple algorithmic detection agents (trend detection), can operate on. [0039] These interpolated friction factors are transposed into a time-based series for the different sampling times for the measured torque and drag parameters. Using the interpolated friction factors … it is determined that one or more of the friction factors at a particular point in time deviates from its expected behaviors. This deviation from its expected behavior is called an anomaly. According to examples, an anomaly can be detected by a comparison with previously defined thresholds, trend changes, changepoint detection algorithms, or anomaly detection algorithms The parameters (e.g., the threshold to compare with) for all of these algorithms could be determined by physics-based models for the specific well or could be based on data-driven models based on previous wells. [0057] The graph 820 plots friction forces including a pickup friction force (i.e., pickFF_num), a slackoff friction force (i.e., slackFF_num), a torque friction force (i.e., torqueFF_num), average friction force (i.e., avgFF_num), and friction force standard deviation e(i.e., ffSTD_num). Examiner note: See 112(b) set forth above, the limitation requires automatic determination of at least one of the five recited friction factor values. The reference teaches identifying a torque friction factor value, torqueFF_num, as one of the determined friction factor values, and further teaches the determined friction factor values are transposed into a time based series that algorithmic detection agents operate on the series to automatically determine the status of a friction factor associated with a particular point in time. Thus, automatic determination is based upon the friction factor time based series, rather than requiring an operator to determine the friction factor from the modeled torque and drag force curves, corresponding to the determination based upon the friction factor track in place of a broomstick plot.); and
automatically issuing a control signal to alter operation of at least one subsystem of a drilling rig performing the rig operations when the friction factor value exceeds a threshold to reduce a risk of the drill bit becoming stuck, damage to the specified borehole, or damage to the specified drillstring ([0045] … One example of this deviation is that one or more of the friction factors falls outside of a range bounded by a lower limit threshold and an upper limit threshold. As shown in FIG. 7, a lower limit threshold 710 and an upper limit threshold 711 can be set, for example, based on predicted drilling dysfunctions. When it is determined that one or more of the friction factors at a particular point in time is indicative of the one or more of the friction factors deviating from their expected value … a corrective action can be performed. Examples of corrective actions include alerting an operator/technician, adjusting a drilling trajectory, adjusting a weight on a drill bit, adjusting a rotation rate of the drill bit, and the like, including combinations thereof. [0036] … Alarms can be triggered during this monitoring that trigger procedures or automatic adjustment of operating parameters to mitigate potential stuck-pipe events, for example. [0029] Drilling control signals can be generated by the processing system 12 and conveyed downhole or can be generated within the downhole electronic components 9 or by a combination of the two according to embodiments of the present disclosure. Examiner note: the reference teaches that a friction factor falling outside a threshold can trigger corrective action, including adjustment of drilling operating parameters, the operating parameter may be adjusted automatically, and the drilling control signals may be generated and conveyed downhole).
