DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 6/20/25 has been entered.
Response to Arguments
Response: 35 U.S.C. § 101
1. Applicants argue:
The applicant argues that the current claims are not directed towards an abstract idea, but rather are an improvement to computer-aided exploration technology. The applicant points to the recently amended limitation of claim 1 that states “wherein the algorithmic solver generates a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan” as a limitation that cannot be conducted in the human mind or with pencil and paper. (Remarks: pages 7-8)
2. Examiner Response:
The examiner notes that with the recent amendment that states “wherein the algorithmic solver generates a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan”, this limitation is solving a multi-objective optimization problem. In paragraph [0010] it states that the algorithmic solver is based on a heuristic or linear algorithm; a metaheuristic algorithm; a metaheuristic SCP algorithm, etc. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Also, the examiner notes that the computer is an additional element. The computer would be recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Further, the examiner notes that the limitations of claim 1 that have not been amended are abstract, where they do not integrate the abstract idea into a practical application.
3. Applicants argue:
The applicant argues that even if the claims were considered abstract under step 2A Prong 1, the current claims integrate the abstract idea into a practical application. The applicant points to the amended limitation of claim 1 that states “wherein the algorithmic solver generates a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan” that results in a tangible technical improvement, where a more efficient and cost-effective drill plan, leading to less wasted drilling and a better understanding of the mineral deposit. (Remarks: pages 8-9)
4. Examiner Response:
The examiner notes that computer is an additional element. The computer would be recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Also, the recent amendment that states “wherein the algorithmic solver generates a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan” this limitation is solving a multi-objective optimization problem. In paragraph [0010] it states that the algorithmic solver is based on a heuristic or linear algorithm; a metaheuristic algorithm; a metaheuristic SCP algorithm, etc. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Further, the applicant argues that the current claims results in a tangible technical improvement, where a more efficient and cost-effective drill plan. The examiner notes that in MPEP 2106.05(f) (2) it states “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not “provide a sufficient inventive concept.” Intellectual Ventures I LLC v. Capital One Bank (USA) (“Intellectual Ventures v. Capital One Bank”), 792 F.3d 1363, 1367 (Fed. Cir. 2015).
5. Applicants argue:
The applicant argues that the drilling limitation of claim 1 is not insignificant post-solution activity. The applicant argues that the drilling is the concrete, physical culmination of the planning method, demonstrating that the process results in a tangible, real-world action, where the output is not merely data, but a specific, executable plan for a physical industrial process. (Remarks: page 9)
6. Examiner Response:
The examiner respectfully disagrees. The examiner notes that the drilling limitation of claim 1 that states “drilling the sampling holes based on the mineral resource exploration or classification sampling drill plan using the drilling equipment” amounts to mere instructions to apply an exception, where it recites an idea of a solution. This limitation doesn’t indicate what the mineral resource exploration or the classification sampling drill plan is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The 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".
Response: 35 U.S.C. § 103
Applicants argue:
The applicant argues that the prior art of record is not analogous art to the claimed invention. (Remarks: pages 10-11)
8. Examiner Response:
The examiner respectfully disagrees. The examiner notes that the Sequerira JR, et al.
reference teaches that the process of designing a drill well to produce or inject oil, gas or other fluids involves planning and designing a well path trajectory to optimally produce from or inject into an underground reservoir. The Pop et al. reference teaches planning and dynamically updating sampling operations while drilling in a subterranean formation. This demonstrates that the Sequerira, JR et al. and Pop et al. references teach the claim language of the current application of generating an optimized drill plan for drilling sampling holes in a geological volume of earth for mineral resource exploration and classification. The examiner considers the oil and/or gas to be the mineral resource that the drill plan is being generated for, see paragraphs [0005] and [0019] of the Sequerira JR, et al. and paragraph [0105] of the Pop et al. reference.
Applicants argue:
The applicant argues that the recent amendment that states “wherein the algorithmic
solver generates a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan” is not taught by the Sequerira JR, et al. reference. (Remarks: pages 11-12)
10. Examiner Response:
The examiner notes that the specification doesn’t show support for the recent
amendment to claim 1 that states “wherein the algorithmic solver generates a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan”. The specification doesn’t mention of simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan. In paragraph [0078] of the specification it states “[0078] In certain further embodiments, the algorithmic solver and/or resulting drill plan may be constrained by a budget constraint such that only drill plans meeting a specified budget constraint will be allowed or produced. A budget constraint may include, for example, one or more of constraints which limit the allowable total drill hole length of the drill plan, the drill hole length of individual drill holes, the total number of setup locations, the total time or predicted time to drill the plan, the location or position of drill holes, the collar locations, and/or may limit drill holes to positions which are more easily accessible, for example. A budget constraint may limit, for example, aggregate drill hole length of the drill plan. In an embodiment, the algorithmic solver may aim to generate a drill plan which attempts to maximize the number of sub-volumes sampled or classified by the drill holes of the drill plan while minimizing the total planned drill length of the drill plan, or while attempting to maximize the number of sub-volumes sampled or classified per unit of planned drill length (i.e., per meter, or per foot).”. In paragraph [0100] states “[0100] In certain embodiments, the modelled SCP of the method may divide the exploration site into blocks or sub-volumes within a target volume, and the solution to the SCP may attempt to maximize or improve the number of blocks or sub-volumes sampled by a collection of drill holes while also minimizing, reducing, or capping the total number of drill holes and/or the total drill hole length in the collection.”. These paragraphs don’t mention generating a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan. For the purpose of examination, the examiner considers the algorithmic solver generating a drill plan that maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan.
Claim Rejections - 35 USC § 112
11. The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-19 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first
paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. In claim 1, the examiner has not seen any written description of “wherein the algorithmic solver generates a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan”. In paragraph [0078] of the specification it states “[0078] In certain further embodiments, the algorithmic solver and/or resulting drill plan may be constrained by a budget constraint such that only drill plans meeting a specified budget constraint will be allowed or produced. A budget constraint may include, for example, one or more of constraints which limit the allowable total drill hole length of the drill plan, the drill hole length of individual drill holes, the total number of setup locations, the total time or predicted time to drill the plan, the location or position of drill holes, the collar locations, and/or may limit drill holes to positions which are more easily accessible, for example. A budget constraint may limit, for example, aggregate drill hole length of the drill plan. In an embodiment, the algorithmic solver may aim to generate a drill plan which attempts to maximize the number of sub-volumes sampled or classified by the drill holes of the drill plan while minimizing the total planned drill length of the drill plan, or while attempting to maximize the number of sub-volumes sampled or classified per unit of planned drill length (i.e., per meter, or per foot).”. In paragraph [0100] states “[0100] In certain embodiments, the modelled SCP of the method may divide the exploration site into blocks or sub-volumes within a target volume, and the solution to the SCP may attempt to maximize or improve the number of blocks or sub-volumes sampled by a collection of drill holes while also minimizing, reducing, or capping the total number of drill holes and/or the total drill hole length in the collection.”. There’s no mentioning of an algorithmic solver generating a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan. For the purpose of examination, the examiner considers the algorithmic solver generating a drill plan that maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan. Also, dependent claims 2-19 are also rejected under 35 U.S.C. 112(a), since these claims depend upon claim 1.
