DETAILED ACTION
Receipt of Applicant’s amendment filed 05/19/2026 is acknowledged.
Claim 1 has been amended.
Claim 8 has been canceled.
Claim 14 has been added.
Claims 1-2, 4-7, 9-10, 12 and 14 are pending.
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 .
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the
references as applied to the claims below for the convenience of the applicant. Although
the specified citations are representative of the teachings in the art and are applied to
the specific limitations within the individual claim, other passages and figures may apply
as well. It is respectfully requested that, in preparing responses, the applicant fully
consider the references in their entirety as potentially teaching all or part of the claimed
invention, as well as the context of the passage as taught by the prior art or disclosed
by the examiner. The entire reference is considered to provide disclosure relating to the
claimed invention. The claims & only the claims form the metes & bounds of the
invention. Office personnel are to give the claims their broadest reasonable
interpretation in light of the supporting disclosure. Unclaimed limitations appearing in the
specification are not read into the claim. Prior art was referenced using terminology
familiar to one of ordinary skill in the art. Such an approach is broad in concept and can
be either explicit or implicit in meaning. Examiner's Notes are provided with the cited
references to assist the applicant to better understand how the examiner interprets the
applied prior art. Such comments are entirely consistent with the intent & spirit of
compact prosecution.
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.
Response to Arguments
Rejections under 35 U.S.C. §101:
Acknowledgment is made of amended claim 1, the cancelation of claim 8, and the addition of claim 14.
Applicant’s arguments have been fully considered, but were not persuasive.
Rejections to claims are maintained.
Applicant argues that claim 1, as amended, “cannot be practically performed in the human mind or with pen and paper [ ] amount to more than mere mathematical concepts”, “amended claim 1 integrates any such exception into a practical application” since it “improves the functioning of a computer”, and the “features of amended claim 1 are not well-understood, routine, conventional activities previously known in the industry”. The Examiner respectfully disagrees.
Regarding Applicant’s first argument, per MPEP 2106.03(II), “[a]s described in MPEP § 2106, subsection III, Step 1 of the eligibility analysis asks: Is the claim to a process, machine, manufacture or composition of matter? Like the other steps in the eligibility analysis, evaluation of this step should be made after determining what the inventor has invented by reviewing the entire application disclosure and construing the claims in accordance with their broadest reasonable interpretation (BRI).” As shown in 35 USC § 101 analysis below, claims 1-2, 4-7, 9-10, 12 and 14 are directed to a method, thus fall within the statutory category of a process. Under BRI and review of the Specification, the invention as a whole is directed towards a method to create a 3D geological model, which is considered an abstract idea since a person can reasonably create in their mind or draft on a piece of paper a 3D geological model (i.e. mental processes). Additionally, independent claim 1 recites limitations amounting to mathematical concepts per MPEP 2106.04. The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation. Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. Thus, Applicants argument not persuasive.
Regarding Applicant’s second argument, per MPEP 2106.04(d), “after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception 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 judicial exception.” Applicant argues that the invention is an improvement in the functioning of a computer, therefore integrates into a practical application. Under Step 2A and 2B of the eligibility analysis, the examiner must determine if the claim recites additional elements that amount to significantly more than the judicial exception. As shown in 35 USC §101 analysis section below, the additional elements as described in Step 2A Prong 2 are not sufficient to amount to significantly more than the judicial exception because the additional limitations are considered Mere Instructions to Apply an Exception per MPEP 2106.05(f). The additional elements identified (Claim 1) recite only the idea of a solution or outcome and/or invoke computers or other machinery merely as a tool to perform an existing process (such as numerical (3D) modeling, calculation/computation), i.e. requiring the use of software to tailor information and provide it to the user on a generic computer. The claim, as a whole, is linked to a computer implemented method for the formation of a coarse-scale three-dimensional geological model, but there are no particular physical elements or steps that impose any meaningful limits on practicing the abstract idea. Thus, the claim does not integrate the identified abstract ideas into a practical application. Applicant’s argument not persuasive.
Regarding Applicant’s third argument, per 2106.05(d), “[a]nother consideration when determining whether a claim recites significantly more than a judicial exception is whether the additional element(s) are well-understood, routine, conventional activities previously known to the industry.” The additional elements identified, upscaling 3D models and computing fluid flow and permeability values, are well-understood, routine, and conventional activity previously known in the industry, as evident by referenced art Khan, Gunasekera, Le Ravalec, Usadi, and Bosna cited in Claim Rejections - 35 U.S.C. §103 section below. Thus, Applicant’s argument not persuasive.
Rejections under 35 U.S.C. §103:
Acknowledgment is made of amended claim 1, the cancelation of claim 8, and the addition of claim 14.
Applicant’s arguments have been fully considered, but were not persuasive.
Rejections to claims are maintained.
Applicant’s amendment necessitated the new ground(s) of rejection presented in this Office Action.
Applicant argues Khan “fails to teach a transmissivity reduction coefficient associated with two- dimensional meshed surfaces representing layers of lithology, where the coefficient describes an imperviousness degree of the surface”. The examiner respectfully disagrees.
Kahn discloses “The upscaling technique of this invention can also be applied to 3-D structured as well as 3-D layered PEBI grids [ ] Extension to 3-D unstructured grids is also possible. The layered PEBI (i.e. Perpendicular bisection) grids are unstructured areally and structured (layered) vertically. One way to create such grids is to project 2-D areal PEBI grids on geologic sequence surfaces (i.e. two-dimensional meshed surfaces representing layers of lithology). Areal connection permeabilities can be upscaled layer-by-layer or over multiple layers. For upscaling vertical (inter-layer) connection permeabilities, the flow equations would be solved with the pressure gradient in the vertical direction (i.e. solving perpendicular/normal to 2D meshed surface).” [Col.12 Ln.22]. Khan also discloses “In 2-D, a connection property (such as flux, pressure gradient or connection permeability (i.e. imperviousness)) can be represented” [Col.13 Ln.21]. A connection property is interpreted to include a transmissivity reduction coefficient since Khan discloses “Assuming, but not limited to, a scalar connection permeability, the discretized form of Eq. (1) for PEBI grids is:
∑
i
Τ
t
j
(
P
j
-
P
i
)
=
0
, where
T
is transmissibility (i.e. transmissivity), subscript
j
refers to the node of interest and subscript
i
refers to all of its neighbors. The term transmissibility as used in this description refers to a measure of the capability of a given viscosity fluid to move across a cell boundary (or inter-node connection) under a pressure drop. More specifically, transmissibility is known to those skilled in the art as a measure of the ability of a fluid to flow between two neighboring cells within a porous medium. Transmissibility is expressed as
k
A
Δ
s
” , where
k
is the effective permeability (i.e. imperviousness) of the porous medium,
A
is the area of the boundary between the neighboring cells, and
Δ
s is the average or characteristic distance that the fluid must travel in moving between the two cells.” [Col.9 Ln.40-65]. Thus, Applicant’s argument not persuasive.
Applicant argues “Begg does not attribute a transmissivity reduction coefficient to two-dimensional meshed surfaces”, “[t]he Examiner’s interpretation of Begg’s parameter r is also misplaced [and] it does not describe the imperviousness degree of a lithology layer”. The examiner respectfully disagrees when combined with primary art of reference, Khan.
