1DETAILED ACTION
Status of the Claims
Claims 1-20 are pending.
Notice of AIA Status
The present application, filed on or after 16 March 2013, is being examined under the first inventor to file provisions of the AIA .
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.
Claim Objections
Claims 1 and 11 are objected to because of the following informalities:
Claim 1 recites the limitation “applying the deep learning model to one or more unclassified inspection logs of the second database, wherein the one or more unclassified inspection logs of the second database comprising anomalies.” The phrase “wherein the one or more unclassified inspection logs of the second database comprising anomalies” contains a typographical/grammatical error. Appropriate correction is required.
Claim 11 is objected to for substantially the same reasons given above.
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.
Claims 1-8 and 11-18 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 may be characterized as a method for classifying a detected anomaly in an underground metal casing as being due to either actual metal loss or other factors. This claim has been evaluated under the Alice/Mayo subject matter eligibility test as provided in MPEP § 2106.
I. Step 2A Prong 1: The claim recites an abstract idea.
Courts have defined a mental process to include both concepts that may be performed entirely in the human mind and concepts that require a human to employ a physical aid (e.g., a pen and paper or slide rule). MPEP § 2106.04(a)(2)(III). Examples of mental processes include observations, evaluations, judgments, and opinions. Id.
The following limitation encompasses a mental process:
“subsequently classifying the one or more unclassified inspection logs of the second database into either the first label or the second label.”
The above limitation is drawn to classifying an inspection log as having actual metal loss or an anomaly due to other factors. For example, this activity may be performed by a human using his/her own judgment. For example, a human may visually detect a trapezoid pattern in an EM waveform that is the signature of actual metal loss across the outer most casing barrier. See Specification ¶ 31, fig. 5.
II. Step 2A Prong 2: The claim does not recite an additional element that integrates the abstract idea into a practical application.
Integration into a practical application should be determined by: “(1) identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application, using one or more of the [listed] considerations.” MPEP § 2106.04(d)(II) (emphasis added).
The claim recites the following additional elements:
“accessing a first database holding results of interpreting casing integrity, wherein each result provides a label for a detected anomaly at a depth location of an inspection log, wherein the label is one of: a first label of actual metal loss, or a second label of anomaly due to other factors, and wherein the inspection log records electromagnetic (EM) survey data of an underground metal casing that runs a plurality of depth locations;”
“accessing a second database holding inspection logs, wherein each inspection log record EM survey data of a corresponding underground metal casing that runs the plurality of depth locations;”
“based on, at least in part, the results of interpreting casing integrity, training a deep learning model configured to classify an input inspection log comprising an anomaly into the first label or the second label;” and
“applying the deep learning model to one or more unclassified inspection logs of the second database, wherein the one or more unclassified inspection logs of the second database comprising anomalies.”
A. The invention does not improve the functioning of a computer or any other technology.
Neither the claim nor the specification asserts that the invention improves upon the conventional functioning of a computer, conventional technology, or technological processes.
Rather, the claim merely invokes a computer as a tool. See Specification ¶ 22.
In particular, the training of a deep learning model does not represent a technological improvement. Training a machine learning model is incident to the very nature of machine learning. Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437, slip op. at 12 (Fed. Cir. Apr. 18, 2025).
B. Databases and a machine learning model are not particular machines.
A general-purpose computer that applies an abstract idea by use of conventional computer functions does not qualify as a particular machine. MPEP § 2106.05(b)(I). The claim recites the additional elements of performing the claimed process using databases and a “deep learning model.” A database and a machine learning model are generic computer technologies. Accordingly, the recited abstract idea is not applied with, or by use of, a particular machine.
C. Accessing a database is an insignificant extra-solution activity.
The recitation of an insignificant extra-solution activity does not amount to an inventive concept. MPEP § 2106.05(g). The claim recites the additional elements of accessing a first database and a second database. Accessing a database is an insignificant pre-solution activity related to mere data gathering.
D. The application of a deep learning model merely indicates a field of use or technological environment.
Limitations that merely generally link the use of an abstract idea to a field of use or technological environment cannot integrate an abstract idea into a practical application. MPEP § 2106.05(h). Specifically, applying generic machine learning techniques to a new environment does not create patent eligibility. Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437, slip op. at 18 (Fed. Cir. Apr. 18, 2025). The claim does not delineate steps through which the machine learning technology achieves an improvement. Accordingly, the limitation directed to applying the deep learning model to an inspection log does not make the claim patent eligible.
