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 . The rejections from the Office Action of 5/23/2025 are hereby withdrawn. New grounds for rejection are presented below.
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 1-4, 7-9, 12, 13, 16, 17 and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the abstract idea of a mathematical algorithm for updating subsurface models to produce a subsurface image for determining the presence of hydrocarbons.
This judicial exception is not integrated into a practical application because the generation of the subsurface image using the updated model data amounts to merely displaying the results of the algorithm results. The model updating and image production are not used to improve the underlying context of hydrocarbon production. Determining the presence of hydrocarbons is an extension of the abstract idea and does not result in any specific improvement to any real-world process.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the recited simulator and computer processor amount to the recitation of general-purpose computer components for implementing the abstract idea (see Alice Corp. v. CLS Bank International, 573 U.S. 208 (2014)). The obtaining of the data needed for implementing the algorithm must necessarily be performed and the recited structure for obtaining the needed data is through use of well-understood, routine, and conventional measurement devices (see the application of the corresponding prior art references regarding those limitations, below).
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) 1-4, 7, 12-13, 16, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sun et al. (US 20200301035 A1)[hereinafter “Sun”]; Colombo et al. (US 20210264262 A1)[hereinafter “Columbo II”]; Dransfield et al., Performance of airborne gravity gradiometers, The Leading Edge, 2013 [hereinafter “Dransfield”]; Colombo et al. (US 20100014384 A1)[hereinafter “Columbo”]; and Crawley et al. (US 20170168178 A1)[hereinafter “Crawley”].
Regarding Claims 1 and 12, Sun discloses a method (and corresponding system including a reservoir simulator comprising a computer processor)[Paragraph [0017] – “This disclosure generally describes methods and systems, including computer-implemented methods, computer program products, and computer systems, for generating a velocity model and a density model.”], comprising:
obtaining acquired seismic data for a geological region of interest, wherein the acquired seismic data is acquired using a seismic surveying system comprising a plurality of seismic receivers and a seismic source [Paragraph [0017] – “The velocity and density models are generated based on seismic data.”Paragraph [0017] – “In some cases, seismic signals can be transmitted into the subsurface of the earth at a source location by a source device. Examples of the seismic signals include acoustic signals. The seismic signals travel through the subsurface and can be received by a receiver device placed at a receiver location.”Paragraph [0017] – “The signals can propagate downwards until they reach a reflecting structure and reflect upwards towards the surface. Because the signals have refracted and reflected through the substructure, the characteristics of the received signals contain information of the substructure.”];
determining, by a computer processor [Paragraph [0017]], synthetic seismic data using a slowness model and a reflectivity model [Paragraph [0033] – “The simulated data, denoted as D.sub.q, is obtained based on a set of given model, including a velocity model and a density model.”The velocity model can be considered a slowness model in light of Paragraph [0067] of the instant Specification – “slowness may be the reciprocal of velocity.”The density model can be considered a reflectivity model per Paragraphs [0034]-[0035].];
determining, by the computer processor [Paragraph [0017]], a plurality of slowness gradients for the slowness model [Paragraph [0029] – “The gradients of velocity and density discussed previously are obtained from wavefields propagating in more than one direction. For example, in a 3D space having X, Y, and Z spatial directions, the wavefield separation in equations (5) to (9) can be performed for X, Y, and Z direction separately. Therefore, the velocity gradient and reflectivity gradient for each of these directions can be obtained.”Paragraph [0030] – “At 202, the velocity gradient is calculated using equation (12). The velocity gradient is then normalized within the range [−1, 1]. The normalized velocity gradient is denoted at ngv.”] based on the synthetic seismic data [Paragraph [0033] – “simulated data”], the acquired seismic data [Paragraph [0033] – “measured data, denoted as D, represents the signals received at the receiver devices”], and an objective function [Paragraph [0032], iteratively determined “dv*ngv”], wherein the objective function comprises an objective function that uses a first data misfit between the acquired seismic data and the synthetic seismic data [Paragraph [0032] – “At 210, the normalized velocity gradient (denoted as ngv), is used to update