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 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Under the broadest reasonable interpretation, the claims cover performance of the limitation in the mind or by pencil and paper and as a mathematical concept.
Claim 1
Regarding step 1, claim 1 is directed towards a method, which has the claims fall within the eligible statutory categories of processes, machines, manufactures and composition of matter under 35 U.S.C. 101.
Claim 1
Regarding step 2A, prong 1, claim 1 recites “producing a mineral resource exploration or classification sampling drill plan”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “whereby the mineral resource exploration or classification sampling drill plan is produced by: - defining one or more target volumes of interest containing a mineral deposit or suspected mineral deposit in 3D space”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “segmenting the one or more target volumes into a plurality sub-volumes in the form of blocks to which one or more attributes indicating relative desirability may be assigned”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Also, the limitation is segmenting the one or more target volumes into a plurality sub-volumes in the form of blocks. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Claim 1 recites “iteratively generating and improving a drill plan using an algorithmic solver executed by a processor”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “wherein the drill plan aims to provide an optimal or near optimal solution for drill hole distribution within the one or more target volumes containing a mineral deposit or suspected mineral deposit such that all or nearly all the sub-volumes, or at least the sub-volumes of greatest desirability, of the one or more target volumes containing a mineral deposit or suspected mineral deposit are sampled to a specified or desired level”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “wherein the resulting drill plan comprises a collection of one or more planned drill holes which are defined in 3D space”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “wherein a set of operational constraints constrains the iteratively generated and improved drill plan”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “and wherein the algorithmic solver generates a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan”. This limitation is solving a multi-objective optimization problem. In paragraph [0010] it states that the algorithmic solver is based on a heuristic or linear algorithm; a metaheuristic algorithm; a metaheuristic SCP algorithm, etc. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Clam 1 recites “Claim 1 recites “wherein the mineral resource exploration or classification sampling drill plan produced identifies the drill holes to be drilled by drilling equipment”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Regarding step 2A, prong 2, the limitation of including obtaining information from a drill rig to be supplied to the algorithmic solver for the iteratively generating amounts to insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of graphically presenting the drill plan using an interface communicatively connected to the processor amounts to insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “drilling the sampling holes based on the mineral resource exploration or classification sampling drill plan using the drilling equipment” amounts to mere instructions to apply an exception, where it recites an idea of a solution. This limitation doesn’t indicate what the mineral resource exploration or the classification sampling drill plan is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The 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".
Further, the claim recites the additional element of a processor. The processor would be recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Regarding Step 2B, the limitations of “including obtaining information from a drill rig to be supplied to the algorithmic solver for the iteratively generating” and “graphically presenting the drill plan using an interface communicatively connected to the processor” are also shown to reflect the court decisions of Versata Dev. Group, Inc. v. SAP Am., Inc. iv. Storing and retrieving information in memory, shown in MPEP 2106.05(d) (II).
Also, the limitation of “drilling the sampling holes based on the mineral resource exploration or classification sampling drill plan using the drilling equipment” amounts to mere instructions to apply an exception, where it recites an idea of a solution. This limitation doesn’t indicate what the mineral resource exploration or the classification sampling drill plan is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The 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".
Further, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of the computer amounts no more than mere instructions to apply the exception using a generic computer component that does not impose any meaningful limits on practicing the abstract idea and therefore cannot provide an inventive concept (See MPEP 2106.05(b).
Claim 2
Dependent claim 2 recites “wherein the set of operational constraints comprises a historical drill hole locations constraint, a potential drilling setup location constraint, a drilling direction constraint, a drilling dips constraint, a drilling azimuth constraint, a drilling budget constraint, a sampling requirement constraint, a drilling setup availability constraint, a constraint regarding distribution of drill holes from setups, a constraint regarding the total amount of surface ground disturbance, a topographical constraint, an environmental constraint, a constraint regarding environmental exclusion zones, a geological fault constraint, a geological contacts constraint, a geological structure constraint, or a constraint regarding existing underground workings or operations, or any combination thereof”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 3
Dependent claim 3 recites “wherein the algorithmic solver is based on a heuristic algorithm, a linear algorithm, a metaheuristic algorithm, a metaheuristic SCP algorithm, a localized random search, a modified random search, an annealing algorithm, a taboo search, or a multiple metaheuristic algorithm comprising a genetic algorithm component, a taboo search algorithm and an iterated local search algorithm”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 4
Dependent claim 4 recites “wherein the one or more attributes indicating relative desirability of a sub-volume are selected from one or more of: - distance of the sub-volume from an existing drill hole; - estimate variance; - grade estimates; - bounding of the sub-volume by site specific geological contacts, structures, or faults; or - variability or uncertainty of sub-volume grade estimation or interpolation”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 5
Dependent claim 5 recites “wherein the drill plan aims to sample sub-volumes of the one or more target volumes such that a highest aggregate desirability is achieved”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Dependent claim 5 recites “wherein an aggregate desirability primarily considers a value of resource classification, an identification of geological features bounding the one or more target volumes, or a combination thereof”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 6
Dependent claim 6 recites “wherein the drill plan is iteratively improved by improving a global distribution of drill holes within the drill plan based on newly acquired information as drilling operations progress”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. This limitation doesn’t indicate how the improving is being conducted or what the acquired information is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The 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".
