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
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 17 November 2023 and 28 November 2023 were filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
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 an abstract idea without significantly more.
Claims 1 (and dependent claims 2-9) recite “A method for imaging a formation of a subsurface, the method comprising: receiving input data d related to the subsurface; generating synthetic data u related to the subsurface, by applying an implicit finite-difference approach to a reflectivity model r; updating a velocity model V based on the input data d and the synthetic data u; and generating an image of the formation in the subsurface based on the updated velocity model, wherein the formation is used to locate natural resources.”
Claims 1-9, in view of the claim limitations, recite the abstract idea of “receiving input data d related to the subsurface; generating synthetic data u related to the subsurface, by applying an implicit finite-difference approach to a reflectivity model r; updating a velocity model V based on the input data d and the synthetic data u; and generating an image of the formation in the subsurface based on the updated velocity model, wherein the formation is used to locate natural resources.”
As a whole, in view of the claim limitations, but for the computer components and systems performing the claimed functions, the broadest reasonable interpretation of the recited “receiving input data d related to the subsurface; generating synthetic data u related to the subsurface, by applying an implicit finite-difference approach to a reflectivity model r; updating a velocity model V based on the input data d and the synthetic data u; and generating an image of the formation in the subsurface based on the updated velocity model, wherein the formation is used to locate natural resources.”; therefore, the claims recite mental processes. Accordingly, the claims recite a mental process, and thus, the claims recite an abstract idea under the first prong of Step 2A.
This judicial exception is not integrated into a practical application under the second prong of Step 2A. In particular, the claims recite the additional elements beyond the recited abstract idea of“[a] computer- implemented method” and “the method is carried out by one or more physical processors configured by machine-readable instructions” as recited in claims 10 and 20, individually and when viewed as an ordered combination, and pursuant to the broadest reasonable interpretation, each of the additional elements are computing elements recited at high level of generality implementing the abstract idea on a computer (i.e. apply it), and thus, are no more than applying the abstract idea with generic computer components. Moreover, aside from the aforementioned additional elements, the remaining elements of dependent claims 11-19 do not integrate the abstract idea into a practical application because these claims merely recite further limitations that provide no more than simply narrowing the recited abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception under Step 2B. As noted above, the aforementioned additional elements beyond the recited abstract idea, as an order combination, are no more than mere instructions to implement the idea using generic computer components (i.e. apply it), and further, generally link the abstract idea to a field of use, which is not sufficient to amount to significantly more than an abstract idea; therefore, the additional elements are not sufficient to amount to significantly more than an abstract idea. Additionally, these recitations as an ordered combination, simply append the abstract idea to recitations of generic computer structure performing generic computer functions that are well-understood, routine, and conventional in the field as evinced by Applicant’s Specification at [0075]-[0077] (describing that the disclosure is not limited to the disclosed implementations, but, on the contrary, is intended to cover modifications and equivalent arrangements that are within the spirit and scope of the appended claims). Furthermore, as an ordered combination, these elements amount to generic computer components performing repetitive calculations, receiving or transmitting data over a network, which, as held by the courts, are well-understood, routine, and conventional. See MPEP 2106.05(d); July 2015 Update, p. 7. Moreover, aside from the aforementioned additional elements, the remaining elements of dependent claims 11-19 do not transform the recited abstract idea into a patent eligible invention because these claims merely recite further limitations that provide no more than simply narrowing the recited abstract idea. Looking at these limitations as an ordered combination adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use a generic arrangement of generic computer components and recitations of generic computer structure that perform well-understood, routine, and conventional computer functions that are used to “apply” the recited abstract idea. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amounts to significantly more than the abstract idea itself. Since there are no limitations in these claims that transform the exception into a patent eligible application such that these claims amount to significantly more than the exception itself, claims 1-20 are rejected under 35 U.S.C. 101 as being directed to non-statutory 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 (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 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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wang et al (US 11,215,720).
Wang et al disclose the following claimed features:
Regarding claim 1, a method for imaging a formation of a subsurface (Figure 1), the method comprising: receiving input data d related to the subsurface; generating synthetic data u related to the subsurface, by applying an implicit finite-difference approach to a reflectivity model r; updating a velocity model V based on the input data d and the synthetic data u; and generating an image of the formation in the subsurface based on the updated velocity model, wherein the formation is used to locate natural resources (column 2, lines 5-25).
Regarding claim 2, wherein the implicit finite-difference approach is run on plural graphics processor units, GPUs (column 11, lines 41-49).
Regarding claim 3, further comprising: discretizing a domain of the input data d along three different axes; selecting a first axis of the three different axes of the domain that has a largest number of grid points; and splitting the domain, along the selected first axis, into plural subdomains, corresponding to the plural GPUs (column 9, lines 10-28).
Regarding claim 4, further comprising: discretizing the reflectivity model to form a system of linear equations (column 10, line 60 to column 11, line 12).
Regarding claim 5, wherein the implicit finite-difference approach comprises: calculating a first order partial derivative P′(x.sub.i) of a quantity P, with respect to a spatial variable x, as a sum of 2M+1 products of (1) an implicit finite-difference coefficient b.sub.j and (2) the first order partial derivative P′(x.sub.i+j), where x.sub.i is a discrete point, x.sub.i+j is another discrete point, i describes a point where the first order partial derivative is calculated, i+j describes a point where the implicit finite-difference is calculated, and M is related to a stencil size (column 10, line 60 to column 11, line 12).
