DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are 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.
Specifically, representative Claim 1 recites:
A method, comprising: acquiring, using a seismic acquisition system, a seismic dataset; using a seismic processor: obtaining, from the seismic dataset, an event in two-way traveltime (TWT), obtaining, from the seismic dataset, a velocity model in TWT; converting the velocity model in TWT into a velocity model in depth, producing a final velocity model in depth, wherein: the final velocity model is produced using a full waveform inversion (FWI) and the velocity model in depth; and a TWT-preserving method preserves the event in TWT at each iteration of the FWI, and forming a seismic image in depth using the final velocity model in depth and the seismic dataset; identifying, using a seismic interpretation workstation and based, at least in part, on the seismic image in depth, a drilling target; and planning, using a borehole planning system, a borehole path to the drilling target.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
Under the Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (process).
Under the Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the grouping of subject matter when recited as such in a claim limitation, that covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) and mental processes – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion.
For example, steps of “converting the velocity model in TWT into a velocity model in depth, producing a final velocity model in depth, wherein: the final velocity model is produced using a full waveform inversion (FWI) and the velocity model in depth” are treated by the Examiner as belonging to mathematical concept grouping, while the steps of “and a TWT-preserving method preserves the event in TWT at each iteration of the FWI, and forming a seismic image in depth using the final velocity model in depth and the seismic dataset; identifying, using a seismic interpretation workstation and based, at least in part, on the seismic image in depth, a drilling target; and planning, using a borehole planning system, a borehole path to the drilling target” are treated as belonging to mental process grouping.
Similar limitations comprise the abstract ideas of Claims 11.
Next, under the Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application.
In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
The above claims comprise the following additional elements:
In Claim 1: a seismic acquisition system, seismic processor;
In Claim 11: a seismic acquisition system, seismic processor;
The additional element in the preamble of “a seismic acquisition system, seismic processor” (generic processor) are generally recited and are not qualified as particular machines.
The limitation of Claim 1/11 disclosing “acquiring, using a seismic acquisition system, a seismic dataset; using a seismic processor: obtaining, from the seismic dataset, an event in two-way traveltime (TWT), obtaining, from the seismic dataset, a velocity model in TWT” are consider by MPEP 2106.05(g) as insignificant extra-solution activity, mere data gathering.
In conclusion, the above additional elements, considered individually and in combination with the other claim elements do not reflect an improvement to other technology or technical field, and, therefore, do not integrate the judicial exception into a practical application. Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
However, the above claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B analysis).
The claims, therefore, are not patent eligible.
With regards to the dependent claims, claims 2-10 and 12-20 provide additional features/steps which are part of an expanded algorithm, so these limitations should be considered part of an expanded abstract idea of the independent claims.
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 1-4, 7-8, 10-14, 17-18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhao et al. (WO2022198220A1, 2022-09-22) herein referred to as Zhao, in view of Salem (US20230243991A1, 2023-08-03).
Regarding Claim 1, Zhao teaches a method, comprising: acquiring, using a seismic acquisition system [0012; Fig. 10], a seismic dataset [0004]; using a seismic processor [0012]: identifying, using a seismic interpretation workstation and based, at least in part, on the seismic image in depth, a drilling target [0076; 0083]; and planning, using a borehole planning system, a borehole path to the drilling target [0076; 0083].