Begg discloses “For the present we assume that all the shales are aligned normal to the flow [ ] Using this scheme KVE (i.e. effective vertical permeability) is calculated using equation (21) [i.e. KVE =
K
1
-
F
S
H
2
N
S
∑
i
=
1
N
S
1
S
i
2
], where:
S
i
=
H
+
∑
j
=
1
H
s
+
1
r
l
j
(22), and
s
= number of shales per metre (e.g. from well cores or logs),
r
= random number between 0 and 1,
l
j
= length of the
j
th shale taken from CDF” [§2.3.3]. As shown, equation (21) calculates an effective vertical permeability (i.e. imperviousness) where
S
i
(i.e. equation 22) includes a random number
r
between 0 and 1. Hence, “
r
” describes the imperviousness degree of a lithography layer. Note: “
r
” is interpreted as a transmissivity reduction coefficient due to Applicant’s disclosure “The value of the transmissivity reduction coefficient is assigned to each sedimentary surface by a user according to its knowledge of the sedimentary structure to be modelled.” Spec. [Pg.7 Ln.29]. i.e. “
r
” (the coefficient) is a user assigned random number. Also note, the cited shales are interpreted as 2D surfaces because “the effective vertical permeability of a reservoir containing stochastic shales in both two and three dimensions.” Begg [Abstract]. As disclosed in 35 USC §103 section below, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have attributed Begg’s user assigned transmissivity reduction coefficients, between 0 and 1, to the two-dimensional meshed surfaces of Khan to quickly and efficiently model impervious layers of lithology. Applicant’s argument not persuasive.
Applicant’s argument regarding Usadi and the interpretation of the term -1/pv is moot given new grounds of rejection necessitated by amendment. See Khan in 35 USC §103 section 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.
To determine if a claim is directed to patent ineligible subject matter, the Court has guided the Office to apply the Alice/Mayo test, which requires:
Step 1. Determining if the claim falls within a statutory category of a Process, Machine, Manufacture, or a Composition of Matter (see MPEP 2106.03);
Step 2A. Determining if the claim is directed to a patent ineligible judicial exception consisting of a law of nature, a natural phenomenon, or abstract idea (MPEP 2106.04);
Step 2A is a two-prong inquiry. MPEP 2106.04(II)(A).
Under the first prong, examiners evaluate whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. Abstract ideas include mathematical concepts, certain methods of organizing human activity, and mental processes. MPEP 2106.04(a)(2).
The second prong is an inquiry into whether the claim integrates a judicial exception into a practical application. MPEP 2106.04(d).
Step 2B. If the claim is directed to a judicial exception, determining if the claim recites limitations or elements that amount to significantly more than the judicial exception. (See MPEP 2106).
Claims 1-2, 4-7, 9-10, 12 and 14 are rejected under 35 U.S.C. 101 because the
claimed invention recites a judicial exception, is directed to that judicial exception (an abstract idea), as it has not been integrated into a practical application and the claims further do not recite significantly more than the judicial exception. Examiner has evaluated the claims under the framework provided in the 2019 Patent Eligibility Guidance published in the Federal Register 01/07/2019 and has provided such analysis below.
Step 1:
Claims 1-2, 4-7, 9-10, 12 and 14 are directed to a method, as such these claims fall within the statutory category of a process.
Step 2A, Prong I:
The examiner submits that the foregoing claim limitations constitute abstract ideas, as the claims cover Mental Processes performed on a generic computer and/or Mathematical Concepts, given the broadest reasonable interpretation.
In order to apply Step 2A, a recitation of claims is copied below. The limitations of those claims which describe an abstract idea are bolded.
As per claim 1, the claim recites the limitations of:
forming a fine-scale three dimensional model of the subsurface reservoir, (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a generic computer. For example, a person can reasonably create (i.e. form), either within the mind or with the aid of pen and paper, a fine-scale 3D subsurface reservoir model.)
modeling a plurality of meshed surfaces, each meshed surface being a two-
dimensional surface delimiting superposed layers of lithology extending between two consecutive two-dimensional meshed surfaces (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a generic computer. For example, a person can reasonably draw a model with a plurality of 2D meshed surfaces, with/without the aid of pen and paper.),
forming an unstructured grid comprising a plurality of three-dimensional cells, wherein each three-dimensional cell extends between two-dimensional meshed surfaces (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a generic computer. For example, a person can reasonably create (i.e. form), either within the mind or with the aid of pen and paper, an unstructured grid comprising a plurality of 3D cells extending between 2D meshed surfaces.)
attributing petrophysical parameters to each three-dimensional cell of the grid based on ground data acquired on the subsurface reservoir (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a generic computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I). For example, this limitation encompasses a user evaluating ground data then determining, based on the ground data, which petrophysical parameters to assign (i.e. attribute) to each 3D cell. Also, the mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. A mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words or using mathematical symbols. Attributing parameters to each 3D cell is interpreted as mathematical relationships.),
representing, in the fine-scale three-dimensional model, impervious layers of lithology by attributing, to at least some of the two-dimensional meshed surfaces, a transmissivity reduction coefficient between 0 and 1, that describes an imperviousness degree of the considered layer of lithology; (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a generic computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I). For example, this limitation encompasses a user evaluating a layer’s imperviousness, then assigning / attributing (i.e. mathematical relationship) a transmissivity reduction coefficient, based on that evaluation (i.e. observation, opinion/judgement), to the 2D meshed surfaces determined to receive a coefficient.)
wherein each three-dimensional cell of the coarse-scale geological model is associated with petrophysical parameters determined from the petrophysical parameters of the three-dimensional cells of the fine-scale three-dimensional model, and from the transmissivity reduction coefficients of the two-dimensional meshed surfaces (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a generic computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I). For example, this limitation encompasses a user evaluating petrophysical parameters then assigning a transmissivity reduction coefficient (“according to its knowledge of the sedimentary structure” [Spec. Ln.30]) then determining, based on the evaluation, which petrophysical parameters to associate with each 3D cell. Also, the mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. A mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words or using mathematical symbols. Associating petrophysical parameters is interpreted as mathematical relationships.)
numerically solving Darcy's equation, by the computer, to obtain, in each cell of the fine-scale three-dimensional model, a fluid head in the cell, said fluid head being determined from fluid head values imposed at the limits of the fine-scale three-dimensional model (As drafted and under its broadest reasonable interpretation, this limitation amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a generic computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I). For instance, a person can reasonably solve Darcy’s equation, numerically, with/without the aid of pen/paper.)
Step 2A, Prong II:
As per claim 1, this judicial exception is not integrated into a practical application
because the additional claim limitations outside the abstract idea only mere instructions to implement an abstract idea or other exception on a generic computer. In particular, the claim recites the additional limitations:
upscaling the fine-scale three-dimensional model to obtain the coarse-scale three dimensional geological model comprising a plurality of three-dimensional cells (The additional feature is considered to disclose Mere Instructions to Apply an Exception per MPEP 2106.05(f). The additional limitation amounts to mere instructions to implement an abstract idea or other exception on a generic computer. Specifically, the limitation recites only the idea of a solution or outcome, i.e. fails to recite details of how upscaling the fine-scale 3D model is accomplished; and/or invokes computers or other machinery merely as a tool to perform an existing process (such as numerical (3D) modeling), i.e. requiring the use of software to tailor information and provide it to the user on a generic computer.)
