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 .
Status of Claims
Claims 1-20 are pending and are examined herein.
Claims 11-20 recite at least one limitation which is invokes 35 USC 112(f).
Claims 1-20 are rejected under 35 USC 112(b).
Claims 1-20 are rejected under 35 USC 101 as being directed to an abstract idea without significantly more.
Claims 1-20 are rejected under 35 USC 103.
Information Disclosure Statement
The attached information disclosure statement(s) (IDS) is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the attached information disclosure statement(s) is/are being considered by the examiner.
Claim Interpretation – 35 U.S.C. 112(f)
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “seismic processing system” and “seismic acquisition system” in claim 11 and claims dependent thereon and also “data visualization system” in claim 17. For the purposes of examination, the “seismic processing system” is being interpreted as computer hardware configured to perform the claimed functions as indicated by the published specification at [0053]. The “seismic acquisition system” is being interpreted as any of the embodiments described at published [0084] and equivalents thereof. The specification does not describe a structure corresponding to the “data visualization system” (note rejection under 35 USC 112(b) below), but for the purposes of examination will be interpreted as computer hardware configured to perform the claimed functions.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Independent claims 1 and 11 recite “machine learning (ML) network”. This is not a term of art and is not defined by the specification. Moreover, the published specification at [0029] includes a definition of “machine learning” as “the extraction of patterns and insights from data”, which is broader than the meaning that the term would typically be given in the art. Note that this definition does not even restrict “machine learning” to being performed on a computer. Applicant is entitled to act as their own lexicographer and has provided a clear and unequivocal definition of this term. However, Applicant has failed to provide a definition of “machine learning (ML) network” in view of the redefinition of “machine learning”. For the purposes of examination, anything which performs the function(s) attributed by the claims to the “machine learning network” will be interpreted as falling within the scope of the limitation. Dependent claims 2-10 and 12-20 do not resolve the issue and are rejected with the same rationale. Some of the dependent claims include further recitations of “machine learning network”. Note that the term “neural network” is a term of art. Amending “machine learning network” to “neural network” would be supported by the specification.
Claim limitation “data visualization system” in claim 17 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The specification at no point links structure or material to the data visualization system. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim Rejections - 35 USC § 101 – Abstract Idea
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.
Step 1 Analysis
Each of the claims fall within one of the four statutory categories (i.e. process, machine, manufacture, or composition of matter).
Step 2 Analysis
Claim 1 includes the following recitation of an abstract idea:
A method for training a machine learning (ML) network to predict a likelihood of a presence of a geological fracture from an observed drill-bit seismic dataset, comprising: (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process. Note in particular the expansive redefinition of “machine learning” at published [0029]. In that context, the “training” would encompass any change to a pattern recognition technique.)
…simulating, …for each geophysical model a corresponding simulated drill-bit seismic dataset for seismic waves emanating from the drill bit and recorded by at least one seismic receiver; (This is a recitation of a mathematical concept.)
…training, using the training dataset, the ML network to predict the likelihood of the presence of the geological fracture from the observed drill-bit seismic dataset. (This is practical to perform in the human mind under its broadest reasonable interpretation. This is a recitation of a mental process. Note in particular the expansive redefinition of “machine learning” at published [0029]. In that context, the “training” would encompass any change to a pattern recognition technique.)
Claim 1 recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
obtaining, using a seismic processing system, a plurality of geophysical models, wherein each geophysical model comprises a location of a drill bit; (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, sending or receiving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example i. Receiving or transmitting data.)
… using the seismic processing system, (This is a high level recitation of generic computer components for performing the abstract idea. This does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. See MPEP 2106.05(f).)
… forming a training dataset comprising a plurality of training pairs, wherein each training pair comprises a geophysical model from the plurality of geophysical models and the corresponding simulated drill-bit seismic dataset; and (This is a recitation of using data of a particular type or source to perform the abstract idea. This is an attempt to limit the abstract idea to a particular field of use or technological environment. See MPEP 2106.05(h).)
