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 .
Election/Restrictions
Applicant’s election without traverse of Group I, corresponding to claims 1-20 in the reply filed on 05/04/5026 is accepted. Claims 21-33 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected Group II and Group III, corresponding to Claims 21-33, there being no allowable generic or linking claim. Election was made without traverse in the reply filed as above.
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 05/17/2026. The
submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the
information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1 -20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1, 19, and 20 recite: “detecting leaks near an emitter”. The term “near” renders the limitation indefinite. Review of specification reveals the term recited in [0033] and [0127] without further guidance for meaning to understand claim limitation. For purposes of examination, Examiner applies broadest reasonable interpretation (BRI) and plain meaning, that an emitter is within a detectable physical distance from a source.
Claim 4 recites: “wherein the processor is further configured to: determine a state for the particular location corresponds to an unsampled state at a particular time”. This language renders the claim to be indefinite. Review of specification leads to understanding of sampling used to “determine” a “leak state”. The term “unsampled state” is understood to mean a state which has not been measured, without clarity regarding how an unsampled state is determined.
Similarly, Claim 5 recites: “third subset of data corresponding to the unsampled state”. This language renders the claim to be indefinite with inconsistent meaning for how “data” corresponds to an “unsampled state”.
Claim 6 recites the limitation “location corresponds to particular region corresponding to a cluster of sensor data”. The term shown in bold renders the claim to be indefinite because it is not clear in meaning. The limitation may imply the “cluster” is related to a geographic location. However, in review of specification for guidance in understand intended limitation, the term “cluster” is found in FIGs. 13, 16, and in [0028]: “model uses robust statistical analysis to provide an accurate prediction of when a leak is detected, where the leak is occurring (e.g., clustering positive pollutant detections into different leaks)”, indicating that “cluster” in a result of computational processing of sensor data, consistent with [0029]: “system clusters positive pollutant detections as a leak”, and further in [0107], where term “cluster” is recited in relation to a probability calculation, and in [0128], where further details of data processing of data clustering is recited. For examination purposes, the limitation will be interpreted as a mathematical process related to sensor data analysis.
Claim 6 further recites: “herein the particular location corresponds to particular region corresponding to a cluster of sensor data indicative.” The sentence, ending with the term in bold appears to be missing information limitation appears to be omitting information regarding meaning, leaving unknown the intention of the limitation regarding what the cluster of sensor data indicates or is indicative of.
Dependent Claims 2-3, and 7-18 are rejected based on direct or indirect dependence to independent Claim 1.
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 1-20 are held to be patent ineligible.
Specifically, Claim 1 limitations, and similarly limitations of Claims 19 and 20, recite abstract ideas (bold emphasis added):
“system for detecting leaks near an emitter, comprising:
a processor configured to:
receive, from one or more mobile sensors, a first stream of information indicative of a leak state;
determine that an initial leak state exists based at least in part on the first stream of information indicative of the leak state;
receive a second stream of information indicative of a no-leak state;
use a statistical model to determine that the leak state has ended based at least in part on the first stream of information and the second stream of information;
receive a third stream of information indicative of the leak state; and
determine that a new leak state exists, wherein the new leak state is a distinct leak state from the initial leak state;
and a memory coupled to the processor and configured to provide the processor with instructions.
Evaluation steps are explained below.
STEP 1 – Determination of statutory category: Independent Claim 1 falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101, namely, Manufacture (System). Likewise, Independent Claims 19 and 20, fall into the categories of Process (method) and machine/manufacture (computer program product with structural limits recited), respectively.
STEP 2A PRONG ONE – Determination regarding whether claim recites a judicial exception: Applying broadest reasonable interpretation (BRI) and using plain meaning, Claim 1 limitations noted in bold emphasis above recite a judicial exception. Such limitations constitute a judicial exception of Abstract Idea because under BRI and using 2024 Revised Patent Subject Matter Eligibility Guidance, the limitations fall into the grouping of subject matter that covers performing mathematics or mental steps ((MPEP 2106.04(a)(2), I.A,C, III.B,C) Examiner notes that performing the mathematical abstract idea involves using at least some generic computer components, as indicated in preamble by reciting “system for detecting leaks near an emitter, comprising: a processor”, with the abstract ideas of “receive”, “determine that an initial leak state exists” “use a statistical model to determine” recite mathematical analysis of acquired data values. It is possible that some processes may involve mental steps involving pen and paper depending on the complexity of the calculation, as supported in specification in at least [0044]: “provide environmental data, a score, confidence score and/or other assessment of the environmental data to a user”.