computing, by the computer, from the fluid head, a fluid flow value in each cell of the fine-scale three-dimensional model (The additional feature is considered to disclose Mere Instructions to Apply an Exception per MPEP 2106.05(f). The additional limitation amounts to mere instructions to implement an abstract idea or other exception on a generic computer. Specifically, the limitation recites only the idea of a solution or outcome, i.e. fails to recite details of how “computing” a fluid flow value in each cell is accomplished; and/or invokes computers or other machinery merely as a tool to perform an existing process (such as calculation/computation), i.e. requiring the use of software to tailor information and provide it to the user on a generic computer.),
computing, by the computer, from the fluid flow value in each cell of the fine scale three-dimensional model and from the transmissivity reduction coefficients associated with two-dimensional meshed surfaces located in a cell of the coarse-scale model, an equivalent fluid flow value for the cell of the coarse-scale model (The additional feature is considered to disclose Mere Instructions to Apply an Exception per MPEP 2106.05(f). The additional limitation amounts to mere instructions to implement an abstract idea or other exception on a generic computer. Specifically, the limitation recites only the idea of a solution or outcome, i.e. fails to recite details of how “computing” an equivalent fluid flow value is accomplished; and/or invokes computers or other machinery merely as a tool to perform an existing process (such as calculation/computation), i.e. requiring the use of software to tailor information and provide it to the user on a generic computer.), and
computing, by the computer, an equivalent permeability value of the cell of the coarse-scale model from the equivalent fluid flow value (The additional feature is considered to disclose Mere Instructions to Apply an Exception per MPEP 2106.05(f). The additional limitation amounts to mere instructions to implement an abstract idea or other exception on a generic computer. Specifically, the limitation recites only the idea of a solution or outcome, i.e. fails to recite details of how “computing” an equivalent permeability value of the cell of a course-scale model is accomplished; and/or invokes computers or other machinery merely as a tool to perform an existing process (such as calculation/computation), i.e. requiring the use of software to tailor information and provide it to the user on a generic computer.).
These additional limitations must be considered individually and with the claim as
a whole to determine if it integrates the judicial exception into a practical application.
The claim, as a whole, is linked to a computer implemented method for the formation of a coarse-scale three-dimensional geological model, but there are no particular physical elements or steps that impose any meaningful limits on practicing the abstract idea. Thus, the claim does not integrate the identified abstract ideas into a practical application.
Step 2B:
Moving on to step 2B of the analysis, the Examiner must consider whether each
claim limitation individually or as an ordered combination amounts to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations are considered directed towards Mere Instructions to Apply an Exception - MPEP 2106.05(f). Per MPEP 2106.05(f), “[t]he recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it" [ ] Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.”
Another consideration when determining whether a claim recites significantly more than a judicial exception is whether the additional element(s) are well-understood, routine, conventional activities previously known to the industry. Per MPEP 2106.05(d)(II), the courts have recognized the following computer functions, pertinent to the claimed invention, as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, ii. Performing repetitive calculations, iii. Electronic recordkeeping, iv. Storing and retrieving information in memory.
For the foregoing reasons, claim 1 is directed to an abstract idea without significantly more and is rejected as not patent eligible under 35 U.S.C 101.
Claim 2 further recites, “wherein the meshed surfaces are meshed with
triangles, and the forming the unstructured grid comprises forming a plurality of tetrahedral cells between two consecutive two-dimensional meshed surfaces, such that one face of a tetrahedral cell corresponds to a triangular mesh of a meshed surface, and the summit of the tetrahedral cell belongs to an adjacent meshed surface.” The additional feature(s) elaborate on claim 1’s meshed surfaces and the unstructured grid; thus, the limitation further amounts to Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a generic computer and/or Mathematical Concepts per MPEP 2106.04(a)(2)(I). For example, a mesh is “defined by three types of elements: vertices, edges, and faces (or facets)” [https://www.sciencedirect.com/topics/engineering/three-dimensional-mesh]. By definition, a mesh is a mathematical relationship between variables or numbers. What’s more, “one face of a tetrahedral cell corresponds to a triangular mesh” is also a mathematical relationship between the cell face and triangular mesh. Therefore, the claim is considered to be ineligible under 35 U.S.C 101.
Claim 4 further recites, “wherein a modeled meshed surface having a
transmissivity reduction coefficient of 0 represents a shale layer of the subsurface reservoir.” The additional feature(s) are considered to further disclose Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a generic computer, since the limitation simply elaborates on the transmissivity reduction coefficient which was considered a mental process within the claim 1 analysis. Therefore, the claim is considered to be ineligible under 35 U.S.C 101.
Claim 5 further recites, “wherein the attributing petrophysical parameters to
each three-dimensional cell of the grid of the fine-scale three-dimensional model comprises: determining a number of lithology types within the fine-scale three-dimensional model and defining each lithology type, determining a distribution pattern of the lithology types within the grid, and attributing to each cell petrophysical parameters according to the determined distribution pattern.” The additional feature(s) are considered to further disclose Mental Processes (MPEP 2106.04(a)(2)(III)) performed on a generic computer. For example, “determining”, “defining”, and “attributing” are all mental processes (observation, evaluation, judgment, opinion). Therefore, the claim is considered to be ineligible under 35 U.S.C 101.
Claim 6 further recites, “wherein the petrophysical parameters comprise at least porosity and permeability values.” The additional feature(s) are considered to further disclose Mathematical Relationships per MPEP 2106.04(a)(2)(I). For example, further defining the petrophysical parameters associated with each cell of the model is a mathematical relationship between the parameters and each cell. Therefore, the claim is considered to be ineligible under 35 U.S.C 101.
Claim 7 further recites, “wherein the upscaling comprises providing a
coarse-scale grid comprising a plurality of cells, each cell of the coarse-scale grid having dimensions greater than a plurality of cells of the fine-scale three-dimensional model, and the upscaling of the permeability values comprises computing equivalent fluid flow values of the cells of the coarse-scale grid from fluid flow values of the cells of the grid of the fine-scale three-dimensional model and inferring equivalent permeability values of the coarse-scale grid.” The additional feature(s) elaborate on “upscaling”, thus further amounts to Mere Instructions to Apply an Exception per MPEP 2106.05(f). Therefore, the claim is considered to be ineligible under 35 U.S.C 101.
Claim 8 has been canceled.
Claim 9 further recites, “wherein the modelling of the plurality of meshed
surfaces comprises: selecting a bedform type to be modelled among a library of previously established bedform types, wherein each bedform type defines a disposition of a plurality of sedimentary surfaces, and parameterizing the selected bedform type.” The additional feature(s) are considered to further disclose Mental Process (MPEP 2106.04(a)(2)(III)) performed on a generic computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I)). For example, this limitation encompasses a user selecting an option. A user “selecting a bedform type” from a “library of previously established bedform types” is an evaluation, judgement, and/or an opinion. Also, parameterizing the selected bedform type amounts to Mathematical Relationships per MPEP 2106.04(a)(2)(I)(A). Therefore, the claim is considered to be ineligible under 35 U.S.C 101.
Claim 10 further recites, “wherein the parameterizing of the selected bedform
type is performed according to at least one of the following parameters: wavelength of a cyclic geometric pattern of the sedimentary surfaces included in the bedform type, steepness of said cyclic geometric pattern, angular orientation of said cyclic geometric pattern, number of sedimentary surfaces, and mean thickness between two adjacent sedimentary surfaces.” The additional feature(s) elaborate on the selected bedform type parameterization, thus is considered to further disclose Mental Processes MPEP 2106.04(a)(2)(III) performed on a generic computer and/or Mathematical Concepts (MPEP 2106.04(a)(2)(I)). Therefore, the claim is considered to be ineligible under 35 U.S.C 101.
Claim 11 has been canceled.
