DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined
under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
Under Step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance, the claims are directed to a process (claim 1, a method) or a manufacture (claim 11, a non-transitory computer-readable medium) or a machine (claim 16, system), which are statutory categories.
However, evaluating claim 1, under Step 2A, Prong One, the claim is
directed to the judicial exception of an abstract idea using the grouping of a mathematical relationship/mental process. The limitations include:
determining, based on the obtained one or more seismic attributes, a plurality of prior velocity maps of the hydrocarbon reservoir; determining, based on the plurality of prior velocity maps, a plurality of velocities; determining, based on the plurality of velocities, a plurality of depth map realizations; determining, based on the plurality of depth map realizations, a plurality of gross volumetric uncertainties of the hydrocarbon reservoir; and providing the plurality of gross volumetric uncertainties for hydrocarbon exploration of the hydrocarbon reservoir.
Next, Step 2A, Prong Two evaluates whether additional elements of the claim “integrate the abstract idea into a practical application” in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. The claim does not recite additional elements that integrate the judicial exception into a practical application.
This judicial exception is not integrated into a practical application because the remaining elements amount to no more than general purpose computer components programmed to perform the abstract ideas. As set forth in the 2019 Eligibility Guidance, 84 Fed. Reg. at 55 “merely include[ing] instructions to implement an abstract idea on a computer” is an example of when an abstract idea has not been integrated into a practical application.
The claim does not recite any particular seismic acquisition hardware. Rather, the results are used only for hydrocarbon exploration decisions, which is an intended use and extra-solution activity that dies not impose a meaningful limit on the abstract idea (see MPEP § 2106.05 (g)).
Therefore, the claims are directed to an abstract idea.
At Step 2B, consideration is given to additional elements that may make the abstract idea significantly more. Under Step 2B, there are no additional elements that make the claim significantly more than the abstract idea.
The additional element of “obtaining one or more seismic attributes at a plurality of wellbores of a hydrocarbon reservoir” is considered insignificant extra-solution activity of collecting data that is not sufficient to integrate the claim into a particular practical application. The act of data gathering is considered insufficient to elevate the claim to a practical application.
The claim is implemented on a generic computer and does not include a specific algorithm improvement, unconventional data structure, or specialized processing technique that improves computer functionality or seismic technology itself. These steps recite result-oriented functional language (e.g., “determining”, “providing”) without specifying how the results are achieved in a non-conventional manner. As such, the additional elements amount to no more than well-understood, routine, and conventional computer implementation of mathematical modeling and analysis.
Accordingly, the claim is directed to an abstract idea and does not include “significantly more”, and is therefore not patent-eligible under 35 U.S.C § 101.
Dependent claims 2-10 do not add anything which would render the claimed invention a patent eligible application of the abstract idea. The claims merely extend (or narrow) the abstract idea which do not amount for "significant more" because they merely add details to the algorithm which forms the abstract idea as discussed above.
Claims 11 and 16 are rejected 35 USC § 101 for the same rationale as in
claim 1.
Dependent claims 12-15 and 17-29, either dependent from 11 or 16, do not add anything which would render the claimed invention a patent eligible application of the abstract idea. The claims merely extend (or narrow) the abstract idea which do not amount for "significant more" because they merely add details to the algorithm which forms the abstract idea as discussed above.
Examiner reminds to the Applicant that during patent examination, the pending
claims must be given the broadest reasonable interpretation consistent with the specification. Under a broadest reasonable interpretation (BRI), words of the claim must be given their plain meaning, unless such meaning is inconsistent with the specification. The plain meaning of a term means the ordinary and customary meaning given to the term by those of ordinary skill in the art at the relevant time. See MPEP 2111.01. Moreover, although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
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.
Claims 1-3, 5-7, 10-14, and 16-19 are rejected under 35 U.S.C. 103 as being
unpatentable over Buland (Pub. No. US 2013/0054212) in view of Haase et al. (Pub. No. US 2009/0164186) (hereinafter Haase).
