DETAILED ACTION
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05/17/2026 has been entered.
Claims 41 – 60 have been presented for examination. Claims 1 – 40 are cancelled.
Response to Response to§ 112(b) Indefiniteness Rejection
Applicant has cancelled the rejected claim(s), therefore the rejection is moot and withdrawn.
Response to Response to§ 112(a) Written Description Rejection
Applicant has cancelled the rejected claim(s), therefore the rejection is moot and withdrawn. However, a new 112(a) rejection is included which is necessitated by the amendments (see Claim Rejections - 35 USC § 112).
Response to § 101 Rejections
Applicant’s arguments have been fully considered. However, the Office does not consider them to be persuasive.
Applicant argues: “A human cannot mentally execute a fracture-geometry simulator over real-time pressure and flow-rate data during a hydraulic-stimulation treatment, mentally compute deviation-and relevance-weighted updates to a fracture-network state representation in real time as additional measurements arrive, and mentally generate a control parameter targeted at adjusting injection rates, pressures, and proppant concentrations during ongoing stimulation” (emphasis added)
Applicant argues that various limitations cannot be conducted in “real-time” or “during ongoing stimulation”. Examiner notes that only claim 44 (and similarly claim 55) recite “updating the fracture-network state representation in real time during the hydraulic-stimulation treatment as additional pressure-response deviations are identified”. Claim 44 notwithstanding, Examiner notes that a stimulation treatment cycle can be on the order of hour(s) (see Lehmann Figure 5
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) and related treatment parameters (i.e., pumping pressure) also vary on the order of hour(s) (see Figure 14
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). Therefore any “real time” performance covers time scales over which a human mind operates. Therefore, Applicant’s arguments are not persuasive.
Applicant argues: “Dependent claims 49 (method) and 59 (apparatus) further tie the claimed control parameter to a specific physical action - issuance of an instruction”
Examiner acknowledges that issuing a control instruction cannot practically be performed in the mind. However, the instruction is merely limited by what practical effect it accomplishes at a functional level, and is not specific with regard to the tangible action performed (i.e., close a valve, activate an inflatable packer, etc.) to achieve said practical effect. Therefore, the issuance of the instruction amounts to reciting the words “apply it”. Further, Paragraph 41 of the instant application (also Paragraph 50 of the PGPUB) does not give any more detail on how said instruction is implemented (“Additionally the invention may be used to provide operators with data driven suggestions of when the shut off of that frac zone, stopping it from further growth toward the parent wells/secondary wells”).
Applicant argues: “Even if any element were considered abstract, the claims integrate it into a practical application by producing a control parameter that is, by the specification's own definition, an input to "specific operational variables and conditions that are controlled and adjusted during the fracturing process" (Spec Paragraph,22). The claimed architecture improves the operation of hydraulic stimulation systems by closing the loop between simulator prediction, measured pressure response, production-data correlation, and adjustment of physical treatment parameters.
This is not "linking" an abstract idea to a technological environment (cf. MPEP 2106.0S(h)); the claims define a particular technical arrangement in which (i) the simulator's prediction error is the input, (ii) the relevance-weighted iterative update is the intermediate computation, and (iii) a control parameter targeted at specifically-enumerated physical treatment parameters is the output. Each element is tied to physical pressure measurement, physical fracture-network state, and physical treatment parameters - not to generic computational operations. The claimed improvement is in the operation of hydraulic-stimulation systems, which is one of the categories of practical application recognized under MPEP 2106.0S(a) ("improvements to ... another technology or technical field"). The improvement is concrete: a control parameter that targets the specifically-defined operational variables of injection rate, injection pressure, proppant concentration, fracture stage spacing, fracture fluid volume, or fracture fluid composition.” (emphasis added)
As previously remarked, the instruction is merely limited by what practical effect it accomplishes at a functional level, and is not specific with regard to the tangible action performed (i.e., close a valve, activate an inflatable packer, etc.) to achieve said practical effect. Further, the improved operation of any hydraulic-stimulation systems is almost entirely enabled by previously recited limitations including the abstract idea limitations. Therefore, the issuance of the instruction amounts to reciting the words “apply it”.
