DETAILED ACTION
Claims 1-23 are currently presented for Examination.
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 .
Response to Arguments
Following Applicants amendments to the Claims, the objections of the Claims is Withdrawn.
Following Applicants arguments and amendments, and in light of the 2019 Patent Eligibility guidance, the 101 rejection of the Claims is Maintained.
Applicant’s Argument: Applicant’s arguments directed to 101 rejection are based on newly amended subject matter."
Examiner’s Response: All arguments are addressed in the 101 rejection of the claims below.
Therefore, the 101 rejection of the claims is Maintained.
Following Applicants amendments, the 102 rejection of the claims is Withdrawn.
Following Applicants arguments and amendments, the 103 rejection of the claims is Maintained.
Applicant’s Argument: Applicant’s arguments directed the 103 rejection are based on newly amended subject matter.
Examiner’s Response: All arguments are addressed in the 103 rejection of the claims below.
Therefore, the 103 rejection is Maintained.
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.
Regarding claims 1-14 and 23, are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. abstract idea) without anything significantly more.
Step 1: Claims 1-14 are directed to a method, which is a process, which is a statutory category of invention. Claim 23 is directed to a non-transitory computer readable medium, which is a manufacture, which is a statutory category of invention. Therefore, claims 1-14 and 23 are directed to patent eligible categories of invention.
Step 2A, Prong 1: Claims 1 and 23 recite the abstract idea of simulating a thermal modeling using finite element, constituting a Mental Processes based on concepts performed in the human mind, or with the aid of pencil and paper. The limitation of "analyzing a hydrocarbon fluid flowing through a positive choke manifold portion of the choke manifold enabling a … to generate a first flow state, wherein an adjustable choke manifold portion of the choke manifold is isolated to direct the hydrocarbon fluid to the positive choke manifold portion, the positive choke manifold portion utilizes a choke bean of an equivalent size to a choke size in a set of designated choke sizes, and the hydrocarbon fluid is flowing from a wellbore at the well site;” covers mental processes including evaluating a fluid based on a set of conditions that are used in the evaluation. But for the addition of the “choke manifold controller”, there is nothing that precludes operation of the claim in the human mind. This follows for each subsequent recitation. Additionally, the limitation of “analyzing, at a time when the positive choke manifold portion is isolated to direct the hydrocarbon fluid to the adjustable choke manifold portion, the hydrocarbon fluid flowing through the adjustable choke manifold portion utilizing input parameters enabling the choke manifold system to generate a second flow state, and the adjustable choke manifold portion uses an adjustable choke position for the adjustable choke valve that is equivalent to the choke size; and” covers mental processes including evaluating the hydrocarbon fluid based on more parameters that limit the flow. Thus, the claims recite the abstract idea of a mental process performed in the human mind, or with the aid of pencil and paper.
Dependent claims 2-14 further narrow the abstract ideas, identified in the independent claims.
Step 2A, Prong 2: The judicial exception is not integrated into a practical application. In Claim 23, the additional element of “non-transitory computer-readable storage medium”, “a data processing apparatus” merely uses a computer device as a tool to perform the abstract idea. (MPEP 2106.05(f)) The limitations of “directing the choke manifold controller to modify the adjustable choke position modified using a first margin of error calculated utilizing the first flow state and the second flow state” in claims 1 and 23 “communicating the choke size, the first margin of error, or an amount of adjustment for the adjusting to one or more systems” in claim 3, as well as “receiving the input parameters from one or more of equipment upstream of the choke manifold, equipment downstream of the choke manifold, or downhole the wellbore.” in claim 13 are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. See MPEP (2106.05(f)) Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process) does not integrate a judicial exception into a practical application. (MPEP 2106.05(f)(2)) Alternatively, the limitation of “directing the choke manifold controller to modify the adjustable choke position modified using a first margin of error calculated utilizing the first flow state and the second flow state” can be viewed as mere instructions to apply as it only recites the idea of a solution or outcome and fails to recite details of how a solution to a problem is accomplished MPEP 2106.05(f), “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it"… In contrast, claiming a particular solution to a problem or a particular way to achieve a desired outcome may integrate the judicial exception into a practical application or provide significantly more.” It is noted the generic recitation of “directing the choke manifold controller to modify the adjustable choke position” only recites the idea of causing a modification of “the adjustable choke position” as there are no further limitations on what causes the adjustable choke system to change position other than a signal directing it to do so. Additionally, the claim does not explicitly recite how an adjustment of the choke position effects the margin of error and what problem the reduction of error is solving. Therefore, the judicial exception is not integrated into a practical application.