Zhao fails to specifically teach obtaining, from the seismic dataset, an event in two-way traveltime (TWT), obtaining, from the seismic dataset, a velocity model in TWT, converting the velocity model in TWT into a velocity model in depth, producing a final velocity model in depth, wherein: the final velocity model is produced using a full waveform inversion (FWI) and the velocity model in depth; and a TWT-preserving method preserves the event in TWT at each iteration of the FWI, and forming a seismic image in depth using the final velocity model in depth and the seismic dataset. However, Zhao does teach seismic waves may be reflected and received by a plurality of seismic receivers, captured and recorded as a record of seismic data [0061]. One of ordinary skill in the art would correlate this with two-way traveltime event. It would also be obvious to one of ordinary skill in the art that building and modify the velocity model and ultimately using it for well planning and drilling determinations [0076], would require the velocity models to be converted from time to depth. Zhao further teaches producing a final velocity model using a full waveform inversion (FWI) and the velocity model in depth (Fig. 4-5; [0073; 0075]). Zhao further teaches a TWT preserving method preserves the event in TWT at each iteration of the FWI via RTM (Fig. 4-5; [0073; 0075]) (Examiner’s Note: It is known to one of ordinary skill in the art that RTM is a TWT preserving method). For purposes of continued examination, a second reference is provided to teach the TWT conversion from time to depth.
Salem teaches TWT conversion from time to depth (Fig. 8; [0060]). Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Zhao to incorporate the teachings of Salem by including: TWT conversion from time to depth in order to revise interpretation, enhancing the quality of estimating velocity parameters.
Regarding Claim 2, the combination further teaches the method of claim 1, further comprising drilling, using a drilling system, the borehole path to the drilling target ( Zhao: [0033, 0035, 0039]).
Regarding Claim 3, the combination further teaches the method of claim 1, wherein, at each iteration of FWI, the TWT-preserving method comprises re-interpolating the velocity model in depth (Zhao: Fig. 4-5; [0073, 0075]).
Regarding Claim 4, the combination further teaches the method of claim 1, wherein, at each iteration of the FWI, the TWT-preserving method comprises re-interpolating the velocity model in TWT (Zhao teaches at each iteration of the FWI, the TWT preserving method comprising re-interpolation (RTM) (Fig. 4-5; [0073, 0075]), whereas Salem teach the velocity model in TWT (Fig. 8, [0060]).
Regarding Claim 7, combination further teaches the method of claim 1, wherein he TWT-preserving method is applied at each of a plurality of surface locations above the velocity model in depth (Examiner’s Note: this is inherent being that the data is sent to surface units (Zhao: [0035] which are above the velocity model in depth) ((Fig. 4-5; [0073, 0075])).
Regarding Claim 8, the combination teaches the method of claim 1. The combination further teaches wherein the event was determined from a time-migrated seismic dataset (Salem: [0060]; Fig. 8).
Regarding Claim 10, the combination teaches all of the limitations of Claim 1. The combination further teaches wherein the velocity model in TWT is obtained from a migration velocity analysis (Zhao: RTM (Fig. 4-5; [0073; 0075])
Regarding Claim 11, Zhao teaches a system, comprising: a seismic acquisition system [0012; Fig. 10], configured to acquire a seismic dataset [0004]; a seismic processor, configured to: receive the seismic dataset from the seismic acquisition system [0012]; a seismic interpretation workstation, configured to identify a drilling target based, at least in part, on the seismic image in depth [0076; 0083]; a borehole planning system, configured to plan a borehole path to the drilling target [0076; 0083].
Zhao fails to specifically teach obtain, from the seismic dataset, an event in two-way traveltime (TWT), obtain, from the seismic dataset, a velocity model in TWT, convert the velocity model in TWT into a velocity model in depth, produce a final velocity model in depth, wherein: the final velocity model is produced using a full waveform inversion (FWI) and the velocity model in depth; and a TWT-preserving method preserves the event in TWT at each iteration of the FWI, and form a seismic image in depth using the final velocity model in depth and the seismic dataset. However, Zhao does teach seismic waves may be reflected and received by a plurality of seismic receivers, captured and recorded as a record of seismic data [0061]. One of ordinary skill in the art would correlate this with two-way traveltime event. It would also be obvious to one of ordinary skill in the art that building and modify the velocity model and ultimately using it for well planning and drilling determinations [0076], would require the velocity models to be converted from time to depth. Zhao further teaches produce a final velocity model using a full waveform inversion (FWI) and the velocity model in depth (Fig. 4-5; [0073; 0075]). Zhao further teaches a TWT preserving method preserves the event in TWT at each iteration of the FWI via RTM (Fig. 4-5; [0073; 0075]) (Examiner’s Note: It is known to one of ordinary skill in the art that RTM is a TWT preserving method). For purposes of continued examination, a second reference is provided to teach the TWT conversion from time to depth.