the velocity model for the subsurface layer above the interface 120 (ξ=ξ.sub.m), for example, the subsurface layer between the interface 110 (ξ=ξ.sub.m−1) and the interface 120 (ξ=ξ.sub.m). In the illustrated example, an adaptive step length search process is used. At 212, an initial velocity update step dv is set to dv.sub.0. At 214, whether the velocity update step can decrease the surface data residual is determined. A new velocity model υ.sub.updated is generated based on the current velocity model υ.sub.current by using the following equation:υ.sub.updated=υ.sub.current+dv*ngv”Paragraph [0033] – “The surface data residual, denoted as D.sub.s, represents the difference between the measured data and the simulated data. The measured data, denoted as D, represents the signals received at the receiver devices. The simulated data, denoted as D.sub.q, is obtained based on a set of given model, including a velocity model and a density model. Accordingly, D.sub.s=D−D.sub.q. The surface data residual that is calculated using the new velocity model υ.sub.updated is compared with the surface data residual that is calculated using the current velocity model υ.sub.current. If the surface data residual obtained based on the new velocity model is the same as or is greater than the surface data residual obtained based on the previous velocity model, the search process proceeds to 216, where dv is adjusted by using a line search scheme.”];
updating, by the computer processor [Paragraph [0017]], the slowness model using the plurality of slowness gradients to produce an updated slowness model [Paragraph [0033] – “The search process continues to 214 where the adjusted dv is used to determine whether the new velocity model obtained based on the adjusted dv would decrease the surface data residual. The search process continues until a dv value is found to make the new velocity model decrease the surface data residual. At 218, the updated velocity model is obtained using the found dv value.”]; and
generating, by the computer processor [Paragraph [0017]] and based on the updated slowness model and the reflectivity model, a subsurface image of the geological region of interest [Paragraph [0043] – “The velocity and density models obtained according to the process discussed in this disclosure provide accurate characteristics of the subsurface structures. Thus, they can be used to improve the imaging resolution of subsurface structures. In seismic exploration, these improved quality subsurface images can provide a better understanding of the subsurface structure.”].
Sun fails to disclose acquiring, using an electromagnetic surveying system with transient electromagnetic (TEM) sensing, electromagnetic data for the geological region of interest.
However, Colombo II discloses that such data can be gathered in such a manner [Paragraph [0103] – “The dense spatial sampling of helicopter-borne TEM methods (one of the several implementations of airborne TEM measurements) provides an accurate description of the near-surface in terms of resistivity that is then mapped to seismic velocity for near-surface corrections by the discussed process of joint inversion.”]. It would have been obvious to gather the electromagnetic data in such a manner because Colombo II discloses that this is a viable option for doing so.
Sun fails to disclose acquiring, using a gravity surveying system, gravity data for the geological region of interest, wherein the gravity surveying system comprises an aircraft device and a plurality of gravity gradiometers that generate the gravity data.
However, Dransfield discloses the use of such an aircraft and plurality of gravity gradiometers for performing exploration [Page 908, first column – “Airborne gravity gradiometry (AGG) is becoming a widely accepted tool in exploration. It provides rapid acquisition of accurate gravity data at high spatial resolution with complete coverage over large areas.”Page 908-909 – “All currently operating gravity gradiometers are of the rotating wheel type and consist of one or more gravity gradiometer instruments (GGI), each mounted on a rotating wheel and all contained within rotationally stabilized gimbals. The FALCON AGG has a single doublecomplement GGI with a large wheel diameter rotating about a near-vertical axis. FTGs have three single-complement GGIs with a small wheel diameter rotating about three orthogonal axes, each at about 55$ from the vertical.”]. It would have been obvious to gather gravity data in such a manner because Dransfield discloses this as an effective manner for doing so.
Sun fails to disclose determining, by the computer processor, an electrical resistivity model for the geological region of interest using the electromagnetic data;
determining, by the computer processor, a density model for the geological region of interest using the gravity data; and
the use of a plurality of objections functions, wherein the plurality of objective functions comprises a second objective function that uses a second data misfit between the slowness model, the electrical resistivity model, and the density model.