Dependent claims 2-14 further narrow the abstract ideas, identified in the independent claims, and do not introduce further additional elements for consideration beyond those addressed above.
Step 2B: Claims 1 and 23 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. In Claim 23, the additional element of “non-transitory computer-readable storage medium”, “a data processing apparatus” merely uses a computer device as a tool to perform the abstract idea. (MPEP 2106.05(f)) The limitations of “directing the choke manifold controller to modify the adjustable choke position modified using a first margin of error calculated utilizing the first flow state and the second flow state” in claims 1 and 23 “communicating the choke size, the first margin of error, or an amount of adjustment for the adjusting to one or more systems” in claim 3, as well as “receiving the input parameters from one or more of equipment upstream of the choke manifold, equipment downstream of the choke manifold, or downhole the wellbore.” in claim 13 are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. See MPEP (2106.05(f)) Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a mental process) does not amount to significantly more. (MPEP 2106.05(f)(2)) Alternatively, the limitation of “directing the choke manifold controller to modify the adjustable choke position modified using a first margin of error calculated utilizing the first flow state and the second flow state” can be viewed as mere instructions to apply as it only recites the idea of a solution or outcome and fails to recite details of how a solution to a problem is accomplished MPEP 2106.05(f), “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it"… In contrast, claiming a particular solution to a problem or a particular way to achieve a desired outcome may integrate the judicial exception into a practical application or provide significantly more.” It is noted the generic recitation of “directing the choke manifold controller to modify the adjustable choke position” only recites the idea of causing a modification of “the adjustable choke position” as there are no further limitations on what causes the adjustable choke system to change position other than a signal directing it to do so. Additionally, the claim does not explicitly recite how an adjustment of the choke position effects the margin of error and what problem the reduction of error is solving. Therefore, the claim as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered alone or in combination, do not amount to significantly more than the judicial exception. As stated in Section I.B. of the December 16, 2014 101 Examination Guidelines, “[t]o be patent-eligible, a claim that is directed to a judicial exception must include additional features to ensure that the claim describes a process or product that applies the exception in a meaningful way, such that it is more than a drafting effort designed to monopolize the exception.”
The dependent claims include the same abstract ideas recited as recited in the independent claims, and merely incorporate additional details that narrow the abstract ideas and fail to add significantly more to the claims.
Dependent claim 2 is directed to further analysis and modification of the choke position, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 4 is directed to further defining the choke size parameters, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 5 is directed to further defining where the choke position comes from, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 6 is directed to further defining the calculation method, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 7 is directed to further defining how the choke model is updated, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 8 is directed to further defining the data sources, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 9 is directed to further defining the factors of the flow rates, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 10 is directed to further defining the time period, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 11 is directed to further defining the change of the choke position, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 12 is directed to further defining how flow states are generated, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Dependent claim 14 is directed to further defining the input parameters, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes.”
Accordingly, claims 1-14 and 23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without anything significantly more.
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 (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 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 1-15, 17-18 and 20-23 are rejected under 35 U.S.C. 103 as being unpatentable over Parthasarathy et al. USPPN 2020/0208479 in view of Rossi USPPN 2020/0133251.
