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 .
DETAILED ACTION
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “unit” in claims 1-8,10.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claim 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to nonstatutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claim(s) is/are directed mere information in the form of data (e.g. a transitory computer program).
Claims 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Regarding independent claims 1,9,10 the claimed invention recites an abstract idea without significantly more. The claims recites the abstract idea of generating and selecting a project plan/scenario which is a mental process. Other than reciting a device or unit nothing in the claims precludes the steps from being performed mentally. But for the device or unit the limitations on generate draft scenarios, generate baseline draft plans, acquire evaluation results of operational draft plans (a combination of draft scenarios and baseline draft plans), aggregate draft scenarios into groups based on results, select draft scenario as representative scenario is a process that under its broadest reasonable interpretation could be performed by mentally but for the recitation of generic computer elements. If claim limitations, under the broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Further the above limitations related to generating and selecting a project plan/scenario stripped of the identified additional and insignificant elements could also be considered a “Method of Organizing Human Activity” relating to the managing human behavior and interactions. The examiner considers project management to be a fundamental economic practice. Thus, the claims recite an abstract idea.
The judicial exception is not integrated into a practical application. The computers are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components. The additional element(s) does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Simply implementing the abstract idea on a generic computer environment is not a practical application of the abstract idea and does not take the claim out of the mental process or method of organizing human activity grouping. ]
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, with respect to integration of the abstract idea into a practical application, the additional element of a device or unit amounts to no more than mere instructions to apply the exception using a generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept Collecting, analyzing and displaying information, and receiving and transmitting over a network are conventional in the computing arts. (MPEP 2106.05h; See also MPEP 2106.05, Alice v. CLS, “. Nearly every computer will include a ‘communications controller’ and ‘data storage unit’ capable of performing the basic calculation, storage, and transmission functions required by the method claims.”). The claims are not patent eligible.
Regarding dependent claims 2-8 these claims are directed to limitations which serve to limit the generating and selecting a project plan/scenario steps. The subject matter of claims 2 (generate approximation evaluator with training), 3 (calculate degree influence of draft scenario on results and aggregate based on degree of influence), 4 (select representative scenario based on degree of influence), 5 (search for value of uncertainty parameter by which results become lowest as draft scenario), 6 (search for value of uncertainty parameter by which results become highest as baseline draft scenario), 7 (generate predetermined count of draft scenarios), 8 (evaluate error of strict evaluation results and approximation evaluation results and update approximation evaluator)
appear to add additional steps to the abstract idea, implemented by generic computers. These claims neither introduce a new abstract idea nor additional limitations which are significantly more than an abstract idea. They provide descriptive details that offer helpful context, but have no impact on statutory subject matter eligibility.
Therefore the limitations on the invention, when viewed individually and in ordered combination are directed to in-eligible subject matter.
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 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 1,2,5-7, 9,10 are rejected under 35 U.S.C. 102a1 as being anticipated by AlShahri 12385393
Regarding Claim 1 ,
a draft scenario generation unit configured to generate, based on uncertainty information in which values of an uncertainty parameter relating to uncertainty concerning the planning target are expressed as a probability, a plurality of draft scenarios indicating values that the uncertainty parameter can take;
Alshari is directed to a system for calculating parameters for oil wells based on historic attributes. (Alshari, abstract). Alshari discloses producing scenarios based on oil well parameters. (AlShari, col.,13,lns.1-24, “As an example, assume there are four wells: W1 through W4, and two scenarios are made. As used herein, “scenario” refers to parameters that are applied for a simulation. In the first scenario, higher priorities are given to drill wells within the same field, before considering the distances between wells. In this case, a rig starting in W1 will move to W2 before W3 because they are within the same field (i.e., field X), even though the distance between W1 and W2 is longer than the distance between W1 and W3. In the second scenario, the priorities are changed and it is opted to consider shorter distances before changing the field. Now the rig, starting in W1, will move to W3 before W2. As mentioned previously, these priorities may be taken into consideration only for wells that have the same well class and share the same transition probability. In the example shown in FIG. 9, W4 will never be drilled from rigs starting in W1, W2, or W3. The rig movement priorities may be set up considering many attributes (e.g., distance, field, year, well cost, well drill time . . . etc.). Embodiments are not limited by any particular priority rules.)”
