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 Objections
Claims 5 and 15 objected to because of the following informalities:
Claims 5 and 15: “computing the probing gradient” should be corrected to “computing [[the]]a probing gradient”. The claims 5 and 15 could also be corrected by amending the claims to depend from claims 2 or 12 respectively.
Appropriate correction is required.
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.
With respect to claim 1 the limitation(s):
receiving seismic data related to the subsurface, wherein the seismic data includes a baseline dataset dB and a monitor dataset dM, with the monitor dataset dM being acquired later in time than the baseline dataset dB, for the same subsurface;
defining an objective function of the FWI method;
calculating, for an iteration of the FWI, a baseline gradient gB of the objective function for the baseline dataset dB, and a monitor gradient gM of the objective function for the monitor dataset dM;
computing a baseline preconditioner P′B for the baseline dataset dB and a monitor preconditioner P′M for the monitor dataset dM so that each of the baseline preconditioner P′B and the monitor preconditioner P′M reflects similarities and/or differences of geometrical features of the baseline and monitor acquisition surveys; and
determining physical properties of the subsurface based on a baseline physical properties update and a monitor physical properties update, the baseline and monitor physical properties updates being calculated based on the baseline preconditioner P′B, the baseline gradient gB, the monitor preconditioner P′M, and the monitor gradient gM.
These limitation(s) highlighted in (bold) is/are directed to an abstract idea and would fall within the “Mental Processes” and “Mathematical Concepts” groupings of abstract ideas. The above portion(s) of the claim(s) constitute(s) an abstract idea because:
The limitation(s) regarding “defining an objective function of the FWI method”, as drafted, is an act of observation and evaluation that, under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind. That is, nothing in the claim language precludes the Step(s) from practically being performed in the mind. For example, “determining” in the context of this claim encompasses the user manually defining an objective function.
Furter, the limitation regarding “defining an objective function of the FWI method”, as drafted, falls within the “Mathematical Concepts” groupings of abstract ideas. This interpretation is supported in the specification as shown in paragraph [0031] equation (1) of the specification as filed which is an explicit recitation of an equation corresponding to the claimed limitation. It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989).
The limitation regarding “calculating, for an iteration of the FWI, a baseline gradient gB of the objective function for the baseline dataset dB, and a monitor gradient gM of the objective function for the monitor dataset dM”, as drafted, falls within the “Mathematical Concepts” groupings of abstract ideas. This interpretation is supported in the specification as shown in paragraph [0032] equation (2) of the specification as filed which is an explicit recitation of an equation corresponding to the claimed limitation. It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989).
The limitation regarding “computing a baseline preconditioner P′B for the baseline dataset dB and a monitor preconditioner P′M for the monitor dataset dM so that each of the baseline preconditioner P′B and the monitor preconditioner P′M reflects similarities and/or differences of geometrical features of the baseline and monitor acquisition surveys”, as drafted, falls within the “Mathematical Concepts” groupings of abstract ideas. This interpretation is supported in the specification as shown in paragraph [0032] equation (3) of the specification as filed which is an explicit recitation of an equation corresponding to the claimed limitation. It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989).
The limitation(s) regarding “determining physical properties of the subsurface based on a baseline physical properties update and a monitor physical properties update, the baseline and monitor physical properties updates being calculated based on the baseline preconditioner P′B, the baseline gradient gB, the monitor preconditioner P′M, and the monitor gradient gM”, as drafted, is an act of observation and evaluation that, under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind. That is, nothing in the claim language precludes the Step(s) from practically being performed in the mind. For example, “determining” in the context of this claim encompasses the user manually determining physical properties.
Further, the limitation regarding “determining physical properties of the subsurface based on a baseline physical properties update and a monitor physical properties update, the baseline and monitor physical properties updates being calculated based on the baseline preconditioner P′B, the baseline gradient gB, the monitor preconditioner P′M, and the monitor gradient gM”, as drafted, falls within the “Mathematical Concepts” groupings of abstract ideas. This interpretation is supported in the specification as shown by paragraph [0034] equation (5) which is an explicit recitation of an equation corresponding to the claimed limitation. It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989).