Regarding claim 1, Parthasarathy teaches analyzing a hydrocarbon fluid flowing through a positive choke manifold portion of the choke manifold enabling a choke manifold controller to generate a first flow state, (Abstract, Figure 1A and 1B, [0002], [0006], a first flow is generated through the choke manifold that is determined by the controller)
wherein an adjustable choke manifold portion of the choke manifold is isolated to direct the hydrocarbon fluid to the positive choke manifold portion, (Figure 1B, [0034], [0040], the fluid is directed based on opening and closing the choke manifold)
the hydrocarbon fluid is flowing from a wellbore at the well site; (Abstract, Figure 1A and 1B, [0002], the hydrocarbon is flowing from a wellbore at the well site)
analyzing, at a time when the positive choke manifold portion is isolated to direct the hydrocarbon fluid to the adjustable choke manifold portion, the hydrocarbon fluid flowing through the adjustable choke manifold portion utilizing input parameters enabling the choke manifold controller to generate a second flow state, and ([0004], the adjustable choke is at a state between fully open and closed, when closed, the flow is directed to the other portion of the valve; Figure 2, [0008], [0012], [0015], [0044], [0048], a second flow rate is generated through the second choke and through each choke as they are opened or adjusted)
the adjustable choke manifold portion uses an adjustable choke position for the adjustable choke valve that is equivalent to the choke size; and (Figures 1-2, [0004], [0028], the adjustable choke opening is from 0 to 100% of the choke size)
directing the choke manifold controller to modify the adjustable choke position modified using a first margin of error calculated utilizing the first flow state and the second flow state. (Abstract, Figure 1A and 1B, [0036], [0048], the choke is adjusted based on the error; [0036], the two fluid flow rates are compared and a error is calculated to be compared to a predetermined error range)
Parthasarathy does not explicitly recite the positive choke manifold portion utilizes a choke bean of an equivalent size to a choke size in a set of designated choke sizes,
Rossi the positive choke manifold portion utilizes a choke bean of an equivalent size to a choke size in a set of designated choke sizes, (Fig 25, [0077], [0087], [0102], [0114], a choke bean that has an equivalence to the choke size, in a set is used)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Parthasarathy with Rossi as the references deal with directing fluids in a wellbore, in order to implement a system that uses a choke bean, as well as a machine learning model that implements a Bayesian optimization and history matching. Rossi would modify Parthasarathy by using a choke bean, as well as a machine learning model that implements a Bayesian optimization and history matching. The benefit of doing so is the system can improve the multiphase virtual flow rate estimates, as well as to validate and improve the quality of the simulation model. As well as displaying and automatically correcting flow rates with the components of the system (Rossi [0122], [0185])
Regarding claim 2, the combination of Parthasarathy and Rossi teach the limitations of claim 1. Parthasarathy teaches wherein the positive choke manifold portion is isolated to direct the hydrocarbon fluid to the adjustable choke manifold portion; and (Figure 1B, [0034], [0040], the fluid is directed based on opening and closing the choke manifold)
Parthasarathy does not explicitly recite analyzing the hydrocarbon fluid flowing through the adjustable choke manifold portion, utilizing the modified adjustable choke position, to generate a third flow state, modifying the modified adjustable choke position to compensate for a second margin of error, wherein the second margin of error is calculated utilizing the second flow state and the third flow state.
Rossi teaches analyzing the hydrocarbon fluid flowing through the adjustable choke manifold portion, utilizing the modified adjustable choke position, to generate a third flow state, (Figures 15 and 22, [0076], [0077], [0095], [0102], a Bayesian statistical algorithm is used to generate a third flow state using new information as variables of the system are adjusted)
modifying the modified adjustable choke position to compensate for a second margin of error, wherein the second margin of error is calculated utilizing the second flow state and the third flow state. (Figures 15 and 22, [0077], [0095], [0102], [0184], at each timestep, based on the error at that timestep, the choke is adjusted to compensate for the error calculated)
See motivation of claim 1.
Regarding claim 3, the combination of Parthasarathy and Rossi teach the limitations of claim 1. Parthasarathy teaches communicating the choke size, the first margin of error, or an amount of adjustment for the adjusting to one or more systems. ([0040], the controller communicates the adjusted choke size to the system for adjusting)
Regarding claim 4, the combination of Parthasarathy and Rossi teach the limitations of claim 1. Parthasarathy teaches wherein the set of designated choke sizes includes more than one choke size in a sequence, and (Figures 1-2, [0004], [0028], the adjustable choke opening is from 0 to 100% of the choke size)
the method is executed for two or more choke sizes in the set of designated choke sizes, where each execution of the method utilizes a next designated choke size in the set of designated choke sizes. (Figures 1-2, [0004], [0028], the adjustable choke opening is from 0 to 100% of the choke size; [0040], the controller communicates the adjusted choke size to the system for adjusting)
Regarding claim 5, the combination of Parthasarathy and Rossi teach the limitations of claim 1. Parthasarathy teaches wherein the adjustable choke position is received from one or more of a choke model, a design of experiments algorithm, a reliability methodology algorithm, a physics-based algorithm, or a manufacturer's recommendation. (Figures 1-2, [0004], [0007], [0029], the adjustable choke position is received from the choke model and a design of experiments algorithm)
Regarding claim 6, the combination of Parthasarathy and Rossi teach the limitations of claim 5. Parthasarathy does not explicitly teach wherein the one or more of the choke model, the design of experiments algorithm, or the physics-based algorithm are combined using a statistical algorithm, where the statistical algorithm is one of an average, a mean, a median, a maximum, a minimum, a derivation of a highest efficiency, a derivation of a highest accuracy, a Bayesian optimization, an ensemble learning method, a stacked ensemble model, a weighted average, a method of quadrature, a Lagrange multiplier, or a derivative optimization.