Applicant argues: “The claimed elements, considered as an ordered combination, recite significantly more than any alleged abstract idea. The combination of: [claimed limitations] …
is neither well-understood, routine, nor conventional. The Examiner's prior characterization of the receiving, training, and displaying steps as "well-understood, routine, and conventional" (MPEP 2106.05(d)(II)) does not apply to this ordered combination. None of the cited references discloses this architecture, and the Final Office Action expressly recognized - in connection with old claim 25 - that "correlating the detected pressure events with production data to determine a value of each pressure event, wherein the value indicates a relevance of the pressure event to reservoir performance" is not disclosed by the prior art of record (Final OA ,i 5). That examiner acknowledged novel feature is now integrated into independent claim 41 as the relevance score determination.” (emphasis added)
Applicant argues that one or more combinations of recited limitations, which largely include limitations of the abstract idea itself, are other than well-understood, routine, and conventional activity (see emphasis above). Examiner notes that the novelty of the limitations is of no relevance (see MPEP 2106.05(I) “As made clear by the courts, the "‘novelty’ of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the § 101 categories of possibly patentable subject matter”). Further, simply appending one or more additional elements does not amount to significantly more, especially when such activities are recited at high-level of generality (see MPEP 2106.05(I)(A) “ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception,”). Further, Applicant has not articulated how the recited combination of abstract idea plus additional elements adds anything more than when considering them individually, beyond arguing the novelty of one or more of the limitations.
Response to Rejections under 35 U.S.C. § 103
Applicant has cancelled all previous claims 21 – 40, and presented new claims 41 – 60. Applicant’s new claims overcome the prior art rejection. Therefore, it is withdrawn.
Applicant argues: “Importantly, the Final Office Action expressly recognized that "correlating the detected pressure events with production data to determine a value of each pressure event, wherein the value indicates a relevance of the pressure event to reservoir performance" is not disclosed by the prior art of record (Final OA ,i 5, Allowable Subject Matter). Independent claim 41 now incorporates that examiner-acknowledged novel feature directly, recasting it as a "relevance score" with a defined computational role (weighting the contribution of each pressure-response deviation to the iterative update of the fracture-network state representation).”
Examiner notes that the “correlating” recited in the instant application is fundamentally different from the “correlating” in canceled claim 25 since the instant “correlating” is with regards to “pressure-response deviations” and the canceled claim 25 “correlating” is with regard to “pressure events” which are not analogous quantities.
Allowable Subject Matter
The following is a statement of reasons for the indication of allowable subject matter, subject to overcoming the 101 and 112(a) rejection.
None of the prior art of record taken individually or in combination discloses the claim 41 (and similarly claim 51, and by incorporation claims 42 – 50 and 52 – 60) method for controlling a hydraulic-stimulation treatment of a subterranean formation, the method comprising: “d) correlating, using the at least one processor, the identified pressure-response deviations with hydrocarbon production data associated with the target well to determine a relevance score for each pressure-response deviation, wherein the relevance score is indicative of an impact of the pressure-response deviation on reservoir performance; e) iteratively updating, using the at least one processor, a fracture-network state representation during the hydraulic-stimulation treatment as a function of the identified pressure-response deviations weighted by the corresponding relevance scores, wherein the fracture-network state representation represents one or more fracture network conditions of fractures formed during the hydraulic-stimulation treatment”, in combination with the remaining elements and features of the claim. It is for these reasons that the applicant’s invention defines over the prior art of record.
Morton et al. “Global Sensitivity Analysis for Natural Fracture Geological Modeling Parameters from Pressure Transient Tests” teaches a conductivity a semi-analytical solution for pressure transient behavior of fractured reservoirs. However, does not appear to explicitly disclose: correlating, using the at least one processor, the identified pressure-response deviations with hydrocarbon production data associated with the target well to determine a relevance score for each pressure-response deviation, wherein the relevance score is indicative of an impact of the pressure-response deviation on reservoir performance; iteratively updating, using the at least one processor, a fracture-network state representation during the hydraulic-stimulation treatment as a function of the identified pressure-response deviations weighted by the corresponding relevance scores, wherein the fracture-network state representation represents one or more fracture network conditions of fractures formed during the hydraulic-stimulation treatment.