Further, referring to the MPEP 2106.04, the claim limitations are analogous to a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Further, if a claim limitation, under its broadest reasonable interpretation, recites mathematical relationships, mathematical formulas or equations, and mathematical calculations, then it fall within the “Mathematical Concepts” groupings of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application because the non- abstract additional elements of the claims do not impose meaningful limits on practicing the abstract idea(s) recited in the preceding claim(s). In particular, the claims recited the additional elements of:
The limitation(s) regarding “estimating physical properties of a subsurface” does/do not integrate the abstract idea into a practical application, because it is recited at such a high-level of generality that it is viewed as generally linking the use of the judicial exception to subsurfaces. Generally linking the use of the judicial exception to a particular technological environment or field of use, fails to integrate the abstract ideas into a practical application, because the claim does not specify what practical application the claim is directed to.
The limitation(s) regarding “receiving seismic data related to the subsurface, wherein the seismic data includes a baseline dataset dB and a monitor dataset dM, with the monitor dataset dM being acquired later in time than the baseline dataset dB, for the same subsurface” does/do not integrate the abstract idea into a practical application because the claim does not specify what practical application the claim is directed to. Rather the limitation is recited at such a high-level of generality that it amounts to no more than adding insignificant extra- solution activity to the judicial exception, i.e. data gathering. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they are regarded as data gathering steps necessary or routine to implement the abstract idea.
As such Examiner does NOT view that the claims:
-Improve the functioning of a computer, or to any other technology or technical field;
-Apply the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b);
-Effect a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c); or
-Apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception – see MPEP 2106.05(e) and Vanda Memo.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements amount to no more than mere instructions to apply the exception using a generic computer component, or are well-understood, routine, and conventional (WURC) data gathering functions.
As discussed above with respect to integration of the abstract idea into a practical application, the additional element of “physical properties of a subsurface” is/are seen as generally linking the use of the judicial exception to a particular technological environment. Linking a judicial exception to a technological environment cannot provide an inventive concept. Similarly, with regards to the additional element(s) of “receiving seismic data” is/are viewed as insignificant extra-solution activity, such as mere data gathering in a conventional way and, therefore, does not provide an inventive concept.
Examiner further notes that such additional elements are viewed to be well- understood, routine, and conventional (WURC) as evidenced by: Willemsen et al. (Willemsen, B., and A. Malcolm. "Regularizing velocity differences in time-lapse FWI using gradient mismatch information: 85th Annual International Meeting, SEG, Expanded Abstracts, 5384–5388." 2015.); Fu (Fu, Xin. Time-lapse seismic imaging, full-waveform inversion, and uncertainty quantification. Diss. University of Calgary (Canada), 2023.); Wang et al. (Wang, Ming, Shouting Huang, and Ping Wang. "Improved iterative least-squares migration using curvelet-domain Hessian filters." SEG International Exposition and Annual Meeting. SEG, 2017.); Raknes et al. (Raknes, Espen Birger, and Børge Arntsen. "A numerical study of 3D elastic time-lapse full-waveform inversion using multicomponent seismic data." Geophysics 80.6 (2015): R303-R315.); Gerea et al. (Gerea, Constantin, Enrico Zamboni, and Bertrand Duquet. "HPC-Driven Seismic Processing and Time-Lapse 4D Monitoring." SPE Offshore Europe Conference and Exhibition. SPE, 2017.); Alemie et al. (Alemie, W., and M. Sacchi. "Joint reparametrized time-lapse full-waveform inversion: 86th Annual International Meeting, SEG, Expanded Abstracts, 1309–1314." 2016.); Xue et al. (US 20220308246 A1).