As per claims 1, 3, 11, 13, 16 and 18, Buland teaches obtaining one or more seismic attributes (i.e., seismic amplitude events) at a plurality of wellbores of a hydrocarbon reservoir (see ¶¶ [0044] and [0090]); determining, based on the obtained one or more seismic attributes, a plurality of prior velocity maps of the hydrocarbon reservoir (see ¶¶ [0090]-[0092], i.e., “A prior model is also derived for the geological region 1. This model represents the best knowledge of a user of what the interval velocities should be, without knowledge of the sampled RMS velocity trend. Typically, this may take account of geological knowledge of the region and may include data regarding seismic or elastic rock properties from nearby wells or the like”; determining, based on the plurality of prior velocity maps, a plurality of velocities (see ¶ [0093]).
While Buland teaches evaluating reservoir structure and volumes and providing data for exploring hydrocarbon reservoirs (see ¶ [0157]), Buland, however, does not explicitly disclose determining, based on a plurality of depth map realizations, a plurality of gross volumetric uncertainties of a hydrocarbon reservoir, nor providing such a plurality of gross volumetric uncertainties for hydrocarbon exploration (emphasis underlined).
However, Haase teaches performing probabilistic seismic inversion using a Bayesian framework to generate ensembles of acceptable surface models (see Abstract; ¶¶ [0018]-[0020], [0042-[0045] and Fig. 12), wherein each realization yields a valid depth interpretation of reservoir horizons, and volumetric properties are computed across the ensemble to produce probabilistic volumetric estimates that quantify uncertainty and risk for hydrocarbon reservoirs (see ¶¶ [0054]-[0056]); the cited portions therefore describe probabilistic subsurface models, multiple realizations of subsurface geometry, and volumetric uncertainty calculations that inherently involve variations in horizon position and layer thickness and thus disclose multiple depth outcomes. It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify Buland’s teaching with the teaching of Haase because Haase teaches performing probabilistic Bayesian seismic inversion to generate ensembles of acceptable subsurface models and corresponding probability distributions of reservoir properties, including net sand thickness and related volumetric uncertainty used for hydrocarbon risk assessment and development decisions, thereby enabling the velocity-based depth maps produced by Buland to be extended in a predictable manner to a plurality of depth map realizations and associated gross volumetric uncertainty estimates for hydrocarbon exploration. Therefore, achieving more accurate reservoir characterization.
Regarding “a non-transitory computer-readable medium storing one or more instructions executable by a computer system” (claim 11) and “one or more computers; and one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions” (claim 16) (see Haase ¶ [0017]).
As per claims 2, 12 and 17, the combination of Buland and Haase teach the system as stated above. Haase further teaches that wherein the hydrocarbon exploration of the hydrocarbon reservoir comprises at least one of reservoir development, field appraisal, or well placement in the hydrocarbon reservoir (see ¶¶ [0002] and [0047], i.e., “appraisal of oil or gas fields”).
As per claim 5, the combination of Buland and Haase teach the system as stated
Above. Buland further teaches that the one or more seismic attributes comprise a plurality of seismic stacking velocities of the hydrocarbon reservoir, and determining the plurality of prior velocity maps of the hydrocarbon reservoir comprises determining, based on the plurality of seismic stacking velocities, the plurality of prior velocity maps (see ¶¶ [0090]-[0094], i.e., “seismic data processors selecting a stacking velocity. Each RMS velocity sample has a standard deviation associated with it, which may be derived when an RMS velocity is estimated from the seismic data” and “A prior model is also derived for the geological region … include data regarding seismic or elastic rock properties from nearby wells or the like”).
As per claim 6, the combination of Buland and Haase teach the system as stated
above. Buland further teaches obtaining a plurality of interpreted seismic two-way time horizons of the hydrocarbon reservoir; and determining the plurality of prior velocity maps comprises determining, based on the plurality of interpreted seismic two-way time horizons and the obtained one or more seismic attributes, the plurality of prior velocity maps (see (see ¶¶ [0090]-[0094], i.e., “The RMS velocity data typically comprises RMS velocities at several TWT points defining various intervals or subsurface layers 5. The TWT represents the travel time of a seismic pulse”).