Claim 1 does not reflect an improvement to computer technology or any other technology.
Claim 2 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
obtaining, using a seismic acquisition system, the observed drill-bit seismic dataset for a subterranean region of interest; (This is a recitation of using data of a particular type or source to perform the abstract idea. This is an attempt to limit the abstract idea to a particular field of use or technological environment. See MPEP 2106.05(h).)
predicting, using the trained ML network, the likelihood of the presence of the geological fracture from the observed drill-bit seismic dataset; and (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process.)
altering a drilling parameter based, at least in part, on the likelihood. (The claim does not indicate what the drilling parameter is or how it is altered. This could encompass simply changing one number from one value to another. The claim does not require, for example, a change in the actual operation of drilling equipment. This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process. This is also a recitation of a mathematical concept.)
Claim 2 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 2 does not reflect an improvement to computer technology or any other technology.
Claim 3 recites at least the abstract idea identified above in the claim upon which it depends, and further comprises
wherein predicting the likelihood of the presence comprises predicting a location of the geological fracture. (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process.)
Claim 3 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 3 does not reflect an improvement to computer technology or any other technology.
Claim 4 recites at least the abstract idea identified above in the claim upon which it depends.
Claim 4 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
wherein at least one geophysical model from the plurality of geophysical models comprises a geological fracture. (This is an attempt to limit the abstract idea to a particular field of use or technological environment, which does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. See MPEP 2106.05(h).)
Claim 4 does not reflect an improvement to computer technology or any other technology.
Claim 5 recites at least the abstract idea identified above in the claim upon which it depends.
Claim 5 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
wherein the seismic acquisition system comprises three-component seismic receivers. (This is a recitation of using data of a particular type or source to perform the abstract idea. This is an attempt to limit the abstract idea to a particular field of use or technological environment. See MPEP 2106.05(h).)
Claim 5 does not reflect an improvement to computer technology or any other technology.
Claim 6 recites at least the abstract idea identified above in the claim upon which it depends.
Claim 6 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
wherein the seismic acquisition system further comprises a pilot seismic sensor disposed in acoustic contact with a drillstring attached to the drill bit. (This is a recitation of using data of a particular type or source to perform the abstract idea. This is an attempt to limit the abstract idea to a particular field of use or technological environment. See MPEP 2106.05(h).)
Claim 6 does not reflect an improvement to computer technology or any other technology.
Claim 7 recites at least the abstract idea identified above in the claim upon which it depends.
Claim 7 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
wherein obtaining the observed drill-bit seismic dataset comprises cross-correlating a recording from the pilot seismic sensor with raw data recorded by three-component seismic receivers. (This is a recitation of using data of a particular type or source to perform the abstract idea. This is an attempt to limit the abstract idea to a particular field of use or technological environment. See MPEP 2106.05(h).)
Claim 7 does not reflect an improvement to computer technology or any other technology.
Claim 8 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
identifying, using the ML network, diffracted seismic waves within the observed drill-bit seismic dataset; and (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. This is a recitation of a mental process.)
migrating, using the seismic processing system the diffracted seismic waves. (This is a recitation of a mathematical concept.)
Claim 8 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 8 does not reflect an improvement to computer technology or any other technology.
Claim 9 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
wherein migrating the diffracted seismic waves comprises updating a seismic velocity model. (This is a recitation of a mathematical concept.)
Claim 9 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 9 does not reflect an improvement to computer technology or any other technology.
Claim 10 recites at least the abstract idea identified above in the claim upon which it depends.
Claim 10 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
wherein predicting the likelihood of the presence further comprises eliminating direct seismic waves and surface seismic waves within the observed drill-bit seismic dataset. (This is a recitation of using data of a particular type or source to perform the abstract idea. This is an attempt to limit the abstract idea to a particular field of use or technological environment. See MPEP 2106.05(h).)
