DETAILED ACTION
Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claims 1-28 are currently pending in this application.
Priority
2. No foreign priority has been claimed. This application is a CIP of 17/698,123 filed 3/18/2022, now US Pat # 12,338,686 which is a CON of 17/320,423 filed 5/14/2021 now US Pat # 11,301,989 which claims benefit to provisional application 63/024,754 filed 5/14/2020
Information Disclosure Statement
4. The information disclosure statement (IDS) submitted on 7/7/2023 was received. The submission is in compliance with the provisions of 37 CFR 1.97 and 37 CFR 1.98. Accordingly, the information disclosure statement has being considered by the examiner.
Drawings
5. The drawings submitted on 2/15/2023 are in compliance with 37 CFR § 1.81 and 37 CFR § 1.83 and have been accepted by the examiner.
Double Patenting
6. The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claim 1 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1&17 of U.S. Patent No. 11,301,989. Although the claims at issue are not identical, they are not patentably distinct from each other because the limitations of the claims in the current application are encompassed in the previous application. The latter pending application encompasses the same process as the pending application.
Claim Rejections - 35 USC § 101 Non-Statutory
7. 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.
8. Claims 1-28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Specifically, representative Claim 1 recites:
A method of well tool inspection, comprising:
training a neural network with a plurality of failure mode images;
scanning a used well tool with a scanner to obtain wear input data;
classifying one or more failure modes sustained by the used well tool using the trained neural network and the wear input data; and
outputting classified failure mode data.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements.”
Similar limitations comprise the abstract ideas of Claims 13 and 26.
Under Step 1 of the analysis, claim 1 does belong to a statutory category, namely it is a process claim. Likewise, claim 13 is a system claim and claim 26 a system claim.
Under Step 2A, prong 1, claim 1 is found to include at least one judicial exception, that being a mental and/or mathematical process. This can be seen in the claim limitation of “training a neural network with a plurality of failure mode images; classifying one or more failure modes sustained by the used well tool using the trained neural network and the wear input data;”, which is the judicial exception of a mental process and/or a mathematical concept because it is merely a data evaluation including calculations, and/or judgements capable of being performed mentally.
Similar limitations comprise the abstract ideas of Claims 13 and 26.
Step 2A, prong 2 of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception(s) into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
In addition to the abstract ideas recited in claim 1, the claimed method recites additional elements including scanning a used well tool with a scanner to obtain wear input data (claims 1, 13, and 26) which are merely data gathering steps recited at a high level of generality and therefore merely amount to “insignificant extra-solution” activity(ies). See MPEP 2106.05(g) “Insignificant Extra-Solution Activity,”. The claim also recites “neural network” (claims 1, 13, and 26) however the “neural network” is recited at a high level of generality, e.g. Spec. [0128] describing a variety of different types of “neural network” models that may be used, and merely amounts to the use of computer technology as a tool to apply the abstract idea (see MPEP 2106.05(f)) and/or the use of “neural networks” to perform the predictions, that are otherwise abstract, is merely an attempt at limiting the abstract to a particular field of use (See MPEP 2106.05(h)).
The generic data gathering, processing, and output steps, and other elements, are recited so generically that it represents no more than mere instructions to apply the judicial exceptions on a computer. It can also be viewed as nothing more than an attempt to generally link the use of the judicial exceptions to the technological environment of a computer. Noting MPEP 2106.04(d)(I): “It is notable that mere physicality or tangibility of an additional element or elements is not a relevant consideration in Step 2A Prong Two. As the Supreme Court explained in Alice Corp., mere physical or tangible implementation of an exception does not guarantee eligibility. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1983-84 (2014) ("The fact that a computer ‘necessarily exist[s] in the physical, rather than purely conceptual, realm,’ is beside the point")”.
Thus, under Step 2A, prong 2 of the analysis, even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception. No specific practical application is associated with the claimed system. For instance, nothing is done with the output from the first model.