a baseline draft plan generation unit configured to generate, based on definition region information indicating a range of values of a determinate parameter relating to the planning target that is different from the uncertainty parameter, a plurality of baseline draft plans indicating values that the determinate parameter can take;
(Alshari, col.16,lns.25-50, “The simulation is performed using the user-preferences for the MC model, the rig movement priorities, initial rig location information, adding/removing rig parameters, and any other specified user parameters. For each simulation forecast, the output file contains all specifications set by the user, including maximum number of additional rigs that is allowed to be added per year, the rig stopping date in gas and oil wells, in addition to the cutoff dates for releasing rigs. FIG. 12 shows an example of simulation parameters used in one of the simulations. In FIG. 12, the parameters are user-defined inputs, and embodiments offer the flexibility of varying the parameters in every run. The non-limiting example parameters include simulation start year, simulation end year, global multiplier to well cost, global multiplier to well drill time, maximum number of rigs added for various years of the simulation period, rig starting/stopping month and day in gas and oil wells, released rigs cut-off month, and released rigs cut-off day. It is noted that the global multiplier to well cost and the global multiplier to well drill time are to account for higher cost and time or lower cost and time to increase or decrease the estimated time and cost taken to drill future wells. These parameters may be set to run any correction required in the case of an overestimate of the cost and time where a less than 1 multiplier can be applied or underestimate of the cost and time where a higher than 1 multiplier can be applied.”)
an approximation evaluation unit configured to acquire, by using an approximation evaluator that has learned strict evaluation results evaluated a plurality of an operational draft plans for training obtained by a strict evaluator that evaluates an operational draft plan, which is a combination of the draft scenarios and the baseline draft plans, approximation evaluation results in which a plurality of the operational draft plans for evaluation are evaluated;
(Alshari, col.10,lns.49-62, “Referring once again to FIG. 1, embodiments of the present disclosure are also directed to systems and methods for generation of long-term drilling schedules for oil and gas business planning (blocks 17 and 18). Generally, embodiments model the movement of rigs between wells while honoring operational and logistical restrictions to mimic reality. The machine-learning algorithm of the present disclosure learns from historic drilling schedules, and extracts rules and applies them for futures wells. Use of the Markov Chain models described herein enable embodiments to automatically generate drilling schedules with significantly reduced time and significantly reduced computer processing power as compared with traditional methods.”)
an aggregation unit configured to aggregate the draft scenarios into a plurality of groups, based on the approximation evaluation results; and
(Alshari, fig.2)
a selection unit configured to select, for each of the groups, one of the draft scenarios belonging to that group as a representative scenario, based on the approximation evaluation results.
(Alshari, col.7, lns. 30-38, “ The three-dimensional plot allows a user to quickly evaluate multiple simulated scenarios according to three dimensions. Depending on the requirements of the business plan, the most desirable scenario provided by the simulation outputs may be the simulation that has the lowest well count, the highest NPV, and the highest cumulative production. However, this may not be the case for all business plans.”)
Regarding Claim 2, Alshari discloses the device of claim 1.
an approximation evaluator generation unit configured to generate the approximation evaluator by causing the strict evaluator to evaluate a combination of the draft scenarios for training and the baseline draft plans for training as the operational draft plans for training.
(Alshari, col.10,ln.62-col.14,ln.24, “First, rig capabilities are learned from historical drilling activities. Rig capabilities refer to the various rig parameters, such as, without limitation, shore type (e.g, onshore or offshore), fluid type (e.g, whether a rig can be assigned to oil wells, water wells, or gas wells, or any combinations of these wells), and rig horsepower (e.g., rigs with relatively low horsepower may not be able to drill horizontal wells). Contracting conditions may also be considered as part of rig capabilities because they influence the assignment of rigs to certain wells. Contracting conditions refer to specific contracts that limit the drilling for a given rig(s) to certain type of well(s) in certain field(s).
(72) In embodiments, rig capabilities and movements are learned by building a Markov Chain (MC) model that tracks the movement of each rig in the history and analyses the type of wells drilled in the process. From this, the algorithm computes transition probabilities that control the assignment of rigs to future wells in prediction. Historic rig data is accessed from one or more databases. This historic rig data includes information about the movements of a plurality of rigs, such as the types of wells and under what conditions the rigs moved from well to well. Historical well data is also accessed to gain an understanding of the well parameters of the wells that the rigs drilled in the past. The historic rig data and the historical well data is used to learn the rig capabilities and movements to further predict the movement of rigs to future wells in the business plan.”)
Regarding Claim 5, Alshari
wherein the draft scenario generation unit is configured to search, for each of the plurality of baseline draft plans, a value of the uncertainty parameter by which the approximation evaluation results become the lowest, and generate that search result as the draft scenario.
(Alshari, col.7,lns.3-40, “The three-dimensional plot allows a user to quickly evaluate multiple simulated scenarios according to three dimensions. Depending on the requirements of the business plan, the most desirable scenario provided by the simulation outputs may be the simulation that has the lowest well count, the highest NPV, and the highest cumulative production. However, this may not be the case for all business plans.”)