However, Colombo discloses a velocity model updating process [Paragraph [0001] – “The present invention refers to a method for building velocity models for Pre-Stack Depth Migration (PSDM) via the simultaneous Joint Inversion (JI) of seismic, gravity and magnetotelluric data.”] that relies on an objective function for minimizing mismatch between multiple parameters during simultaneous joint inversion [See Fig. 7 and Paragraphs [0149]-[0152] and [0157]-[0162]. The velocity model can be considered a slowness model in light of Paragraph [0067] of the instant Specification – “slowness may be the reciprocal of velocity.”]. Colombo discloses the use of electromagnetic data and gravity data [See Fig. 7 and Paragraph [0149] – “gravity forward output and constraints parameters 87, magnetotelluric forward output and constraints parameters 88”] in updating models for electrical resistivity, density, and slowness [Paragraph [0155] – “The output of the Joint Inversion is a multiparametric model (step 91), or in other words represents the distribution of cross-correlated seismic velocity (V.sub.p), density (.delta.) and resistivity (.rho.).”] using a rock-physics constraint that provides an objective function based on a misfit between the slowness model, the electrical resistivity model, and the density model [Paragraph [0156] – “The Joint Inversion model results are evaluated for quality requirements and geological reliability (step 92) and, if they are not optimal, they can be subject to other iterations where the chosen Joint Inversion parameters are modified (step 84).”Paragraph [0029] – “The external constraints that can be applied for the inverse problem consist of the knowledge of geophysical parameter distributions within the model (e.g. from well logs) and the interpretative knowledge about the patterns and shapes of geologic bodies (i.e. geologic interpretation).”].
It would have been obvious to perform such a simultaneous joint inversion in order to produce a multi-parametric model. It would have been obvious to include the model updating of Sun into such a procedure in order to make the multi-parametric model more accurate.
Sun fails to explicitly disclose determining, by the computer processor, a presence of hydrocarbons in the geological region of interest using the subsurface image. However, Crawley discloses that a velocity model can be used to indicate the presence of hydrocarbons [Paragraph [0026] – “FWI can produce a higher resolution velocity model, which may be useful to determine a property of a subsurface, such as the presence of a reservoir that may contain hydrocarbons.”]. It would have been obvious to use the velocity model to indicate the presence of hydrocarbons in the image because doing so would have been helpful in the determination of how to use the analysis results.
Regarding Claims 2 and 13, Sun discloses determining a plurality of pressure wavefields [Paragraphs [0036]-[0037] – “for the subsurface layer beneath the interface 120 (ξ=ξ.sub.m), for example, the subsurface layer between the interface 120 (ξ=ξ.sub.m) and the interface 130 (ξ=ξ.sub.m+1)[.]” This is a different layer area from previously.] using the updated slowness model and the reflectivity model; determining a plurality of reflectivity gradients for the reflectivity model based on the plurality of pressure wavefields and the acquired seismic data; and updating the reflectivity model using the plurality of reflectivity gradients to produce an updated reflectivity model [Paragraph [0036] – “At 230, the normalized velocity gradient is used to update the velocity model for the next iteration of the inversion. The next iteration of the inversion can be performed for the subsurface layer beneath the interface 120 (ξ=ξ.sub.m), for example, the subsurface layer between the interface 120 (ξ=ξ.sub.m) and the interface 130 (ξ=ξ.sub.m+1). The same adaptive step search algorithm used in the step 210 can be used here.”Paragraph [0037] – “At 240, the normalized reflectivity gradient is used to update the density model for the next iteration of the inversion. The next iteration of the inversion can be performed for the subsurface layer beneath the interface 120 (ξ=ξ.sub.m), for example, the subsurface layer between the interface 120 (ξ=ξ.sub.m) and the interface 130 (ξ=ξ.sub.m+1). The same adaptive step search algorithm used in the step 220 can be used here.”].