Claim 7
Dependent claim 7 recites “wherein the specified or desired level is selected from a range spanning geological, inferred, indicated, measured resource, and probable or proven reserve”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 8
Dependent claim 8 recites “wherein the specified or desired level is at least about 60% indicated while minimizing measured.”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 9
Dependent claim 9 recites “wherein the algorithmic solver aims to generate a drill plan which attempts to maximize a number of sub-volumes sampled or classified per unit of planned drill length”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 10
Dependent claim 10 recites “wherein the drill plan provides a ranking for each planned drill hole which is based on a relative value of each planned drill hole to an overall drill plan, and wherein one or more of a lowest ranked drill holes are eliminated from the drill plan”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 11
Dependent claim 11 recites “wherein the ranking includes a penalty for moving a drill hole of the drill plan away from a position at the one or more target volumes which is easily drilled, or away from a position at the one or more target volumes at which drilling equipment is already located.”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 12
Dependent claim 12 recites “wherein the relative value to the drill plan of changing one or more collar locations while dynamically updating dip and dip direction is assessed.”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 13
Dependent claim 13 recites “wherein the iteratively generated drill plans are scored by a resource conversion calculator”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Dependent claim 13 recites “and the algorithmic solver improves a drill plan score using one or more parameters which are changed using a constraint modifier between iterations”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Dependent claim 13 recites “and wherein the constraint modifier changes or flexes one or more parameters selected from a historical drill hole locations constraint, a potential drilling setup location constraint, a drilling direction constraint, a drilling dips constraint, a drilling azimuth constraint, a drilling budget constraint, a sampling requirement constraint, a drilling setup availability constraint, a constraint regarding distribution of drill holes from setups, a constraint regarding the total amount of surface ground disturbance, a topographical constraint, an environmental constraint, a constraint regarding environmental exclusion zones, a geological fault constraint, a geological contacts constraint, a geological structure constraint, or a constraint regarding existing underground workings or operations, or any combination thereof, the specified or desired level, or a combination thereof, between iterations”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 14
Dependent claim 14 recites “wherein the scoring of the drill plans includes rewarding drill plans which provide information about location of geological structures and contacts of the one or more target volumes, or rewarding drill plans which have a reasonable probability of success”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 15
Dependent claim 15 recites “wherein the method is an iterative method which is repeated using input which is based on newly acquired information obtained from drilling one or more planned drill holes from a previously generated drill plan”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Dependent claim 15 recites “wherein the one or more planned drill holes from the previously generated drill plan are drill holes which have been drilled quickly but with reduced precision for geological drilling or bounding of the one or more target volumes, allowing in-fill planning, and improving the drill plan with less invested time.”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 16
Dependent claim 16 recites “wherein the orientation of a drill hole of the drill plan can be recalculated in real-time to accommodate for on-site drilling limitations”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Dependent claim 16 recites “and wherein the on-site drilling limitations are any one of drill site accessibility, drill hole geometry, drill hole timing limitations, a requirement for movement of the drill rig, setup availability, or any combination thereof”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 17
Dependent claim 17 recites “wherein a completion constraint is used to identify a point at which sufficient drilling has been completed”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Dependent claim 17 recites “and wherein the point at which sufficient drilling has been completed is a point at which further increase in drill hole density provides additional value which is below a specified threshold”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 18
Dependent claim 18 recites “wherein the method further comprises: - using implicit modeling to model geological contacts, faults, shells, and surfaces”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Dependent claim 18 recites “and - updating the implicit modeling of the one or more target volume surfaces, geological structures, geological contacts, or a combination thereof, as drill hole data is acquired”. This limitation amounts to mere instructions to apply an exception, where it recites an idea of a solution. This limitation doesn’t indicate how the updating is occurring or what the drill hole data is. See MPEP 2106.05 (f) (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The 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".
Dependent claim 18 recites “thereby dynamically identifying high value sub-volumes to be converted from unclassified to geological, inferred, indicated, or measured”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Dependent claim 18 recites “and wherein the drill plan is recalculated and the scoring of the resulting drill plan includes a reward for solutions which allow for conversion of the identified high value sub-volumes from unclassified to inferred, indicated or measured”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Also, this limitation is recalculating the drill plan. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Claim 19
Dependent claim 19 recites “wherein drill holes of the drill plan are ranked based on their value to the drill plan, and this ranking is used to indicate which holes of the drill plan should be drilled first.”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claims 1-19 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness
rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35
U.S.C. 103 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.
Claim(s) 1-3, 7-14, 16 and 18-19 is/are rejected under 35 U.S.C. 103 as being
unpatentable over Sequeira, JR, et al. (U.S. PGPub 2013/0140037) (from IDS dated 5/28/21) in view of Pop et al. (U.S. PGPub 2011/0266056).
With respect to claim 1, Sequeira, JR, et al. discloses “A computer-implemented method for generating an optimized drill plan for drilling sampling holes in a geological volume of earth for mineral resource exploration and classification, said method performed by a computer system comprising a processor” as [Sequerira, JR et al. (paragraph [0005] “The process of designing a drill well to produce or inject oil, gas, or other fluids involves planning and designing a well path trajectory to optimally produce from or inject into an underground reservoir.”, Sequerira, JR et al. paragraph [0019] “One exemplary embodiment relates to a method for producing hydrocarbons from an oil and/or gas field using a physical property model representative of a physical property of the oil and/or gas field. This exemplary method comprises defining a proxy constraint volume as a 3D cellular volume where each cell has at least one value derived from data from a 3D earth model representing the oil and/or gas field.”, Sequerira, JR et al. paragraph [0023] “The exemplary computer system may comprise a processor and a non-transitory, computer-readable storage medium that stores computer-readable instructions for execution by the processor.”, Sequerira, JR et al. paragraph [0066] “For well path optimization, a set of conditions and/or constraints for an acceptable well trajectory is defined (block 202). The conditions may include minimizing total drilling costs, and maximizing the well profitability through sufficient hydrocarbon volumes, and production rates, etc. Constraints can include, but are not limited to, minimum distance to certain subsurface structures, minimum distance to other well paths, maximum reach from a drill center, and maximum well inclination, etc. A constraint optimization process is then used to automatically iterate through potential well trajectories based on the given conditions and constraints, as shown by blocks 208 through 212.”, The examiner considers the oil and/or gas to be the mineral resource that the drill plan is being generated for)];
“producing a mineral resource exploration or classification sampling drill plan” as [Sequerira, JR et al. (paragraph [0096] “Once the distance proxy constraint volume is created, the optimization process may first propose a new well trajectory starting from one of the available slot locations in a drill center 618. The well path segments are created based on defined drilling algorithms and pre-set constraints. The path should pass through the top and base of the targeted reservoir areas 614, 616. All the cells intersected by the well path can then be identified”, Sequerira, JR et al. paragraph [0097] “Once a valid well trajectory is obtained, the total cost of the well trajectory can then be calculated. The same process could be repeated for fixed number of iterations or until the optimization analysis has converged.”)];
“- defining one or more target volumes of interest containing a mineral deposit or suspected mineral deposit in 3D space” as [Sequerira, JR et al. (paragraph [0005] “The process of designing a drill well to produce or inject oil, gas, or other fluids involves planning and designing a well path trajectory to optimally produce from or inject into an underground reservoir.”, Sequerira, JR et al. paragraph [0015] “An exemplary method comprises defining a proxy constraint volume as a 3D cellular volume where each cell has at least one value derived from data from a 3D earth model. An initial well path is defined within user defined drilling parameter constraints”, Sequerira, JR et al. paragraph [0019] “One exemplary embodiment relates to a method for producing hydrocarbons from an oil and/or gas field using a physical property model representative of a physical property of the oil and/or gas field. This exemplary method comprises defining a proxy constraint volume as a 3D cellular volume where each cell has at least one value derived from data from a 3D earth model representing the oil and/or gas field.”, The examiner notes that the phrase “mineral deposit” isn’t defined within the claims or the specification. The examiner considers the hydrocarbons to be the mineral deposit, where the hydrocarbons can be found in natural gas and crude oil or petroleum)];