Claim 10 does not reflect an improvement to computer technology or any other technology.
Claim 11 recites substantially similar subject matter to claim 1 including substantially the same abstract idea.
Claim 11 recites the following additional elements which, considered individually and as an ordered combination with the additional elements addressed above with respect to claim 1, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
A …, comprising: a drilling system comprising a drillstring and a drill bit; (This is an attempt to limit the abstract idea to a particular field of use or technological environment, which does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. See MPEP 2106.05(h).)
a seismic processing system, configured to: (This is a high level recitation of generic computer components for performing the abstract idea. This does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. See MPEP 2106.05(f).)
…a seismic acquisition system, configured to obtain the observed drill-bit seismic dataset for a subterranean region of interest. (This is a recitation of using data of a particular type or source to perform the abstract idea. This is an attempt to limit the abstract idea to a particular field of use or technological environment. See MPEP 2106.05(h).)
Claim 11 does not reflect an improvement to computer technology or any other technology.
Claims 12-16 recite substantially similar subject matter to claims 5, 6, 7, 4, 3, respectively, and are rejected with the same rationale, mutatis mutandis.
Claim 17 recites at least the abstract idea identified above in the claim upon which it depends.
Claim 17 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
further comprising a data visualization system configured to (This is a high level recitation of generic computer components for performing the abstract idea. This does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. See MPEP 2106.05(f).)
receive the location of the geological fracture and (This is insignificant extra-solution activity. See MPEP 2106.05(g). Moreover, sending or receiving data is well-understood, routine, conventional as evidenced by the court cases cited at MPEP 2106.05(d), example i. Receiving or transmitting data.)
to plot the location of the geological fracture. (This is a mere instruction to apply the judicial exception. The limitation is recited at a high level, uses the computer as a tool to implement an existing process, and does not meaningfully limit the applicability of the abstract idea. See MPEP 2106.05(f).)
Claim 17 does not reflect an improvement to computer technology or any other technology.
Claims 18-20 recite substantially similar subject matter to claims 8, 8, and 9, respectively, and are rejected with the same rationale, mutatis mutandis.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-4, 11 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Mao (US 2020/0200931 A1) in view of Luo (US 2020/0233113 A1).
Regarding claim 1, Mao teaches
A method for training a machine learning (ML) network to predict a likelihood of a presence of a geological fracture from an observed drill-bit seismic dataset, comprising: (Mao, Figure 3, described at [0027-0037]. See more detailed mapping below.)
obtaining, using a seismic processing system, a plurality of geophysical models, (Mao, [0026, 0028] describes assembling a training dataset comprising representations of physical space, where each physical space may be divided into spatial units. Each unit of physical space is being interpreted as a geophysical model. See Figure 13 and [0053-0060] for the seismic processing system.)
…simulating, using the seismic processing system, for each geophysical model a simulated … seismic dataset for seismic waves … and recorded by at least one seismic receiver; forming a training dataset comprising a plurality of training pairs, wherein each training pair comprises a geophysical model from the plurality of geophysical models and the corresponding simulated drill-bit seismic dataset; and (Mao, Figure 3, step 304 and [0028] indicate that the training dataset may be acquired by from seismic equipment or by generating simulations and that each unit of the physical space may be labeled by a computer system. The computer-based determination of the labels is a simulation representing whether or not a fault/fracture is present. The unit/label pairs are training pairs.)
training, using the training dataset, the ML network to predict the likelihood of the presence of the geological fracture from the observed …seismic dataset. (Mao, Figure 3, step 308 and [0029-0030] describe training the model using the training data to determine a fault/fracture likelihood. [0021] describes applying the model during real-time drilling operations to interpret seismic data and to modify an operational parameter and to control the drilling so as to avoid drilling into a fault.)