Thus, Claim 1, and likewise Claims 19 and 20, recites a judicial exception of Abstract Idea in the Mathematical Concept and/or Mental Steps groupings.
STEP 2A-PRONG TWO - Evaluation of additional elements to determine whether
the claim integrates the judicial exception into a practical application of that exception:
Claim 1, and similarly Claims 19 and 20, recites additional elements that do not recite significantly more than the judicial exception to integrate the recited abstract idea into a practical application. Further there is no improvement to another technology or technical field; improvements to the functioning of the computer itself; a particular machine; or effecting a transformation or reduction of a particular article to a different state or thing.
Claim 1 does recite additional elements, including “one or more mobile sensors”, interpreted as source of received data, considered as necessary data gathering required to provide values for carrying out the abstract idea. Limitations reciting necessary data gathering , even when linked to a particular data source or a type of data, are considered to be insignificant extra solution activity, as recited in MPEP section 2106.05(g), necessary data gathering (i.e. receiving data) is considered extra solution activity in light of Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015).
Further, as noted above, Claim 1 limitations recite “processor” and “memory coupled to the processor and configured to provide the processor with instructions”. These additional elements are generic computer components recited at a high level of generality. As recited in MPEP, 2106.05(b), merely adding a generic computer implementation does not automatically overcome an eligibility rejection. (see Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Application/Control Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94.)
Individually, or when viewed in combination, additional elements recited in
Claim 1 do not integrate the recited judicial exception into a practical application.
Thus, Claim 1 is directed to the judicial exception, with similar reasoning applied to Claims 19 and 20.
STEP 2B – Consideration of whether the claim amounts to significantly more than the abstract idea: Additional elements, as discussed above, do not amount significantly more than the judicial exception because, as noted, limitations reciting necessary data gathering, even when linked to a particular data source or a type of data, are considered to be insignificant extra solution activity. As recited in MPEP, 2106.05(b), merely adding a generic computer implementation does not automatically overcome an eligibility rejection. (see Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359- 60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Application/Control Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94.)
Thus, identified additional elements in the Claim 1 are recited in generality
and represent necessary data gathering, or insignificant field of use limitations and do not meaningfully integrate the judicial exception into a practical application.
Evaluation under STEP 2B finds additional elements when considered individually or as a whole do not amount to significantly more than the abstract ide and do not indicate integration of the judicial exception into a practical application. Thus, Claim 1, with similar reasoning applied to Claims 19 and 20, is directed to a judicial exception and is held to be patent ineligible.
Further eligibility consideration includes evaluation of dependent Claims 2-18, with direct or indirect dependence on Claim 1. Review of dependent Claims 2-18 reveals further limitations to the performance of the judicial exception (at least Claims 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18), reciting, for example, limitations interpreted as mathematics using computational processes and/or mental steps, including computational processing and determination of quantitative or qualitative results.
Dependent claims also recite limitations directed to necessary data gathering to perform the judicial exception, as described above (at least Claims 2, 3, 7, 8, 9, 17, 18), reciting, for example, “a communication interface” and receiving, collecting, or monitoring sensor data and/or obtaining stored information (“obtain repair data from a third-party service”, as an example, recited in Claim 7).
In addition, dependent claim limitations recite limitations relating the judicial exception to a field of use recited in generality and not meaningful to indicate a practical application (at least Claims 6,, 7, 9, 10 11 ,12, 18). Such limitations include at least, “particular location corresponds to particular region” “initial leak state exists at a particular location within a geographic region”, “collected over a geographic region for a period of time”, or “associated with the leak as a biogenic source type or a thermogenic source type”. Such language is considered as generally linking the use of a judicial exception to a particular technological environment or field of use, but does not integrate a judicial exception into a practical application. (MPEP § 2106.05(h)). As above, these additional elements do not integrate the judicial exception into a practical application because there is no improvement to another technology or technical field; improvements to the functioning of the computer itself; a particular machine; effecting a transformation or reduction of a particular article to a different state or thing.