Considering the claim as a whole, one of ordinary skill in the art would not know the practical application of the present invention since the claims do not apply or use the judicial exception in some meaningful way. As currently claimed, Examiner views that the additional elements do not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, because the claims fails to recite clearly how the judicial exception is applied in a manner that does not monopolize the exception because the limitation regarding “a subsurface” and “receiving seismic data” can be viewed as a field of use, necessary data gathering, and any device and do not impose a meaningful limitation describing what problem is being remedied or solved.
Independent claims 11 and 20 are also held to be patent ineligible under 35 U.S.C. 101 because the additionally recited limitations fail to establish that the claims are not directed to an Abstract idea. Claims 11 and 20 recite(s) the additional elements of:
The limitation(s) regarding “a computing device,” “an interface,” “a processor,” and “a non-transitory computer readable medium” does/do not integrate the abstract idea into a practical application because the claim does not specify what practical application the claim is directed to. Rather the limitation is recited at such a high-level of generality that it amounts to a generic computer component performing the generic computer function of receiving, storing, and comparing data such that it amounts to no more than mere instruction to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Dependent claims 2-10 and 12-19 when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additionally recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea, as detailed below: there are no additional element(s) in the dependent claims that adds a meaningful limitation to the abstract idea to make the claims significantly more than the judicial exception (abstract idea).
Claims 10 and 19 recite limitations regarding data gathering steps and insignificant application necessary or routine to implement the abstract idea and thus are not significantly more than the abstract idea and viewed to be well known routine and conventional as evidenced by the prior art shown above.
Claims 2-10 and 12-19 further limit the abstract idea with an abstract idea, such as an “Mental Processes” and “Mathematical Concepts”, and thus the claims are still directed to an abstract idea without significantly more.
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.
Claim(s) 1-6, 9-16, and 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Willemsen et al. (Willemsen, B., and A. Malcolm. "Regularizing velocity differences in time-lapse FWI using gradient mismatch information: 85th Annual International Meeting, SEG, Expanded Abstracts, 5384–5388." 2015.) in view of Fu (Fu, Xin. Time-lapse seismic imaging, full-waveform inversion, and uncertainty quantification. Diss. University of Calgary (Canada), 2023.).
Regarding Claims 1, 11, and 20. Willemsen teaches:
A joint timelapse full waveform inversion (FWI) method for estimating physical properties of a subsurface, the method comprising:
receiving seismic data related to the subsurface, wherein the seismic data includes a baseline dataset dB and a monitor dataset dM, with the monitor dataset dM being acquired later in time than the baseline dataset dB, for the same subsurface (See Page 5384 Col. 2: baseline data d0 and the monitor data d1.);
defining an objective function of the FWI method (See Page 5385 Col. 1: objective function c is minimized for the baseline model m0 and the monitor model m1.);
calculating, for an iteration of the FWI, a baseline gradient gB of the objective function for the baseline dataset dB, and a monitor gradient gM of the objective function for the monitor dataset dM (See Page 5385 Col. 1: where g0,i(x) and g1,i(x) are the gradients of the baseline and monitor terms at iteration i respectively.);
determining physical properties of the subsurface based on a baseline physical properties update and a monitor physical properties update, the baseline and monitor physical properties updates being calculated based on the baseline preconditioner P′B, the baseline gradient gB, the monitor preconditioner P′M, and the monitor gradient gM (See Page 5384 Col. 1, Page 5385 Col. 1: A method for recovering time-lapse velocity changes using full waveform inversion (FWI). To reduce the effects of differences in illumination we precondition the gradients using the inverse diagonal of the pseudo-Hessian.).
Willemsen does not explicitly disclose:
computing a baseline preconditioner P′B for the baseline dataset dB and a monitor preconditioner P′M for the monitor dataset dM so that each of the baseline preconditioner P′B and the monitor preconditioner P′M reflects similarities and/or differences of geometrical features of the baseline and monitor acquisition surveys.