“segmenting the one or more target volumes into a plurality sub-volumes in the form of blocks to which one or more attributes indicating relative desirability may be assigned” as [Sequerira, JR et al. (paragraph [0061] “Moreover, the data contained in a proxy constraint volume may be used to determine whether property data in a corresponding cell of the data volume 100 is within an acceptable range specified by one or more constraint parameters.”, Sequerira, JR et al. (paragraph [0062] “Each cell of the proxy constraint volume may contain initial gathered, aggregated and/or derived information such as, but not limited to, reservoir connectivity properties, anti-collision distance attributes between subsurface objects, geologic properties, and/or engineering properties at the geographical location of the cell.”, The examiner considers the cells of the Sequerira, JR et al. reference to be the blocks, since the cells contain data volume)];
“and - iteratively generating and improving a drill plan using an algorithmic solver executed by a processor, wherein the drill plan aims to provide an optimal or near optimal solution for drill hole distribution within the one or more target volumes containing a mineral deposit or suspected mineral deposit such that all or nearly all the sub-volumes, or at least the sub-volumes of greatest desirability, of the one or more target volumes containing a mineral deposit or suspected mineral deposit are sampled to a specified or desired level, including obtaining information from a drill rig to be supplied to the algorithmic solver for the iteratively generating” as [Sequerira, JR et al. (paragraph [0047] “Exemplary embodiments of the present techniques also provide real time interactivity for a well planning process. In addition, a wide range of drilling variables may be considered. In particular, an exemplary embodiment relates to a method for evaluating the "goodness" or quality of a well trajectory during the well path planning and screening process by utilizing one or more volume-based objects in a 3D earth environment.”, Sequerira, JR et al. paragraph [0048] “An exemplary embodiment allows rapid evaluation of many alternative well trajectories and leads to a more optimal solution. Moreover, exemplary embodiments can also be used in an interactive well planning session in which the user can rapidly modify a well path while evaluating the results on the fly, taking into account minimum acceptable distance criteria and safety considerations.”, Sequerira, JR et al. paragraph [0069] “A stochastic optimization method, such as a genetic algorithm, may randomly select a new trajectory based on the previous iteration by adjusting failed constraint parameters to improve the result. A deterministic optimization method, such as dynamic programming, would evaluate the current trajectory based on the previous iterations to predict the next best solution.”, The examiner considers the genetic algorithm as being the algorithmic solver, since the well path optimization can include a genetic algorithm that can select a new trajectory based on the previous iteration to improve the result of the trajectory. The algorithmic solver can be a multiple metaheuristic algorithm that comprises a genetic algorithm component, see paragraphs [0026] and [0069] of the specification.)];
“- graphically presenting the drill plan using an interface communicatively connected to the processor” as [Sequerira, JR et al. (paragraph [0023] “The exemplary computer system may comprise a processor and a non-transitory, computer-readable storage medium that stores computer-readable instructions for execution by the processor.”, Sequerira, JR et al. paragraph [0109] “The computer system 900 may also include an input/output (I/O) adapter 910, a communications adapter 922, a user interface adapter 924, and a display adapter 918. In an exemplary embodiment of the present techniques, the display adapted 918 may be adapted to provide a 3D representation of a 3D earth model.”, Fig. 9)];
“wherein the resulting drill plan comprises a collection of one or more planned drill holes which are defined in 3D space” as [Sequerira, JR et al. (paragraph [0015] “An exemplary method comprises defining a proxy constraint volume as a 3D cellular volume where each cell has at least one value derived from data from a 3D earth model. An initial well path is defined within user defined drilling parameter constraints. The exemplary method comprises defining acceptable constraint parameters to be applied to values derived from an intersection of the initial well path and the proxy constraint volume. If the intersection of the initial well path and the proxy constraint volume is not within the acceptable constraint parameters, the initial well path may be iteratively adjusted to create successive well paths until at least one of the successive well paths is within the acceptable constraint parameters for the values derived from the intersection of the well path and proxy constraint volume.”, Sequerira, JR et al. paragraph [0016] “In one exemplary method of well path planning, the proxy constraint volume comprises a distance value for each cell in the volume created by calculating distance from at least one object type defined from the 3D earth model to all cells in the volume.”)];
“wherein a set of operational constraints constrains the iteratively generated and improved drill plan” as [Sequerira, JR et al. (paragraph [0049] “If well trajectories are planned and designed in a three-dimensional earth model, identified constraints can be located and evaluated interactively to create an optimal well trajectory or group of optimal trajectories.”, Sequerira, JR et al. paragraph [0056] “Examples of possible constraints that may be used for well planning include designing a viable path trajectory based on drilling physics. A drilling constraint such as "maximum dogleg severity" may be used to constrain the degree of well path curvature.”)];
“and wherein the algorithmic solver generates a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan” as [Sequerira, JR et al. (paragraph [0066] “For well path optimization, a set of conditions and/or constraints for an acceptable well trajectory is defined (block 202). The conditions may include minimizing total drilling costs, and maximizing the well profitability through sufficient hydrocarbon volumes, and production rates, etc. Constraints can include, but are not limited to, minimum distance to certain subsurface structures, minimum distance to other well paths, maximum reach from a drill center, and maximum well inclination, etc. A constraint optimization process is then used to automatically iterate through potential well trajectories based on the given conditions and constraints, as shown by blocks 208 through 212.”, Sequerira, JR et al. paragraph [0069] “In one exemplary embodiment, a well path optimization process may use the results from the previous iterations to propose a new well trajectory, when appropriate. A stochastic optimization method, such as a genetic algorithm, may randomly select a new trajectory based on the previous iteration by adjusting failed constraint parameters to improve the result. A deterministic optimization method, such as dynamic programming, would evaluate the current trajectory based on the previous iterations to predict the next best solution. The process would gradually converge to one or more optimal well trajectory or set of well trajectories. The use of proxy constraint volumes according to the present techniques may make this automated optimization process more effective and more efficient.”, As stated in section 10 of the current office action, the examiner has not seen any written description for the algorithmic solver generating a drill plan by solving a multi-objective optimization problem that simultaneously maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan. For the purpose of examination, the examiner considers the algorithmic solver generating a drill plan that maximizes the number of blocks sampled by the drill holes of the drill plan, and minimizes the total planned drill length of the drill plan.)];
“wherein the mineral resource exploration or classification sampling drill plan produced identifies the drill holes to be drilled by drilling equipment” as [Sequerira, JR et al. (paragraph [0096] “Once the distance proxy constraint volume is created, the optimization process may first propose a new well trajectory starting from one of the available slot locations in a drill center 618. The well path segments are created based on defined drilling algorithms and pre-set constraints. The path should pass through the top and base of the targeted reservoir areas 614, 616. All the cells intersected by the well path can then be identified”, Sequerira, JR et al. paragraph [0097] “Once a valid well trajectory is obtained, the total cost of the well trajectory can then be calculated. The same process could be repeated for fixed number of iterations or until the optimization analysis has converged.”)];
While Sequerira, JR et al. teaches producing a mineral resource exploration or
classification sampling drill plane, “Sequerira, JR et al. does not explicitly disclose “drilling the sampling holes based on the mineral resource exploration or classification sampling drill plan using the drilling equipment”
Pop et al. discloses “drilling the sampling holes based on the mineral resource exploration or classification sampling drill plan using the drilling equipment” as [Pop et al. (paragraph [0105] “FIG. 7 illustrates that the drilling operation (e.g., drilling) continues until the probe 205 (FIG. 2) reaches the sampling location, at which point the sampling operation is initiated. During the sampling operation, represented by time period t4', the drilling fluid circulation rate may be reduced. After the sampling operation is completed, drilling is reinitiated in the borehole 11. In contrast, FIG. 6 illustrates that the drill bit 105 continues to drill the formation F for a time period after the sampling location is reached and the sampling operation is performed while tripping out of the borehole 11.”, Fig. 7)];
Sequerira, JR et al. and Pop et al. are analogous art because they are from the same field endeavor of analyzing the drilling trajectory within a wellbore.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Sequerira, JR et al. of roducing a mineral resource exploration or classification sampling drill plane by incorporating drilling the sampling holes based on the mineral resource exploration or classification sampling drill plan using the drilling equipment as taught by Pop et al. for the purpose of planning and dynamically updating sampling operations while drilling in a subterranean formation.