Claim 12 further recites, “A non-transitory computer readable storage
medium, having stored thereon a computer program comprising program instructions, the computer program being loadable into a computer and adapted to cause the computer to carry out the steps of the method according to claim 1, when the computer program is run by the computer.” The additional feature(s) are considered to disclose Mere Instructions to Apply an Exception per MPEP 2106.05(f). Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. Therefore, the claim is considered to be ineligible under 35 U.S.C 101.
Claim 13 has been canceled.
Claim 14 (new) recites wherein the fluid flow Q through a face, of surface
S
, of a cell of the coarse-scale geological model, the face being orthogonal to the direction of the flow, is computed by implementing the equation:
Q
=
∑
S
q
s
⃑
(
M
u
l
t
S
)
.
S
where
s
designates all the two-dimensional meshed surfaces representing impervious layers of lithology comprised within the cell of the coarse-scale geological model, and
M
u
l
t
S
is the transmissivity reduction coefficient associated with a two-dimensional meshed surface
S
. The additional feature(s) amounts to Mathematical Concepts (MPEP 2106.04(a)(2)) grouping which is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. A claim that recites a numerical formula or equation will be considered as falling within the "mathematical concepts" grouping. A claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number. Therefore, the claim is considered to be ineligible under 35 U.S.C 101.
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.
The factual inquiries set forth in Graham V. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 4, 6-7, and 12 are rejected under 35 U.S.C. 103 as being
unpatentable over Khan et al. US Patent No. 6826520 B1 (hereinafter referred to as “Khan”) in view of Gunasekera US Patent No. 6018497 (hereinafter referred to as “Gunasekera”) in further view of Begg, S. H., and P. R. King. "Modelling the effects of shales on reservoir performance: calculation of effective vertical permeability." SPE Reservoir Simulation Conference. SPE, 1985. (hereinafter referred to as “Begg”), and in further view of Usadi et al. US Pub No. 20130118736 A1 (hereinafter referred to as “Usadi”).
Regarding claim 1, Khan discloses A method for forming a coarse-scale three dimensional geological model of a subsurface reservoir (“A method is provided for scaling up permeabilities associated with a fine-scale grid of cells representative of a porous medium to permeabilities associated with an unstructured coarse-scale grid of cells representative of the porous medium.” Khan [Col.4 Ln.16-21]), the method being implemented by a computer (“in practicing the present invention, the properties of the domain being simulated can optionally be visualized on 2-D and 3-D unstructured grids using suitable computerized visualization equipment.” Khan [Col.13 Ln.15-20]), and comprising:
forming a fine-scale three-dimensional model of the subsurface
reservoir, by: modeling a plurality of meshed surfaces, each meshed surface being a two-dimensional surface delimiting superposed layers of lithology extending between two consecutive two-dimensional meshed surfaces, (“The upscaling technique of this invention can also be applied to 3-D structured as well as 3-D layered PEBI grids (also referred to by some as 21/2-D PEBI grids). Extension to 3-D unstructured grids is also possible. The layered PEBI grids are unstructured areally and structured (layered) vertically. One way to create such grids is to project 2-D areal PEBI grids on geologic sequence surfaces. Areal connection permeabilities can be upscaled layer-by-layer or over multiple layers.” Khan [Col.12 Ln.22-30]. Layered PEBI grids are understood as a plurality of stacked 2D meshed layers.)
forming an unstructured grid comprising a plurality of three-dimensional cells (“The computational grid is generated in such a way as to produce unstructured, PEBI cells” Khan [Col.6 Ln.66]. The PEBI cells are interpreted as three-dimensional cells because “all cells are three-dimensional” Khan [Col.15 Ln.30]),
representing, in the fine-scale three-dimensional model, impervious layers of lithology by attributing, to at least some of the two-dimensional meshed surfaces, a transmissivity , that describes an imperviousness degree of the- considered layer of lithology: (“Assuming, but not limited to, a scalar connection permeability (i.e. imperviousness), the discretized form of Eq. (1) for PEBI grids (i.e. two-dimensional meshed surfaces/layers) is:
∑
i
Τ
t
j
(
P
j
-
P
i
)
=
0
where
Τ
is transmissibility, subscript j refers to the node of interest and subscript l refers to all of its neighbors. The term transmissibility (i.e. transmissivity) as used in this description refers to a measure of the capability of a given viscosity fluid to move across a cell boundary (or inter-node connection) under a pressure drop. More specifically, transmissibility is known to those skilled in the art as a measure of the ability of a fluid to flow between two neighboring cells within a porous medium. Transmissibility is expressed as
k
A
Δ
s
” where k is the effective permeability of the porous medium,
A
is the area of the boundary between the neighboring cells, and
Δ
s is the average or characteristic distance that the fluid must travel in moving between the two cells.” Khan [Col.9 Ln.39-64])
upscaling the fine-scale three-dimensional model to obtain the coarse-scale three-dimensional geological model comprising a plurality of three-dimensional cells, (“A mathematical basis for upscaling permeabilities from a computational grid to the coarse grid will now be provided [...] The upscaling technique of this invention can also be applied to 3-D structured as well as 3-D layered PEBI grids (also referred to by some as 21/2-D PEBI grids). Extension to 3-D unstructured grids is also possible.” Khan [Col.10 Ln.43 – Col.12 Ln.25])
wherein each three-dimensional cell of the coarse-scale geological model is associated with petrophysical parameters determined from the petrophysical parameters of the three-dimensional cells of the fine-scale three-dimensional model, and from the transmissivity of the two-dimensional meshed surfaces (“Once the fluxes and pressure gradients computed are determined for the computational grid, the average fluxes and average pressure gradients associated with connections of the coarse grid are computed. These pressure gradients and fluxes are averaged over predetermined integration sub-domains associated with each coarse-grid cell, preferably sub-domains associated with each inter-node connection of the coarse grid. The ratio of the upscaled flux to upscaled pressure gradient then gives the upscaled permeability (i.e. petrophysical parameters). This upscaled permeability can then be used to compute transmissibility (i.e. transmissivity).” Khan [Col.10 Ln.31-42], “The upscaling technique of this invention can also be applied to 3-D structured as well as 3-D layered PEBI (i.e. two-dimensional meshed) grids” Khan [Col.12 Ln.20])
computing, by the computer, from the fluid flow value in each cell of the fine scale three-dimensional model and from the transmissivity reduction coefficients associated with two-dimensional meshed surfaces located in a cell of the coarse-scale model, an equivalent fluid flow value for the cell of the coarse-scale model (“The computational grid is then populated with permeabilities associated with the fine-scale grid. Flow equations, preferably single-phase, steady-state pressure equations, are developed for the computational grid, the flow equations are solved, and inter-node fluxes and pressure gradients are then computed for the computational grid. These inter-node fluxes (i.e. fluid flow) and pressure gradients are used to calculate inter-node average fluxes (i.e. equivalent fluid flow) and average pressure gradients associated with the coarse-scale grid. The inter-node average fluxes and average pressure gradients associated with the coarse grid are then used to calculate upscaled permeabilities associated with the coarse-scale grid” Khan [Col.4 Ln.26]. The fine-scale computational grid is interpreted as a 3D model because “The pressure equation is solved in each of the two principal directions for 2-D applications (and in three principal directions for 3-D applications). Fluxes and pressure gradients are then computed for all inter-node connections of the computational grid.” Khan [Col.10 Ln.14]. The flow equations are interpreted to apply to each cell and include transmissivity reduction coefficients because “After the computational grid has been populated with permeabilities, the next step in the practice of this invention is to develop flow equations for the computational grid, preferably single-phase, steady-state pressure equations for each cell of the computational grid, and using an assumed set of boundary conditions, solve the equations for each computational grid cell [ ] where T is transmissibility, subscript j refers to the node of interest and subscript l refers to all of its neighbors” Khan [Col.9 Ln.22-48]. Transmissibility is interpreted as associated with 2D meshed surfaces located in a cell of the coarse scale model because “The upscaling technique of this invention can also be applied to [ ] 3-D layered PEBI grids [ ] One way to create such grids is to project 2-D areal PEBI grids (i.e. mesh) on geologic sequence surfaces. Areal connection permeabilities can be upscaled layer-by-layer or over multiple layers. For upscaling vertical (inter-layer) connection permeabilities, the flow equations would be solved with the pressure gradient in the vertical direction.” Khan [Col.12 Ln.22]), and
computing, by the computer, an equivalent permeability value of the cell of the coarse-scale model from the equivalent fluid flow value (“The inter-node average fluxes and average pressure gradients associated with the coarse grid are then used to calculate upscaled permeabilities associated with the coarse-scale grid” Khan [Col.4 Ln.26]).