Under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as described above with respect to Step 2A Prong 2, merely amount to a general purpose computer system that attempts to apply the abstract idea in a technological environment, limiting the abstract idea to a particular field of use, and/or merely insignificant extra-solution activity (claims 1, 13, and 26). Such insignificant extra-solution activity, e.g. data gathering and output, when re-evaluated under Step 2B is further found to be well-understood, routine, and conventional as evidenced by MPEP 2106.05(d)(II) (describing conventional activities that include transmitting and receiving data over a network, electronic recordkeeping, storing and retrieving information from memory, and electronically scanning or extracting data from a physical document).
Therefore, similarly the combination and arrangement of the above identified additional elements when analyzed under Step 2B also fails to necessitate a conclusion that claim 1, as well as claims 13 and 26, amount to significantly more than the abstract idea.
With regards to the dependent claims, claims 2-12, 14-25, and 27-28, merely further expand upon the algorithm/abstract idea and do not set forth further additional elements therefore these claims are found ineligible for the reasons described for independent claims 1, 13, and 26.
See Supreme court decision in Alice Corporation Pty. Ltd. V. CLS Bank International, et al.
Claim Rejections - 35 USC § 102
9. 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 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.
10. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
11. Claims 1-9,11, 13-22 and 25-28 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Potash US Pat # 2019/0145183.
With regards to claim 1, Potash US Pat # 2019/0145183 teaches a method of well tool inspection, comprising:
training a neural network with a plurality of failure mode images;(paragraph 0027)
scanning a used well tool with a scanner to obtain wear input data;( paragraph 0030)
classifying one or more failure modes sustained by the used well tool using the trained neural network and the wear input data; (paragraph 0027) and
outputting classified failure mode data. (460 wear report; paragraph 0028-0029)
With regards to claim 2, Potash US Pat # 2019/0145183 teaches the neural network comprises a multi-layer convolutional neural network. ( paragraph 0027)
With regards to claim 3, Potash US Pat # 2019/0145183 teaches storing a training dataset having scanned image data and associated labels. (classifying and training must store data; paragraph 0027)
With regards to claim 4, Potash US Pat # 2019/0145183 teaches storing a training dataset having scanned image data and associated labels representative of classification types of failure. (wear characteristics; paragraph 0027)
With regards to claim 5, Potash US Pat # 2019/0145183 teaches the used well tool includes a plurality of cutting elements and wherein the labels are representative of classification types of failure in cutting elements. (125; paragraph 0019-0020)
With regards to claim 6, Potash US Pat # 2019/0145183 teaches the labels are representative of classification types of failure in patterns among the cutting elements. (wear patterns; paragraph 0015)
With regards to claim 7, Potash US Pat # 2019/0145183 teaches the training dataset further includes historical data and live sensor data. (600; figure 6)
With regards to claim 8, Potash US Pat # 2019/0145183 teaches the scanner includes a two-dimensional (2D) scanner and a three-dimensional (3D) scanner, and the scanning includes scanning a drill bit with the 2D scanner and 3D scanner to obtain 2D and 3D images respectively. (paragraph 0030)
With regards to claim 9, Potash US Pat # 2019/0145183 teaches locating a discrete part of interest on the used well tool. (wear on each blade; paragraph 0026)
With regards to claim 11, Potash US Pat # 2019/0145183 teaches the types of substrate damage include one or more of heat checking damage, corrosion, or erosion. (page 2, table 1)
With regards to claim 13, Potash US Pat # 2019/0145183 teaches well tool wear classification system comprising:
a wear classifier tool configured to classify wear of a scanned well tool using a machine learning engine; ( paragraph 0027) and
a computer-readable memory storing a training dataset and a trained ML model, wherein the training data set includes scanned image data and associated labels representative of classification types of failure. (wear characteristics, 125; paragraph 0019-0020 & 0027)
With regards to claim 14, Potash US Pat # 2019/0145183 teaches the trained ML model includes a neural network. (paragraph 0027)