Rossi teaches wherein the one or more of the choke model, the design of experiments algorithm, or the physics-based algorithm are combined using a statistical algorithm, where the statistical algorithm is one of an average, a mean, a median, a maximum, a minimum, a derivation of a highest efficiency, a derivation of a highest accuracy, a Bayesian optimization, an ensemble learning method, a stacked ensemble model, a weighted average, a method of quadrature, a Lagrange multiplier, or a derivative optimization. (Figures 15 and 22, [0076], [0077], [0095], [0102], a Bayesian statistical algorithm is used to generate a third flow state using new information as variables of the system are adjusted)
See motivation of claim 1.
Regarding claim 7, the combination of Parthasarathy and Rossi teach the limitations of claim 5. Parthasarathy teaches wherein the choke model is updated using one or more of the first flow state, the second flow state, the first margin of error, or an amount of adjustment for the adjusting. (Fig.2, [0029], the choke model is updated with flow rates and an amount that needs to be adjusted)
Regarding claim 8, the combination of Parthasarathy and Rossi teach the limitations of claim 5. Parthasarathy does not explicitly teach wherein the choke model is updated using historical data from one or more of the well site or other well sites.
Rossi teach wherein the choke model is updated using historical data from one or more of the well site or other well sites. ([0139], history matching is used with data from the well site)
See motivation of claim 1.
Regarding claim 9, the combination of Parthasarathy and Rossi teach the limitations of claim 1. Parthasarathy teaches wherein the first flow state and the second flow state utilize one or more factors of a gas to oil ratio (GOR), a density, a viscosity, a pressure, a temperature, a solids content, or a data from a multi-phase flow meter, (Abstract Figures 1a and 1b, [0010], [0036], a flow meter is used; [0006], [0007] a pressure is one of the factors)
where the one or more factors are collected at one or more of an upstream location or a downstream location, where the upstream location and downstream location are relative to the choke manifold. (figures 1a and 1b, the factors are collected upstream relative to the choke manifold)
Regarding claim 10, the combination of Parthasarathy and Rossi teach the limitations of claim 1. Parthasarathy teaches wherein the method is performed during a well testing operation, a production flowback operation, a production cleanup operation, a hydrocarbon fluid change event, or a specified time. ((Abstract, Figure 1A-1B, 2, [0002], [0006], [0040], a the method is performed for a specified time)
Regarding claim 11, the combination of Parthasarathy and Rossi teach the limitations of claim 1. Parthasarathy teaches wherein the adjusting is applied automatically by the adjustable choke manifold portion. ([0029], [0030], [0040], the adjusting of the manifold is automatic)
Regarding claim 12, the combination of Parthasarathy and Rossi teach the limitations of claim 1. Parthasarathy teaches wherein the first flow state and the second flow state are generated utilizing a target optimization, where the target optimization is one or more of minimized emissions, minimized solids, maximized gas output, maximized oil output, minimized water output, maximum flow rate while laminar, a pulsed flow, an equipment protection, or a balanced combination. (Figure 2, [0002], [0006]-[0007], a maximized output is achieved)
Regarding claim 13, the combination of Parthasarathy and Rossi teach the limitations of claim 1. Parthasarathy teaches receiving the input parameters from one or more of equipment upstream of the choke manifold, equipment downstream of the choke manifold, or downhole the wellbore. (Figures 1A-1B, [0006], [0007], the parameters are received upstream of the manifold)
Regarding claim 14, the combination of Parthasarathy and Rossi teach the limitations of claim 1. Parthasarathy teaches wherein the input parameters include one or more of a geographic region, a subterranean formation parameter, a choke error threshold, a statistical algorithm to utilize, a target optimization, an adjustable choke manifold manufacturer and model, a hydrocarbon fluid, or a pumped fluid composition. ([0002], [0036], a hydrocarbon fluid and a target optimization to reduce error are used as the input parameters)