Khan fails to specifically disclose wherein each three-dimensional cell extends between two two-dimensional meshed surfaces, attributing petrophysical parameters to each three-dimensional cell of the grid based on ground data acquired on the subsurface reservoir, a transmissivity reduction coefficient between 0 and 1, numerically solving Darcy's equation, by the computer, to obtain, in each cell of the fine-scale three-dimensional model, a fluid head in the cell, said fluid head being determined from fluid head values imposed at the limits of the fine-scale three-dimensional model, and computing, by the computer, from the fluid head, a fluid flow value in each cell of the fine-scale three-dimensional model.
However, Gunasekera discloses wherein each three-dimensional cell extends between two two-dimensional meshed surfaces (“In FIG. 13a, the earth formation 15 of FIG. 1 is again illustrated, the formation 15 including four (4) horizons 13 which traverse the longitudinal extent of the formation 15 in FIG. 13a. Recall that a "horizon" 13 is defined to be the top surface of an earth formation layer, the earth formation layer comprising, for example, sand or shale or limestone, etc.” Gunasekera [Col.10 Ln.62-67])
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attributing petrophysical parameters to each three-dimensional cell of the grid based on ground data acquired on the subsurface reservoir (“FIG. 13c1 (see below) illustrates the more relevant and novel aspects of the Petragrid software program of the present invention shown in FIG. 10 which operate on the gridded horizons of FIG. 13a (also see 3D cells)“ Gunasekera [Col.5 Ln.56]. As seen in FIG.13c1 below, each cell’s attributes are obtained via well log and seismic data (i.e. acquired ground data). The attributes are interpreted to include petrophysical parameters because “The primary property values within each cell include porosity, permeability” Gunasekera [Col.28 Ln.35] and Applicant’s disclosure “The petrophysical parameters preferably comprise at least porosity and permeability values.” Spec. [Pg.4 Ln.5])
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Khan and Gunasekera are analogous art as both patents address the modeling of subsurface formations using grids, involve the calculation of properties (permeability or transmissibility) associated with grid cells, and are relevant to reservoir simulation. Both utilize unstructured grids (triangular/tetrahedral cells) and reference Delaunay triangulation or similar geometric constructs. Both ultimately support simulation of fluid flow in porous media and require mapping or transformation between different grid resolutions or types (i.e. fine/coarse-scale).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Khan to include the extension of 3D cells between 2D meshed surfaces and attribute petrophysical parameters to those 3D cells obtained from ground data, as disclosed by Gunasekera, in order to generate “a corresponding plurality of "more accurate" information relating, for example, to the transmissibility properties of the plurality of cells of the grid, the plurality of "more accurate" information being input to a conventional simulator which generates a corresponding plurality of simulation results (such as pressures and saturations)” Gunasekera [Col.1 Ln.26-32].
Although, Khan-Gunasekera fail to specifically disclose a transmissivity reduction coefficient between 0 and 1, numerically solving Darcy's equation, by the computer, to obtain, in each cell of the fine-scale three-dimensional model, a fluid head in the cell, said fluid head being determined from fluid head values imposed at the limits of the fine-scale three-dimensional model, and computing, by the computer, from the fluid head, a fluid flow value in each cell of the fine-scale three-dimensional model.
However, Begg discloses a transmissivity reduction coefficient between 0 and 1 (“This method requires the shales to be defined on a fine-scale numerical grid similar to that described for the simulation method. The major difference is that, at present, the sand permeability must be constant and that of the shale zero.” Begg [Pg.4 Sec.2.3.2]. The shale permeability (i.e. KVE) is interpreted to include a transmissivity reduction coefficient because “Using this scheme KVE is calculated using equation (21) where: Si = H+
∑
j
=
1
H
s
+
1
r
l
j
(22) and s = number of shales per metre (e.g. from well cores or logs),
r
= random number between 0 and 1, Ij = length of the jth shale taken from CDF” Begg [Pg.4 Sec.2.3.3]. Note: “r” is interpreted as a transmissivity reduction coefficient due to Applicant’s disclosure “The value of the transmissivity reduction coefficient is assigned to each sedimentary surface by a user according to its knowledge of the sedimentary structure to be modelled.” Spec. [Pg.7 Ln.29]. i.e. “r” (the coefficient) is a user assigned random number. Also note, the cited shales are interpreted as 2D surfaces because “the effective vertical permeability of a reservoir containing stochastic shales in both two and three dimensions.” Begg [Abstract])
Begg is analogous art as it relates to modelling the effects of shales on reservoir performance (i.e. permeability). Begg discloses, “In this paper we address the problem of estimating the effective vertical permeability of a reservoir volume which contains a distribution of small, laterally discontinuous permeability barriers embedded in a porous medium.” Begg [Pg.1 Intro.].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have attributed Begg’s user assigned transmissivity reduction coefficients, between 0 and 1, to the two-dimensional meshed surfaces of Khan-Gunasekera, to quickly and efficiently model impervious layers of lithology.
Khan-Gunasekera-Begg fail to specifically disclose numerically solving Darcy's equation, by the computer, to obtain, in each cell of the fine-scale three-dimensional model, a fluid head in the cell, said fluid head being determined from fluid head values imposed at the limits of the fine-scale three-dimensional model, and computing, by the computer, from the fluid head, a fluid flow value in each cell of the fine-scale three-dimensional model.