As per claims 7, 14 and 19, the combination of Buland and Haase teach the
system as stated above. Buland further teaches obtaining a plurality of depth geological markers at the plurality of wellbores of the hydrocarbon reservoir; and determining the plurality of prior velocity maps comprises determining, based on the plurality of depth geological markers and the obtained one or more seismic attributes, the plurality of prior velocity maps (see ¶¶ [0090]-[0091], i.e., determining prior velocity models by deriving seismic velocities from seismic reflection data, ¶ [0092], i.e., constraining those velocities using well-derived geological information as prior knowledge, and ¶¶ [0122]-[0124], [0149], i.e., followed by spatial prediction and mapping of interval velocities onto subsurface grids to form velocity maps or models). Although, Buland does not explicitly use the term “depth geological markers” , the well-derived depth-constrained information used to condition the velocity inversion in Buland reasonably corresponds, under broadest reasonable interpretation, to geological markers associated with known depths at wellbores that are used to constrain velocity estimation.
As per claim 10, the combination of Buland and Haase teach the system as stated
above.
While Buland teaches that seismic-derived RMS/stacking velocities are obtained from seismic data and used as velocity information for subsurface modeling (see ¶¶ [0090]-[0091]). Buland further teaches deriving interval velocities from such RMS velocities using Bayesian/Dix inversion techniques (see ¶¶ [0093]-[0094] and [0024]-[0033]) and spatially predicting and mapping those interval velocities onto grids to form velocity models or velocity maps of the subsurface (¶¶ [0122]-[0124] and [0149]). Under the broadest reasonable interpretation, these disclosures teach prior average velocity maps (e.g., RMS/stacking velocity maps) and prior interval velocity maps, as recited.
Accordingly, It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to configure the prior velocity maps of the method to comprise one of prior interval velocity maps or prior average velocity maps, as such velocity representations are explicitly disclosed alternatives in Buland and represent routine, interchangeable velocity models used in seismic interpretation and depth conversion workflows, because RMS/average velocities and interval velocities are both standard forms of prior velocity information derived from seismic data, thereby enabling predictable and conventional construction of velocity maps suitable for subsurface characterization and hydrocarbon exploration.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Buland in
view of Haase and further in view of Alkhalaf (Pub. No. US 2022/0073809).
As per claim 4, the combination of Buland and Haase teach the system as stated
above except that determining the plurality of velocities comprises: determining, based on the plurality of prior velocity maps, a plurality of variogram estimates and determining, based on the plurality of variogram estimates, the plurality of velocities.
Alkhalaf teaches determining variogram estimates from spatially distributed well-based data and using the variogram estimates in kriging-based spatial interpolation to determine values at unsampled locations, explicitly disclosing computing a variogram for a plurality of points (see ¶¶ [0024]-[0025]), fitting variogram models including range, still, and nugget (see ¶¶ [0026]-[0027]), and determining interpolated values based on the fitted variogram models (see ¶ [0028]). It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to incorporate the variogram-based spatial modeling taught by Alkhalaf to the combination of Buland and Haase because variograms and kriging were well-established geostatistical tools for modeling spatial dependence and interpolating subsurface properties between wells, thereby enabling the plurality of velocities in Buland to be determined based on a plurality of variogram estimates derived from prior velocity maps in a predictable and routine manner. Therefore, facilitating accurate reservoir characterization for hydrocarbon exploration.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Buland in
view of Haase and further in view of Nowak et al. (Pub. No. US 2015/0109885) (hereinafter Nowak).
As per claim 8, the combination of Buland and Haase teach the system as stated
above except that obtaining the plurality of depth geological markers comprises obtaining the plurality of depth geological markers based on check- shots at the plurality of wellbores of the hydrocarbon reservoir.
