DETAILED ACTION
Claims 1 and 3-14 are presented for examination. Claims 1 and 3 stand currently amended.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 13 April 2026 has been entered.
Response to Arguments
Applicant's remarks filed 9 April 2026 have been fully considered and Examiner’s response is as follows:
Applicant remarks page 5 argues:
Solving conservation equations on mass, momentum and energy in both time and space is not reasonably equivalent to "performing a spatial segmentation and performing a dynamic segmentation" let alone ''performing a spatial segmentation to generate vectors representing the one or more segments based on original drawings or information and performing a dynamic segmentation that incorporates other attributes into the vectors based on data of the other attributes over time" as recited by amended claim 1.
This argument has been fully considered and is persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made over Gabetta, G., et al. “Internal Corrosion Prediction Using Fluid Dynamics For Pipeline Integrity” 10th Offshore Mediterranean Conf. & Exh. (2011) [herein “Gabetta”] in view of US 2016/0071059 A1 Petering, et al. [herein “Petering”].
Petering paragraph 201 teaches storing pipeline segments as vector data types.
Claim Interpretation
Claim 6 recitation “operational philosophy” is interpreted in light of Specification paragraph 27 “operating philosophies, such as maintenance cleaning frequencies, corrosion inhibition treatment, shut in periods, shut in processes, and the like.”
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-7, 9, 10, 12, and 14
Claims 1, 3-7, 9, 10, 12, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Gabetta, G., et al. “Internal Corrosion Prediction Using Fluid Dynamics For Pipeline Integrity” 10th Offshore Mediterranean Conf. & Exh. (2011) [herein “Gabetta”] in view of US 2016/0071059 A1 Petering, et al. [herein “Petering”].
Claim 1 recites “1. A method for predicting locations at risk of internal corrosion, comprising performing a pipeline condition simulation.” Gabetta title discloses “Internal Corrosion Prediction using Fluid Dynamics for Pipeline Integrity.” Internal corrosion prediction corresponds with predicting internal corrosion. Using fluid dynamics corresponds with a pipeline condition simulation.
Gabetta page 2 second paragraph disclose “The objective of this approach is to locate pipe sections where the risk of CO2 corrosion rate is higher.”
Claim 1 further recites “comprising: segmenting a flow line into one or more segments based, at least in part, on pipeline attributes.” Gabetta page 2 second paragraph disclose “The objective of this approach is to locate pipe sections where the risk of CO2 corrosion rate is higher.” Pipe sections correspond with respective pipe segments.
Gabetta page 2 discloses:
With the aim to couple corrosion and fluid dynamics models, there is need to build the hydraulic pipeline model… the following information are required and listed below:
Pipe material and internal coating, if any.
Diameter and roughness …
Pressure and temperatures at boundaries
Multiphase flow composition and PVT analysis, including water content, carbon dioxide, hydrogen sulphide.
Flow rates…
Curves, junction and change of level….
Each of these list information correspond with respective pipeline attributes.
Claim 1 further recites “wherein the segmenting comprises performing a spatial segmentation to generate vectors representing the one or more segments based on original drawings or information.” From the above list of alternatives Examiner is selecting “information.”
Gabetta page 3 disclose:
Computational Fluid Dynamics (CFD, such as Fluent®, [5]) can describe very thoroughly the flow field, solving the three conservation equations on mass, momentum and energy in both time and space. A CFD code can be used in close synergy with a one-dimensional code targeting critical points for study. A one-dimensional code can give the local conditions needed to a CFD code for a closer fluid dynamics examination.
Solving CFD equations across space is a spatial segmentation.
Gabetta does not explicitly disclose vectors representing the segments; however, in analogous art of information management of a pipeline, Petering paragraph 201 teaches “The project management system 2 in a preferred embodiment supports several data types. The first data type is vector data, which is used to store items such as survey points, pipeline segments, and tracts.” Storing pipeline segments using a vector data type corresponds with generating vectors representing one or more segments based on information.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Gabetta and Petering. One having ordinary skill in the art would have found motivation to use a vector data type into the system of internal corrosion prediction because a vector data type is art recognized as a preferred data type suitable for storing pipeline segment information. See Petering ¶ 201 and MPEP §2144.07.