However, Forshaw fails to teach, but Ho teaches acquiring data during rig operations, wherein the data comprise downhole survey data (Col.11, lines 36-59, “A specific method of utilizing a typical torque-drag log according to the present invention comprises the following steps, performed in sequence: (1) The drill string's actual or measured torque and axial load conditions are recorded, measured at the surface and, if desired, downhole … These actual torque and/or drag measurements are carried out both while tripping in and tripping out of the well, and while rotating or drilling … (3) Survey data, preferably of the MWD variety, may be recorded to indicate the trajectory of the well bore.”); modeled loads depend on at least a portion of the survey data (Col.11-12,” (3) Survey data, preferably of the MWD variety, may be recorded to indicate the trajectory of the well bore … (5) Assuming that the coefficient of friction does not change, the incremental torque and drag between depth D and D+dD may then be calculated by the use of the torque-drag analysis according to the model of the present invention.” Col.12, lines 29-35, “According to the torque-drag analysis of the present invention, the magnitude of the contact force on each incremental portion of the drill string is determined as a function of the trajectory of the well, the clearance of the drill string and its adjacent portion of the well … and the stiffness … of that portion of the drill string.”); the plurality of different friction factor values comprises a slackoff no rotation run in hole friction factor value, a pickup no rotation pull out of hole friction factor value; generating the slackoff no rotation run in hole friction factor value based upon a comparison of a hook load slackoff value as the drillstring load with at least one modeled load of the plurality of modeled loads; generating the pickup no rotation pull out of hole friction factor value based upon a comparison of a hook load pickup value as the drillstring load with at least one modeled load of the plurality of modeled loads (Col.11, lines 40-51, “(1) The drill string's actual or measured torque and axial load conditions are recorded, measured at the surface and, if desired, downhole. … Drag may be inferred from axial (hook) load measurements using a sensor attached to the deadline, or by other hook-load measurement devices. These actual torque and/or drag measurements are carried out both while tripping in and tripping out of the well, and while rotating or drilling.” Col.13, lines 15-24, “The measured torque and drag while tripping in may be compared to the calculated torque and drag according to the model, and the measured torque and drag while tripping out similarly compared the calculated values. The coefficient of friction may be changed for analysis by both the trip in and trip out conditions until the variance between the measured and calculated data is minimized. The coefficient of friction resulting in this minimized variance may be presumed to be the actual coefficient of friction.” Examiner note: the “tripping in” and “tripping out” corresponds to running in hole and pulling out of hole, respectively. The reference also teaches obtaining drag from an axial hookload measurement, comparing the measured torque and drag for the respective tripping condition with calculated torque and drag according to the model, and determining the actual coefficient of friction from the measured versus calculated comparison.).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Forshaw to incorporate the teachings of Ho, and apply Ho’s teaching of using MWD survey data to define wellbore trajectory and comparing measured tripping in and tripping out load data with modeled torque and drag data with modeled torque and drag data to determine friction coefficients, in order to improve the accuracy and reliability of Forshaw’s toque and drag monitoring by accounting for the actual well trajectory and the friction behavior associated with the particular tripping condition, thereby providing more reliable identification of abnormal torque and drag behavior during drilling operations.
However, Forshaw in view of Ho fails to teach, but Bimastianto teaches generating a friction factor track to account for changes in one or more rig parameters or changes in mud weight or string conditions in conjunction with the rig operations (Page.2, Introduction, “The digital twin solution using live data delivers foresight through real-time software that dynamically models physical drilling environments, accommodating small changes in the operating process …” Page.10, Torque and Drag Model, “The torque and drag workflow enables real time analysis of different friction models against measured points for pick-up and slack-off events … These resulting models are plotted superimposed over the observed pick up or slack off points to determine the current friction factor.” Page.11, Top, “The required inputs to generate the models are: … • BHA and drillstring design including diameters and weights … • Mud weight and type • Drilling parameters like actual hook load, torque, RPM and flow rate … The platform allows to produce not only depth based results, but also time domain ones, in both, real time and offline modes …” Examiner note: the reference teaches using live operational data to dynamically accommodate changes in the drilling process, determining current friction factors from measured drilling data relative to friction factor models, and producing the resulting information in the time domain in real time. The model inputs include drillstring/HNA information, mud weight, hookload, torque, RPM, and flow rate. Thus, the reference teaches generating a real-time friction factor track that account for changes in drilling operating conditions);
the plurality of different friction factor values comprises a slackoff no rotation drilling friction factor value, a pickup no rotation drilling friction factor value; generating the slackoff no rotation drilling friction factor value based upon a comparison of a hook load slackoff value as the drillstring load with at least one modeled load of the plurality of modeled loads; generating the pickup no rotation drilling friction factor value based upon a comparison of a hook load pickup value as the drillstring load with at least one modeled load of the plurality of modeled loads (Page.10, Torque and Drag Model, “The torque and drag workflow enables real time analysis of different friction models against measured points for pick-up and slack-off events … These resulting models are plotted superimposed over the observed pick up or slack off points to determine the current friction factor.” Page.12, Drilling,” During drilling a 6" section … the detected hookload values for Slack off … and Pick up … are plotted along the different friction factor models … Both, the Slack off and pick Up values can be seen tracking the 0.2 FF model curves till a depth of around 12000 ft.” Examiner note: the reference teaches “during drilling” detected slackoff and pickup hookload value evaluated against different friction factor model curves, with the slackoff and pickup values tracking a corresponding friction factor model, and determining the current friction factor from the observed pickup or slackoff points relative to the modeled curves. Thus, the reference teaches slackoff drilling and pick drilling fraction factor values, and determining those friction factor values based on comparison of the respective measure hookload values with modeled loads).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Forshaw in view of Ho to incorporate the teachings of Bimastianto, and apply Bimastianto’s teaching of obtaining actual survey information, including inclination, azimuth, and measure depth, and using live operational data to dynamically model the drilling environment and determine current friction factors from measured pickup and slackoff data relative to friction factor modes during drilling, in order to improve the responsiveness and reliability of the torque and drag monitoring to changing operating conditions and provide a more accurate indication of current friction behavior during drilling.