Nevertheless Fu teaches:
computing a baseline preconditioner P′B for the baseline dataset dB and a monitor preconditioner P′M for the monitor dataset dM so that each of the baseline preconditioner P′B and the monitor preconditioner P′M reflects similarities and/or differences of geometrical features of the baseline and monitor acquisition surveys (See Page 45, Page 59, Page 75: As for the difference in wavelets, we believe the impact is also limited since the gradient is preconditioned by the diagonal approximation of the Hessian matrix, in which the wavelet effect can be eliminated.
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Willemsen by computing a baseline preconditioner P′B for the baseline dataset dB and a monitor preconditioner P′M for the monitor dataset dM so that each of the baseline preconditioner P′B and the monitor preconditioner P′M reflects similarities and/or differences of geometrical features of the baseline and monitor acquisition surveys such as that of Fu. One of ordinary skill would have been motivated to modify Willemsen, because preconditioning the baseline dataset and monitor dataset would have helped to eliminate differences in wavelets, as recognized by Fu.
Regarding Claims 2 and 12. Williamsen is silent as to the language of:
The method of claim 1 or The device of claim 11,
wherein, for reflecting the similarities and/or differences of the geometrical features of the baseline and monitor acquisition surveys, the baseline and monitor preconditioners satisfy P′BHBγ=P′MHMγ, where HB is a Hessian of a cost function of the FWI for the baseline dataset, HM is a Hessian of the cost function for the monitor dataset, and γ is a probing gradient in a gradient space.
Nevertheless Fu teaches:
wherein, for reflecting the similarities and/or differences of the geometrical features of the baseline and monitor acquisition surveys, the baseline and monitor preconditioners satisfy P′BHBγ=P′MHMγ (See Pages 61 - 62: we observe that the implicit baseline model can be eliminated from the inverted monitor model under the conditions: The stepsizes are the same, i.e. ukmon = ukbas. The updated baseline models are the same, i.e. mk-1mon;bas = mk-1bas),
where HB is a Hessian of a cost function of the FWI for the baseline dataset, HM is a Hessian of the cost function for the monitor dataset (See Page 44:
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γ is a probing gradient in a gradient space (See Page 45 and Page 48: Stepsize calculation is a key factor in ensuring inversion efficiency and accuracy.
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Willemsen wherein, for reflecting the similarities and/or differences of the geometrical features of the baseline and monitor acquisition surveys, the baseline and monitor preconditioners satisfy P′BHBγ=P′MHMγ, where HB is a Hessian of a cost function of the FWI for the baseline dataset, HM is a Hessian of the cost function for the monitor dataset, and γ is a probing gradient in a gradient space such as that of Fu. One of ordinary skill would have been motivated to modify Willemsen, because setting P′BHBγ=P′MHMγ, would have helped to eliminate the implicit baseline model from the inverted monitor model, as recognized by Fu.
Regarding Claims 3 and 13. Williamsen teaches:
The method of claim 2 or The device of claim 12,
wherein the cost function includes a first term that depends on a baseline model mB for the baseline dataset, a second term that depends on a monitor model mM for the monitor dataset, and a third term that depends on both the baseline and monitor models (See Page 5385 Col. 1:
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Regarding Claims 4 and 14. Williamsen teaches:
The method of claim 3,
wherein the baseline model and the monitor models are velocity models, density models or models of any other physical property of the subsurface associated with wave propagation (See Page 5384 Col. 1: A method for recovering time-lapse velocity changes using full waveform inversion (FWI). Invert for subsurface material properties such as seismic velocity and density.).
Regarding Claims 5 and 15. Willemsen is silent as to the language of:
The method of claim 1 or The device of claim 11
wherein the step of computing comprises:
computing the probing gradient.
Nevertheless Fu teaches:
computing the probing gradient (See Page 45 and Page 48: Stepsize calculation is a key factor in ensuring inversion efficiency and accuracy.