Claim 1 further recites “and performing a dynamic segmentation that incorporates other attributes into the vectors based on data of the other attributes over time.” Gabetta page 3 disclose:
Computational Fluid Dynamics (CFD, such as Fluent®, [5]) can describe very thoroughly the flow field, solving the three conservation equations on mass, momentum and energy in both time and space. A CFD code can be used in close synergy with a one-dimensional code targeting critical points for study. A one-dimensional code can give the local conditions needed to a CFD code for a closer fluid dynamics examination.
Solving CFD equations across time corresponds with being over time.
Petering paragraph 201 teaches “the GeoDataBase is built from survey data collected into feature classes, such as joints, welds, bores, and other location based facilities.” Survey data, feature classes, joints, welds, and bore information are other attributes incorporated with the pipeline information.
Claim 1 further recites “running a hydraulics model to calculate flow parameters along the pipeline.” Gabetta abstract discloses “Corrosion models were thus coupled with hydraulic analysis performed with the help of flow dynamics codes.” Gabetta page 3 disclose:
Computational Fluid Dynamics (CFD, such as Fluent®, [5]) can describe very thoroughly the flow field, solving the three conservation equations on mass, momentum and energy in both time and space. A CFD code can be used in close synergy with a one-dimensional code targeting critical points for study. A one-dimensional code can give the local conditions needed to a CFD code for a closer fluid dynamics examination.
This CFD modeling corresponds to running a hydraulics model to calculate flow parameters. Solving mass, momentum, and energy are flow parameters.
Claim 1 further recites “modeling corrosion rate based, at least in part, on results from the hydraulics model.” Gabetta abstract discloses “Corrosion models were thus coupled with hydraulic analysis performed with the help of flow dynamics codes. …. The predicted corrosion rate is actually a function of local flow conditions.”
Gabetta page 2 third bullet discloses “Besides, by the results of CO2 corrosion rate calculations integrated with multiphase flow models, some pipeline sections show corrosion rates (and thus failure likelihood) higher than others.” The corrosion rate calculations to determine pipeline section corrosion rates corresponds with modeling a corrosion rate.
Claim 1 further recites “identifying segments of the one or more segments that are at risk of internal corrosion.” Gabetta page 2 third bullet discloses “Besides, by the results of CO2 corrosion rate calculations integrated with multiphase flow models, some pipeline sections show corrosion rates (and thus failure likelihood) higher than others.” Higher corrosion rates for some pipeline sections identified as having a higher failure likelihood corresponds with identifying segments that are at risk of internal corrosion.
Claim 1 further recites “and excavating around the segments.” Gabetta page 10 last paragraph discloses “The predicted corrosion rate is actually a function of local flow conditions and the comparison with observed damage is expected to help in the planning of inspection and maintenance activities.” Gabetta page 1 last sentence to page 2 first sentence disclose “The common way to determine the location and extent of internal corrosion and high shear stress zone is to excavate and examine the pipe. However, typical oil and gas pipelines are hundreds of miles long and extensive excavation is impractical.” Helping plan inspection and maintenance where the common way to examine (i.e. inspect) is to excavate the pipe corresponds with a subsequent excavation of segments at risk of internal corrosion.
Claim 3 further recites “3. The method of claim 1, wherein performing the spatial segmentation comprises creating a vector for each segment that comprises pipe identification, segment length, elevation changes, or any combinations thereof.” From the above list of alternatives the Examiner is selecting “elevation changes.”
Gabetta page 2 discloses:
With the aim to couple corrosion and fluid dynamics models, there is need to build the hydraulic pipeline model… the following information are required and listed below:
Pipe material and internal coating, if any.
Diameter and roughness …
Pressure and temperatures at boundaries
Multiphase flow composition and PVT analysis, including water content, carbon dioxide, hydrogen sulphide.