Mu, Nan et al. (WO 2020/097060) teaches detecting an abnormal pressure trend or deviation. However, does not appear to explicitly disclose: correlating, using the at least one processor, the identified pressure-response deviations with hydrocarbon production data associated with the target well to determine a relevance score for each pressure-response deviation, wherein the relevance score is indicative of an impact of the pressure-response deviation on reservoir performance; iteratively updating, using the at least one processor, a fracture-network state representation during the hydraulic-stimulation treatment as a function of the identified pressure-response deviations weighted by the corresponding relevance scores, wherein the fracture-network state representation represents one or more fracture network conditions of fractures formed during the hydraulic-stimulation treatment.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
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 the first paragraph of pre-AIA 35 U.S.C. 112:
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 of carrying out his invention.
Claims 41 – 60 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
With regard to claim 41 (and similarly claim 51), it recites “correlating … the identified pressure-response deviations with hydrocarbon production data associated with the target well to determine a relevance score for each pressure-response deviation, wherein the relevance score is indicative of an impact of the pressure-response deviation on reservoir performance”. As indicated by Applicant, the “correcting” is related to verification data and an “accuracy score” (see Applicant’s remarks, dated 05/17/2026, Page 3 cited to PGBPUB paragraph 27, 31 – 34 , 44 and 49). Looking to Paragraph 44 in particular, the “accuracy score” concerns the accuracy of an ML model. In contrast, the recited “relevance score” concerns the impact of pressure-response deviation on reservoir performance (i.e., the impact of deviations between measured and predicted behavior on reservoir performance). This is different from the disclosed “accuracy” which can be used to indicated when retraining is needed for an ML classifier. Examiner further notes that Paragraph 32 does not explicitly mention the recites “pressure-response deviations” (“Categories may include normal reading, abnormal reading, high/low pressure readings, high/low temperature readings, high/low viscosity readings, geographic conditions, well conditions, and the like”).
Further, it recites “as a function of the identified pressure-response deviations weighted by the corresponding relevance scores,” in “iteratively updating, using the at least one processor, a fracture-network state representation during the hydraulic-stimulation treatment as a function of the identified pressure-response deviations weighted by the corresponding relevance scores, wherein the fracture-network state representation represents one or more fracture network conditions of fractures formed during the hydraulic-stimulation treatment”. As indicated by Applicant, the “iteratively updating ” has support is various disparate paragraph (see Applicant’s remarks, dated 05/17/2026, Page 3 cited to PGBPUB paragraph 38, 41 – 43, 65). However, these paragraphs do not appear to explicitly disclose any weighting between pressure-response deviations and relevance scores. Looking to Paragraph 41 – 43 in particular, a user provides feedback which is used for ML model updates (see Paragraph 42 “Incorporating the user feedback may include updating the training data by removing or adding correlations of user data to a path or resources as indicated by the feedback.”).
With regard to claim 45 (and similarly claim 55), it recites “applying a trained mapping function that maps output of the fracture geometry simulation model to a corrected fracture-network state representation based on previously observed pressure-response behavior”. As indicated by Applicant, the “applying a trained mapping function” is related to iterative retraining using prior inputs/outputs and/or a supervised machine learning process (see Applicant’s remarks, dated 05/17/2026, Page 4 cited to PGBPUB paragraph 39, 41 and 65 - 68). However, these paragraphs do not appear to explicitly disclose trained mapping function as part of an iterative updating. Looking to Paragraph 41 in particular, a previous machine learning model is used to continuously train a later machine learning model, and continuously incorporating user feedback (“The reservoir machine learning model may then be updated by using previous inputs and outputs from the first reservoir machine-learning model as second training data to then train a second machine learning model”). In contrast, the recited “trained mapping function” would be a third trained element to effectuate a later model from a previous model. A search in the disclosure for “mapping function” did not produce any results.