Mao does not appear to explicitly teach (italics are used to emphasize the portions of the claim no taught by Mao):
wherein each geophysical model comprises a location of a drill bit;
simulating, using the seismic processing system, for each geophysical model a corresponding simulated drill-bit seismic dataset for seismic waves emanating from the drill bit and recorded by at least one seismic receiver;
..the observed drill-bit seismic dataset
However, Luo—directed to analogous art—teaches
wherein each geophysical model comprises a location of a drill bit; simulating, using the seismic processing system, for each geophysical model a corresponding simulated drill-bit seismic dataset for seismic waves emanating from the drill bit and recorded by at least one seismic receiver; ..the observed drill-bit seismic dataset (Luo, Figure 1 and [0027-0028] describes performing SWD (seismic while drilling) operations (see also overview at [0001-0002]) including tracking a location of a drill bit and measuring seismic waves generated by the drill bit (see also discussion at [00019, 0023-0024]). In the proposed combination with Mao, the teaching of Luo directed to using the drill bit as an energy source for the seismic waves as taught by Luo would be used in combination with the techniques of Mao where the energy source is unspecified.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Mao by Luo because the real-time SWD system provides real-time insight and information to drilling and geosteering personnel which allows for the mitigation of risk as described by Luo at [0025].
Regarding claim 2, the rejection of claim 1 is incorporated herein. Furthermore, Mao teaches
obtaining, using a seismic acquisition system, the observed … seismic dataset for a subterranean region of interest; predicting, using the trained ML network, the likelihood of the presence of the geological fracture from the observed … seismic dataset; and altering a drilling parameter based, at least in part, on the likelihood. (Mao, Figure 3, step 308 and [0029-0030] indicate that the model may be trained to determine a fault/fracture likelihood. [0021] describes applying the model during real-time drilling operations to interpret seismic data (i.e., observed seismic data that is necessarily obtained) and to modify an operational parameter and to control the drilling so as to avoid drilling into a fault. )
Mao does not appear to explicitly teach (italics are used to emphasize the portions of the claim no taught by Mao):
observed drill-bit seismic dataset
However, Luo—directed to analogous art—teaches
observed drill-bit seismic dataset (Luo, Figure 1 and [0027-0028] describes performing SWD (seismic while drilling) operations (see also overview at [0001-0002]) including tracking a location of a drill bit and measuring seismic waves generated by the drill bit (see also discussion at [00019, 0023-0024]). In the proposed combination with Mao, the teaching of Luo directed to using the drill bit as an energy source for the seismic waves as taught by Luo would be used in combination with the techniques of Mao where the energy source is unspecified.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have combined these references in this way for the same reasons given above with respect to claim 1.
Regarding claim 3, the rejection of claim 1 is incorporated herein. Furthermore, Mao teaches
wherein predicting the likelihood of the presence comprises predicting a location of the geological fracture. (Mao, [0021, 0038] indicate that the model may predict a location of a fault/fracture.)
Regarding claim 4, the rejection of claim 1 is incorporated herein. Furthermore, Mao teaches
wherein at least one geophysical model from the plurality of geophysical models comprises a geological fracture. (Mao, [0028-0029] indicate that some of the spatial units may include faults/fractures.)
Regarding claim 11, Mao teaches
A system for training a machine learning (ML) network to predict a likelihood of a presence of a geological fracture from an observed drill-bit seismic dataset, comprising: a drilling system comprising a drillstring and a drill bit; a seismic processing system, configured to: …a seismic acquisition system, (Mao, Abstract, Figures 10 and 13, [0044-0045, 0053-0054])
The remainder of claim 11 is substantially similar to claim 2 (including the subject matter from claim 1) and is rejected with the same rationale, mutatis mutandis.
Regarding claims 15-16, the rejection of claim 11 is incorporated herein. Claims 16-15 recite substantially similar subject matter to claims 4 and 3, respectively, and are rejected with the same rationale, mutatis mutandis.
Claims 5-7, 10, and 12-14 are rejected under 35 U.S.C. 103 as being unpatentable over Mao (US 2020/0200931 A1) in view of Luo (US 2020/0233113 A1), and further in view of Liu (US 2026/0110248 A1).