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Willemsen by computing the probing gradient such as that of Fu. One of ordinary skill would have been motivated to modify Willemsen, because calculating a probing gradient would have helped to ensure inversion efficiency and accuracy, as recognized by Fu.
Regarding Claims 6 and 16. Williamsen is silent as to the language of:
The method of claim 5 or The device of claim 15,
further comprising:
computing a traditional baseline preconditioner and a traditional monitor preconditioner;
computing the baseline preconditioner P′B based on the traditional baseline preconditioner, the traditional monitor preconditioner, and the probing gradient; and
computing the monitor preconditioner P′M based on the traditional monitor preconditioner, the traditional baseline preconditioner, and the probing gradient.
Nevertheless Fu teaches:
computing a traditional baseline preconditioner and a traditional monitor preconditioner See Page 45, Page 59, Page 75: As for the difference in wavelets, we believe the impact is also limited since the gradient is preconditioned by the diagonal approximation of the Hessian matrix, in which the wavelet effect can be eliminated.
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computing the baseline preconditioner P′B based on the traditional baseline preconditioner, the traditional monitor preconditioner, and the probing gradient See Page 45, Page 59, Page 75: As for the difference in wavelets, we believe the impact is also limited since the gradient is preconditioned by the diagonal approximation of the Hessian matrix, in which the wavelet effect can be eliminated.
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computing the monitor preconditioner P′M based on the traditional monitor preconditioner, the traditional baseline preconditioner, and the probing gradient (See Page 45, Page 59, Page 75: As for the difference in wavelets, we believe the impact is also limited since the gradient is preconditioned by the diagonal approximation of the Hessian matrix, in which the wavelet effect can be eliminated.
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Willemsen by computing a traditional baseline preconditioner and a traditional monitor preconditioner; computing the baseline preconditioner P′B based on the traditional baseline preconditioner, the traditional monitor preconditioner, and the probing gradient; and computing the monitor preconditioner P′M based on the traditional monitor preconditioner, the traditional baseline preconditioner, and the probing gradient such as that of Fu. One of ordinary skill would have been motivated to modify Willemsen, because preconditioning the baseline dataset and monitor dataset would have helped to eliminate differences in wavelets, as recognized by Fu.
Regarding Claims 9 and 18. Williamsen is silent as to the language of:
The method of claim 1 or The device of claim 11,
further comprising:
calculating a baseline model improvement ΔmB of a baseline model mB by applying the baseline preconditioner P′B to the baseline gradient of the cost function of the FWI; and
calculating a monitor model improvement ΔmM of a monitor model mM by applying the monitor preconditioner P′M to the monitor gradient of the cost function.
Nevertheless Fu teaches:
calculating a baseline model improvement ΔmB of a baseline model mB by applying the baseline preconditioner P′B to the baseline gradient of the cost function of the FWI (See Page 45, Page 59, Page 75: As for the difference in wavelets, we believe the impact is also limited since the gradient is preconditioned by the diagonal approximation of the Hessian matrix, in which the wavelet effect can be eliminated.
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calculating a monitor model improvement ΔmM of a monitor model mM by applying the monitor preconditioner P′M to the monitor gradient of the cost function (See Page 45, Page 59, Page 75: As for the difference in wavelets, we believe the impact is also limited since the gradient is preconditioned by the diagonal approximation of the Hessian matrix, in which the wavelet effect can be eliminated.
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Willemsen by calculating a baseline model improvement ΔmB of a baseline model mB by applying the baseline preconditioner P′B to the baseline gradient of the cost function of the FWI; and calculating a monitor model improvement ΔmM of a monitor model mM by applying the monitor preconditioner P′M to the monitor gradient of the cost function such as that of Fu. One of ordinary skill would have been motivated to modify Willemsen, because calculating a model update using a preconditioner and a gradient would have helped to eliminate differences in wavelets, as recognized by Fu.