With regard to claim 46 (and similarly claim 56), it recites “wherein the trained mapping function comprises a neural network trained using supervised training data derived from simulated fracture behavior and measured pressure-response data from prior hydraulic-stimulation treatments”. As discussed with regards to claim 45, there does not appear to be explicitly disclosed the “training mapping function”, which would amount to a third ML model in the disclosure of Paragraph 41.
With regard to claims 42 – 44, 47 – 50, 52 – 54 and 57 – 60, they are rejected by virtue of depending from a rejected parent claim, and without reciting any further limitations to overcome the deficiency.
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 41 – 60 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
Independent claim 41 recites at Step 1 a statutory category (i.e. a process) computer-implemented method for controlling a hydraulic-stimulation treatment of a subterranean formation, the method comprising: c) identifying pressure-response deviations between measured pressure behavior of injected fluid and pressure behavior predicted by the fracture geometry simulation model; d) correlating the identified pressure-response deviations with hydrocarbon production data associated with the target well to determine a relevance score for each pressure-response deviation, wherein the relevance score is indicative of an impact of the pressure-response deviation on reservoir performance; e) iteratively updating a fracture-network state representation during the hydraulic-stimulation treatment as a function of the identified pressure-response deviations weighted by the corresponding relevance scores, wherein the fracture-network state representation represents one or more fracture network conditions of fractures formed during the hydraulic-stimulation treatment; and f) generating a control parameter configured to adjust at least one treatment parameter of the hydraulic-stimulation treatment based on the updated fracture-network state representation, wherein the treatment parameter comprises at least one of injection rate, injection pressure, proppant concentration, fracture stage spacing, fracture fluid volume, or fracture fluid composition. At Step 2A, Prong I the recited limitations, alone or in combination, amount to steps that, under its broadest reasonable interpretation, cover performance of the limitations in the mind in combination with using a pen and paper (see MPEP 2106.04(a)(2)(III)). For example, the “identifying” and “correlating” amounts to modeling actions recited at a high-level of generality. The “iteratively updating” uses a previously generated state and updates it recited at a high-level of generality, which requires no more than judgements and evaluations for performing update operations on the fracture-network state. The “generating” covers merely created the control, and does not require transmitting the control parameter for controlling. Accordingly, the claim recites an abstract idea.
At Step 2A, Prong II this judicial exception is not integrated into a practical application since the claimed invention further claims: that the method is computer-implemented; that the “identifying” and “correlating” and “iteratively updating” and “generating” and “using the at least one processor”; a) receiving, using at least one processor, pressure data and flow-rate data measured during the hydraulic-stimulation treatment of a target well; b) executing, using the at least one processor, a fracture geometry simulation model configured to predict pressure behavior for the hydraulic-stimulation treatment. The “computer-implemented” and “processor” are recited at a high-level of generality such that they amount to no more than mere application of the judicial exception using generic computer components which does not amount to an improvement in computer functionality (see MPEP 2106.04(a)(I)). The “receiving” amounts to insignificant data gathering since it is recited at a high-level of generality, and since the “identifying” and “correlating” steps rely on the received elements in a generic manner (see MPEP 2106.04(d)). The “executing” amounts to the idea of an outcome since the “fracture geometry simulator” covers a generic simulator. The claim is directed to an abstract idea.
At Step 2B the claim does not recite additional elements that, alone or in an ordered combination, are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the recited “computer-implemented” and “processor” amount to no more than mere instructions to apply the judicial exception using generic computer components. The recited “receiving” covers well-understood, routine, and conventional activity since it is generic and covers receiving data by any electronics means (see MPEP 2106.05(d)(II) “i. Receiving or transmitting data over a network”). The “executing” amounts to reciting the words “apply-it”. Considering the additional elements in combination does not add anything more than when considering them individually since the “receiving” and “executing” require no more than generic computer functions. For at least these reasons, the claim is not patent eligible.
