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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/21/2025 and 08/21/2025 has/have been considered by the examiner.
Claim Rejections - 35 USC § 102
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.
Claim(s) 1-2, 6, 8-9, 13, 15-16 and 20 is/are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Zheng et al (US 20210374404 A1), hereinafter Zheng.
-Regarding claim 1, Zheng discloses a method for monitoring fracturing activities, comprising (Abstract; FIGS. 1-6; [0040];[0067]; [0089]): receiving, by a computing system, aerial images of a geographical region (FIG. 1, Satellite image processor 120; [0024]; [0025], “receive satellite image data … location information … latitudinal and longitudinal coordinates …”; FIG. 2, satellite image data 212; FIGS. 3, 5-7); analyzing, by the computing system, the aerial images to detect a presence of a well pad within the geographical region (FIGS. 1-3, 5-7; [0017]-[0018]; [0028], “identify new energy projects … well pad … in a target location …”; [0036], “ … well pad … Land clearing may be identified …”; [0038]; [0049]); receiving, by the computing system, further aerial images of the well pad (FIG. 3, steps 304-308; [0067], “… repeated to detect the start of well completion and the end of well completion … well pad …”); monitoring, by the computing system, the further aerial images to identify fracking activity on the well pad (FIGS. 1-7; [0017], “… The completion stage includes operations such as hydraulic fracturing …”; [0036], “process satellite image data … at various stages of energy project … initiation or completion … detect next stage activity … a second stage may include well drilling and completion activities”; [0049], “continues to monitor and process satellite image data …determines that the land has been cleared, method 300 proceeds to step 316”; [0067], “detecting the start of drilling and the end of drilling … start of well completion and the end of well completion … Fracking crew with facilities such as frac fleets …”; [0040], “detect … drilling, and/or completion stages … fracking activity”; [0054]); and recording, by the computing system, the fracking activity (FIGS. 1, 7; [0004], “memory”; [0029], “store various information associated with detection system 116 and identified energy projects …”; [0040], “historical data”; [0084]).
-Regarding claim 8, Zheng discloses a non-transitory computer readable medium comprising one or more sequences of instructions, which, when executed by a processor, causes a computing system to perform operations comprising (Abstract; FIGS. 1-6; [0040];[0067]; [0089]): receiving, by a computing system, aerial images of a geographical region (FIG. 1, Satellite image processor 120; [0024]; [0025], “receive satellite image data … location information … latitudinal and longitudinal coordinates …”; FIG. 2, satellite image data 212; FIGS. 3, 5-7); analyzing, by the computing system, the aerial images to detect a presence of a well pad within the geographical region (FIGS. 1-3, 5-7; [0017]-[0018]; [0028], “identify new energy projects … well pad … in a target location …”; [0036], “ … well pad … Land clearing may be identified …”; [0038]; [0049]); receiving, by the computing system, further aerial images of the well pad (FIG. 3, steps 304-308; [0067], “… repeated to detect the start of well completion and the end of well completion … well pad …”); monitoring, by the computing system, the further aerial images to identify fracking activity on the well pad (FIGS. 1-7; [0017], “… The completion stage includes operations such as hydraulic fracturing …”; [0036], “process satellite image data … at various stages of energy project … initiation or completion … detect next stage activity … a second stage may include well drilling and completion activities”; [0049], “continues to monitor and process satellite image data …determines that the land has been cleared, method 300 proceeds to step 316”; [0067], “detecting the start of drilling and the end of drilling … start of well completion and the end of well completion … Fracking crew with facilities such as frac fleets …”; [0040], “detect … drilling, and/or completion stages … fracking activity”; [0054]); and recording, by the computing system, the fracking activity (FIGS. 1, 7; [0004], “memory”; [0029], “store various information associated with detection system 116 and identified energy projects …”; [0040], “historical data”; [0084]).
-Regarding claim 15, Zheng discloses a system comprising: a processor; and a memory having programming instructions stored thereon, which, when executed by the processor, causes the system to perform operations comprising (Abstract; FIGS. 1-6; [0040];[0067]; [0089]): receiving aerial images of a geographical region (FIG. 1, Satellite image processor 120; [0024]; [0025], “receive satellite image data … location information … latitudinal and longitudinal coordinates …”; FIG. 2, satellite image data 212; FIGS. 3, 5-7); analyzing the aerial images to detect a presence of a well pad within the geographical region (FIGS. 1-3, 5-7; [0017]-[0018]; [0028], “identify new energy projects … well pad … in a target location …”; [0036], “ … well pad … Land clearing may be identified …”; [0038]; [0049]); receiving further aerial images of the well pad (FIG. 3, steps 304-308; [0067], “… repeated to detect the start of well completion and the end of well completion … well pad …”); monitoring the further aerial images to identify fracking activity on the well pad (FIGS. 1-7; [0017], “… The completion stage includes operations such as hydraulic fracturing …”; [0036], “process satellite image data … at various stages of energy project … initiation or completion … detect next stage activity … a second stage may include well drilling and completion activities”; [0049], “continues to monitor and process satellite image data …determines that the land has been cleared, method 300 proceeds to step 316”; [0067], “detecting the start of drilling and the end of drilling … start of well completion and the end of well completion … Fracking crew with facilities such as frac fleets …”; [0040], “detect … drilling, and/or completion stages … fracking activity”; [0054]); and recording the fracking activity (FIGS. 1, 7; [0004], “memory”; [0029], “store various information associated with detection system 116 and identified energy projects …”; [0040], “historical data”; [0084]).
-Regarding claims 2, 9, and 16, Zheng discloses the method of claim 1, the non-transitory computer readable medium of claim 8, and the system of claim 15. Zheng further discloses creating a chronological series of aerial images for each detected well pad location to form a time-series repository (FIGS. 3-5; [0027], “time series representation of the satellite activity index”; [0038]; [0054], “time series for activity for the energy project (e.g., detecting drilling and completion activity …”; [0062]; [0064]).
-Regarding claims 6, 13, and 20, Zheng discloses the method of claim 1, the non-transitory computer readable medium of claim 8, and the system of claim 15. Zheng further discloses employing a machine learning model that has been trained using a set of training images labeled to indicate the presence or absence of a well pad (FIG. 1, machine learning module 126; FIGS. 2-6; [0028], “Machine learning module 126 may be configured to identify new energy projects … well pads … in target areas … Using images … and labeled energy project information, convolutional neural network may be trained to identify an energy project and/or components of the energy project from image data …”; [0072], “the training set … each image may include labeled information …”; [0088]).
Allowable Subject Matter
Claims 3-5, 7, 10-12, 14 and 17-19 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
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Li et al (US 20220099855 A1), hereinafter Li teaches a method for training of machine learning models to predict stratigraphy of a geologic region from seismic image data of the geologic region.
Jaitly (US 12020337 B2), hereinafter Jaitly teaches a method for analyzing features of an image at a given set of geographic coordinates and determining presence or absence of a well pad using machine learning models.
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/XIAO LIU/Primary Examiner, Art Unit 2664
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