With regards to claim 15, Potash US Pat # 2019/0145183 teaches the neural network comprises a multi-layer convolutional neural network. ( paragraph 0027)
With regards to claim 16, Potash US Pat # 2019/0145183 teaches the used well tool includes a plurality of cutting elements and wherein the labels are representative of classification types of failure in cutting elements. (wear characteristics, 125; paragraph 0019-0020 & 0027)
With regards to claim 17, Potash US Pat # 2019/0145183 teaches the labels are representative of classification types of failure in patterns among the cutting elements. (wear characteristics, 125; paragraph 0019-0020 & 0027)
With regards to claim 18, Potash US Pat # 2019/0145183 teaches the training dataset further includes historical data and live sensor data. (600; figure 6)
With regards to claim 19, Potash US Pat # 2019/0145183 teaches a database coupled to the wear classifier tool, wherein the database is configured to stored historical data on scanner type, patterns of scanner cutting elements, sensor type, and age and usage conditions. (wear characteristics, 125; paragraph 0019-0020, 0027 and 0034-0035)
With regards to claim 20, Potash US Pat # 2019/0145183 teaches the wear classifier tool is further configured to output data identifying a failure mode of the scanned well tool based on classification of input by the machine learning engine. (wear characteristics, 125; paragraph 0019-0020 & 0027)
With regards to claim 21, Potash US Pat # 2019/0145183 teaches the wear classifier tool is further configured to generate an alert for a user for certain types of failure modes. (wear report; paragraph 0004)
With regards to claim 22, Potash US Pat # 2019/0145183 teaches a scanning system including a 2D scanner and a 3D scanner, wherein the scanning system is configured to scan a drill bit with the 2D scanner and the 3D scanner to obtain 2D and 3D images respectively. (paragraph 0038 & 0040)
hist
With regards to claim 25, Potash US Pat # 2019/0145183 teaches the 2D scanner comprises a digital camera. (paragraph 0038 & 0040)
With regards to claim 26, Potash US Pat # 2019/0145183 teaches well tool wear classification system comprising:
a camera configured to capture at least one image of a well tool representative of wear of the well tool; (950; paragraph 0038 & 0040)
a 3D scanner configured to capture at least one image and distance data of the well tool; (950; paragraph 0038 & 0040) and
a wear classifier tool configured to classify wear of the well tool using a machine learning engine provided with an image and distance data captured by the 3D scanner. ( paragraph 0027, 0038,0040)
With regards to claim 27, Potash US Pat # 2019/0145183 teaches computer-readable memory storing a training dataset and a trained model, wherein the training data set includes training image data and associated labels representative of classification types of failure. (wear characteristics, 125; paragraph 0019-0020 & 0027)
With regards to claim 28, Potash US Pat # 2019/0145183 teaches the computer-readable memory further stores the image captured by the camera, whereby, the stored image can be processed or cropped for inclusion in a report on the wear of the well tool. (paragraph 0027-0029)
Claim Rejections - 35 USC § 103
12. 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.
13. 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.
14. Claim(s) 23-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Potash US Pat # 2019/0145183 in view of Nassir et al US Pat # 11,170,494
With regards to claims 23-24, Potash US Pat # 2019/0145183 does not appear to teach a robot coupled to the scanners.
Nassir et al US Pat # 11,170,494 teach a robot coupled to the scanners. (Col. 4, lines 4-5)
It would’ve been obvious to one of ordinary skill in the art at the time of the invention to modify the Potash invention to include the robot coupled to the scanner in order to arrive at the claimed invention as it would be desirable to be able to move the scanners as desired.
Allowable Subject Matter
15. Claims 10 and 12 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
16. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Gooneratne et al. US Pat# 11,280,177 teaches monitoring rig activities.
17. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ADITYA S BHAT whose telephone number is (571)272-2270. The examiner can normally be reached on Monday-Friday 8 am-6pm.
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19. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby Turner can be reached on 571-272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ADITYA S BHAT/Primary Examiner, Art Unit 2857 December 27, 2025