F. The relevant considerations indicate that the additional elements do not integrate the abstract idea into a practical application.
When evaluated as a whole, the above-identified considerations indicate that the recited additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
III. Step 2B: The claim does not recite an additional element that amounts to significantly more than the abstract idea.
Whether a claim recites significantly more than an abstract idea should be determined by: (1) identifying any additional elements recited in the claim beyond the judicial exception; and (2) evaluating those additional elements, individually and in combination, with respect to the relevant considerations. MPEP § 2106.05(II).
First, as discussed above, the recited invention does not improve the functioning of a computer or any other technology. Second, as discussed above, the recited databases and machine learning model are generic computer technologies. Third, as discussed above, accessing a database is an insignificant extra-solution activity related to mere data gathering. Furthermore, courts have recognized that receiving data over a network is a well-understood, routine, and conventional activity. MPEP § 2106.05(d)(II). Fourth, as discussed above, the application of the machine learning model to an inspection log merely indicates a field or use or technological environment.
Thus, individually, the recited additional elements do not amount to significantly more than the abstract idea itself.
Finally, the combined additional elements do not result in a non-conventional or non-generic arrangement. Rather, the combined additional elements merely embody conventional data processing and data output functions performed by a generic computer.
Accordingly, when evaluated individually and in combination, the above-identified considerations indicate that the recited additional elements do not amount to significantly more than the recited abstract idea.
IV. Conclusion: Ineligible
The claim has been found to be directed to an abstract idea without reciting additional elements that amount to significantly more than the abstract idea. Therefore, the claim does not qualify as patent eligible subject matter under 35 U.S.C. § 101.
Claim 2, which depends on claim 1, is directed to analyzing a log to detect anomalies. This limitation encompasses a mental process. Therefore, the claim is not patent eligible.
Claim 3, which depends on claim 1, is directed to a human determining results. This limitation encompasses a mental process. Therefore, the claim is not patent eligible.
Claim 4, which depends on claim 3, is directed to a human determining results in view of a schematic. This limitation encompasses a mental process. Therefore, the claim is not patent eligible.
Claim 5, which depends on claim 4, is directed to a human determining results in view of a schematic revealing a casing pipe configuration or size transition. This limitation encompasses a mental process. Therefore, the claim is not patent eligible.
Claim 6, which depends on claim 1, is directed to an inspection log recording EM survey data comprising an EM spectrum map. This language does not require any steps to be performed. Accordingly, this claim has no limiting effect. See MPEP § 2111.04. Therefore, the claim is not patent eligible.
Claim 7, which depends on claim 6, is directed to label characterized by a trapezoid pattern in an EM spectrum map. This language does not require any steps to be performed. Accordingly, this claim has no limiting effect. See MPEP § 2111.04. Therefore, the claim is not patent eligible.
Claim 8, which depends on claim 1, is directed to the deep learning model including a U-Net classifier. A U-Net classifier is a well-understood, routine, and conventional technology. See, e.g., Ronneberger et al., “U-Net: Convolutional Networks for Biomedical Image Segmentation.” Accordingly, the abstract idea neither is integrated into a practical application nor includes additional elements that amount to significantly more than the abstract idea. Therefore, the claim is not patent eligible.
Claims 11-18 are directed to a system that implements the methods recited in claims 1-8, respectively. The system claims are no different than the corresponding method claims in substance. Accordingly, these claims are subject matter ineligible for substantially the same reasons indicated above. See Alice Corp. Pty. Ltd. v. CLS Bank Intern., 573 U.S. 208, 226-27 (2014).
Allowable Subject Matter
Claims 9-10 and 19-20 contain allowable subject matter.
Claims 9-10 and 19-20 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
Although particular portions of the prior art may have been cited in support of the rejections, the specified citations are merely representative of the teachings. Other passages and figures in the cited prior art may apply. Accordingly, Applicant should consider the entirety of the cited prior art for potentially teaching all or part of the claims.
The following prior art made of record and not relied upon is considered pertinent to applicant’s disclosure:
Assous et al., US 2023/0213323 A1, discloses a process for determining variations in thickness in a casing.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Asher D Kells whose telephone number is (571)270-7729. The examiner can normally be reached Mon. - Fri., 8 a.m. - 4 p.m..
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Asher D. Kells
Primary Examiner
Art Unit 2171
/Asher D Kells/ Primary Examiner, Art Unit 2171