Evaluation of limitations recited in dependent claims, taken individually or as a whole, are not sufficient to amount to significantly more than the abstract idea or that indicate integration into a practical application.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 19, and 20 are rejected under 35 U.S.C. 102 (a)(1)/(a)(2) as being anticipated by EICHENLAUB (US 20230304981 A1).
With regard to Claim 1, 19, and 20 EICHENLAUB teaches:
A system for detecting leaks near an emitter, (EICHENLAUB is in same technical field, [0010]: “systems and methods for reducing fugitive emissions…system(s) and method(s) described herein provide remote monitoring of facilities and/or equipment that often emit gasses”; Examiner interprets “emitter” using BRI to mean anything that expels or ejects something or some source of emission.)
comprising: a processor configured to: receive, from one or more mobile sensors, a first stream of information indicative of a leak state; (EICHENLAUB, [0013]: “methods are based on obtaining certain parameters using one or more air quality monitors provided at the site…one or more air quality monitors may include various sensors”; [0170]: “using a mobile sensor”; and FIGs. 9A and 9B with [0047]: “operational flowchart for the qualification of emission type using statistical inference, in accordance with an illustrative configuration of the present disclosure…illustrates an embodiment of a certain unqualified fugitive leak identification method (i.e., “indicative of a leak state”)”
determine that an initial leak state exists based at least in part on the first stream of information indicative of the leak state; (EICHENLAUB, as above, FIG. 9B with [0047]: “embodiment of a certain unqualified fugitive leak identification method through a graph, in accordance with an illustrative configuration” and FIG. 10B with [0048]: “graph related to the number of observations and average emission rates” OR [0065]: “ FIGS. 27-28 … a consistently leaking emissions source at two different times of the day”; Examiner interprets “indicative of the leak state” using BRI to mean generally some evidence that indicates presence of an unintended release of a substance as analogous to reference “stream of information” )
receive a second stream of information indicative of a no-leak state; (EICHENLAUB, [0132]: “point source 449 is not emitting”; and [0158]: “successfully detecting, localizing, and quantifying an emission may not mean that a leak has been detected, and may in fact indicate that the site is operating as designed (i.e., “no-leak state”); and [0193: “Another source of information may be equipment reference measurements…when the operations are supposed nominal (i.e., “no-leak state”)”)
use a statistical model to determine that the leak state has ended based at least in part on the first stream of information and the second stream of information; (EICHENLAUB, [0017]: “methods rely on statistical analysis of large amounts of data”; and FIG. 9A with [0047]: “operational flowchart for the qualification of emission type using statistical inference…illustrates an embodiment of a certain unqualified fugitive leak identification method through a graph” and see FIG. 9B base line “site normal emission average”; Examiner interprets “leak state has ended” using BRI and plane meaning as analogous to reference FIG. 9B illustrating “site normal emission average”.)
receive a third stream of information indicative of the leak state; and determine that a new leak state exists, wherein the new leak state is a distinct leak state from the initial leak state; (EICHENLAUB, [0029]: “receive, from a first air quality monitor, a plurality of individual measurements of each parameter of the first set of onsite parameters, measured over a period of time”; and [0269]: “multiple sensors, for example, three sensors (i.e., the predominate air quality monitor 2104(1), the secondary air quality monitor 2104(2), and the tertiary air quality monitor 2104(3)) may be deployed at the site, for example, a gas pad” (i.e., “third stream of information”); and [0219]: “to the regression model’s predicted concentration, it will not be representative of conditions that did not exist in the data that was used to train the model, such as a new leak or fugitive emission”; and [0136]: “The same model may allow for reconstructing a detection limit…may be specified for different leak size or different confidences of detection”; Examiner interprets “third stream of data” using BRI and plain meaning as generally an additional acquisition of data, in addition to other streams of information as recited above, and not as a number operation of steps, as supported with guidance in specification in at least, [0025]: “”In general, the order of the steps of disclosed processes may be altered within the scope of the invention”)
and a memory coupled to the processor and configured to provide the processor with instructions. (EICHENLAUB, [0029]: “server for locating an emission source of a target substance at a site…server includes a processor and a memory communicatively coupled to the processor…memory stores instructions, which on execution by the processor, cause the processor to: receive, from a first air quality monitor, a plurality of individual measurements of each parameter of the first set of onsite parameters, measured over a period of time.)