Claim 2, Forshaw teaches The method of claim 1, wherein the drillstring load comprises a directional load ([0060] The pickup weight is the weight measured when the whole drillstring is moved up without rotation.).
Claim 3, Forshaw teaches The method of claim 2, wherein the directional load comprises a pickup direction load ([0060] The pickup weight is the weight measured when the whole drillstring is moved up without rotation.).
Claim 4, Forshaw teaches The method of claim 2, wherein the directional load comprises a slackoff direction load ([0064] The slack off weight is the weight measured when the whole drillstring is moved down without rotation.).
Claim 5, Forshaw teaches The method of claim 1, wherein the drillstring load comprises a rotational load ([0067] The rotating off bottom torque is the torque measured when the drillstring is rotating constantly close to the drilling rotary speed (or above a certain threshold when tripping or running in the casing) and the drill bit is off bottom.)).
Claim 6, Forshaw in view of Ho fails to teach, but Bimastianto teaches The method of claim 1, wherein the drillstring load corresponds to a stand of the specified drillstring (Page.6, AutoStates and RigStates, “The algorithm self-calibrates and adapt to the changes in conditions over the well duration, identifying the hookload value for "on slips" condition for each stand or joint added to the string.”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Forshaw in view of Ho to incorporate the teachings of Bimastianto, and apply Bimastianto’s teaching of identifying a hookload value for each stand or joint added to the drillstring, in order to provide consistent load measurements associated with successive drillstring additions and thereby improve monitoring of changes in wellbore conditions during the drilling operation.
Claim 8, Forshaw teaches The method of claim 1, comprising detecting an activity state based on the at least a portion of the data, wherein the activity state comprises a pickup state or a slackoff state ([0038] … Based on the three-step (or two-step) approach, multiple features can be determined from the surface measurements to classify torque and drag states (e.g., pickup drag) that show characteristics particular to the states … If the current observation is one of the torque and drag classes (e.g., pick up drag, slack off drag, rotating off bottom drag, rotating off bottom torque, etc.), the system quantifies the torque and drag parameters.).
Claim 10, Forshaw teaches The method of claim 1, comprising rendering the friction factor value to a display with respect to time or with respect to depth ([0043] At block 306, the processing system 12 interpolates friction factors at different sampling times for the measured torque and drag parameters. [0044] At block 308, the processing system 12 transposes the friction factors at the different sampling times for the measured torque and drag parameters to a time-based series. An example of such a time-based series is depicted in FIG. 7 and further described herein. [0055] FIG. 7 depicts a graph 700 of a time-based series of the friction factors interpolated in FIG. 6 according to one or more embodiments described herein. The graph 700 depicts the friction factors interpolated in FIG. 6 as unit less values plotted versus sample time (that is, the time the torque and drag parameters were measured). [0032] A display (e.g., a display monitor) 35 is connected to system bus 33 by display adaptor 32 … Examiner note: the reference teaches that processing system 12 generates friction factors at different sampling times, transposes those friction factors into a time based series, and depicts the friction factors in graph 700 as values plotted versus sample time. The same processing system includes a display monitor).