Dependent claim 42 – 50 recite(s) at Step 1 the same statutory category as the parent claim(s), and further recite(s): Claim 43 wherein identifying the pressure-response deviations comprises detecting increases or decreases in pressure behavior associated with changes in injection rate during the hydraulic-stimulation treatment; Claim 44 wherein iteratively updating the fracture-network state representation comprises updating the fracture-network state representation in real time during the hydraulic-stimulation treatment as additional pressure-response deviations are identified; Claim 45 wherein iteratively updating the fracture-network state representation comprises applying a trained mapping function that maps output of the fracture geometry simulation model to a corrected fracture-network state representation based on previously observed pressure-response behavior; Claim 50 predicting an effect of the hydraulic-stimulation treatment on a secondary well based on the updated fracture-network state representation. At Step 2A, Prong I the recited limitations, alone or in combination, amount to steps that, under its broadest reasonable interpretation, cover performance of the limitations in the mind in combination with using a pen and paper (see MPEP 2106.04(a)(2)(III)). For example, the “detecting increases or decreases” covers mentally analyzing the acquired data for changes, which requires no more than judgements and evaluations based on observations. The “updating” and “applying a trained mapping function” uses a previously generated state and updates it recited at a high-level of generality since the “trained mapping function” is not limited to any particular function, which requires no more than judgements and evaluations for performing update operations on the fracture-network state. The ”predicting” requires no more than judgement and evaluations based on observations. Accordingly, the claim(s) recite(s) an abstract idea.
At Step 2A, Prong II this judicial exception is not integrated into a practical application since the claimed invention further claims: Claim 42 wherein the pressure data and flow-rate data are acquired from at least one of surface sensors, down hole sensors, inferred reservoir data, or simulated data; Claim 46 wherein the trained mapping function comprises a neural network trained using supervised training data derived from simulated fracture behavior and measured pressure-response data from prior hydraulic-stimulation treatments; Claim 47 wherein the supervised training data comprises fracture geometry parameters generated by a reservoir model paired with corresponding measured pressure-response data indicative of fracture behavior.
Claim 48 outputting the updated fracture-network state representation to a display device during the hydraulic-stimulation treatment; Claim 49 wherein the control parameter comprises an instruction to shut off a frac zone of the hydraulic-stimulation treatment, the instruction issued in response to the updated fracture-network state representation indicating fracture propagation toward a parent well or a secondary well; Claim 50 that the “predicting” is using the at least one processor. For example, the “acquired” amounts to insignificant data gathering since it further limits the received condition data (see MPEP 2106.04(d)). The “neural network trained” and “supervised training data comprises” recites the idea of an outcome of training a model with specific training data, therefore, it amounts to reciting the words “apply it”. The “outputting” amounts to insignificant data outputting since it is recited at a high-level of generality. The “an instruction” and “instruction issued” recites the idea of an outcome, therefore, it amounts to reciting the words “apply it” (see Response to § 101 Rejections). The “processor” is recited at a high-level of generality such that they amount to no more than mere application of the judicial exception using generic computer components which does not amount to an improvement in computer functionality (see MPEP 2106.04(a)(I)). The claim is directed to an abstract idea.
At Step 2B the claim(s) do not recite additional elements that, alone or in an ordered combination, are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the recited “computer-implemented” and “processor” amount to no more than mere instructions to apply the judicial exception using generic computer components. The recited “acquired” and “outputting” covers well-understood, routine, and conventional activity since it is generic and covers receiving and outputting data by any electronics means (see MPEP 2106.05(d)(II) “i. Receiving or transmitting data over a network”). The “executing” amounts to reciting the words “apply-it”. The “neural network trained” and “supervised training data comprises” amounts to reciting the words “apply it”. The “outputting” amounts to insignificant data outputting since it is recited at a high-level of generality. The “an instruction” and “instruction issued” recites the idea of an outcome, therefore, it amounts to reciting the words “apply it” (see Response to § 101 Rejections). Considering the additional elements as an ordered combination does not add any more than considering them individually since the “acquired” and “neural network trained” and “supervised training data comprises” and “outputting” and “an instruction” and “instruction issued” require no more than generic computer functions and/or ordinary equipment operating in their ordinary capacity. For at least these reasons, the claim(s) are not patent eligible.