Regarding Claims 10 and 19. Williamsen teaches:
The method of claim 9 or The device of claim 18,
further comprising:
generating an image of the physical properties based on a difference between the updated baseline model and the updated monitor model after a convergence criteria is met, wherein the physical properties includes at least one of a velocity or density (See Fig. 2 and Page 5385 Col. 1: the following objective function X is minimized for the baseline model m0 and the monitor model m1,
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Williamsen is silent as to the language of:
adding the baseline model improvement to the baseline model to obtain an updated baseline model;
adding the monitor model improvement to the monitor model to obtain an updated monitor model.
Nevertheless Fu teaches:
adding the baseline model improvement to the baseline model to obtain an updated baseline model (See Page 45, Page 59, Page 75:
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adding the monitor model improvement to the monitor model to obtain an updated monitor model (See Page 45, Page 59, Page 75:
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Willemsen by adding the baseline model improvement to the baseline model to obtain an updated baseline model; adding the monitor model improvement to the monitor model to obtain an updated monitor model such as that of Fu. Fu teaches, “By comparing these synthetic waveforms with the recorded data, FWI seeks to update the subsurface model parameters, such as velocity or density, to minimize the misfit” (See Page 43). One of ordinary skill would have been motivated to modify Willemsen, because updating a model would have helped to minimize the misfit between the synthetic waveforms and recorded data, as recognized by Fu.
Claim(s) 7-8 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Willemsen et al. (Willemsen, B., and A. Malcolm. "Regularizing velocity differences in time-lapse FWI using gradient mismatch information: 85th Annual International Meeting, SEG, Expanded Abstracts, 5384–5388." 2015.) in view of Fu (Fu, Xin. Time-lapse seismic imaging, full-waveform inversion, and uncertainty quantification. Diss. University of Calgary (Canada), 2023.) as applied to claims 1 and 11 above, and further in view of Wang et al. (Wang, Ming, Shouting Huang, and Ping Wang. "Improved iterative least-squares migration using curvelet-domain Hessian filters." SEG International Exposition and Annual Meeting. SEG, 2017.).
Regarding Claim 7. Williamsen is silent as to the language of:
The method of claim 1,
wherein the baseline preconditioner P′B and the monitor preconditioner P′M are calculated in a filter space.
Nevertheless Wang teaches:
wherein the baseline preconditioner P′B and the monitor preconditioner P′M are calculated in a filter space (See Page 4556 Col. 2: We can use the CHF operator s defined in Equation 4 as a curvelet domain approximation of (LTL )-1. The preconditioned gradient can then be written as:
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Williamsen wherein the baseline preconditioner P′B and the monitor preconditioner P′M are calculated in a filter space such as that of Wang. Wang teaches, “we demonstrated that CHF-preconditioning can significantly speed up the convergence rate of iterative LSM and gives better amplitude fidelity with a smaller number of iterations than conventional iterative LSM” (See Page 4557 Col. 2). One of ordinary skill would have been motivated to modify Williamsen, because calculating a preconditioner using a filter space would have helped to speed up the convergence rate of an objective function, as recognized by Wang.
Regarding Claim 8. Williamsen is silent as to the language of:
The method of claim 7,
wherein the filter space is a curvelet space, or a Fourier space, or a wavelet space, and a baseline filter and a monitor filter are applied to calculate the baseline preconditioner P′B and the monitor preconditioner P′M, respectively.
Nevertheless Wang teaches:
wherein the filter space is a curvelet space, or a Fourier space, or a wavelet space, and a baseline filter and a monitor filter are applied to calculate the baseline preconditioner P′B and the monitor preconditioner P′M, respectively (See Page 4556 Col. 1: the matching filter between and can be found to approximate the inverse of the Hessian Matrix H-1 in the curvelet domain.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Williamsen wherein the filter space is a curvelet space, or a Fourier space, or a wavelet space, and a baseline filter and a monitor filter are applied to calculate the baseline preconditioner P′B and the monitor preconditioner P′M, respectively such as that of Wang. Wang teaches, “we demonstrated that CHF-preconditioning can significantly speed up the convergence rate of iterative LSM and gives better amplitude fidelity with a smaller number of iterations than conventional iterative LSM” (See Page 4557 Col. 2). One of ordinary skill would have been motivated to modify Williamsen, because calculating a preconditioner using a filter space would have helped to speed up the convergence rate of an objective function, as recognized by Wang.