Usadi discloses numerically solving Darcy's equation, by the computer (“In some exemplary embodiments, the surrogate solution may be a formulation of Darcy's law, and supervised machine learning may be used to generate a coarse scale approximation of the phase permeability of a coarse grid cell.” Usadi [P.0061]), to obtain, in each cell of the fine-scale three-dimensional model (“The coarse scale approximation of the phase permeability for the coarse grid cell 700 may be characterized as a function of the fine grid permeability of each of the fine grid cells” Usadi [P.0095]. The model is interpreted as three-dimensional because “The physical system may include a three-dimensional reservoir model” Usadi [P.0052]), a fluid head in the cell, said fluid head being determined from fluid head values (“The multi-phase extension of Darcy's law, yields the formula shown in Eqn. 6. In the above equation, Kv is phase permeability which contains both the absolute and relative phase permeability, μv is the phase viscosity, and the pressure gradient,
∇
Pv, may include saturation dependent capillary pressure and gravity force. Thus, the phase velocity,
V
→
v, is a function of potential gradient and phase permeability, which is itself a function of phase saturation and scale lengths.” Usadi [P.0094]. Examiner interprets “
∇
Pv” as the “fluid head value” because of Applicant’s disclosure “K is the permeability value of the domain, and h is a head gradient vector.” [Spec. Pg.10 Ln.1-3]. i.e.“
∇
Pv” = “h”) imposed at the limits of the fine-scale three-dimensional model (“the solution surrogate may be an approximation of the inverse operator of a matrix equation that relates the fluid flow through a porous media with the boundary conditions of the corresponding grid cell” Usadi [P.0077]. Examiner interprets “boundary conditions” as “the limits of the fine-scale model”.),
computing, by the computer, from the fluid head, a fluid flow value in each cell of the fine-scale three-dimensional model (“The coarse scale approximation of the phase permeability for the coarse grid cell 700 may be characterized as a function of the fine grid permeability of each of the fine grid cells.” Usadi [P.0095]. Examiner interprets “function of the fine grid permeability” as “fluid flow value”.),
Usadi is analogous art as it relates to modeling hydrocarbon reservoirs. Specifically, Usadi teaches a method of modeling hydrocarbon reservoirs using machine learning techniques to generate surrogate solutions that approximate fluid flow through porous media. The method involves constructing a reservoir model with coarse grid cells and generating fine grid models for cells surrounding flux interfaces. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s claimed invention to incorporate the teachings of Usadi with the modelling methods of Khan-Gunasekera-Begg to “provide a fast and accurate method [ ] for performing a reservoir simulation” Usadi [P.0014].
Regarding claim 2, Khan in view of Gunasekera in view of Begg in further view of Usadi disclose the method according to claim 1, although Khan fails to specifically disclose wherein the meshed surfaces are meshed with triangles and the forming the unstructured grid comprises forming a plurality of tetrahedral cells between two consecutive two-dimensional meshed surfaces, such that one face of a tetrahedral cell corresponds to a triangular mesh of a meshed surface and the summit of the tetrahedral cell belongs to an adjacent meshed surface.
However, Gunasekera further discloses, wherein the meshed surfaces are meshed with triangles (“The surface of a cell face is defined by a local triangulation of its vertices” Gunasekera [Col.27 Ln.4-5]. Examiner interprets “triangulation” to mean “meshed with triangles” because “prior to generating a simulation grid, such as the grids of FIGS. 13a and 13b, the elements or cells of a base triangulation (triangular grid in 2D space)” Gunasekera [Col.13 Ln.6-8]. Examiner interprets “cell face” to mean “sedimentary surfaces” in light of FIGS 13a and 13b.), and the forming the unstructured grid comprises forming a plurality of tetrahedral cells between two consecutive two-dimensional meshed surfaces, (“In FIG. 13a, the earth formation 15 of FIG. 1 is again illustrated, the formation 15 including four (4) horizons 13 which traverse the longitudinal extent of the formation 15 in FIG. 13a. Recall that a "horizon" 13 is defined to be the top surface of an earth formation layer (i.e. two-dimensional meshed surface), the earth formation layer comprising, for example, sand or shale or limestone, etc.” Gunasekera [Col.10 Ln.62], “FIG. 13a clearly shows a multitude of cells 15a1 where each cell 15a1 has a cross sectional shape which is either approximately "polygonal" or "tetrahedral"” Gunasekera [Col.11 Ln.35])
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such that one face of a tetrahedral cell corresponds to a triangular mesh of a meshed surface (“Cells for 3D TET and PEBI grids are generated in a manner analogous to their 2D counterparts using tetrahedra...The surface of a cell face is defined by a local triangulation of its vertices” Gunasekera [Col.27 Ln.4-5] Examiner interprets “cell face” to mean “sedimentary surfaces” in light of FIGS 13a and 13b.),
and the summit of the tetrahedral cell belongs to an adjacent meshed surface. (“In FIG. 18, points v1,v2,v3 and v4 are cell vertices; c1,c2,c3 and c4 are cell centers and m12, m13 and m14 are intersection points of cell faces and lines joining centers” Gunasekera [Col.21 Ln. 45-47]. Examiner interprets “cell vertices” to mean “summit of the tetrahedral cell” and to belong to an “adjacent sedimentary surface” in light of FIG.18).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Khan to include meshed surfaces and tetrahedral cells, as disclosed by Gunasekera, in order to generate “a corresponding plurality of "more accurate" information relating, for example, to the transmissibility properties of the plurality of cells of the grid, the plurality of "more accurate" information being input to a conventional simulator which generates a corresponding plurality of simulation results (such as pressures and saturations)” Gunasekera [Col.1 Ln.26-32].
Regarding claim 4, Khan-Gunasekera-Begg-Usadi disclose the method according to claim 1, although Khan fails to specifically disclose wherein a modeled meshed surface having a transmissivity reduction coefficient of 0 represents a shale layer of the subsurface reservoir.
However, Begg further discloses wherein a modeled meshed surface having a transmissivity reduction coefficient of 0 represents a shale layer of the subsurface reservoir. (“This method requires the shales to be defined on a fine-scale numerical grid similar to that described for the simulation method. The major difference is that, at present, the sand permeability must be constant and that of the shale zero.” Begg [Pg.4 Sec.2.3.2]. The shale permeability (i.e. KVE) is interpreted to include a transmissivity reduction coefficient because “Using this scheme KVE is calculated using equation (21) where: Si = H+
∑
j
=
1
H
s
+
1
r
l
j
(22) and s = number of shales per metre (e.g. from well cores or logs),
r
= random number between 0 and 1, Ij = length of the jth shale taken from CDF” Begg [Pg.4 Sec.2.3.3]. Note: “r” is interpreted as a transmissivity reduction coefficient due to Applicant’s disclosure “The value of the transmissivity reduction coefficient is assigned to each sedimentary surface by a user according to its knowledge of the sedimentary structure to be modelled.” Spec. [Pg.7 Ln.29]. i.e. the coefficient is a user assigned random number.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention have modified the teachings of Khan to include Begg’s user assigned transmissivity reduction coefficient of 0 to represent a shale layer, in order to quickly and efficiently model impervious layers of lithology.
Regarding claim 6, Khan-Gunasekera-Begg-Usadi disclose the method according to claim 1, although Khan fails to specifically disclose wherein the petrophysical parameters comprise at least porosity and permeability values.
However, Gunasekera further discloses wherein the petrophysical parameters comprise at least porosity and permeability values (“The primary property values within each cell include porosity, permeability, net to gross, as well as other primary cell based properties. Secondary properties in each cell, such as pore volumes and transmissibilities, are calculated using the primary property values and the cell geometry.” Gunasekera [Col.28 Ln.35-40])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Khan to include petrophysical parameters comprising at least porosity and permeability values, as disclosed by Gunasekera, in order to generate “a corresponding plurality of "more accurate" information relating, for example, to the transmissibility properties of the plurality of cells of the grid, the plurality of "more accurate" information being input to a conventional simulator which generates a corresponding plurality of simulation results (such as pressures and saturations)” Gunasekera [Col.1 Ln.26-32].