Regarding claim 6, wherein the stencil size for the implicit finite-difference approach for the input data d is smaller than a stencil size for an explicit finite-different approach for the input data d (column 9, lines 10-28).
Regarding claim 7, further comprising: performing, in each GPU of the plural GPUs, for a corresponding subdomain, first order partial derivatives along second and third axes of the three axes, without coordinating with other GPUs for other subdomains (column 9, lines 10-28).
Regarding claim 8, further comprising: selecting corresponding overlapping areas between pairs of adjacent subdomains of the plural subdomains; and performing, in each GPU of the plural GPUs, for the corresponding subdomain, first order partial derivatives along the first axis of the three axes, except for the corresponding overlapping area, without coordinating with the other GPUs for the other subdomains (column 9, lines 10-28).
Regarding claim 9, further comprising: for the corresponding overlapping area, exchanging data with the other GPUs, and only then performing first order partial derivatives along the first axis of the three axes (column 10, line 60 to column 11, line 12).
Regarding claim 10, a computing system for imaging a formation of a subsurface, the computing system (Figure 12) comprising: plural compute nodes, each compute node comprising, an interface (1222) configured to receive input data d related to the subsurface; and plural graphics processor units (1202), GPUs connected to the interface (1222), and configured to, generate synthetic data u related to the subsurface, by applying an implicit finite-difference approach to a reflectivity model r; update a velocity model V based on the input data d and the synthetic data u; and generate an image of the formation in the subsurface based on the updated velocity model, wherein the formation is used to locate natural resources (column 2, lines 5-25).
Regarding claim 11, wherein the implicit finite-difference approach is run on the plural GPUs (column 11, lines 41-49).
Regarding claim 12, wherein the GPUs are further configured to: discretize a domain of the input data d along three different axes; select a first axis of the three different axes of the domain that has a largest number of grid points; and split the domain, along the selected first axis, into plural subdomains, corresponding to the plural GPUs (column 9, lines 10-28).
Regarding claim 13, wherein the GPUs are further configured to: discretize the reflectivity model to form a system of linear equations (column 10, line 60 to column 11, line 12).
Regarding claim 14, wherein the implicit finite-difference approach comprises: calculating a first order partial derivative P′(x.sub.i) of a quantity P, with respect to a spatial variable x, as a sum of 2M+1 products of (1) an implicit finite-difference coefficient b.sub.j and (2) the first order partial derivative P′(x.sub.i+j), where x.sub.i is a discrete point, x.sub.i+j is another discrete point, i describes a point where the first order partial derivative is calculated, i+j describes a point where the implicit finite-difference is calculated, and M is related to a stencil size (column 10, line 60 to column 11, line 12).
Regarding claim 15, wherein the stencil size for the implicit finite-difference approach for the input data d is smaller than a stencil size for an explicit finite-different approach for the input data d (column 9, lines 10-28).
Regarding claim 16, wherein each GPU of the plural GPUs is configured to perform, for a corresponding subdomain, first order partial derivatives along second and third axes of the three axes, without coordinating with other GPUs for other subdomains (column 9, lines 10-28).
Regarding claim 17, wherein the plural GPUs are configured to, select corresponding overlapping areas between pairs of adjacent subdomains of the plural subdomains, and performing, in each GPU of the plural GPUs, for the corresponding subdomain, first order partial derivatives along the first axis of the three axes, except for the corresponding overlapping area, without coordinating with the other GPUs for the other subdomains (column 9, lines 10-28).
Regarding claim 18, wherein a GPU of the plural GPUs is configured to exchange data, for the corresponding overlapping area, with the other GPUs, and only then performing first order partial derivatives along the first axis of the three axes (column 10, line 60 to column 11, line 12).
Regarding claim 19, wherein the input data is seismic data (Abstract).
Regarding claim 20, a non-transitory computer readable medium including computer executable instructions, wherein the instructions, when executed by one or more graphics processor units, implement a method for imaging a formation in a subsurface (column 2, line 48 to column 3, line 3), the medium comprising instructions for: receiving input data d related to the subsurface; generating synthetic data u related to the subsurface, by applying an implicit finite-difference approach to a reflectivity model r; updating a velocity model V based on the input data d and the synthetic data u; and generating an image of the formation in the subsurface based on the updated velocity model, wherein the formation is used to locate natural resources (column 2, lines 5-25).
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Alwon (US 11,105,942) discloses a method that includes: generating seismic data; training a generator network utilizing at least a portion of the generated seismic data and a discriminator network; and outputting a trained generator network. Turquais et al (US 10,983,234) disclose a method and a system that generate seismic images of a subterranean formation from recorded seismic data gathers obtained in a marine seismic survey of the subterranean formation. Cooper et al (US 10,976,457) disclose a method and an apparatus for seismic exploration of an underground structure obtain improved images by integrating partial match filtering in an FWI. Filtered (auxiliary) data replaces one of the observed data and the synthetic data in the FWI's objective function to avoid cycle skipping.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AN H DO whose telephone number is (571)272-2143. The examiner can normally be reached on M-F 7:00am-4:00pm.
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/AN H DO/Primary Examiner, Art Unit 2853
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