Regarding claim 5, the rejection of claim 2 is incorporated herein. Mao does not appear to explicitly teach
wherein the seismic acquisition system comprises three-component seismic receivers.
However, Liu—directed to analogous art—teaches
wherein the seismic acquisition system comprises three-component seismic receivers. (Liu, Abstract describes techniques for acquiring and storing signals generated as part of a tunnelling process and using the data to identify geological anomalies. [0049-0050, 0079-0080, 0084-0085, 0110] indicate that that sensors may comprise three-component seismic receivers.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Mao by Liu because the techniques taught by Liu allow for the solution of the problems identified at [0007-0010] and allows for unfavorable geological bodies in front of the tunneling face to be found in time.
Regarding claim 6, the rejection of claim 2 is incorporated herein. Mao does not appear to explicitly teach
wherein the seismic acquisition system further comprises a pilot seismic sensor disposed in acoustic contact with a drillstring attached to the drill bit.
However, Liu—directed to analogous art—teaches
wherein the seismic acquisition system further comprises a pilot seismic sensor disposed in acoustic contact with a drillstring attached to the drill bit. (Liu, Abstract describes techniques for acquiring and storing signals generated as part of a tunnelling process and using the data to identify geological anomalies. Figure 2, [0018-0019, 0049, 0057, 0076-0077, 0088] indicate that the pilot sensor 3 may be placed onto a support plate being the cutterhead.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have combined these references in this way for the same reasons given above with respect to claim 5.
Regarding claim 7, the rejection of claim 6 is incorporated herein. Mao does not appear to explicitly teach
wherein obtaining the observed drill-bit seismic dataset comprises cross-correlating a recording from the pilot seismic sensor with raw data recorded by three-component seismic receivers.
However, Liu—directed to analogous art—teaches
wherein obtaining the observed drill-bit seismic dataset comprises cross-correlating a recording from the pilot seismic sensor with raw data recorded by three-component seismic receivers. (Liu, Abstract describes techniques for acquiring and storing signals generated as part of a tunnelling process and using the data to identify geological anomalies. [0049-0050, 0079-0080, 0084-0085, 0110] indicate that that sensors may comprise three-component seismic receivers. Figure 2, [0018-0019, 0049, 0057, 0076-0077, 0088] indicate that the pilot sensor 3 may be placed onto a support plate being the cutterhead. [0086, 0102, 0118, 0121] describe cross-correlating the seismic signals.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have combined these references in this way for the same reasons given above with respect to claim 5.
Regarding claim 10, the rejection of claim 2 is incorporated herein. Mao does not appear to explicitly teach
wherein predicting the likelihood of the presence further comprises eliminating direct seismic waves and surface seismic waves within the observed drill-bit seismic dataset.
However, Liu—directed to analogous art—teaches
wherein predicting the likelihood of the presence further comprises eliminating direct seismic waves and surface seismic waves within the observed drill-bit seismic dataset. (Liu, [0110] describes filtering direct waves. [0100] describes separating surface waves from rock-breaking seismic source waves.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have combined these references in this way for the same reasons given above with respect to claim 5.
Regarding claim 12-14, the rejection of claim 11 is incorporated herein. Claims 12-14 recite substantially similar subject matter to claims 5-7, respectively, and are rejected with the same rationale, mutatis mutandis.
Claims 8-9 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Mao (US 2020/0200931 A1) in view of Luo (US 2020/0233113 A1), and further in view of Kim (Extraction of diffractions from seismic data using convolutional U-net and transfer learning).
Regarding claim 8, the rejection of claim 1 is incorporated herein. Mao does not appear to explicitly teach
identifying, using the ML network, diffracted seismic waves within the observed drill-bit seismic dataset; and
migrating, using the seismic processing system the diffracted seismic waves.