Sequerira, JR et al. in view of Pop et al. teaches drilling the sampling holes based on the mineral resource exploration or classification sampling drill plan using the drilling equipment.
The motivation for doing so would have been because Pop et al. teaches that by planning and dynamically updating sampling operations while drilling in a subterranean formation, the ability to increase the effectiveness and/or efficiency of a formation fluid sampling operation or job can be accomplished, which enables integral planning of drilling (Pop et al. (paragraph [0014])).
With respect to claim 2, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above, and Sequerira, JR et al. further discloses “wherein the set of operational constraints comprises a historical drill hole locations constraint, a potential drilling setup location constraint, a drilling direction constraint, a drilling dips constraint, a drilling azimuth constraint, a drilling budget constraint, a sampling requirement constraint, a drilling setup availability constraint, a constraint regarding distribution of drill holes from setups, a constraint regarding the total amount of surface ground disturbance, a topographical constraint, an environmental constraint, a constraint regarding environmental exclusion zones, a geological fault constraint, a geological contacts constraint, a geological structure constraint, or a constraint regarding existing underground workings or operations, or any combination thereof.” as [Sequerira, JR et al. (paragraph [0015] “An exemplary method comprises defining a proxy constraint volume as a 3D cellular volume where each cell has at least one value derived from data from a 3D earth model. An initial well path is defined within user defined drilling parameter constraints. The exemplary method comprises defining acceptable constraint parameters to be applied to values derived from an intersection of the initial well path and the proxy constraint volume..”, Sequerira, JR et al. paragraph [0016] “In one exemplary method of well path planning, the proxy constraint volume comprises a distance value for each cell in the volume created by calculating distance from at least one object type defined from the 3D earth model to all cells in the volume.”, Sequerira, JR et al. paragraph [0056] “Examples of possible constraints that may be used for well planning include designing a viable path trajectory based on drilling physics. A drilling constraint such as "maximum dogleg severity" may be used to constrain the degree of well path curvature.”)];
With respect to claim 3, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above, and Sequerira, JR et al. further discloses “wherein the algorithmic solver is based on a heuristic algorithm, a linear algorithm, a metaheuristic algorithm, a metaheuristic SCP algorithm, a localized random search, a modified random search, an annealing algorithm, a taboo search, or a multiple metaheuristic algorithm comprising a genetic algorithm component, a taboo search algorithm and an iterated local search algorithm.” as [Sequerira, JR et al. (paragraph [0069] “A stochastic optimization method, such as a genetic algorithm, may randomly select a new trajectory based on the previous iteration by adjusting failed constraint parameters to improve the result. A deterministic optimization method, such as dynamic programming, would evaluate the current trajectory based on the previous iterations to predict the next best solution.”, The examiner considers the well path optimization as being the algorithmic solver, since the well path optimization can include a genetic algorithm that can select a new trajectory based on the previous iteration to improve the result of the trajectory. The algorithmic solver can be a multiple metaheuristic algorithm that comprises a genetic algorithm component, see paragraphs [0026] and [0069] of the specification.)];
With respect to claim 7, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above, and Sequerira, JR et al. further discloses “wherein the specified or desired level is selected from a range spanning geological, inferred, indicated, measured resource, and probable or proven reserve.” as [Sequerira, JR et al. (paragraph [0061] “In addition to constraint parameters, proxy constraint volumes may be created using geological, engineering, economic, land, and production information or any other attribute which would be deemed appropriate for a desired well planning analysis.”)];
With respect to claim 8, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 7 above, and Sequerira, JR et al. further discloses “wherein the specified or desired level is at least about 60% indicated while minimizing measured.” as [Sequerira, JR et al. (paragraph [0049] “Such an exemplary embodiment may determine a minimum acceptable distance from specific objects based on a type of object. Moreover, different object types may have differing minimum acceptable distances from a proposed well path.”)];
With respect to claim 9, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above, and Sequerira, JR et al. further discloses “wherein the algorithmic solver aims to generate a drill plan which attempts to maximize a number of sub-volumes sampled or classified per unit of planned drill length.” as [Sequerira, JR et al. (paragraph [0069] “In one exemplary embodiment, a well path optimization process may use the results from the previous iterations to propose a new well trajectory, when appropriate. A stochastic optimization method, such as a genetic algorithm, may randomly select a new trajectory based on the previous iteration by adjusting failed constraint parameters to improve the result. A deterministic optimization method, such as dynamic programming, would evaluate the current trajectory based on the previous iterations to predict the next best solution. The process would gradually converge to one or more optimal well trajectory or set of well trajectories.”, Sequerira, JR et al. paragraph [0070] “New drilling parameters and/or new surface/target locations can be proposed in this iterative manner until a satisfactory well path is obtained relative to all constraint parameters of interest.”)];
With respect to claim 10, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above, and Pop et al. further discloses “wherein the drill plan provides a ranking for each planned drill hole which is based on a relative value of each planned drill hole to an overall drill plan, and wherein one or more of a lowest ranked drill holes are eliminated from the drill plan.” as [Pop et al. (paragraph [0088] “The sorter 314 may rank the processes (e.g., the scenarios) according to the sample fluid quality (e.g., a final sample quality), the duration of the sampling process, the cost associated with the sampling process (e.g., the cost of sampling), and/or according to the amount of risk associated with obtaining the fluid sample. Additionally, the sorter 314 may enable the identification of the parameter(s) (e.g., the drilling and/or sampling parameters(s)), which have the greatest impact on the sample fluid quality. Further, the comparator 310 may compare the predictions associated with the different scenarios, plans or processes to identify scenarios, plans, processes and/or parameters that reduce the cost of sampling, increase sample fluid quality and/or reduce the sampling process duration.”, The examiner considers the comparator comparing the predictions associated with the different scenarios, plans or processes to identify scenarios, plans and processes that reduce the cost, to be elimination of a drill plan, since these scenarios, plans and processes aren’t cost efficient)];
With respect to claim 11, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 10 above, and Pop et al. further discloses “wherein the ranking includes a penalty for moving a drill hole of the drill plan away from a position at the one or more target volumes which is easily drilled, or away from a position at the one or more target volumes at which drilling equipment is already located.” as [Pop et al. (paragraph [0015] “Those gathered or measured parameter values may then be used to update (e.g., modify) the initially selected drilling and/or sampling plan(s). Such updates may, for example, occur dynamically during a formation fluid sampling operation and/or may occur between drilling activities (i.e., while drilling is temporarily halted or stopped) during the course of a sampling job, which may entail sampling formation fluid at one or more locations along a borehole being drilled”, Pop et al. paragraph [0089] “In particular, based on the ranked predictions, the processing unit 250 may identify a bottomhole assembly configuration, a type of drilling fluid, drilling practices to be employed”)];