Independent claim 51 recites at Step 1 a statutory category (i.e. a machine) apparatus for controlling a hydraulic-stimulation treatment of a subterranean formation, comprising: (iii) identify pressure-response deviations between measured pressure behavior of injected fluid and pressure behavior predicted by the fracture geometry simulation model; (iv) correlate the identified pressure-response deviations with hydrocarbon production data associated with the target well to determine a relevance score for each pressure-response deviation, wherein the relevance score is indicative of an impact of the pressure-response deviation on reservoir performance; (v) iteratively update a fracture-network state representation during the hydraulic-stimulation treatment as a function of the identified pressure-response deviations weighted by the corresponding relevance scores, wherein the fracture-network state representation represents one or more fracture network conditions of fractures formed during the hydraulic-stimulation treatment; and (vi) generate a control parameter configured to adjust at least one treatment parameter of the hydraulic-stimulation treatment based on the updated fracture-network state representation, wherein the treatment parameter comprises at least one of injection rate, injection pressure, proppant concentration, fracture stage spacing, fracture fluid volume, or fracture fluid composition. At Step 2A, Prong I the recited limitations, alone or in combination, amount to steps that, under its broadest reasonable interpretation, cover performance of the limitations in the mind in combination with using a pen and paper (see MPEP 2106.04(a)(2)(III)). For example, the “identify” and “correlate” amounts to modeling actions recited at a high-level of generality. The “iteratively update” uses a previously generated state and updates it recited at a high-level of generality, which requires no more than judgements and evaluations for performing update operations on the fracture-network state. The “generate” covers merely created the control, and does not require transmitting the control parameter for controlling. Accordingly, the claim recites an abstract idea.
At Step 2A, Prong II this judicial exception is not integrated into a practical application since the claimed invention further claims: a) at least one processor; and b) a non-transitory memory communicatively connected to the at least one processor and storing instructions that, when executed by the at least one processor, cause the apparatus to; (i) receive pressure data and flow-rate data measured during the hydraulic-stimulation treatment of a target well; (ii) execute a fracture geometry simulation model configured to predict pressure behavior for the hydraulic-stimulation treatment. The “processor” and “memory” are recited at a high-level of generality such that they amount to no more than mere application of the judicial exception using generic computer components which does not amount to an improvement in computer functionality (see MPEP 2106.04(a)(I)). The “receive” amounts to insignificant data gathering since it is recited at a high-level of generality, and since the “identify” and “correlate” steps rely on the received elements in a generic manner (see MPEP 2106.04(d)). The “execute” amounts to the idea of an outcome since the “fracture geometry simulator” covers a generic simulator. The claim is directed to an abstract idea.
At Step 2B the claim does not recite additional elements that, alone or in an ordered combination, are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the recited “processor” and “memory” amount to no more than mere instructions to apply the judicial exception using generic computer components. The recited “receive” covers well-understood, routine, and conventional activity since it is generic and covers receiving data by any electronics means (see MPEP 2106.05(d)(II) “i. Receiving or transmitting data over a network”). The “execute” amounts to reciting the words “apply-it”. Considering the additional elements in combination does not add anything more than when considering them individually since the “receive” and “execute” require no more than generic computer functions. For at least these reasons, the claim is not patent eligible.
Dependent claim 52 – 60 recite(s) at Step 1 the same statutory category as the parent claim(s), and further recite(s): the same limitations as claims 42 – 50. Accordingly, the claim(s) recite(s) an abstract idea for the same reasons.
At Step 2A, Prong II this judicial exception is not integrated into a practical application since the claimed invention further claims: the same additional elements as claims 42 – 50. The claim is directed to an abstract idea for the same reasons.
At Step 2B the claim(s) do not recite additional elements that, alone or in an ordered combination, are sufficient to amount to significantly more than the judicial exception since they recite the same additional elements as claims 42 - 50. For at least these same reasons, the claim(s) are not patent eligible.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALFRED H. WECHSELBERGER whose telephone number is (571)272-8988. The examiner can normally be reached M - F, 10am to 6pm.
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/ALFRED H. WECHSELBERGER/ExaminerArt Unit 2187
/EMERSON C PUENTE/Supervisory Patent Examiner, Art Unit 2187
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