Flow rates…
Curves, junction and change of level….
Each of these list information correspond with respective pipeline attributes. A change of level corresponds with an elevation change. The set of information together corresponds with a vector of such information.
Claim 4 further recites “4. The method of claim 1, wherein running the hydraulics model comprises determining water wetting conditions for each segment.” Gabetta abstract discloses “Flow regimes and the potential water wetting at the pipeline wall are estimated using one-dimensional code and simple models available in literature.” Estimating water wetting corresponds with determining water wetting conditions.
Claim 5 further recites “5. The method of claim 4, wherein modeling the corrosion rate comprises: entering the water wetting conditions into a corrosion rate calculation; entering pipe characteristics into the corrosion rate calculation.” Gabetta abstract discloses “Flow regimes and the potential water wetting at the pipeline wall are estimated using one-dimensional code and simple models available in literature.”
Gabetta page 2 discloses:
With the aim to couple corrosion and fluid dynamics models, there is need to build the hydraulic pipeline model… the following information are required and listed below:
Pipe material and internal coating, if any.
Diameter and roughness …
Pressure and temperatures at boundaries
Multiphase flow composition and PVT analysis, including water content, carbon dioxide, hydrogen sulphide.
Flow rates…
Curves, junction and change of level….
Flow composition including water content corresponds with a water wetting condition. Pipe internal coating, diameter, roughness, curves, and junctions are each pipe characteristics.
Claim 5 further recites “and generating a corrosion rate for each segment.” Gabetta abstract discloses “Corrosion models were thus coupled with hydraulic analysis performed with the help of flow dynamics codes. …. The predicted corrosion rate is actually a function of local flow conditions.” Locality of the flow conditions correspond with determination of predicted corrosion rate for each segment.
Gabetta page 2 third bullet discloses “Besides, by the results of CO2 corrosion rate calculations integrated with multiphase flow models, some pipeline sections show corrosion rates (and thus failure likelihood) higher than others.” The corrosion rate calculations to determine pipeline section corrosion rates corresponds with modeling a corrosion rate.
Claim 6 further recites “6. The method of claim 5, comprising combining operational philosophy parameters with the corrosion rate for each segment to generate an internal corrosion likelihood ranking.” Claim 6 recitation “operational philosophy” is interpreted in light of Specification paragraph 27 “operating philosophies, such as maintenance cleaning frequencies, corrosion inhibition treatment, shut in periods, shut in processes, and the like.”
Gabetta page 2 discloses:
With the aim to couple corrosion and fluid dynamics models, there is need to build the hydraulic pipeline model… the following information are required and listed below:
Pipe material and internal coating, if any.
The internal coating of a pipe, if any, is a consideration of at least a corrosion inhibition treatment of the pipe.
Gabetta page 2 third bullet discloses “Besides, by the results of CO2 corrosion rate calculations integrated with multiphase flow models, some pipeline sections show corrosion rates (and thus failure likelihood) higher than others.” The failure likelihood corresponds with a likelihood rating.
Claim 7 further recites “7 The method of claim 6, wherein identifying segments is based, at least in part, on the internal corrosion likelihood ranking.” Gabetta page 2 third bullet discloses “Besides, by the results of CO2 corrosion rate calculations integrated with multiphase flow models, some pipeline sections show corrosion rates (and thus failure likelihood) higher than others.”
Claim 8 further recites “8. The method of claim 1, comprising reducing variables to eliminate variables that do not affect the identification of segments.” Gabetta page 4 third paragraph discloses “The equations are reduced to their finite-difference by integration over the computational cells into which the domain is divided.” Reducing the equations is a reduction of variables.
Alternatively, Lu paragraph 63 more explicitly discloses “Dimension Reduction.” See §103 below.
