DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Action is FINAL and is in response to the claims filed March 24, 2026. Claims 1, 3-8, 10-15, and 17-20 are currently pending, of which claims 1, 7, 8, 14, and 15 are currently amended. Claims 2, 9, and 16 have been canceled.
Response to Arguments
Drawings
Applicant has submitted replacement drawings and these drawings have been accepted and entered. Therefore, the previous objections have been withdrawn.
Claim Objections
Applicant has amended or canceled the claims at issue and the previous objections have therefore been withdrawn. However, in light of the amended claim language, a new objection has been introduced, as detailed below.
§101 Rejection of the Claims
Applicant has amended the claims to positively recite physical manipulation of the control of gas flow with the SCSSV. Therefore, the claims are integrated into a practical application and the previous rejections under 35 U.S.C. §101 have been withdrawn.
Prior Art Rejections
Applicant’s arguments regarding the previously cited art have been fully considered and are not persuasive. Specifically, Applicant argues that Ahmari does not teach or disclose predicting closure of a subsurface safety valve (SCSSV) and that the choke valve of Ahmari is fundamentally different from the SCSSV of the claims. See Remarks 8-9. Examiner respectfully disagrees.
Firstly, at no point does Applicant make any argument as to why Ahmari is different from the claimed SCSSV. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). The rejection is one of obviousness under 35 U.S.C. §103 and while the valve of Ahmari is controlled based predictions and measurements, Al-Anazi teaches that these predictions would apply to an SCSSV. Both references teach controlling valves in wells.
Furthermore, Applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. As discussed above, the combination is one of Ahmari and Al-Anazi. Together, they teach the valve predictions and how that would apply to an SCSSV.
Therefore, it is for at least these reasons, and the reasons cited below, that the claims remain rejected in this Action.
Claim Objections
Claim 1 is objected to for the following informality:
Claim 1 recites “in response predicting” and this appears to be a typographical/grammatical error and should read “in response to predicting”.
Appropriate correction is required.
Examiner’s Note
The prior art rejections below cite particular paragraphs, columns, and/or line numbers in the references for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art.
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.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 3, 5-8, 10, 12-15, 17, 19, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ahmari (U.S. Publication No. 2022/0003071) and further in view of Al-Anazi et al. (U.S. Publication No. 2023/0383633; hereinafter “Al-Anazi”).
As per claim 1, Ahmari teaches a method for predicting closure of a subsurface safety valve (SCSSV) configured to shut-in a well without any sensors on the SCSSV, the method comprising:
obtaining, by a learning machine, sensor readings indicating downhole conditions in the well (See Ahmari paras. [0021] and [0038]: subsurface well conditions obtained via various sensors from the well);
predicting, by the learning machine, closure of the SCSSV based on the sensor readings indicating downhole conditions in the well; transmitting a communication predicting closure of the SCSSV (See Ahmari Fig. 4 and paras. [0035] and [0052-54]: predicting well profile and operating rates, which a choke setting corresponds to. The choke settings can be various valve positions, including fully closed. Therefore, at certain measurements the valve will be predicted to be closed); and
moving, in response predicting closure of the SCSSV, one or more components that control gas flow in the well to prevent closure of the SCSSV (See Ahmari paras. [0035]: multiple positions for the choke valve varying from 0% open to 100% open. “[T]he operational position of the choke valve 150 may be dictated by a variety of factors, such as a desired production rate and observed characteristic of production of the well 106”).
However, while Ahmari teaches valve closures below the surface of the well, Ahmari does not explicitly state that this valve is a subsurface safety valve (SCSSV).
Al-Anazi teaches subsurface safety valve (SCSSV) to which the valve actions of Ahmari would apply (See Al-Anazi paras. [0018]: subsurface safety valve).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine, with a reasonable expectation of success, the choke valve of Ahmari with the subsurface safety valve of Al-Anazi. One would have been motivated to combine these references because both references disclose modeling and predicting gas flows in wells as they relate to valve actuations. Al-Anazi further enhances the valve system of Ahmari by ensuring that emergencies are quickly addressed, preventing damage to the system or the well itself (See Al-Anazi paras. [0018-19]).
As per claim 3, Ahmari/Al-Anazi further teaches the method of claim 1. Ahmari further teaches storing, in a sensor data repository, sensor samples captured by sensors in the well (See Ahmari para. [0038]: various sensor data that is stored in the memory of the control system).
training, using the training data set, the learning machine to identify pre-shut-in behavior in training data set (See Ahmari para. [0041]: neural network training function, where “the production data 160 received by the choke valve control system 152 may be input to an ANN that identifies patterns in the production data 160 and generates corresponding well rate-pressure profiles 180 and well pressure-choke profiles 182 for some or all of the possible sets/combinations of well conditions”; Fig. 4 and para. [0035]: different choke valve positions based on target operating rate and determined well profile. Therefore, the data is trained on the sensors that match up to the different profiles and the choke settings, and thus their normal and/or pre-shut-in behavior are associated accordingly)
However, while Ahmari teaches training a neural network, Ahmari does not explicitly teach labeling the samples in the training data set.
Al-Anazi teaches labeling each of the sensor samples to create a training data set, the labels indicating that each respective sensor sample indicates normal well behavior or pre-shut-in behavior (See Al-Anazi paras. [0035] and [0049-50]: labelled database associated with field instruments and measurements, such as gas flow rates. This data is fed into the trained machine-learning model, such as the model of Ahmari. Where these rates/predictions can be used in management decisions, such as in the valve settings of Ahmari).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Ahmari with the teachings of Al-Anazi for at least the same reasons as discussed above in claim 1. Furthermore, this database enhances the training model of Ahmari by “promot[ing] robustness and generalization performance of the final machine-learned model” (See Al-Anazi para. [0035]).