Regarding claim 7, Khan-Gunasekera-Begg-Usadi disclose the method according to claim 6, Khan further discloses wherein the upscaling is performed by providing a coarse-scale grid comprising a plurality of cells (“A method is provided for scaling up permeabilities associated with a fine-scale grid of cells representative of a porous medium to permeabilities associated with an unstructured coarse-scale grid of cells representative of the porous medium. The first step is to generate an areally unstructured, Voronoi, computational grid using the coarse-scale grid as the genesis of the computational grid.” Khan [Col.4 Ln.16-23]),
each cell having dimensions greater than a plurality of cells of the fine-scale model, (“The cells of the computational grid are smaller than the cells of the coarse-scale grid ” Khan [Col.4 Ln.24])
and the upscaling of the permeability values is performed by computing equivalent fluid flow values of the cells of the coarse-scale grid from fluid flow values of the cells of the fine-scale grid and inferring equivalent permeability values of the coarse-scale grid. (“The computational grid is then populated with permeabilities associated with the fine-scale grid. Flow equations, preferably single-phase, steady-state pressure equations, are developed for the computational grid, the flow equations are solved, and inter-node fluxes and pressure gradients are then computed for the computational grid. These inter-node fluxes and pressure gradients are used to calculate inter-node average fluxes and average pressure gradients associated with the coarse-scale grid. The inter-node average fluxes and average pressure gradients associated with the coarse grid are then used to calculate upscaled permeabilities associated with the coarse-scale grid.” Khan [Col.4 Ln.26-39])
Regarding claim 12, Khan, in view of Gunasekera, in view of Begg, in further view of Usadi disclose the method according to claim 1, although Khan fails to specifically disclose a non-transitory computer readable storage medium, having stored thereon a computer program comprising program instructions, the computer program being loadable into a computer and adapted to cause the computer to carry out the steps of the method according to claim 1, when the computer program is run by the computer.
However, Gunasekera further discloses A non-transitory computer readable storage medium, having stored thereon a computer program comprising program instructions, the computer program being loadable into a computer and adapted to cause the computer to carry out the steps of the method according to claim 1, when the computer program is run by the computer. (“The subject matter of the present invention relates to a workstation based software method and apparatus, which is responsive to received seismic data and well log data, for generating a grid composed of a plurality of individual cells which is imposed upon each horizon of an earth formation and further generating a corresponding plurality of "more accurate" information relating, for example, to the transmissibility properties of the plurality of cells of the grid, the plurality of "more accurate" information being input to a conventional simulator which generates a corresponding plurality of simulation results (such as pressures and saturations) pertaining, respectively, to the plurality of cells of the grid, the plurality of simulation results being overlayed, respectively, upon the plurality of cells of the grid so that a new simulation result is associated with each cell of the grid, the cells of the grid and the new simulation results associated therewith being displayed on the workstation display monitor for viewing by an operator of the workstation.” Gunasekera [Col.1 Ln.20-40])
Gunasekera discloses the limitations of claim 12 and maintains the same rationale for combination with Khan as claim 1.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Khan, in view of Gunasekera, in view of Begg, in further view of Usadi, and in further view of Le Ravalec et al. US Pub. No. 2013/0346049 A1 (hereinafter referred to as “Le Ravalec”).
Regarding claim 5, Khan-Gunasekera-Begg-Usadi disclose the method according to claim 1, but fail to specifically disclose wherein the attributing petrophysical parameters to each three-dimensional cell of the grid of the fine-scale three-dimensional model comprises: determining a number of lithology types within the fine-scale three-dimensional model and defining each lithology type, determining a distribution pattern of the lithology types within the grid, and attributing to each cell petrophysical parameters according to the determined distribution pattern.
However, Le Ravalec discloses wherein the attributing petrophysical parameters to each three-dimensional cell of the grid of the fine-scale three-dimensional model comprises: (“A reservoir model... has a grid with N dimensions (N>0 and generally equal to two or three) in which each of the mesh cells is assigned the value of a property characteristic of the area being studied. It may be, for example, the porosity, the permeability (horizontal or vertical) or the facies...Thus, a model is a grid” Le Ravalec [P.0091], “A property characteristic of the area being studied is represented by a random variable (V), which can be continuous or discrete... The petrophysical properties such as saturation, porosity or permeability are associated with continuous variables, whereas the facies, of which there are a finite number, are associated with discrete variables.” Le Ravalec [P.0092])
determining a number of lithology types within the fine-scale three-dimensional model and defining each lithology type, (“In the case of the discrete variables, the realizations can take only a finite number of values such as, for example, 1, 2 or 3, which are the identifiers of a class (for example a facies)” Le Ravalec [P.0126]. Examiner interprets “realizations” to mean “determining” and “1, 2 or 3, which are the identifiers of a class (for example a facies)” to mean “defining each lithology type”.)
determining a distribution pattern of the lithology types within the grid (“A random path is defined for sequentially visiting all the mesh cells of the second model MR2” Le Ravalec [P.0112]. Examiner interprets “random path is defined for sequentially visiting” as “determining a distribution pattern”. The “second model MR2” is interpreted as the fine-scale model because “MR2 is considered to be a model on a second scale, called a fine-scale model” Le Ravalec [P.0094] and the model is interpreted to include “lithology types within the grid” due to the reasons given within claim limitations above.),
and attributing to each cell petrophysical parameters according to the determined distribution pattern. (“A random path is defined for sequentially visiting all the mesh cells of the second model MR2... For each mesh cell i of this path, a. If the mesh cell i contains a value, go directly to step b, and if the mesh cell i does not contain any value, i. Identify the vicinity of the mesh cell in the first and second grids and in this neighborhood, recognize the mesh cells that have known values of V2 and/or V1... ii. Compute the mean m and the variance” Le Ravalec [P.0112-0116]. Examiner interprets “V2” to include “petrophysical parameters” because “a second random variable V2 is defined... This random variable characterizes the petrophysical property considered in the second scale, called fine scale.” Le Ravalec [P.0101])
Le Ravalec is analogous art as it relates to oil/gas reservoir modelling. Its intended use is to construct and parameterize reservoir models at multiple scales to integrate static and dynamic data for accurate reservoir representation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the reservoir model methods of Khan-Gunasekera-Begg-Usadi with the petrophysical parameters, as determined by Le Ravalec, in order to establish reservoir models that are more “consistent with the various data collected in the field” Le Ravalec [P.003].
Claims 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Khan, in view of Gunasekera, in view of Begg, in further view of Usadi, and in further view of Freeman et al. US Patent No. 10571601 B2 (hereinafter referred to as “Freeman”).
Regarding claim 9, Khan in view of Gunasekera, in further view of Begg, and in further view of Usadi, disclose the method according to claim 1, but fail to specifically disclose wherein the modelling of the plurality of meshed surfaces comprises: selecting a bedform type to be modelled among a library of previously established bedform types, wherein each bedform type defines a disposition of a plurality of sedimentary surfaces, and parameterizing the selected bedform type.
However, Freeman discloses wherein the modelling of the plurality of meshed surfaces comprises: selecting a bedform type to be modelled among a library of previously established bedform types, wherein each bedform type defines a disposition of a plurality of sedimentary surfaces, and parameterizing the selected bedform type. (“The model simulation layer 180 may be configured to model projects. As such, a particular project may be stored where stored project information may include inputs, models, results and cases. Thus, upon completion of a modeling session, a user may store a project. At a later time, the project can be accessed and restored using the model simulation layer 180” Freeman [Col.7 Ln.35-39]. Examiner interprets “project” to include “bedform types”, “plurality of meshed surfaces” and “parameterizing” said bedform type because “A convention such as the convention 240 may be used with respect to an analysis, an interpretation, an attribute, etc. (see, e.g., various blocks of the system 100 of FIG. 1). As an example, various types of features may be described, in part, by dip (e.g., sedimentary bedding, faults and fractures, cuestas, igneous dikes and sills, metamorphic foliation, etc.” Freeman [Col.10 Ln. 56-58]. Examiner interprets “sedimentary bedding” to mean “bedform”. Examiner also interprets storing a model and then accessing it at a later time to mean “selecting a bedform type to be modelled among a library of previously established bedform types”.)