Claim 9 further recites “9. The method of claim 1, comprising optimization of the pipeline condition simulation.” Gabetta page 2 fourth bullet item discloses “Eventually, in the more risky sections of the pipeline, a 3D simulation is performed, using a CFD (Computational Fluid Dynamics) code.” Performing 3D CFD simulation only on the more risky sections of pipeline is optimizing the pipeline simulation because CFD calculations are computationally expensive. Performing these calculations only on the more risky sections thus makes the pipeline simulation more computationally efficient than a simulation which performs 3D CFD on all sections. Without loss of generality, this computational optimization of the simulation corresponds with an optimization of the pipeline condition simulation.
Claim 10 further recites “10. The method of claim 1, comprising performing a vectorization of variables.” Gabetta page 2 discloses:
With the aim to couple corrosion and fluid dynamics models, there is need to build the hydraulic pipeline model… the following information are required and listed below:
Pipe material and internal coating, if any.
Diameter and roughness …
Pressure and temperatures at boundaries
Multiphase flow composition and PVT analysis, including water content, carbon dioxide, hydrogen sulphide.
Flow rates…
Curves, junction and change of level….
Each of these list information correspond with respective pipeline attributes.
Gabetta does not explicitly disclose vectors representing the segments; however, in analogous art of information management of a pipeline, Petering paragraph 201 teaches “The project management system 2 in a preferred embodiment supports several data types. The first data type is vector data, which is used to store items such as survey points, pipeline segments, and tracts.” Storing pipeline segments using a vector data type corresponds with generating vectors representing one or more segments based on information.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Gabetta and Petering. One having ordinary skill in the art would have found motivation to use a vector data type into the system of internal corrosion prediction because a vector data type is art recognized as a preferred data type suitable for storing pipeline segment information. See Petering ¶ 201 and MPEP §2144.07.
Claim 12 further recites “12. The method of claim 1, comprising iterating the pipeline condition simulation across multiple time scales.” Gabetta abstract discloses “Corrosion models were thus coupled with hydraulic analysis performed with the help of flow dynamics codes.” Gabetta page 3 disclose:
Computational Fluid Dynamics (CFD, such as Fluent®, [5]) can describe very thoroughly the flow field, solving the three conservation equations on mass, momentum and energy in both time and space. A CFD code can be used in close synergy with a one-dimensional code targeting critical points for study. A one-dimensional code can give the local conditions needed to a CFD code for a closer fluid dynamics examination.
This CFD modeling in time is performing the simulation across multiple times. Performing the calculations for the respective different sections and times corresponds with different iterations of the calculations.
Claim 14 further recites “14. The method of claim 1, comprising performing a risk ranking on the segments.” Gabetta page 2 third bullet discloses “Besides, by the results of CO2 corrosion rate calculations integrated with multiphase flow models, some pipeline sections show corrosion rates (and thus failure likelihood) higher than others.” The likelihood of failure corresponds with a risk of the respective segment. Gabetta page 10 lines 1-2 disclose “flow dynamics can help in assessing risk levels, which can be different in different region of a long pipeline.” Different risk levels correspond with respective rankings of the risks.
Dependent Claims 8, 11, and 13
Claims 8, 11, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Gabetta and Petering as applied to claims 1 and 10 above, and further in view of US 2025/0200255 A1 Lu, et al. [herein “Lu”].
Claim 8 further recites “8. The method of claim 1, comprising reducing variables to eliminate variables that do not affect the identification of segments.” Gabetta page 4 third paragraph discloses “The equations are reduced to their finite-difference by integration over the computational cells into which the domain is divided.” Reducing the equations is a reduction of variables.
Alternatively, if Gabetta is determined to not explicitly disclose a reducing variables, in analogous art of predicting pipe corrosion, Lu paragraph 64 “Dimension Reduction.”
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Gabettta, Petering, and Lu. One having ordinary skill in the art would have found motivation to use dimension reduction into the system of internal corrosion prediction for the advantageous purpose of “generat[ing] the estimated value[s] … much faster than the full physics-based simulation can.” See Lu ¶63 and abstract.
Claim 11 further recites “11. The method of claim 10, comprising forming a matrix of vectors to represent the pipeline.” Gabetta page 2 discloses:
With the aim to couple corrosion and fluid dynamics models, there is need to build the hydraulic pipeline model… the following information are required and listed below:
Pipe material and internal coating, if any.