Regarding Claim 3, Sun discloses that the slowness model [Fig. 2, step 210 and 216] and the reflectivity model [Fig. 2, step 220 and 226] are alternately updated in an iterative process until the slowness model converges to a minimum [Paragraph [0038] – “The steps in the process 200 can be repeated for multiple iterations to update the solution space.”].
Regarding Claim 4, Sun discloses that the synthetic seismic data [Paragraph [0023] – “The forward-going outgoing wavefields Q.sup.+(ξ.sub.m) and the backward-going outgoing wavefield Q.sup.−(ξ.sub.m) can be generated using the wavefield propagation simulation by using the two-way wave equations followed by wavefield separation techniques.”] comprises a plurality of upgoing pressure wavefields [See Fig. 1 and Paragraph [0023] – P.sup.−(ξ.sub.m-1) and Q.sup.-(ξ.sub.m))] and a plurality of downgoing pressure wavefields [See Fig. 1 and Paragraph [0023] – “the forward-going incoming wavefield P.sup.+(ξ.sub.m)” and Q.sup.+(ξ.sub.m-1)], and wherein the synthetic seismic data are determined using a forward modeling function [Paragraph [0023] – “W(ξ.sub.m, ξ.sub.m−1) represents the forward propagation matrix constructed from the one-way wave equation between the interfaces 120 and 110, and (ξ.sub.m, ξ.sub.m+1) represents the forward propagation matrix constructed from the one-way wave equation between the interfaces 120 and 130.”].
Regarding Claims 7 and 16, Sun fails to disclose that the electromagnetic data is acquired using a helicopter transient electromagnetic survey, and wherein the second objective function uses a structural constraint based on a cross-gradient function that is performed between the slowness model and the electrical resistivity model.
However, Colombo discloses obtaining an electrical resistivity model for a geological region of interest [Paragraph [0120] – “Similarly to the preparation of the gravity data portion 2 of the Joint Inversion, the preparation of the MT data 3 for the Joint Inversion involves the calculation of the forward parameters and of the residuals (step 62) using as input the apparent resistivity and phase curves obtained from a pre-processing of the observed electromagnetic (EM) field data (step 63) and an initial resistivity model (step 64).”] using a portion of first geophysical data, wherein the portion of the first geophysical data comprises electromagnetic data this is acquired using an electromagnetic survey [Paragraph [0041] – “The workflow starts from the seismic pre-migrated domain (pre-migration process) where the input data are the first arrival times 1 (known as First Breaks--FB) for the seismic portion, gravity data 2 in the form of the Bouguer anomaly and magnetotelluric (MT) data 3 for the electromagnetic (EM) portion.”], and wherein a first geophysical constraint is a structural constraint based on a cross-gradient function that is performed between a slowness model and an electrical resistivity model [Paragraphs [0152]-[0154]. Paragraph [0153] – “m.sub.1 and m.sub.2 are two models (e.g. velocity and density, velocity and resistivity, and resistivity and gravity).” The velocity model can be considered a slowness model in light of Paragraph [0067] of the instant Specification – “slowness may be the reciprocal of velocity.”].
It would have been obvious to perform such a simultaneous joint inversion in order to produce a multi-parametric model. It would have been obvious to include the model updating of Sun into such a procedure in order to make the multi-parametric model more accurate.
Colombo fails to disclose that the electromagnetic data is from a helicopter transient electromagnetic survey. However, Colombo II discloses that such data can be gathered in such a manner [Paragraph [0103] – “The dense spatial sampling of helicopter-borne TEM methods (one of the several implementations of airborne TEM measurements) provides an accurate description of the near-surface in terms of resistivity that is then mapped to seismic velocity for near-surface corrections by the discussed process of joint inversion.”]. It would have been obvious to gather the electromagnetic data in such a manner because Colombo II discloses that this is a viable option for doing so.
Regarding Claim 20, Sun fails to disclose that the electromagnetic surveying system comprises a second aircraft device and a plurality of electromagnetic sensors, and wherein the electromagnetic surveying system is coupled to the reservoir simulator.
