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 .
Claim Rejections - 35 USC § 102
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 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.
Claims 1-2, 9, 11, 19-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by (“SCADACore”, web page archived by Wayback Machine on 01/25/2021, see PTO-892 for full citation).
Regarding claim 1, SCADACore teaches a method comprising: obtaining, at a mobile device, an input image representing a pump card (met by Cellular Modem for Pump Controller Monitoring). This is read in (Page 6).
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SCADACore further teaches mapping, based on the input image, the pump card to one of a plurality of possible pump operating conditions (met by dynamometer surveys can be analyzed to reveal a defective pump, tubing leaks, excessive vibration, or other problems). This is read in (Page 2).
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SCADACore further teaches outputting, at the mobile device, the mapped pump operating condition (met by charting options and intelligent color-coding; further met by alarm callout and alarm history). This is read in (Page 3).
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Regarding claim 2, SCADACore teaches wherein the mapping of the input pump card involves classifying the pump card based on known historical data (met by Current and historical
Card Viewer allows clients to view past and present surface cards and downhole cards). This is read in (Page 2).
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Regarding claim 9, the claim is substantially reiterating the limitation of claim 1 pertaining to mapping the pump card image to one of a plurality of possible pump operating conditions. Therefore, the analysis of claim 1 is incorporated herein.
Regarding claim 11, the claim is substantially identical to claim 1, the analysis of which is incorporated herein.
Regarding claim 12, the claim is substantially identical to claim 2, the analysis of which is incorporated herein.
Regarding claim 19, the claim is substantially identical to claim 9, the analysis of which is incorporated herein.
Regarding claim 20, the claim is substantially identical to claim 1, the analysis of which is incorporated herein.
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.
Claims 3, 13 are rejected under 35 U.S.C. 103 as being unpatentable over SCADACore in view of Duan et al. (CN108122075A, hereinafter referred to as “Duan”).
Regarding claim 3, SCADACore fails to teach wherein the mapping of the pump card comprises classifying the input image as one of a plurality of possible pump operating conditions using trained machine learning based image classification model. However, Duan amends this deficiency.
Duan teaches a convolutional neural network (CNN) to obtain operation data for training. The CNN is then used for practical application of sucker rod pump work condition monitoring. This meets the same intended function of the claimed invention’s trained machine learning based image classification model.
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Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified SCADACore to incorporated the teachings of Duan in order to provide a kind of sucker rod pump operating mode intelligent monitoring method based on convolutional neural networks intensified
Learning (Abstract).
Regarding claim 13, the claim is substantially identical to claim 3, the analysis of which is incorporated herein.
Allowable Subject Matter
Claims 4-8, 10, 14-18 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.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW JAMES BODNARK whose telephone number is (703)756-5378. The examiner can normally be reached 8a-5p.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vu Le can be reached at (571) 272-7332. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MATTHEW JAMES BODNARK/Examiner, Art Unit 2668
/VU LE/Supervisory Patent Examiner, Art Unit 2668