With respect to claim 12, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 10 above, and Sequerira, JR et al. further discloses “wherein the relative value to the drill plan of changing one or more collar locations while dynamically updating dip and dip direction is assessed.” as [Sequerira, JR et al. (paragraph [0097] “If the value of SD is less than 100 ft, then the well trajectory is invalid and should be adjusted based on the segments containing this SD value. If no well path segment adjustment can satisfy the anti-collision constraint, a new well trajectory is proposed by changing the surface location and/or path segments on the targeted areas until a valid well trajectory is obtained.”)];
With respect to claim 13, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above, and Pop et al. further discloses “wherein the iteratively generated drill plans are scored by a resource conversion calculator” as [Pop et al. (paragraph [0088] “the sorter 314 (FIG. 3) sorts and/or ranks the predictions associated with the different scenarios, plans or processes. The sorter 314 may rank the processes (e.g., the scenarios) according to the sample fluid quality (e.g., a final sample quality), the duration of the sampling process, the cost associated with the sampling process (e.g., the cost of sampling), and/or according to the amount of risk associated with obtaining the fluid sample.”, Pop et al. (paragraph [0089] “After the sorter 314 sorts and/or ranks the predictions associated with the different scenarios, plans or processes, the processing unit 250 plans drilling and sampling operations based on the ranked predictions.”)];
Sequerira, JR et al. discloses “and the algorithmic solver improves a drill plan score using one or more parameters which are changed using a constraint modifier between iterations” as [Sequerira, JR et al. (paragraph [0069] “In one exemplary embodiment, a well path optimization process may use the results from the previous iterations to propose a new well trajectory, when appropriate. A stochastic optimization method, such as a genetic algorithm, may randomly select a new trajectory based on the previous iteration by adjusting failed constraint parameters to improve the result.”)];
“and wherein the constraint modifier changes or flexes one or more parameters selected from a historical drill hole locations constraint, a potential drilling setup location constraint, a drilling direction constraint, a drilling dips constraint, a drilling azimuth constraint, a drilling budget constraint, a sampling requirement constraint, a drilling setup availability constraint, a constraint regarding distribution of drill holes from setups, a constraint regarding the total amount of surface ground disturbance, a topographical constraint, an environmental constraint, a constraint regarding environmental exclusion zones, a geological fault constraint, a geological contacts constraint, a geological structure constraint, or a constraint regarding existing underground workings or operations, or any combination thereof, the specified or desired level, or a combination thereof, between iterations.” as [Sequerira, JR et al. (paragraph [0015] “An initial well path is defined within user defined drilling parameter constraints. The exemplary method comprises defining acceptable constraint parameters to be applied to values derived from an intersection of the initial well path and the proxy constraint volume.”, Sequerira, JR et al. paragraph [0069] “In one exemplary embodiment, a well path optimization process may use the results from the previous iterations to propose a new well trajectory, when appropriate. A stochastic optimization method, such as a genetic algorithm, may randomly select a new trajectory based on the previous iteration by adjusting failed constraint parameters to improve the result.”)];
With respect to claim 14, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 13 above, and Sequerira, JR et al. further discloses “wherein the scoring of the drill plans includes rewarding drill plans which provide information about location of geological structures and contacts of the one or more target volumes, or rewarding drill plans which have a reasonable probability of success.” as [Sequerira, JR et al. (paragraph [0046] “Current well path planning design practices, whether manual or automatic, employ geometric constraints to calculate the distance to identified subsurface objects the well bore is intended to intersect (targets) or objects the wellbore is intended to avoid (geo-hazards). In addition, current methods calculate permutations of collision avoidance (between other wells or geo-hazards) concurrently with the constraints of penetrating the reservoir targets along the well path.”, Sequerira, JR et al. paragraph [0049] “An exemplary embodiment of the present techniques evaluates the distance between a proposed well path and potential obstructions. Such an exemplary embodiment may determine a minimum acceptable distance from specific objects based on a type of object. Moreover, different object types may have differing minimum acceptable distances from a proposed well path. Potential objects to maintain a minimal distance from could include engineering objects (other wellbores etc.), geologic objects (faults, salt bodies etc.), and other identified subsurface objects. If well trajectories are planned and designed in a three-dimensional earth model, identified constraints can be located and evaluated interactively to create an optimal well trajectory or group of optimal trajectories”, The examiner considers the rewarding of drill plans to be the drill plan that determines the minimum acceptable distance from an obstruction in the well path, since the ranking or scoring of the resulting drill plan(s) may include rewarding drill plans which provide information about the location of a geological contact or structure which is between different deposit types or two rock types in the target volume, see paragraph [0086] of the specification)];
With respect to claim 16, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above, and Sequerira, JR et al. further discloses “wherein the orientation of a drill hole of the drill plan can be recalculated in real-time to accommodate for on-site drilling limitations” as [Sequerira, JR et al. (paragraph [0046] “These real-time calculations of important drilling variables used in the well-path planning process are considerable, and except in very simple well designs are so lengthy they eliminate the possibility of having a real-time well planning session with the necessary team of experts (geologists, geophysicists, reservoir engineers, drillers, and production engineers), Sequerira, JR et al. paragraph [0047] “Exemplary embodiments of the present techniques also provide real time interactivity for a well planning process. In addition, a wide range of drilling variables may be considered. In particular, an exemplary embodiment relates to a method for evaluating the "goodness" or quality of a well trajectory during the well path planning and screening process by utilizing one or more volume-based objects in a 3D earth environment.”)];
“and wherein the on-site drilling limitations are any one of drill site accessibility, drill hole geometry, drill hole timing limitations, a requirement for movement of the drill rig, setup availability, or any combination thereof.” as [Sequerira, JR et al. (paragraph [0046] “Current well path planning design practices, whether manual or automatic, employ geometric constraints to calculate the distance to identified subsurface objects the well bore is intended to intersect (targets) or objects the wellbore is intended to avoid (geo-hazards). In addition, current methods calculate permutations of collision avoidance (between other wells or geo-hazards) concurrently with the constraints of penetrating the reservoir targets along the well path.”)];
With respect to claim 18, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above, and Sequerira, JR et al. further discloses “wherein the method further comprises: - using implicit modeling to model geological contacts, faults, shells, and surfaces” as [Sequerira, JR et al. (paragraph [0015] “An exemplary method comprises defining a proxy constraint volume as a 3D cellular volume where each cell has at least one value derived from data from a 3D earth model. An initial well path is defined within user defined drilling parameter constraints. The exemplary method comprises defining acceptable constraint parameters to be applied to values derived from an intersection of the initial well path and the proxy constraint volume.”, Sequerira, JR et al. (paragraph [0016] “The object type in the proxy constraint distance volume may comprise a fault, a salt formation, a surface, an overpressured zone, an unstable interval or any subsurface object of interest.”)];