With regard to Claim 2, EICHENLAUB teaches the limitations of Claim 1, and further teaches:
a communication interface configured to receive sensor data from one or more mobile sensors, (EICHENLAUB, [0028]: “communications method may include averaging a plurality of individual measurements of each parameter of a set of onsite parameters obtained by an air quality monitor over a period of time…plurality of individual measurements of the set of onsite parameters”; and FIG. 4B with [0036]: “embodiment of a communication architecture of a set of sensor systems”; Examiner notes communication details found in [0116] AND [0117])
wherein the first stream of information, the second stream of information, and the third stream of information is obtained based at least in part on the sensor data. (EICHENLAUB, as above, teaches at least three streams for data acquisition, [0269]: “multiple sensors, for example, three sensors (i.e., the predominate air quality monitor 2104(1) (i.e., “first stream of information”), the secondary air quality monitor 2104(2) (i.e., “second stream of information”), and the tertiary air quality monitor 2104(3)) may be deployed at the site, for example, a gas pad” (i.e., “third stream of information”); and, [0264]: “predominate air quality monitor 2104(1), the secondary air quality monitor 2104(2), and the tertiary air quality monitor 2104(3) may be configured to obtain the first weather reading of local weather from a weather station and modify transmission of an emission data”
With regard to Claim 3, EICHENLAUB teaches the limitations of Claim 1 and further teaches:
the initial leak state exists at a particular location within a geographic region monitored by the one or more mobile sensors. (EICHENLAUB, [0088]: “Air quality monitors 132-134 may be located at multiple different locations…multiple monitors may be located around a sizable area, such as a county, a city, or a neighborhood…instruments may also be located within a building or a dwelling.” (i.e., “at a particular location”); and [0140] “Centralized computing unit 427 may use other messages from another sensing unit 435 for enhanced localization, quantification, and qualification of the emissions. Sensing unit 435 may include multiple sensing units and may be of the same type as sensing unit 433 or any other sensing units present on the sites”)
With regard to Claim 4, EICHENLAUB teaches the limitations of Claim 3 and further teaches:
the processor is further configured to: determine a state for the particular location corresponds to an unsampled state at a particular time. (EICHENLAUB, [0137]: “sensor systems…deployed in a field for the acquisition of weather measurement and compound measurements…takes these measurements and relays messages related to these measurements with timestamps”; and [0156]: “samples t in a data period T 556 may be used by a solver algorithm…each sample t constitutes only a snapshot of the site…a certain number of samples t are used, all within a contiguous period T”; Examiner notes interpretation as discussed above regarding 112(b) rejection of this limitation, and finds limitation analogous to reference in meaning a known time period between data acquisitions (i.e., “unsampled”) )
With regard to Claim 5, EICHENLAUB teaches the limitations of Claim 4 and further teaches:
the statistical model is used to detect that the leak state has ended based at least in part on a time series data comprising a first subset of data corresponding to the leak state, a second subset of data corresponding to the no-leak state, and a third subset of data corresponding to the unsampled state. (EICHENLAUB, as above, See FIG. 9B, depicting three regimes of data, with “site normal emission average” corresponding to “no-leak state”; Examiner notes interpretation of “unsampled state” as above.)
With regard to Claim 6, EICHENLAUB teaches the limitations of Claim 3 and further teaches:
the particular location corresponds to particular region corresponding to a cluster of sensor data indicative.(EICHENLAUB, as above, [0088]: “Air quality monitors 132-134 may be located at multiple different locations…multiple monitors may be located around a sizable area (i.e., “cluster”), such as a county, a city, or a neighborhood…instruments may also be located within a building or a dwelling.” (i.e., “at a particular region”); Examiner notes interpretation of limitation as discussed above regarding rejection under 112(b). )
With regard to Claim 7, EICHENLAUB teaches the limitations of Claim 1 and further teaches:
the initial leak state exists at a particular location within a geographic region monitored by the one or more mobile sensors; (EICHENLAUB, Abstract: “method of locating (i.e., “ at a particular location”)an emission source (i.e., “leak state”) of a target substance at a site is disclosed”; or [0013]:“methods of locating and quantifying emissions at a site are disclosed.”)