Claim 14, Forshaw teaches The method of claim 1, comprising determining a model-based free rotate load ([0041] At block 302, the processing system 12 models torque and drag parameters for an upstream well construction operation (e.g., a drilling operation). Examples of the discrete torque and drag parameters include … rotating off bottom weight measurement … Modeling the torque and drag parameters can include generating expected (modeled) curves for the torque and drag parameters … [0050] … An example plot 500 is shown in FIG. 5A, which plots expected (modeled) hookload (kilo foot pounds) versus depth (feet) for various torque and drag parameters. Examples of such torque and drag parameters … rotation off bottom. Examiner note: Under BRI, the modeled rotating off bottom hookload corresponds to the model-based free rotate load).
Claim 15, Forshaw teaches The method of claim 14, wherein the data comprises a sensed free rotate load ([0051] As the BHA 13 moves along the borehole 2, the raw data is collected, for example by one or more of the measurement tools 11 (also referred to as a “measurement device”) …FIG. 5B depicts an example plot 501, which plots actual (measured) hookload (kilo foot pounds) versus depth (feet) for actual slack off, actual rotation off bottom, and actual pickup … Examiner note: Under BRI, the actual measured rotation off bottom hookload corresponds to the sensed free rotate load).
Claim 16, Forshaw teaches The method of claim 15, comprising rendering a representation of the model- based free rotate load and the sensed free rotate load to a display ([0051] As the BHA 13 moves along the borehole 2, the raw data is collected, for example by one or more of the measurement tools 11 … and transmitted to the surface 3 for additional processing or display by the processing system 12. FIG. 5B depicts an example plot 501, which plots actual (measured) hookload (kilo foot pounds) versus depth (feet) for actual slack off, actual rotation off bottom, and actual pickup, superimposed with the expected (modeled) hookload of FIG. 5A. See also [0041] and [0050]).
Claim 17, Forshaw teaches The method of claim 15, comprising comparing the model-based free rotate load and the sensed free rotate load ([0051] FIG. 5B depicts an example plot 501, which plots actual (measured) hookload (kilo foot pounds) versus depth (feet) for actual slack off, actual rotation off bottom, and actual pickup, superimposed with the expected (modeled) hookload of FIG. 5A. [0052] Deviations from one of these modeled curves suggest that friction is changing, either increasing or decreasing, in the openhole section of the borehole 2. See also [0041] and [0050]).
However, Forshaw in view of Ho fails to teach, but Bimastianto teaches issuing an alarm based at least in part on the comparing (Page.11, bottom, “The possibility to handle the results in time, provides with the basis to generate alarms and flags by directly comparing the modelled against the actual values at any given time during the operations.”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Forshaw in view of Ho to incorporate the teachings of Bimastianto, and apply Bimastianto’s teaching of generating an alarm based on the comparison between modeled and actual load values, in order to provide an indication when a discrepancy between the modeled and actual operating conditions is detected during drilling operations.
Claim 18, Forshaw teaches The method of claim 1, wherein the drillstring load comprises a pickup load and a slackoff load, and comprising rendering a plurality of pickup loads and slackoff loads with respect to time and/or with respect to depth ([0060] The pickup weight is the weight measured when the whole drillstring is moved up without rotation. [0064] The slack off weight is the weight measured when the whole drillstring is moved down without rotation. [0051] FIG. 5B depicts an example plot 501, which plots actual (measured) hookload (kilo foot pounds) versus depth (feet) for actual slack off, actual rotation off bottom, and actual pickup, superimposed with the expected (modeled) hookload of FIG. 5A. [0052] Actual (measured) values for torque and drag parameters, which can be sampled automatically, have historically been plotted or overlaid on top of the expected (modeled) theoretical curves … ).
The elements of claims 19 and 20 are substantially the same as those of claim 1. Therefore, the elements of claims 19-20 are rejected due to the same reasons as outlined above for claim 1. Further, the additional limitations of claims 10 and 19, “A system comprising: a processor; memory accessible by the processor; processor-executable instructions stored in the memory and executable to instruct the system to: ” and “One or more non-transitory computer-readable storage media comprising processor-executable instructions to instruct a computing system to:” (See Forshaw; [0005]).