Nowak, however, discloses obtaining check-shot and sonic log travel time at known depths within a wellbore and generating a corrected time-depth relationship that associates seismic travel time measurements with discrete wellbore depths(see ¶¶ [0007], [0011], [0035], [0036], [0038] and [0071]-[0076]), thereby providing depth-registered geological markers at the wellbore. It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to combine the velocity modeling and depth-conversion workflow of Buland with the probabilistic seismic inversion and volumetric uncertainty analysis of Haase and further with the check-shot-based time-depth calibration of Nowak, because accurate velocity-based depth modeling and probabilistic volumetric assessment in hydrocarbon exploration depend on reliable depth control at well locations, and check-shot surveys are a well-known and routinely used technique for establishing precise time-depth relationships and depth geological markers at wellbores. Incorporating the check-shot-derived depth markers of Nowak into the velocity modeling and depth mapping of Buland would predictably improve the conditioning of velocity models and depth-calibrated models to multiple realizations and associated volumetric uncertainty estimates, thereby enabling more accurate and reliable hydrocarbon exploration decisions based on depth-calibrated seismic interpretation, velocity modeling, and probabilistic reservoir volume assessment.
Claims 9, 15 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over
Buland in view of Haase and further in view of Wendt et al. (Pub. No. US 2013/0289962) (hereinafter Wendt).
As per claims 9, 15 and 20, the combination of Buland and Haase teach the
system as stated above except that determining the plurality of velocities comprises determining the plurality of velocities based on a Sequential Gaussian Simulation (SGS) method.
Wendt, however, discloses performing subsurface property modeling using stochastic Sequential Gaussian Simulation(SGS), identifying SGS as known geostatistical modeling technique for generating spatial distributions and realizations of subsurface elastic properties, and discussing SGS as an alternative modeling approach alongside kriging and neural-network-based methods (see ¶¶ [0061]-[0064]). It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to implement the teaching of Wendt into the combination of Buland and Haase because SGS is a known, routine stochastic geostatistical modeling technique for generating spatially distributed property realization of subsurface properties using measured subsurface data and known spatial correlation techniques, thereby yielding a plurality of velocity realizations suitable for subsequent depth-map realization generation and uncertainty/volumetric analysis in the same manner as required by the combination of Buland and Haase.
Prior art
The prior art made record and not relied upon is considered pertinent to applicant’s
disclosure:
Gunderson et al. [‘234] discloses a method is described for assessing subsurface structure uncertainty based on at least one subsurface horizon. The method calculates seismic continuity attributes to determine a mappability of the subsurface horizon(s); determines horizontal uncertainty for each fault in vertical uncertainty for each horizon; generates probabilistic scenarios for a subsurface geometry for at least one conceptual model; and generates a map of geological model uncertainty based on the probabilistic scenarios. In some embodiments, the probabilistic scenarios are stochastic simulations. In some embodiments, generating a map of geological model uncertainty is based on information entropy. The method may be executed by a computer system.
Salem [991] discloses a process for generating a velocity model for a sediment-basement interface of a subsurface region includes receiving seismic data representing acoustic signals that are reflected from regions of the subsurface. The process includes receiving potential fields data comprising potential field values that are mapped to locations in the subsurface. The process includes generating weighted time-depth data pairs. The process includes selecting a velocity model that relates a velocity value to a depth value in a time-depth relationship. The process includes optimizing velocity coefficients of the velocity model by determining, for each velocity model of a set, a set of depth estimates for corresponding time values and comparing the set of depth estimates to depth values of the weighted time-depth data pairs. The process includes adjusting the velocity coefficients of the velocity model. The process includes generating a seismic image of the sediment-basement interface.
Jaiswal et al. [‘053] discloses methods for processing seismic data to concurrently produce a velocity model and a depth image. Various embodiments of the methods include: a) acquiring seismic data; b) generating a shallow velocity model from the seismic data; c) generating a stacking velocity model using the shallow velocity model as a guide; d) generating an initial interval velocity model from the stacking velocity model; and e) generating an initial depth image using the initial interval velocity model. The methods also include iterative improvement of the initial depth image and the initial interval velocity model to produce improved depth images and improved interval velocity models. Improvement of the depth images and the interval velocity models is evaluated by using a congruency test.
Contact information
Any inquiry concerning this communication or earlier communications from the
examiner should be directed to MOHAMED CHARIOUI whose telephone number is (571)272-2213. The examiner can normally be reached Monday through Friday, from 9 am to 6 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Schechter can be reached on (571) 272-2302. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Mohamed Charioui
/MOHAMED CHARIOUI/Primary Examiner, Art Unit 2857