“and - updating the implicit modeling of the one or more target volume surfaces, geological structures, geological contacts, or a combination thereof, as drill hole data is acquired” as [Sequerira, JR et al. (paragraph [0015] “An exemplary method comprises defining a proxy constraint volume as a 3D cellular volume where each cell has at least one value derived from data from a 3D earth model.”, Sequerira, JR et al. (paragraph [0019] “The initial well path may be iteratively adjusted to create successive well paths if the intersection of the initial well path and the proxy constraint volume is not within the acceptable constraint parameters”)];
“thereby dynamically identifying high value sub-volumes to be converted from unclassified to geological, inferred, indicated, or measured, and wherein the drill plan is recalculated” as [Sequerira, JR et al. (paragraph [0075] “The shading of the cells in the right panel 304 represents distance proxy constraint volume values indicative of the distance between each cell in the right panel 304 and selected geo-hazard objects intersecting the volume. Moreover, the data values for each cell represent distance from that cell's location to the closest cell occupied by any one of the geo-hazard objects 306a, 306b and 306c.”, [Sequerira, JR et al. (paragraph [0076] “To determine if a planned well trajectory is too close to certain objects imbedded in a distance proxy constraint volume, one can retrieve intersected cell values along the well trajectories. The value in each one of the intersected cells represents the closest distance value to objects in the model. If any one of the cell values, which is essentially the shortest distance from this path location to one or more objects, is smaller than the user defined minimum anti-collision distance (a defined constraint parameter), the well trajectory may be rejected”)];
“and the scoring of the resulting drill plan includes a reward for solutions which allow for conversion of the identified high value sub-volumes from unclassified to inferred, indicated or measured.” as [Sequerira, JR et al. (paragraph [0046] “Current well path planning design practices, whether manual or automatic, employ geometric constraints to calculate the distance to identified subsurface objects the well bore is intended to intersect (targets) or objects the wellbore is intended to avoid (geo-hazards). In addition, current methods calculate permutations of collision avoidance (between other wells or geo-hazards) concurrently with the constraints of penetrating the reservoir targets along the well path.”)];
With respect to claim 19, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above, and Pop et al. further discloses “wherein drill holes of the drill plan are ranked based on their value to the drill plan, and this ranking is used to indicate which holes of the drill plan should be drilled first.” as [Pop et al. (paragraph [0088] “The sorter 314 may rank the processes (e.g., the scenarios) according to the sample fluid quality (e.g., a final sample quality), the duration of the sampling process, the cost associated with the sampling process (e.g., the cost of sampling), and/or according to the amount of risk associated with obtaining the fluid sample. Additionally, the sorter 314 may enable the identification of the parameter(s) (e.g., the drilling and/or sampling parameters(s)), which have the greatest impact on the sample fluid quality. Further, the comparator 310 may compare the predictions associated with the different scenarios, plans or processes to identify scenarios, plans, processes and/or parameters that reduce the cost of sampling, increase sample fluid quality and/or reduce the sampling process duration”, Pop et al. paragraph [0089] “After the sorter 314 sorts and/or ranks the predictions associated with the different scenarios, plans or processes, the processing unit 250 plans drilling and sampling operations based on the ranked predictions.”)];
Claim(s) 4-6, 15 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable
over Sequeira, JR, et al. in view of Pop et al. in further view of Thore (U.S. Patent 6,711,529) (from IDS dated 5/28/21).
With respect to claim 4, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above.
While the combination of Sequerira, JR et al. and Pop et al. teaches segmenting the one or more target volumes into sub-volumes, Sequerira, JR et al. and Pop et al. do not explicitly disclose “wherein the one or more attributes indicating relative desirability of a sub-volume are selected from one or more of: - distance of the sub-volume from an existing drill hole; - estimate variance; - grade estimates; “- bounding of the sub-volume by site specific geological contacts, structures, or faults; or - variability or uncertainty of sub-volume grade estimation or interpolation”
Thore discloses “wherein the one or more attributes indicating relative desirability of a sub-volume are selected from one or more of: - distance of the sub-volume from an existing drill hole; - estimate variance; - grade estimates; “- bounding of the sub-volume by site specific geological contacts, structures, or faults” as [Thore (Col. 4 lines 8-12 “According to another characteristic of the invention, when the centred volume contains, etc.”)];
or - variability or uncertainty of sub-volume grade estimation or interpolation”
Sequerira, JR et al., Pop et al. and Thore are analogous art because they are from the same field endeavor of analyzing the drilling trajectory within a wellbore.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Sequerira, JR et al. and Pop et al. of segmenting the one or more target volumes into sub-volumes by incorporating wherein the one or more attributes indicating relative desirability of a sub-volume are selected from one or more of: - distance of the sub-volume from an existing drill hole; - estimate variance; - grade estimates; “- bounding of the sub-volume by site specific geological contacts, structures, or faults; or - variability or uncertainty of sub-volume grade estimation or interpolation as taught by Thore for the purpose of determining an optimal trajectory for reaching a target in a situated medium.
Sequerira, JR et al. in view of Pop et al. in further view of Thore teaches wherein the one or more attributes indicating relative desirability of a sub-volume are selected from one or more of: - distance of the sub-volume from an existing drill hole; - estimate variance; - grade estimates; “- bounding of the sub-volume by site specific geological contacts, structures, or faults; or - variability or uncertainty of sub-volume grade estimation or interpolation.
The motivation for doing so would have been because Thore teaches that by the driller knowing a target volume to be reached, the driller can create an optimal trajectory for reaching a target in a situated medium, without doing excess drilling (Thore Col. 3 lines 5-10, “The subject of the present invention, etc.”).
With respect to claim 5, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above.
While the combination of Sequerira, JR et al. and Pop et al. teaches segmenting the one or more target volumes into sub-volumes, Sequerira, JR et al. and Pop et al. do not explicitly disclose “wherein the drill plan aims to sample sub-volumes of the one or more target volumes such that a highest aggregate desirability is achieved, wherein an aggregate desirability primarily considers a value of resource classification, an identification of geological features bounding the one or more target volumes, or a combination thereof”
Thore discloses “wherein the drill plan aims to sample sub-volumes of the one or more target volumes such that a highest aggregate desirability is achieved” as [Thore (Col. 3 lines 11 -14, “The method according to the invention for determining at least one, etc.”)];
“wherein an aggregate desirability primarily considers a value of resource classification, an identification of geological features bounding the one or more target volumes, or a combination thereof” as [Thore (Col. 3 lines 50-59, “According to another characteristic of the invention, the medium is a portion of subsurface, etc.”)];
Sequerira, JR et al., Pop et al. and Thore are analogous art because they are from the same field endeavor of analyzing the drilling trajectory within a wellbore.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Sequerira, JR et al. and Pop et al. of segmenting the one or more target volumes into sub-volumes by incorporating wherein the drill plan aims to sample sub-volumes of the one or more target volumes such that a highest aggregate desirability is achieved, wherein an aggregate desirability primarily considers a value of resource classification, an identification of geological features bounding the one or more target volumes, or a combination thereof as taught by Thore for the purpose of determining an optimal trajectory for reaching a target in a situated medium.