a state for the particular location is probabilistically determined to switch from the leak state to a no-leak state based at least in part on the particular location being unsampled over a period of time.(EICHENLAUB, [0019]: “location method may further include generating a mapping of a weighted mean of the plurality of first predicted substance concentrations grouped in each feature group of a predetermined number of feature groups”; and FIG. 14 with [0053]: “analysis performing localization of a…with the probability curves”; and FIG. 5A with [0122]: “sensor system…operates on a dynamic schedule for the sampling…time stamp t as kept and measured by the device and the scheduled start time s…device compares times t and s in step 511 to determine if it is time for starting the sample sequence. If too early (false; t< s), the device waits for the duration m in step 518 and restarts the loop from step 510. (i.e., “being unsampled over a period of time.”)”; and [0158]: “problem 535 may be solved for various periods T using the same dataset in order to achieve different objectives…emissions are to be qualified in step 536…allows further refinements of the understanding of the emissions…successfully detecting, localizing, and quantifying an emission may not mean that a leak has been detected, and may in fact indicate that the site is operating as designed (i.e., “switch from the leak state to a no-leak state”)”)
With regard to Claim 8, EICHENLAUB teaches the limitations of Claim 1 and further teaches:
the first stream of information indicative of the leak state is obtained based at least in part on performing a clustering with respect to sensor data collected over a geographic region for a period of time. (EICHENLAUB, [0018]: “plurality of first predicted substance concentrations may be obtained over a predefined period at a predefined frequency”; and [0102]: “Correlation Process and Calculations:… [0103]: “1) Sort training data into categories using a clustering algorithm…Given a set of d parameters and n observations of each parameter, the present disclosure solved the following minimization equation to cluster the data into k sets S”; and as above, FIG. 1 with [0088]: “example of an air quality monitoring system …a plurality of air quality monitors…may be located at multiple different locations…may be located around a sizable area, such as a county, a city, or a neighborhood. Several instruments may also be located within a building or a dwelling (i.e., “geographic region”)”.
With regard to Claim 9, EICHENLAUB teaches the limitations of Claim 8 and further teaches:
the performing the clustering with respect to the sensor data includes determining a cluster of measurements collected in the sensor data around the emitter.(EICHENLAUB, as above, [0103]: “clustering algorithm…Given a set of d parameters and n observations of each parameter (i.e., “sensor data”), the present disclosure solved the following minimization equation to cluster the data into k sets S”; and, as above, [0013]: “air quality monitors may include various sensors…obtain concentrations of a target substance, for example, methane gas, from one or more potential emission sources (i.e., “emitter”) that may leak the target substance.)
With regard to Claim 14, EICHENLAUB teaches the limitations of Claim 1 and further teaches:
the initial leak state is determined to exist based at least in part on a detection probability (EICHENLAUB, as above, [0019]: “location method may further include generating a mapping of a weighted mean of the plurality of first predicted substance concentrations grouped in each feature group of a predetermined number of feature groups”; and FIG. 14 with [0053]: “analysis performing localization of a…with the probability curves”; and FIG. 47 with [0081]: “graphical plot of degree of uncertainty of detection of an event over a period, in accordance some configurations of the present subject matter”; and [0155]: “uncertainty quantification…rewriting the problem as a function of probability distribution functions of the input parameters, formulating prior probabilities, and using statistical inferences such as Bayesian methods…help in source identification by explicitly solving for the probability that a prospective source is an actual source (i.e., “leak state”) given the sensor system measurements”)
With regard to Claim 15, EICHENLAUB teaches the limitations of Claim 14 and further teaches:
the detection probability includes a leak component corresponding to a probability of detecting a leak, and a no-leak component corresponding to a probability of detecting no leak. (EICHENLAUB, as above, [0155]: “function of probability distribution functions” probability that a prospective source is an actual source (i.e., “leak state”) given the sensor system measurements” [0132]: “point source 449 is not emitting”; and [0158]: “successfully detecting, localizing, and quantifying an emission may not mean that a leak has been detected, and may in fact indicate that the site is operating as designed (i.e., “no-leak state”); and [0193: “Another source of information may be equipment reference measurements…when the operations are supposed nominal (i.e., “no-leak state”)”) )
With regard to Claim 16, EICHENLAUB teaches the limitations of Claim 1 and further teaches:
the processor is further configured to:
determine if a state at a particular location is expected to transition from the leak state to the no-leak state at a particular time; (EICHENLAUB, as above, FIG. 9A with [0047]: “operational flowchart for the qualification of emission type using statistical inference…illustrates an embodiment of a certain unqualified fugitive leak identification method through a graph” and see FIG. 9B base line “site normal emission average”; Examiner interprets “transition from the leak state to the no-leak state” as analogous to graphical indication depicted in reference.)