Diameter and roughness …
Pressure and temperatures at boundaries
Multiphase flow composition and PVT analysis, including water content, carbon dioxide, hydrogen sulphide.
Flow rates…
Curves, junction and change of level….
Each of these list information correspond with respective pipeline attributes. The set of information together corresponds with a vector of such information.
Gabetta does not explicitly disclose a matrix of vectors; however, in analogous art of predicting pipe corrosion, Lu paragraph 52 teaches:
an input query vector comprising query values for each of said one or more geometric parameters and said inflow velocity within the range of the input parameters can then be provided at 50. Such values may for example be dictated by certain design hypotheses for a pipeline.
Lu paragraph 58 teaches:
The Gaussian process (GP) is a stochastic process that characterizes the distribution of functions in a function space determined by the kernel (a symmetric positive definite function
k
·
,
·
:
R
d
×
R
d
→
R
+
). Regression based on GP (i.e. GPR) amounts to homing in on a specific distribution of functions that accounts for observed samples (i.e. a posterior distribution conditioned upon data).
The mathematical descriptor “symmetric positive definite” usually denotes a matrix property. The mathematical description “
R
d
×
R
d
→
R
+
” indicates multi-dimensional input otherwise known as a matrix.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Gabetta, Petering, and Lu. One having ordinary skill in the art would have found motivation to use a matrix of input parameters into the system of internal corrosion prediction for the advantageous purpose of definite the input attribute data in a CFD simulation. See Lu ¶40.
Claim 13 further recites “13. The method of claim 12, comprising forming a tensor of the time scale data across the segments of the pipeline.” Gabetta page 3 disclose:
Computational Fluid Dynamics (CFD, such as Fluent®, [5]) can describe very thoroughly the flow field, solving the three conservation equations on mass, momentum and energy in both time and space. A CFD code can be used in close synergy with a one-dimensional code targeting critical points for study. A one-dimensional code can give the local conditions needed to a CFD code for a closer fluid dynamics examination.
Solving CFD equations across time corresponds with time scale data.
Gabetta page 2 discloses:
With the aim to couple corrosion and fluid dynamics models, there is need to build the hydraulic pipeline model… the following information are required and listed below:
Pipe material and internal coating, if any.
Diameter and roughness …
Pressure and temperatures at boundaries
Multiphase flow composition and PVT analysis, including water content, carbon dioxide, hydrogen sulphide.
Flow rates…
Curves, junction and change of level….
Each of these list information correspond with respective pipeline attributes. The set of information together corresponds with a vector of such information.
Gabetta does not explicitly disclose a tensor of vectors; however, in analogous art of predicting pipe corrosion, Lu paragraph 52 teaches:
an input query vector comprising query values for each of said one or more geometric parameters and said inflow velocity within the range of the input parameters can then be provided at 50. Such values may for example be dictated by certain design hypotheses for a pipeline.
Lu paragraph 58 teaches:
The Gaussian process (GP) is a stochastic process that characterizes the distribution of functions in a function space determined by the kernel (a symmetric positive definite function
k
·
,
·
:
R
d
×
R
d
→
R
+
). Regression based on GP (i.e. GPR) amounts to homing in on a specific distribution of functions that accounts for observed samples (i.e. a posterior distribution conditioned upon data).
The mathematical descriptor “symmetric positive definite” usually denotes a matrix property. The mathematical description “
R
d
×
R
d
→
R
+
” indicates multi-dimensional input otherwise known as a matrix. A matrix is a specific type of the more generalized tensor.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Gabetta, Petering, and Lu. One having ordinary skill in the art would have found motivation to use a matrix of input parameters into the system of internal corrosion prediction for the advantageous purpose of definite the input attribute data in a CFD simulation. See Lu ¶40.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jay B Hann whose telephone number is (571)272-3330. The examiner can normally be reached M-F 10am-7pm EDT.
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/Jay Hann/Primary Examiner, Art Unit 2186 15 May 2026
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