However, Luo—directed to analogous art—teaches
the observed drill-bit seismic dataset (Luo, Figure 1 and [0027-0028] describes performing SWD (seismic while drilling) operations (see also overview at [0001-0002]) including tracking a location of a drill bit and measuring seismic waves generated by the drill bit (see also discussion at [00019, 0023-0024]). In the proposed combination with Mao, the teaching of Luo directed to using the drill bit as an energy source for the seismic waves as taught by Luo would be used in combination with the techniques of Mao where the energy source is unspecified.)
The combination of Mao and Liu does not appear to explicitly teach
identifying, using the ML network, diffracted seismic waves within … seismic dataset; and
migrating, using the seismic processing system the diffracted seismic waves.
However, Kim—directed to analogous art—teaches
identifying, using the ML network, diffracted seismic waves within … seismic dataset; and. (Kim, Abstract describes using deep learning as a classification algorithm to identify diffraction waves in seismic data. This is described in more detail in the sections “Diffraction Extraction Using Synthetic data” and “Diffraction Extraction with TL”. In the combination with Mao, the ML technqiues taught by Mao would be augmented with the model taught by Kim.)
migrating, using the seismic processing system the diffracted seismic waves (Kim, page V120, last paragraph describes applying Kirchhoff migration to the extracted diffraction dataset. See also page V124, second paragraph and page V125, last paragraph before discussion.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Mao and Liu by Kim because the techniques preservers diffraction amplitude and phase information (Kim, page V118, third paragraph) and because they produce quality results that are efficient for field data applications (Kim, page V127, last paragraph of Conclusion).
Regarding claim 9, the rejection of claim 8 is incorporated herein. Mao does not appear to explicitly teach
wherein migrating the diffracted seismic waves comprises updating a seismic velocity model.
However, Kim—directed to analogous art—teaches
wherein migrating the diffracted seismic waves comprises updating a seismic velocity model. (Kim, Abstract indicates that the diffractions can be used to for velocity modeling. Page V120, last paragraph continuing onto page V121 describes applying Kirchhoff migration to the extracted images to enhance weak diffractions in the models. For example, “Then, we applied prestack Kirchhoff migration to the whole extracted diffraction data set using the P-wave velocity model shown in Figure 3. Up to this point, we showed the common-offset gather results with zero offset; however, because diverse diffraction apertures were simulated during the training data generation stage, the trained DL model extracted diffraction events in the various offset gathers (Figure 7a) despite a slight decline in performance as the offset increased because only limited diffraction apertures were included in the training data set due to computational limitations. Therefore, we applied prestack Kirchhoff migration to all extracted diffraction images from target data within 0–1.5 km offsets and stacked whole migrated images to enhance the weak diffractions.”)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have combined these references in this way for the same reasons given above with respect to claim 8.
Regarding claims 18-20, the rejection of claim 11 is incorporated herein. Claims 18-20 recite substantially similar subject matter to claims 8, 8, and 9, respectively, and are rejected with the same rationale, mutatis mutandis.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Mao (US 2020/0200931 A1) in view of Luo (US 2020/0233113 A1), and further in view of Jiang (US 2022/0413173 A1).
Regarding claim 17, the rejection of claim 16 is incorporated herein. Mao does not appear to explicitly teach
further comprising a data visualization system configured to receive the location of the geological fracture and to plot the location of the geological fracture.
However, Jiang—directed to analogous art—teaches
further comprising a data visualization system configured to receive the location of the geological fracture and to plot the location of the geological fracture. (Jiang, [0050-0053] describes performing data analysis to determine a fault location and outputting a plot of the data. The computer equipment that performs these function corresponds to the claimed data visualization system.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Mao by Jiang because this allows an operator to use the information to make decisions about the operation as described by Jiang at [0036].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Zhang (US 2023/0258077 A1) – Abstract describes using machine learning to determine properties related to drilling a well.
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/MARKUS A. VASQUEZ/ Primary Examiner, Art Unit 2121
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