update a sampling plan to cause the one or more mobile sensors to sample the particular location within a predefined time period of the particular time.(EICHENLAUB, teaches sensors at a particular location and time period, as above, and see [0131]: “time-based criteria may define a time period”; and, [0163]: “actionability engine 537 may be a maintenance tracking system 561…actively update the maintenance strategy”; and [0164]: “Emission inventory trends may be used to evaluate the efficacy of practice or equipment change (i.e., “update sampling plan”) using the abatement tracking system 562”)
With regard to Claim 17, EICHENLAUB teaches the limitations of Claim 1 and further teaches:
the processor is further configured to: obtain repair data from a third-party service indicating repair activity within a geographic location over which the one or more mobile sensors collect sensor data; (EICHENLAUB, [0142]: “Once detection, quantification, qualification, and localization of sources is obtained by the processes in the centralized computing unit 427, actionable data may be generated. Actionable data may mean the data necessary to take a corrective action, including, but not limited to, emission reports, maintenance lists, maintenance tracking (i.e., “repair data) … robotic or automated inspection and repair or maintenance of equipment may be deployed as a response to a command”)
determine whether the repair data indicates that a repair was performed within proximity of the emitter between a time at which the first stream of information is received and a time at which the third stream of information is received (EICHENLAUB, as above, [0142], and [0219]: “once initial leaks are repaired (i.e., “a repair was performed”))
in response to determining that the repair was performed within proximity of the emitter, determine that the leak indicated by the third stream of information is distinct from the initial leak. (EICHENLAUB, [0219]: “once initial leaks are repaired, a long period of time may elapse before new leaks occur, meaning that the probability of leaks is dependent on the history of the site and may widely vary. Thus, the use of datastream and statistical inference of the conditional probabilities of leaks is tremendous for the prediction of potential leaks and appropriate inspection schedules and methods. The proposed method weights these various factors to select the most appropriate inspection embodiment”)
With regard to Claim 18, EICHENLAUB teaches the limitations of Claim 1 and further teaches:
the processor is further configured to: obtain repair data from a third-party service indicating repair activity within a geographic location over which the one or more mobile sensors collect sensor data; (As above, parallel limitation as discussed Claim 18)
determine whether the repair data indicates that a repair was performed within proximity of the emitter between a time at which the first stream of information is received and a time at which the third stream of information is received (As above, parallel limitation as discussed Claim 18)
in response to determining that the repair was not performed within proximity of the emitter, determine that the leak indicated by the third stream of information is not distinct from the initial leak. (As above, parallel limitation as discussed Claim 18, and [0163]: “maintenance tracking system 561, where information from the operator may be used, for example as maintenance log 548, to actively update the maintenance strategy. In the oil and gas industry, the maintenance tracking system 561 could be used to track and schedule maintenance efforts based on available resources and to flag resolutions. For example, the maintenance tracking system 561 could limit the number of flags by avoiding notifying the operator multiple times for the same emissions until the emission is marked as fixed”)
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 11-13 are rejected under 35 U.S.C. § 103(a) as being unpatentable over EICHENLAUB, as applied to Claim 1 above, and further in view of LANGLAND (US 20210010929 A1).