However, Colombo discloses obtaining an electrical resistivity data [Paragraph [0041] – “The workflow starts from the seismic pre-migrated domain (pre-migration process) where the input data are the first arrival times 1 (known as First Breaks--FB) for the seismic portion, gravity data 2 in the form of the Bouguer anomaly and magnetotelluric (MT) data 3 for the electromagnetic (EM) portion.”] in performing joint inversion to produce an updated multi-parameter model [Paragraph [0120] – “Similarly to the preparation of the gravity data portion 2 of the Joint Inversion, the preparation of the MT data 3 for the Joint Inversion involves the calculation of the forward parameters and of the residuals (step 62) using as input the apparent resistivity and phase curves obtained from a pre-processing of the observed electromagnetic (EM) field data (step 63) and an initial resistivity model (step 64).”]
It would have been obvious to perform such a simultaneous joint inversion in order to produce a multi-parametric model. It would have been obvious to include the model updating of Sun into such a procedure in order to make the multi-parametric model more accurate.
Colombo fails to disclose that the electromagnetic data is from an electromagnetic surveying system comprising an aircraft device and a plurality of electromagnetic sensors. However, Colombo II discloses that such data can be gathered in such a manner [Paragraph [0103] – “The dense spatial sampling of helicopter-borne TEM methods (one of the several implementations of airborne TEM measurements) provides an accurate description of the near-surface in terms of resistivity that is then mapped to seismic velocity for near-surface corrections by the discussed process of joint inversion.”Paragraph [0104] – “The existence and propagation of such induced Eddy currents are related to the conductivity (or resistivity, which is the inverse of conductivity) of the ground, with more conductive rocks allowing a longer time for Eddy current dissipation, and more resistive rocks causing the rapid decay of the Eddy currents. Such a time variation of Eddy currents causes a corresponding (secondary) time-varying magnetic field (dBz/dt) (per Ampere's law). Such secondary field is what is measured by the receiving loop 144, 154 on the helicopter 132.” The receiving loop considered a plurality of sensing elements for detecting the applied field.]. It would have been obvious to gather the electromagnetic in such a manner because Colombo II discloses that this is a viable option for doing so.
Claim(s) 8 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sun et al. (US 20200301035 A1)[hereinafter “Sun”]; Colombo et al. (US 20210264262 A1)[hereinafter “Columbo II”]; Dransfield et al., Performance of airborne gravity gradiometers, The Leading Edge, 2013 [hereinafter “Dransfield”]; Colombo et al. (US 20100014384 A1)[hereinafter “Columbo”]; Crawley et al. (US 20170168178 A1)[hereinafter “Crawley”]; and Keating et al., A tunneling approach for clustered priors in full waveform inversion, Society of Exploration Geophysicists, 2021 [hereinafter “Keating”].
Regarding Claims 8 and 17, Sun fails to disclose obtaining a geophysical constraint, wherein the geophysical constraint is a clustering constraint; determining a plurality of geological objects based on geophysical data for the geological region of interest; determining a plurality of clusters in the geological region of interest based on a statistical analysis of the plurality of geological objects; and determining whether the slowness model satisfies the clustering constraint based on the plurality of clusters, wherein the slowness model is updated in response to the slowness model failing to satisfy the clustering constraint.