Freeman is analogous art as it relates to modeling and simulation of geological environments, particularly sedimentary basins containing discontinuities such as fault, along with numerical simulations of physical phenomena like fluid flow. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Khan-Gunasekera-Begg-Usadi combination to include model library functionality, as taught by Freeman, in order to integrate previously established geological models for simulation.
Regarding claim 10, Khan in view of Gunasekera, in view of Begg, in further view of Usadi, and in further view of Freeman, disclose the method according to claim 9, although Khan fails to specifically disclose wherein the parameterizing of the selected bedform type is performed according to at least one of the following parameters: wavelength of a cyclic geometric pattern of the sedimentary surfaces included in the bedform type, steepness of said cyclic geometric pattern, angular orientation of said cyclic geometric pattern, number of sedimentary surfaces, and mean thickness between two adjacent sedimentary surfaces.
However, Freeman further discloses wherein the parameterizing of the selected bedform type is performed according to at least one of the following parameters: wavelength of a cyclic geometric pattern of the sedimentary surfaces included in the bedform type, steepness of said cyclic geometric pattern, angular orientation of said cyclic geometric pattern, number of sedimentary surfaces, and mean thickness between two adjacent sedimentary surfaces (“Seismic interpretation may aim to identify and/or classify one or more subsurface boundaries based at least in part on one or more dip parameters (e.g., angle or magnitude, azimuth, etc.). As an example, various types of features (e.g., sedimentary bedding, faults and fractures, cuestas, igneous dikes and sills, metamorphic foliation, etc.) may be described at least in part by angle, at least in part by azimuth, etc.” Freeman [Col.10 Ln. 64-68]. Examiner interprets “sedimentary bedding” to mean “bedform”.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Khan to include parameterization of bedform type, as taught by Freeman, in order “to identify and/or classify one or more subsurface boundaries based at least in part on one or more dip parameters” Freeman [Col.10 Ln.65].
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Khan, in view of Gunasekera, in view of Begg, in further view of Usadi, and in further view of Sebastian Bosma, Hadi Hajibeygi, Matei Tene, Hamdi A. Tchelepi, Multiscale finite volume method for discrete fracture modeling on unstructured grids (MS-DFM), Journal of Computational Physics, Volume 351, 2017, Pages 145-164 (hereinafter referred to as “Bosna”), (prior art of record not relied upon cited in Office Action dated 3/24/2025).
Claim 14 (new), Khan in view of Gunasekera, in view of Begg, in further view of Usadi disclose the method of claim 1, but fail to specifically disclose wherein the fluid flow Q through a face, of surface
S
, of a cell of the coarse-scale geological model, the face being orthogonal to the direction of the flow, is computed by implementing the equation:
Q
=
∑
S
q
s
⃑
(
M
u
l
t
S
)
.
S
where
s
designates all the two-dimensional meshed surfaces representing impervious layers of lithology comprised within the cell of the coarse-scale geological model, and
M
u
l
t
S
is the transmissivity reduction coefficient associated with a two-dimensional meshed surface
S
.
However, Bosna discloses wherein the fluid flow Q through a face, of surface
S
, of a cell of the coarse-scale geological model, the face being orthogonal to the direction of the flow, is computed by implementing the equation:
Q
=
∑
S
q
s
⃑
(
M
u
l
t
S
)
.
S
where
s
designates all the two-dimensional meshed surfaces representing impervious layers of lithology comprised within the cell of the coarse-scale geological model, and
M
u
l
t
S
is the transmissivity reduction coefficient associated with a two-dimensional meshed surface
S
(“the discrete system can be obtained as follows. For every cell i:
∑
j
=
1
n
n
b
T
i
j
p
j
-
p
i
=
q
,
where
n
n
b
is the number of neighbors (i.e. all the 2D meshed surfaces) and
T
i
j
, the transmissibility (i.e. transmissivity) between cell
i
and neighbor cell
j
, which is computed as the harmonic average of the two half-transmissibility values from cell-center to face, according to
T
i
j
=
T
i
f
T
i
f
T
i
f
+
T
i
f
, and
T
i
j
=
A
f
*
(
n
→
f
*
k
*
n
→
f
)
n
→
f
*
v
f
→
. Here,
f
and
c
indicate face and cell, respectively. Hence, the variable
A
f
represents the face area, the unit normal (i.e. orthogonal) vector to the face, the vector from the cell center to any point on the face and
k
the permeability tensor. Figure 1 depicts these quantities in a two-dimensional (2D) cell.” Bosna [Pg.3]. The equations are interpreted to apply to coarse-scale geological model because “ the MSFV approximates the fine scale solution by solving a coarse system constructed with overlapping local problem solutions - i.e., basis functions and a volume-based integration operator. Once the global coarse-scale
system is solved, the solution is interpolated to the fine scale. Thus, the coarse system accounts for the fine scale heterogeneous properties through the use of these physics-based basis functions.” Bosna [Pg.4])
Bosna is analogous art as it relates to coarse-scale modeling of subsurface structures using unstructured grids. Bosna discloses “A multiscale method for Discrete Fracture Modeling (DFM) using unstructured grids is developed. The fine-scale discrete system is obtained by imposing tetrahedron (triangular for 2D domains) shaped grid cells, while lower-dimensional fractures are imposed at the grid interfaces. The DFM approach is then used to describe the transmissibility coefficients for all the interfaces, including those with the lower-dimensional fractures” [Abstract]. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Khan to include implementing the flow equation of Bosna in order for “accurate and efficient simulation of fractured subsurface formations” Bosna [Pg.1 Intro.].
Conclusion
The prior art made of record, listed on form PTO-892, and not relied upon is
considered pertinent to applicant's disclosure:
Darman, N. H., G. E. Pickup, and K. S. Sorbie. "A comparison of two-phase dynamic upscaling methods based on fluid potentials." Computational Geosciences 6, no. 1 (2002): 5-27. “an assessment of several upscaling methods, namely the Kyte and Berry (KB) method, the Stone method, the Hewett and Archer (HA) method and the Transmissibility-Weighted (TW) method.” [Abstract]
Jackson, Matthew D., et al. "Reservoir modeling for flow simulation using surfaces, adaptive unstructured meshes and control-volume-finite-element methods." SPE Reservoir Simulation Conference. Spe, 2013. “We present new approaches to reservoir modeling and flow simulation that dispose of the pillar-grid concept that has
persisted since reservoir simulation began. This results in significant improvements to the representation of multi-scale geological heterogeneity and the prediction of flow through that heterogeneity.” [Abstract]
Jackson, MD D., et al. "Reservoir modeling for flow simulation by use of surfaces, adaptive unstructured meshes, and an overlapping-control-volume finite-element method." SPE Reservoir Evaluation & Engineering 18.02 (2015): 115-132. “The resulting model is discretized for flow simulation by use of an unstructured, tetrahedral mesh that honors the architecture of the surfaces. This approach allows heterogeneity over multiple length-scales to be explicitly captured by use of fewer cells than conventional cornerpoint or unstructured grids.” [Pg.115 Col.1 P.2]
Applicant' s amendment necessitated the new ground(s) of rejection presented in this Office Action. Accordingly, THIS ACTION IS MADE FINAL. 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.
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/ANTHONY CHAVEZ/ Examiner, Art Unit 2186
/RENEE D CHAVEZ/ Supervisory Patent Examiner, Art Unit 2186
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