Claim(s) 7 is rejected under 35 U.S.C. 103 as being unpatentable over Forshaw in view of Ho and
Bimastianto as applied to claim 1 above, and further in view of Kucs (“Automated Real-Time Hookload and Torque Monitoring,” published in 2008).
Claim 7, Forshaw teaches The method of claim 1, comprising repeating the acquiring, determining, comparing, and automatically determining ([0039] One example approach to autonomous torque and drag monitoring is as follows. Torque and drag parameters for an upstream well construction operation are simulated using physics-based modeling. Measured (actual) torque and drag parameters are then acquired during performing the drilling or other operations with a string in the hole. Friction factors are interpolated at different sampling times for the measured torque and drag parameters. See also [0053]-[0054]. Examiner note: the reference teaches an autonomous monitoring process in which measured drillstring load data are acquired at different sampling times, the measured load at each sample is compared with modeled curves, and a corresponding friction factor is determined for each sample).
However, Forshaw in view of Ho and Bimastianto fails to teach, but Kucs teaches a stand-by-stand basis for stands of the specified drillstring (Page.2, Graphical Evaluation of Hook Load Trends, " The solution to this problem was to reduce the data points plotted to one data point per stand by using automated operations recognition to identify different motion patterns (rotating, non-rotating) while moving one stand of drill pipe. By recognizing the relevant operation a data set can be picked and then further processed … The decision was made to use the median value of the measured hook loads collected over the movement pattern of the string within the range of one stand, separated for different movement directions … Nevertheless, the need of one second data is essential for the stand based hook load calculation, to assure that a really representative hook load or torque value can be plotted for this stand. " Examiner note: the reference teaches using automated recognition to identify drillstring movement associated with a stand, selecting and processing the corresponding data set, collecting measured hookload values within the range of the stand, and performing a stand based hookload calculation to obtain a representative hookload or torque value for that stand.).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Forshaw in view of Ho and Bimastianto to incorporate the teachings of Kucs, and apply Kucs’s teaching of reducing the data points to one data point per stand by using automated operations recognition to identify the relevant drillstring movement, select and further process the associated data set, and perform a stand based hookload calculation, to Forshaw’s repeated toque and drag monitoring process, in order to obtain a representative hookload or torque value for each stand while reducing confusing plotted data and avoiding inaccurate trend lines.
Claim(s) 21 is rejected under 35 U.S.C. 103 as being unpatentable over Forshaw in view of Ho and
Bimastianto as applied to claim 1 above, and further in view of Bordakov US20090164125A1.
Claim 21, Forshaw teaches The method of claim 1, further comprising ([0050] … the modeled values for indicated (i.e., what is seen at the surface 3) hookloads for torque and drag, using different friction factors for the openhole section … Examples of such torque and drag parameters as shown in FIG. 5A (and also FIG. 5B) are pickup 0.25 (friction factor), slack off 0.25 (friction factor), pickup 0.30 (friction factor), slack off 0.30 (friction factor), pickup 0.35 (friction factor), slack off 0.35 (friction factor), and rotation off bottom. [0036] …The techniques provided herein utilize real-time and/or near-real-time physics-based modeling in combination with real-time and/or near-real-time parameter sampling as described herein to interpolate those samples and produce a friction factor for each of the discrete samples. [0053] … FIG. 6 also depicts a table 601 of interpolated friction factors that correspond to different sampled times … This friction force (0.29) is determined by comparing the measured hookload at a particular sample time (i.e., 1200 hrs) to the expected (modeled) friction force curves as shown in FIGS. 5A, 5B, and 6. [0054] As another example, at sampling time 1300 hours, a pickup hookload is measured to be 37, and the friction force is interpolated to be 0.21. Thus, FIG. 6 shows interpolating between the theoretical curves (e.g., of FIG. 5A) and assigning a friction factor to each sample taken. Examiner note: the reference teaches modeled hookload curves associated with particular friction factor values and determines an interpolated friction factor value at successive sampling times by comparing measured hookload with the corresponding modeled curves. The reference further teaches real-time or near real-time modeling and sampling to produce a friction factor for each discrete sample. Thus, Under BRI, the reference teaches friction factor values corresponding to respective modeled loads and friction factor determinations on a time increment basis behind real-time).