Regarding claim 15, Parthasarathy anticipates a choke manifold having one or more adjustable choke valves and a positive choke valve, and capable of isolating a fluid flow through one of the one or more adjustable choke valves and the positive choke valve, and the choke manifold is located at a well site of a hydrocarbon fluid producing wellbore; and (Abstract, Figure 1A and 1B, [0002], [0006], a first flow is generated through the choke manifold containing two choke sections; Figure 1B, [0034], [0040], the fluid is directed based on opening and closing the choke manifold, Abstract, Figure 1A and 1B, [0002], the hydrocarbon is flowing from a wellbore at the well site)
a choke model processor capable to receive collected data and generate a recommended position for the one or more adjustable choke valves using an equivalency of a choke … and a first margin of error wherein the margin of error is calculated utilizing a first flow state and a second flow state, the first flow state represents hydrocarbon fluid flowing through the positive choke valve and the second flow state represents hydrocarbon fluid flowing through the one or more adjustable choke valves (Figures 1-2, [0004], [0028], the adjustable choke opening is from 0 to 100% of the choke size; [0006], [0007], the choke is actuated to the determined position based on the received data; Abstract, Figure 1A and 1B, [0036], [0048], the choke is adjusted based on the error; [0036], the two fluid flow rates are compared and a error is calculated to be compared to a predetermined error range)
Parthasarathy does not explicitly recite wherein the positive choke valve uses a choke bean size from a set of designated choke sizes, choke bean size
Rossi teaches wherein the positive choke valve uses a choke bean size from a set of designated choke sizes, (Fig 25, [0077], [0087], [0102], [0114], a choke bean that has an equivalence to the choke size, in a set is used)
choke bean size (Fig 25, [0077], [0087], [0102], [0114], a choke bean that has an equivalence to the choke size, in a set is used)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Parthasarathy with Rossi as the references deal with directing fluids in a wellbore, in order to implement a system that uses a choke bean, as well as a machine learning model that implements a Bayesian optimization and history matching. Rossi would modify Parthasarathy by using a choke bean, as well as a machine learning model that implements a Bayesian optimization and history matching. The benefit of doing so is the system can improve the multiphase virtual flow rate estimates, as well as to validate and improve the quality of the simulation model. As well as displaying and automatically correcting flow rates with the components of the system (Rossi [0122], [0185])
Regarding claim 17, the combination of Parthasarathy and Rossi teach the limitations of claim 15. Parthasarathy teaches wherein collected data used to calculate the first flow state and the second flow state are received from one or more of an upstream location relative to the choke manifold or a downstream location relative to the choke manifold. (Figures 1A-1B, [0006], [0007], the parameters are received upstream of the manifold)
Regarding claim 18, the combination of Parthasarathy and Rossi teach the limitations of claim 15. Parthasarathy teaches wherein the one or more adjustable choke valves utilize a proportional integral derivative (PID) control, a fractional order control, a feedforward compensation, a proportional (P) control, a proportional integral (Pl) control, a proportional derivative (PD) control, a Proportional Integral Feed Forward (PIFF) control, or predictive or rule based logic to maintain a respective adjustable choke position once an optimized position is determined. (Figures 1-2, [0006]-[0007], [0047], a rules base logic is used to adjust the choke)
Regarding claim 20, the combination of Parthasarathy and Rossi teach the limitations of claim 15. Parthasarathy teaches a result transceiver, capable of communicating the recommended position, flow states, margins of errors, or interim outputs to a user, a data store, a computing system, a choke modeler system, or the choke manifold. ([0040], the controller communicates the adjusted choke size to the system for adjusting, including the modeler system and the choke manifold itself)
Regarding claim 21, the combination of Parthasarathy and Rossi teach the limitations of claim 15. Parthasarathy does not explicitly teach wherein the choke model processor utilizes a machine learning system or a deep learning neural network system to determine the recommended position.