Regarding Claim 6, Alshari discloses the device of claim 1
The computation device according to claim 1, wherein the baseline draft plan generation unit is configured to search, for each of the plurality of draft scenarios, a value of the determinate parameter by which the approximation evaluation results become the highest, and generate that search result as the baseline draft plan.
(Alshari, col.7,lns.3-40, “The three-dimensional plot allows a user to quickly evaluate multiple simulated scenarios according to three dimensions. Depending on the requirements of the business plan, the most desirable scenario provided by the simulation outputs may be the simulation that has the lowest well count, the highest NPV, and the highest cumulative production. However, this may not be the case for all business plans.”)
Regarding Claim 7, Alshari discloses the device of claim 1
wherein the draft scenario generation unit is configured to generate a predetermined count of draft scenarios including a draft scenario designated by a user.
(Alshari, col.6,lns.56-64, “A non-limiting example of a three-dimensional plot 20 shown in a graphical user interface is illustrated in FIG. 2. In the example of FIG. 2, eight scenarios were assessed (scenarios S1-S8). However, it should be understood that any number of scenarios may be assessed.”;
Alshari, col.6,lns.24-36, “The simulation is performed using the user-preferences for the MC model, the rig movement priorities, initial rig location information, adding/removing rig parameters, and any other specified user parameters. For each simulation forecast, the output file contains all specifications set by the user, including maximum number of additional rigs that is allowed to be added per year, the rig stopping date in gas and oil wells, in addition to the cutoff dates for releasing rigs. FIG. 12 shows an example of simulation parameters used in one of the simulations. In FIG. 12, the parameters are user-defined inputs, and embodiments offer the flexibility of varying the parameters in every run.”)
Regarding Claims 9,10
See prior art rejection of claim 1.
Claim Rejections - 35 USC § 103
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 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.
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 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 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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over
AlShahri 12385393 in view of
TSUCHIYA 20220374801
Regarding Claim 3, Alshari discloses the device of claim 1.
Alshari does not explicitly disclose
wherein the aggregation unit is configured to calculate, based on the approximation evaluation results, for each draft scenario, a degree of influence of that draft scenario on the approximation evaluation results, and aggregate the draft scenarios into a plurality of groups based on the degree of influence.
Tsuchiya is directed to a system for evaluating a plan. (Tsuchiya, abstract). Tsuchiya discloses calculating degree of influence of a feature with respect to a model to evaluate the results. (Id. “A plan evaluation apparatus, which evaluates a schedule planned by combining a plurality of plans, includes: a feature conversion unit that divides the schedule into plan components based on a predetermined conversion rule, and convert the divided plan components into features; a model learning unit that uses the features as an input and creates a machine learning model having a key performance indicator (KPI) of the schedule as an objective variable; a contribution rate calculation unit that calculates a contribution rate of each of the features with respect to the machine learning model; and an influence degree calculation unit that calculates an influence degree of influence, on the KPI of the schedule, of the plan component which is a conversion source of the feature, based on the contribution rate of the feature.”) It would have been obvious to one of ordinary skill in the art before the filing date of the invention to combine Alshari with the degree of influence of Tsuchiya with the motivation of efficiently evaluating plans. (Tsuchiya, para 0004).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over
AlShahri 12385393 in view of
Soni, “Feedback Loops in Machine Learning Systems”, 9/2022,
https://medium.com/data-science/feedback-loops-in-machine-learning-systems-701296c91787
Regarding Claim 8, Alshari discloses the device of claim 1
Alshari does not explicitly disclose
an error evaluation unit configured to evaluate error between the strict evaluation results and the approximation evaluation results, regarding a confirmational operational draft plan in which the representative scenario and one of the baseline draft plans are combined; and
an updating unit configured to update the approximation evaluator based on the evaluation results from the error evaluation unit.
Soni is an article discussing using feedback to retrain machine learning models. (Soni, p.1) Soni discloses that a machine learning system may consider errors in its output to update the model. (Id. ,”These feedback mechanisms allow the system to get information that is not self-reinforcing with respect to the system’s current behavior. This ensures that, over time, the models do not degrade due to being retrained on biased data that does not reflect the true data distribution.
In many cases, this external data provides feedback on when the model was right and when it was wrong. This often occurs by implicitly or explicitly allowing the user to correct the mistakes of the system in a structured manner.”) It would have been obvious to one of ordinary skill in the art before the filing date of the invention to combine Alshari with the error evaluation of Soni with the motivation of improving machine learning. Id.
Allowable Subject Matter
Claim 4 is 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 and the rejection under 35 USC 101 is overcome.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALLEN C CHEIN whose telephone number is (571)270-7985. The examiner can normally be reached Monday-Friday 8am -5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Florian Zeender can be reached at (571) 272-6790. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALLEN C CHEIN/Primary Examiner, Art Unit 3627