Regarding Claim 17. Williamsen is silent as to the language of:
The device of claim 11,
wherein the baseline preconditioner P′B and the monitor preconditioner P′M are calculated in a filter space and the filter space is a curvelet space, or a Fourier space, or a wavelet space, and a baseline filter and a monitor filter are applied to calculate the baseline preconditioner P′B and the monitor preconditioner P′M, respectively.
Nevertheless
wherein the baseline preconditioner P′B and the monitor preconditioner P′M are calculated in a filter space (See Page 4556 Col. 2: We can use the CHF operator s defined in Equation 4 as a curvelet domain approximation of (LTL )-1. The preconditioned gradient can then be written as:
PNG
media_image8.png
22
396
media_image8.png
Greyscale
.) and
the filter space is a curvelet space, or a Fourier space, or a wavelet space, and a baseline filter and a monitor filter are applied to calculate the baseline preconditioner P′B and the monitor preconditioner P′M, respectively (See Page 4556 Col. 1: the matching filter between and can be found to approximate the inverse of the Hessian Matrix H-1 in the curvelet domain.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Williamsen wherein the baseline preconditioner P′B and the monitor preconditioner P′M are calculated in a filter space and the filter space is a curvelet space, or a Fourier space, or a wavelet space, and a baseline filter and a monitor filter are applied to calculate the baseline preconditioner P′B and the monitor preconditioner P′M, respectively such as that of Wang. Wang teaches, “we demonstrated that CHF-preconditioning can significantly speed up the convergence rate of iterative LSM and gives better amplitude fidelity with a smaller number of iterations than conventional iterative LSM” (See Page 4557 Col. 2). One of ordinary skill would have been motivated to modify Williamsen, because calculating a preconditioner using a filter space would have helped to speed up the convergence rate of an objective function, as recognized by Wang.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Virieux et al. (Virieux, Jean, and Stéphane Operto. "An overview of full-waveform inversion in exploration geophysics." (2010).) discloses multiple methods for performing full wave inversion on seismic data (See Abstract).
Raknes et al. (Raknes, Espen Birger, and Børge Arntsen. "A numerical study of 3D elastic time-lapse full-waveform inversion using multicomponent seismic data." Geophysics 80.6 (2015): R303-R315.) discloses inverting baseline and monitoring seismic data using full waveform inversion, inverse Hessian matrix, and step length (See Page R304).
Gerea et al. (Gerea, Constantin, Enrico Zamboni, and Bertrand Duquet. "HPC-Driven Seismic Processing and Time-Lapse 4D Monitoring." SPE Offshore Europe Conference and Exhibition. SPE, 2017.) discloses inverting baseline and monitoring seismic data using full waveform inversion, inverse Hessian matrix, and step length (See Page 3).
Alemie et al. (Alemie, W., and M. Sacchi. "Joint reparametrized time-lapse full-waveform inversion: 86th Annual International Meeting, SEG, Expanded Abstracts, 1309–1314." 2016.) discloses inverting baseline and monitoring seismic data using full waveform inversion, inverse Hessian matrix, and step length (See Page 1310).
Xue et al. (US 20220308246 A1) discloses inverting baseline and monitoring seismic data using full waveform inversion, inverse Hessian matrix, and step length (See para[0040]).
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/CARTER W FERRELL/ Examiner, Art Unit 2857
/YOSSEF KORANG-BEHESHTI/ Primary Examiner, Art Unit 2857
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