However, Forshaw in view of Ho and Bimastianto fails to teach, but Bordakov teaches dynamically adjusting one or more friction factor values to generate dynamically adjusted friction factor values, wherein dynamically adjusting the one or more friction factor values is performed utilizing a statistical approach considering deviations about a mean to provide for more accurate estimates of the one or more friction factor values ([0051] … The effective sliding friction factor may be calibrated to match TIAH/TIMH and TOAH/TOMH data pairs. Again, any automatic minimization procedure can be used. [0053] …distribution of parameter values such as (TIMH-TIAH)/TIMH and (TOAH-TOMH)/TOMH may be analyzed to get a profile of their distribution … [0054] … the method next calculates the spread and mean of the parameter (step 63). The spread of a particular parameter may be obtained by increasing or lowering the initial calibrated value of the parameter to a point that results in a match between the distribution of a derived parameter … and the distribution actually observed for this secondary parameter. The mean can then be defined from the spread of the parameter. [0055] For example, the parameter (e.g., sliding friction factor) is increased with respect to the given calibrated value, and the TIMH and TOMH curves are calculated based on that increased parameters … The sliding friction factor is increased until medians of these spread values match the above-mentioned 75% percentile values … [0056] … By decreasing the sliding friction factor … one can estimate the 25% percentile value of the sliding friction factor. Then, the calibrated value of this parameter may be defined as the median … of the 25% and 75% percentile values. By assuming a simple distribution … for the sliding friction factors, the standard deviation can be found from a pair of the percentiles. Examine note: the reference teaches automatically calibrating a sliding friction factor associated with modeled hookloads by increasing or decreasing the friction factor value and recalculating the corresponding modeled hookload curves. The reference further teaches analyzes distributions of difference between modeled and actual hookloads, calculates the spread and mean of the parameter, percentile values, a median, and standard deviation to obtain a calibrated friction factor value. Thus, the reference teaches dynamically adjusting friction factor value using a statistical approach considering deviations about a mean to obtain a refined friction factor estimate).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Forshaw in view of Ho and Bimastianto to incorporate the teachings of Bordakov, and apply Bordakov’s teaching of automatically calibrating a sliding friction factor by adjusting the friction factor based on measured and modeled hookload data and utilizing a statistical analysis including the spread and mean of the parameter, to Forshaw’s friction factor determination at successive sampling times, in order to automatically calibrate and refine the friction factor values corresponding to the modeled loads based on agreement between the modeled and measured load data, while reducing human influence and errors associated with manual calibration.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Martinez US10590761B1 teaches integrating a series of data inputs related to a well. The series of data inputs includes at least one real-time data input and at least one non-real-time data input. The method further includes based, at least in part, on a result of the integrating, facilitating a real-time display of performance data for the well. The real-time display includes information related to at least one of hydraulic surveillance and torque-and-drag surveillance.
Sheppard US4760735A teaches Drilling conditions are analyzed by, for example, measuring the torque applied at the surface to the drill string and the effective torque acting on the drill bit. The applied torque and effective torque are compared to determine torque loss. Likewise, applied weight on the drill string and effective weight acting on the drill bit may be measured and compared to determine drag losses. These measurements and comparisons may be done in real-time to diagnose unfavorable drilling conditions. The torque or weight measurements may be used to calculate a variable coefficient of friction acting on the drilling string. Trends in the torque or weight losses, or in the value of the coefficient of friction, may be observed on a plot of these quantities as a function of depth.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action.
Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/YI . HAO/
Examiner, Art Unit 2187
/EMERSON C PUENTE/Supervisory Patent Examiner, Art Unit 2187
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