Salem teaches TWT conversion from time to depth (Fig. 8; [0060]). Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Zhao to incorporate the teachings of Salem by including: TWT conversion from time to depth in order to revise interpretation, enhancing the quality of estimating velocity parameters.
Regarding Claim 12, the combination further teaches the system of claim 11, further comprising drilling, using a drilling system, the borehole path to the target ( Zhao: [0033, 0035, 0039]).
Regarding Claim 13, the combination further teaches the system of claim 11, wherein, at each iteration of FWI, the TWT-preserving method comprises re-interpolating the velocity model in depth (Zhao: Fig. 4-5; [0073, 0075]).
Regarding Claim 14, the combination further teaches the system of claim 11, wherein, at each iteration of the FWI, the TWT-preserving method comprises re-interpolating the velocity model in TWT (Zhao teaches at each iteration of the FWI, the TWT preserving method comprising re-interpolation (RTM) (Fig. 4-5; [0073, 0075]), whereas Salem teach the velocity model in TWT (Fig. 8, [0060]).
Regarding Claim 17, combination further teaches the system of claim 11, wherein he TWT-preserving method is applied at each of a plurality of surface locations above the velocity model in depth (Examiner’s Note: this is inherent being that the data is sent to surface units (Zhao: [0035] which are above the velocity model in depth) ((Fig. 4-5; [0073, 0075])).
Regarding Claim 18, the combination teaches the system of claim 11. The combination further teaches wherein the event was determined from a time-migrated seismic dataset (Salem: [0060]; Fig. 8).
Regarding Claim 20, the combination teaches all of the limitations of Claim 11. The combination further teaches wherein the velocity model in TWT is obtained from a migration velocity analysis (Zhao: RTM (Fig. 4-5; [0073; 0075])
Claims 5-6 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Zhao and Salem as applied to claims 1-4 above, and further in view of Zheng et al. (CN107643541A, 2018-01-30), herein referred to as Zhang.
Regarding Claim 5, the combination of Zhao and Salem teach all of the limitations of Claim 3. The combination further teaches reinterpolation of the velocity model in depth, but fails to teach the re-interpolation is a piecewise linear re-interpolation. However, in a related field, Zhang teaches piecewise linear interpolation (Claim 5). Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Zhao and Salem to incorporate the teachings of Zhang by including: piecewise liner interpolation in order to maintain a specified characteristic of the velocity model during modification.
Regarding Claim 6, the combination of Zhao and Salem teach all of the limitations of Claim 4. The combination further teaches reinterpolation of the in TWT, but fails to teach the re-interpolation is a piecewise linear re-interpolation. However, in a related field, Zhang teaches piecewise linear interpolation (Claim 5). Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Zhao and Salem to incorporate the teachings of Zhang by including: piecewise liner interpolation in order to maintain a specified characteristic of the velocity model during modification.
Regarding Claim 15, the combination of Zhao and Salem teach all of the limitations of Claim 13. The combination further teaches reinterpolation of the velocity model in depth, but fails to teach the re-interpolation is a piecewise linear re-interpolation. However, in a related field, Zhang teaches piecewise linear interpolation (Claim 5). Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Zhao and Salem to incorporate the teachings of Zhang by including: piecewise liner interpolation in order to maintain a specified characteristic of the velocity model during modification.
Regarding Claim 16, the combination of Zhao and Salem teach all of the limitations of Claim 14. The combination further teaches reinterpolation of the in TWT, but fails to teach the re-interpolation is a piecewise linear re-interpolation. However, in a related field, Zhang teaches piecewise linear interpolation (Claim 5). Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Zhao and Salem to incorporate the teachings of Zhang by including: piecewise liner interpolation in order to maintain a specified characteristic of the velocity model during modification.
Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Zhao and Salem as applied to claims 1-4 above, and further in view of Al IsMail et al. (US20220300674A1, 2022-09-22), herein referred to as Al IsMail.
Regarding Claim 9, the combination teaches all of the limitations of Claim 1. The combination fails to teach wherein an optimization method of an objective function in the FWI is a steepest descent method. However, in a related field, AL IsMail teaches wherein an optimization method of an objective function in the FWI is a steepest descent method [0038]. Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Zhao and Salem to incorporate the teachings of Al IsMail by including: an optimization method of an objective function in the FWI is a steepest descent method in order determine how and what direction to modify the velocity model.
Regarding Claim 19, the combination teaches all of the limitations of Claim 11. The combination fails to teach wherein an optimization method of an objective function in the FWI is a steepest descent method. However, in a related field, AL IsMail teaches wherein an optimization method of an objective function in the FWI is a steepest descent method [0038]. Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Zhao and Salem to incorporate the teachings of Al IsMail by including: an optimization method of an objective function in the FWI is a steepest descent method in order determine how and what direction to modify the velocity model.
Conclusion
The prior art made record and not relied upon is considered pertinent to applicant’s disclosure.
Liu et al. (METHOD AND SYSTEMS FOR COMPUTATIONAL EFFICIENCY 3D PRESTACK KIRCHHOFF DEPTH MIGRATION, 2023-06-15) teaches methods and systems for forming a three-dimensional (“3D”) seismic image of a subterranean region of interest is disclosed. The method includes obtaining a seismic dataset a seismic trace for each of a plurality of pairs of one source and one receiver location and obtaining a 3D travel-time cube for each source location and each receiver location. The method further includes dividing the seismic dataset into a plurality of seismic subsets composed of set of source locations, set of receiver locations a seismic trace for each pair of source and receiver location and the 3D travel-time cube for each source for each receiver location. The method still further includes transmitting, to a random-access memory block of a computer processing unit the seismic subset, and forming a seismic partial image based on the seismic subset, and determining the 3D seismic image based on a combination of the seismic partial images;
Liu et al. (High Resolution Full Waveform Inversion, 2023-02-28) teaches methods, systems, and computer-readable medium to perform operations including: generating, using a source wavelet and a current velocity model, modeled seismic data of the subterranean formation; applying a pre-condition to a seismic data residual calculated using the modeled seismic data and acquired seismic data from the subterranean formation; generating a velocity update using the source wavelet and the pre-conditioned seismic data residual; updating, using the velocity update, the current velocity model to generate an updated velocity model; determining that the current velocity model satisfies a predetermined condition; and responsively determining that the updated velocity model is the velocity model of the subterranean formation;
Nivlet et al. (SYSTEMS AND METHODS FOR SEISMIC WELL TIE DOMAIN CONVERSION AND NEURAL NETWORK MODELING, 2022-05-05) teaches systems and methods are provided for seismic well tie domain conversion. In one embodiment, a process is provided to integrate well and seismic data for reservoir characterization. System configurations and processes described herein use neural networks to predict sonic well logs in the two way time (TWT) domain from measured well logs in depth, rather than predicting drift function. Embodiments are also directed to systems for reservoir characterization. Domain conversion of data includes receiving input data, preprocessing the data, and training a model to determine a length of an output sequence. The method also includes training the model for conversion of data based on at least one neural network. A sequence length prediction may be output as part of training and to perform modeling/prediction operations. The method also includes outputting sequence length in a TWT domain and output of transformed data.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J SINGLETARY whose telephone number is (571)272-4593. The examiner can normally be reached Monday-Friday 8:00am-5:00pm.
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/MICHAEL J SINGLETARY/Examiner, Art Unit 2863
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