However, Keating discloses the use of a statistical analysis to determine clusters of subsurface objects and the comparison of derived slowness (i.e., velocity) models in the evaluation of whether the models are accurate or not [See Fig. 2 and Page 679, first column – “In this example, we consider a situation in which prior geologic information suggests significant probabilities of only four potential rock types. Further, we assume that the available prior information suggests vP and ρ are normally distributed for these rock types, and that the mean and standard deviations are known for each. These distributions are shown by the gray regions in Figure 2, with the dark gray region representing the part of vP −ρ space within one standard deviation of a cluster mean, and the light grey region representing the part of vP −ρ space within two standard deviations of a mean. Also represented in Figure 2 are the locations of the true layer properties in vP −ρ space; notably all are approximately consistent with the prior information. … The corresponding distribution of model elements in vp − ρ space for the different inversion results is shown in Figure 2.”]. It would have been obvious to determine the presence of clusters and to use their presence as a constraint in optimizing the velocity model in order to create a more accurate velocity model.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sun et al. (US 20200301035 A1)[hereinafter “Sun”]; Colombo et al. (US 20210264262 A1)[hereinafter “Columbo II”]; Dransfield et al., Performance of airborne gravity gradiometers, The Leading Edge, 2013 [hereinafter “Dransfield”]; Colombo et al. (US 20100014384 A1)[hereinafter “Columbo”]; Crawley et al. (US 20170168178 A1)[hereinafter “Crawley”]; and Mehouachi et al. (US 11551416 B1)[hereinafter “Mehouachi”].
Regarding Claim 9, Sun fails to disclose that the plurality of slowness gradients are determined based on a gradient descent method. However, Mehouachi discloses updating a velocity model using a gradient descent method [Column 16 lines 54-56 – “The Gradient Descent is a fundamental and relatively old inversion method, and simply updates the velocity model with the gradient of the objective function.”]. It would have been obvious to updating the velocity model using a gradient descent method because Mehouachi discloses that the gradient descent method is an effective manner in doing so.
Response to Arguments
Applicant argues:
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Examiner’s Response:
The Examiner respectfully disagrees. Gathering data needed for implementing a mathematical algorithm does not serve to amount to a particular practical application of the mathematical algorithm as the necessary data must be gathered.
Applicant argues:
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232
886
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382
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681
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342
890
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Examiner’s Response:
The Examiner respectfully disagrees. The instant Claims merely recite gathering data for a mathematical algorithm, the performance of the mathematical algorithm, and the generation/display of the algorithm results and a resulting subsurface image.
Applicant argues:
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136
895
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737
894
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Examiner’s Response:
The Examiner respectfully disagrees. "A claim for a new abstract idea is still an abstract idea. The search for a § 101 inventive concept is thus distinct from demonstrating § 102 novelty." Synopsys, Inc. v. Mentor Graphics Corporation, 839 F.3d 1138, 1151 (Fed. Cir. 2016).
Applicant argues:
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280
889
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82
890
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Examiner’s Response:
The Examiner respectfully disagrees. The instant Claims merely recite gathering data for a mathematical algorithm, the performance of the mathematical algorithm, and the generation/display of the algorithm results and a resulting subsurface image.
Applicant argues:
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232
889
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Examiner’s Response:
The Examiner agrees. New grounds for rejection are presented above.
Applicant argues:
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Examiner’s Response:
The Examiner respectfully disagrees. See the new grounds for rejection presented above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Christensen et al., Airborne Gravity Gradiometry for Rapid Mapping of Hydrocarbon Exploration Plays, IPTC, 2014
Choi et al., Waveform inversion of lateral velocity variation from wavefield source location perturbation, SEG, 2013
Igonin et al., Analysis of simultaneous velocity and source parameter updates in microseismic FWI, SEG, 2018
Liu et al., First arrival tomography using depth-varying velocity gradients, SEG, 2009
US 20190302293 A1 – Methods Using Travel-time Full Waveform Inversion For Imaging Subsurface Formations With Salt Bodies
US 20180045839 A1 – Tomographically Enhanced Full Wavefield Inversion
US 20180120464 A1 – Seismic Waveform Inversion
US 20180164453 A1 – Method For Improved Geophysical Investigation
US 20180196154 A1 – REFLECTION FULL WAVEFORM INVERSION METHODS WITH DENSITY AND VELOCITY MODELS UPDATED SEPARATELY
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KYLE ROBERT QUIGLEY whose telephone number is (313)446-4879. The examiner can normally be reached 11AM-9PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Arleen Vazquez can be reached at (571) 272-2619. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KYLE R QUIGLEY/Primary Examiner, Art Unit 2857