As per claim 5, Ahmari/Al-Anazi teaches the method of claim 3. Ahmari further teaches identifying, in the training data set, certain of the sensor samples that contribute to the closure of [the SCSSV] (See Ahmari para. [0041]: neural network training function, where “the production data 160 received by the choke valve control system 152 may be input to an ANN that identifies patterns in the production data 160 and generates corresponding well rate-pressure profiles 180 and well pressure-choke profiles 182 for some or all of the possible sets/combinations of well conditions”; Fig. 4 and para. [0035]: different choke valve positions based on target operating rate and determined well profile. Therefore, the data is trained on the sensors that match up to the different profiles and the choke settings are associated accordingly).
However, while Ahmari teaches valve closures below the surface of the well, Ahmari does not explicitly state that this valve is a subsurface safety valve (SCSSV).
Al-Anazi teaches the subsurface safety valve (SCSSV) to which the valve actions of Ahmari would apply (See Al-Anazi paras. [0018]: subsurface safety valve; paras. [0054-55]: training model associated with field instrument data to determine flow rate characteristics in each well, which could be used to predict emergencies and thus close the SSSV).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Ahmari with the teachings of Al-Anazi for at least the same reasons as discussed above in claim 1.
As per claim 6, Ahmari/Al-Anazi teaches the method of claim 1. Ahmari further teaches wherein the prediction indicates closure of [the SCSSV] will occur one hour from a time of the prediction (See Ahmari Fig. 4 and paras. [0042-43]: “the choke valve control system 152 may assess collected production data 160 to determine whether one or more production parameters have deviated from normal (e.g., the value of a given parameter for a given point in time deviates more than 10% from its average for the one hour preceding the given point in time) and, in response to determining that a production parameter have deviated from normal, send, to the well control system 122, a corresponding observed parameter alert 190 that is indicative of the production parameter having deviated from normal” (emphasis added). Therefore, the alert can be used to predict deviations or unattainable target rates and adjust the choke settings accordingly).
However, while Ahmari teaches valve closures below the surface of the well, Ahmari does not explicitly state that this valve is a subsurface safety valve (SCSSV).
Al-Anazi teaches the subsurface safety valve (SCSSV) to which the valve actions of Ahmari would apply (See Al-Anazi paras. [0018]: subsurface safety valve).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Ahmari with the teachings of Al-Anazi for at least the same reasons as discussed above in claim 1.
As per claim 7, Ahmari/Al-Anazi further teaches the method of claim 1 wherein the downhole conditions in the well include flow rates inside the well (See Ahmari para. [0029]: flowrate sensors and measurements in the well)
As per claims 8, 10 and 12-14, the claims are directed to one or more machine-readable mediums that implement the same or similar features as the method of claims 1, 3, and 5-7, respectively, and are therefore rejected for at least the same reasons therein. Furthermore, Ahmari/Al-Anazi teaches one or more non-transitory machine-readable mediums including instructions that, when executed by one or more processors, predict closure of a subsurface safety valve (SCSSV) configured to shut-in a well without any sensors on the SCSSV, the instructions comprising said methods (See Ahmari paras. [0056-57]; see also Al-Anazi para. [0018]).
As per claims 15, 17, 19, and 20, the claims are directed to an apparatus that implements the same or similar features as the method of claims 1, 3, 5, and 6, respectively, and are therefore rejected for at least the same reasons therein. Furthermore, Ahmari/Al-Anazi teaches an apparatus comprising: one or more processors; one or more non-transitory machine-readable mediums including instructions that, when executed by the one or more processors, predict closure of a subsurface safety valve (SCSSV) configured to shut-in a well without any sensors on the SCSSV, the instructions including said methods (See Ahmari paras. [0056-57]; see also Al-Anazi para. [0018]).
Claims 4, 11, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ahmari/Al-Anazi as applied above, and further in view of Camp et al. (U.S. Publication No. 2021/0255361; hereinafter, “Camp”).
As per claim 4, Ahmari/Al-Anazi further teaches the method of claim 3 further comprising: modifying the training dataset by oversampling the sensor data samples labeled to identify pre-shut-in behavior (See Al-anazi para. [0050]: updating training model and acquiring new data).
However, Ahmari/Al-Anazi does not teach or suggest that the training modifications are done by oversampling.
Camp teaches modifying the training dataset by oversampling (See Camp para. [0069-71]: augmenting data using over-sampling, where this augmented data can be included in the prediction machine learning model of Ahmari/Al-Anazi).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine, with a reasonable expectation of success, the training data and models of Ahmari/Al-Anazi with the oversampling of Camp. One would have been motivated to combine these references because both references disclose modeling and predicting well/borehole characteristics. Camp further enhances the training data of Ahmari/Al-Anazi by increasing model performance by creating a more balanced training data set via the increased size and robustness of a dataset that the augmented data can provide (See Camp paras. [0069-71]).
As per claim 11, the claim is directed to one or more machine-readable mediums that implement the same or similar features as the method of claims 4, and is therefore rejected for at least the same reasons therein.
As per claim 18, the claim is directed to an apparatus that implements the same or similar features as the method of claim 4, and is therefore rejected for at least the same reasons therein.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Nicholas Klicos whose telephone number is (571)270-5889. The examiner can normally be reached Mon-Fri 9:00 AM-5:00 PM.
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/NICHOLAS KLICOS/Primary Examiner, Art Unit 2118
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