With regard to Claim 11, EICHENLAUB teaches the limitations of Claim 1 and further teaches:
the processor is further configured to provide an indication of time at which a particular leak started and a time at which a particular leak ended. (LANGLAND is in same technical field, , Abstract: “method for monitoring air quality is described. The method includes measuring ethane and methane using a mobile sensor platform to provide sensor data”; and [0033]: “ time each sample is taken (i.e. a time stamp) and the location of each sample can be measured and recorded”; and [0061]: “a peak finding mechanism may be utilized. In some embodiments, one or more of the start/end times of a peak (i.e. “time at which a particular leak started and a time at which a particular leak ended”)”)
It would have been obvious to one of ordinary skill in the art before effective filing date of the claimed invention to modify EICHENLAUB to include the processor is further configured to provide an indication of time at which a particular leak started and a time at which a particular leak ended, as taught by LANGLAND because logging start and end times of an identified leak/emission would allow for a better understanding of root cause for an unexpected or undesired emission. One of ordinary skill would also understand how time stamping would allow for improved compliance with any regulatory requirements
With regard to Claim 12, EICHENLAUB teaches the limitations of Claim 1 and further teaches:
the processor is further configured to classify a source type associated with the leak as a biogenic source type or a thermogenic source type. (LANGLAND , [0022]: “Methane and ethane peak(s) are identified in the sensor data. Correlation(s) between the methane and ethane peak(s)…are determined…source for the methane is determined based on the correlation…In order to determine the correlation between the methane and ethane, a ratio range of ethane to methane to methane may be calculated… thermogenic source, such as a wellhead of natural gas, may be determined to exist if the ratio range is greater than six percent. A non-natural gas source, such as a landfill or other biogenic source, may be determined to exist if the ratio range is less than one percent”
It would have been obvious to one of ordinary skill in the art before effective filing date of the claimed invention to modify EICHENLAUB to include the processor is further configured to classify a source type associated with the leak as a biogenic source type or a thermogenic source type, as taught by LANGLAND because this knowledge would have impact on necessary safety, maintenance, and or repair implementation, and would further enhance and strengthen the detection method with more specific and detailed information regarding leak.
With regard to Claim 13, EICHENLAUB in view of LANGLAND, teaches the limitations of Claim 12 and further teaches:
LANGLAND teaches further:
the processor classifies the source type as the biogenic source type, or the thermogenic source type based at least in part on a determination of whether sensor data near the emitter indicates a presence of ethane. (LANGLAND, as above [0022]: “Methane and ethane peak(s) are identified in the sensor data…thermogenic source, such as a wellhead of natural gas, may be determined to exist… biogenic source, may be determined to exist”; and [0023]: “sensor data may also be further analyzed…source location may be determined based on the source identified, the corresponding methane peak(s), the corresponding ethane peak(s), a wind speed and a wind direction. Clustering may be performed for the methane peak(s), the ethane peak(s) and/or the sources. )
It would have been obvious to one of ordinary skill in the art before effective filing date of the claimed invention to modify EICHENLAUB to include the processor classifies the source type as the biogenic source type, or the thermogenic source type based at least in part on a determination of whether sensor data near the emitter indicates a presence of ethane, as taught by LANGLAND because this information would improve accuracy of the detection method and specify emission products (leak types), which would reduce false alarms and allow for prioritization of maintenance/repair activities in the case of exclusively on thermogenic sources.
Claim 10 is rejected under 35 U.S.C. § 103(a) as being unpatentable over EICHENLAUB, as applied to Claim 1 above, and further in view of NOTTROTT (US 10962437 B1).
With regard to Claim 10, EICHENLAUB teaches the limitations of Claim 1 and further teaches:
the processor is further configured to implement a hidden Markov model (HMM) to determine whether a state at a particular location corresponds to the leak state or the no-leak state. (NOTTROTT is in same technical field, Pg 36-Col1L13: “The invention relates to systems and methods for detecting gas leaks such as methane leaks… A clustering algorithm (e.g. Markov, DBScan) may be used to group a set of indications into a cluster characterizing the leak.”; and see FIG. 1, and Pg 40, Col 10L18: FIG. 9 is a schematic diagram illustrating an example of detecting or not detecting a gas leak from a potential gas leak source”)
It would have been obvious to one of ordinary skill in the art before effective filing date of the claimed invention to modify EICHENLAUB to include the processor classifies the source type as the biogenic source type, or the thermogenic source type based at least in part on a determination of whether sensor data near the emitter indicates a presence of ethane, as taught by NOTTROTT because this statistical/modeling process is a proven way to reduce or eliminate environmental noise and discriminate out persistent emission from temporary or localized spikes of a specific emission type.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
COOPER (US 20230393013 A1) – teaches specific statistical/probabilistic process for methane detection using multiple sensors.
THORPE (US 20220412732 A1) - teaches a 3D method for identifying sources and locations of gas emission.
SCOTT (US 20220397521 A1) -teaches multi-monitor assessment of air quality.
LEEN (US 20220187199 A1) – teaches a detailed method for identifying location of leak sources.
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/TONI D SAUNCY/Examiner, Art Unit 2857
/Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2857
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