Rossi teaches wherein the choke model processor utilizes a machine learning system or a deep learning neural network system to determine the recommended position. ([0175], a machine learning model is used in the determination)
See motivation of claim 16
Regarding claim 22, the combination of Parthasarathy and Rossi teach the limitations of claim 15. Parthasarathy teaches wherein the choke model processor is communicatively coupled to the choke manifold, and the choke manifold automatically adjusts the one or more adjustable choke valves using the recommended position. ([0040], the controller communicates the adjusted choke size to the system for adjusting, including the modeler system and the choke manifold itself)
In regards to claim 23, it is the computer readable medium embodiment of claim 1 with similar limitations to claim 1, and is such rejected using the same reasoning found in claim 1.
The additional computer components are taught by the controller of Parthasarathy.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Parthasarathy in view of Rossi in view of Hodges USPAT 3,282,341.
Regarding claim 16, the combination of Parthasarathy and Rossi teach the limitations of claim 15. The combination of Parthasarathy and Rossi does not explicitly teach wherein the choke manifold further includes one or more positive choke valves with a respective choke bean equivalent to the choke size.
Hodges teaches wherein the choke manifold further includes more than one positive choke valve with a respective choke bean size. (Figure 1, Column 3 Lines 22-48, Column 4 Lines 35-61, Column 5 Line 1-Column 6 Line14, the choke system has more than one choke beans in the flow paths of the wellbore fluid)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Parthasarathy and Rossi with Hodges as the references deal with directing fluids in a wellbore, in order to implement a system that uses a choke bean, as well as a machine learning model that implements a Bayesian optimization and history matching. Hodges would modify Parthasarathy and Rossi by using more than one choke bean in the fluid flow system. The benefit of doing so is the system can control the flow of fluids from the wellbore, achieve the desired flow rates of the fluids, and prevent flow of fluids between sources.(Hodges [0122], [0185])
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Parthasarathy in view of Rossi in view of Elichev et al. Understanding Well Events with Machine Learning.
Regarding claim 19, the combination of Parthasarathy and Rossi teach the limitations of claim 15. Parthasarathy teaches calculated margins of error, wherein the generated flow states and calculated margins of error are generated by one or more of the machine learning system or the choke model processor. (Figures 1-2, [0006]. [0007], [0036], a controller calculates the error)
Parthasarathy does not explicitly teach a machine learning system, communicatively coupled to the choke model processor, and calculated margins of error,
Rossi teaches a machine learning system, communicatively coupled to the choke model processor, and ([0175], a machine learning model is used in the determination)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Parthasarathy with Rossi as the references deal with directing fluids in a wellbore, in order to implement a system that uses a choke bean, as well as a machine learning model that implements a Bayesian optimization and history matching. Rossi would modify Parthasarathy by using a choke bean, as well as a machine learning model that implements a Bayesian optimization and history matching. The benefit of doing so is the system can improve the multiphase virtual flow rate estimates, as well as to validate and improve the quality of the simulation model. As well as displaying and automatically correcting flow rates with the components of the system (Rossi [0122], [0185])
The combination of Parthasarathy and Rossi do not explicitly teach capable of identifying choke wear or impending choke failure of the choke manifold utilizing the collected data, generated flow states,
Elichev teaches capable of identifying choke wear or impending choke failure of the choke manifold utilizing the collected data, generated flow states, (Abstract, Introduction, Types of events at the well, Machine learning methods for analyzing well behavior pages 4-9, both wear and failure are calculated from the generated flow states)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Parthasarathy and Rossi with Elichev as the references deal with directing fluids in a wellbore, in order to implement a system that identifies choke wear or failure. Elichev would modify Parthasarathy and Rossi by identifying choke wear or failure. The benefit of doing so is wear and failure can be predicted as well as allowing the analysis of incoming data and identification of well events in real time. (Elichev [0122], [0185])
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Atencio USPPN 2007/0227722: Also teaches a choke system, with an adjustable choke, positive choke and choke bean that is adjusted based on the flow of the system, to get the flow desired by the system.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL COCCHI whose telephone number is (469)295-9079. The examiner can normally be reached 7:15 am - 5:15 pm CT Monday - Thursday.
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/MICHAEL EDWARD COCCHI/Primary Examiner, Art Unit 2188
Prosecution Insights