Sequerira, JR et al. in view of Pop et al. in further view of Thore teaches wherein the drill plan aims to sample sub-volumes of the one or more target volumes such that a highest aggregate desirability is achieved, wherein an aggregate desirability primarily considers a value of resource classification, an identification of geological features bounding the one or more target volumes, or a combination thereof.
The motivation for doing so would have been because Thore teaches that by the driller knowing a target volume to be reached, the driller can create an optimal trajectory for reaching a target in a situated medium, without doing excess drilling (Thore Col. 3 lines 5-10, “The subject of the present invention, etc.”).
With respect to claim 6, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above.
While the combination of Sequerira, JR et al. and Pop et al. teaches segmenting the one or more target volumes into sub-volumes, Sequerira, JR et al. and Pop et al. do not explicitly disclose “wherein the drill plan is iteratively improved by improving a global distribution of drill holes within the drill plan based on newly acquired information as drilling operations progress”
Thore discloses “wherein the drill plan is iteratively improved by improving a global distribution of drill holes within the drill plan based on newly acquired information as drilling operations progress.” as [Thore (Col. 7 lines 42-55, “Although the target and its neighbourhood seem to change position within the subsurface, etc.”)].
Sequerira, JR et al., Pop et al. and Thore are analogous art because they are from the same field endeavor of analyzing the drilling trajectory within a wellbore.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Sequerira, JR et al. and Pop et al. of segmenting the one or more target volumes into sub-volumes by incorporating wherein the drill plan is iteratively improved by improving a global distribution of drill holes within the drill plan based on newly acquired information as drilling operations progress as taught by Thore for the purpose of determining an optimal trajectory for reaching a target in a situated medium.
Sequerira, JR et al. in view of Pop et al. in further view of Thore teaches wherein the drill plan is iteratively improved by improving a global distribution of drill holes within the drill plan based on newly acquired information as drilling operations progress.
The motivation for doing so would have been because Thore teaches that by the driller knowing a target volume to be reached, the driller can create an optimal trajectory for reaching a target in a situated medium, without doing excess drilling (Thore Col. 3 lines 5-10, “The subject of the present invention, etc.”).
With respect to claim 15, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 1 above, and Sequerira, JR et al. further discloses “wherein the method is an iterative method which is repeated using input which is based on newly acquired information obtained from drilling one or more planned drill holes from a previously generated drill plan” as [Sequerira, JR et al. (paragraph [0090] “FIG. 6 is a diagram that shows the use of a well planning optimization in two stacked reservoirs and two targets according to an exemplary embodiment of the present techniques.”, Sequerira, JR et al. paragraph [0097] “Once a valid well trajectory is obtained, the total cost of the well trajectory can then be calculated. The same process could be repeated for fixed number of iterations or until the optimization analysis has converged. Each iteration would base on the previous iterations to fine tune the well trajectory until a valid well trajectory with optimal cost is obtained.”, Fig. 6)];
While the combination of Sequerira, JR et al. and Pop et al. teaches wherein the method is an iterative method which is repeated using input which is based on newly acquired information obtained from drilling one or more planned drill holes from a previously generated drill plan, Sequerira, JR et al. and Pop et al. do not explicitly disclose “wherein the one or more planned drill holes from the previously generated drill plan are drill holes which have been drilled quickly but with reduced precision for geological drilling or bounding of the one or more target volumes, allowing in-fill planning, and improving the drill plan with less invested time”
Thore discloses “wherein the one or more planned drill holes from the previously generated drill plan are drill holes which have been drilled quickly but with reduced precision for geological drilling or bounding of the one or more target volumes, allowing in-fill planning, and improving the drill plan with less invested time.” as [Thore (Col. 7 lines 9-14 “At each node of the medium, the components, etc.”)];
Sequerira, JR et al., Pop et al. and Thore are analogous art because they are from the same field endeavor of analyzing the drilling trajectory within a wellbore.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Sequerira, JR et al. and Pop et al. of wherein the method is an iterative method which is repeated using input which is based on newly acquired information obtained from drilling one or more planned drill holes from a previously generated drill plan by incorporating wherein the one or more planned drill holes from the previously generated drill plan are drill holes which have been drilled quickly but with reduced precision for geological drilling or bounding of the one or more target volumes, allowing in-fill planning, and improving the drill plan with less invested time as taught by Thore for the purpose of determining an optimal trajectory for reaching a target in a situated medium.
Sequerira, JR et al. in view of Pop et al. in further view of Thore teaches wherein the one or more planned drill holes from the previously generated drill plan are drill holes which have been drilled quickly but with reduced precision for geological drilling or bounding of the one or more target volumes, allowing in-fill planning, and improving the drill plan with less invested time.
The motivation for doing so would have been because Thore teaches that by the driller knowing a target volume to be reached, the driller can create an optimal trajectory for reaching a target in a situated medium, without doing excess drilling (Thore Col. 3 lines 5-10, “The subject of the present invention, etc.”).
With respect to claim 17, the combination of Sequerira, JR et al. and Pop et al. discloses the method of claim 16 above.
While the combination of Sequerira, JR et al. and Pop et al. teaches the orientation of a drill hole of the drill plan can be recalculated in real-time to accommodate for on-site drilling limitations and wherein the on-site drilling limitations are any one of drill site accessibility, drill hole geometry, drill hole timing limitations, a requirement for movement of the drill rig, setup availability, or any combination thereof, Sequerira, JR et al. and Pop et al. do not explicitly disclose “wherein a completion constraint is used to identify a point at which sufficient drilling has been completed, and wherein the point at which sufficient drilling has been completed is a point at which further increase in drill hole density provides additional value which is below a specified threshold”
Thore discloses “wherein a completion constraint is used to identify a point at which sufficient drilling has been completed” as [Thore (Col 4 lines 22-40, “Advantageously, for the implementation of the method according to the invention, the medium, etc.”)];
“and wherein the point at which sufficient drilling has been completed is a point at which further increase in drill hole density provides additional value which is below a specified threshold.” as [Thore (Col 4 lines 13-16, “According to another characteristic of the invention, among the trajectories whose, etc.”)];
Sequerira, JR et al., Pop et al. and Thore are analogous art because they are from the same field endeavor of analyzing the drilling trajectory within a wellbore.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Sequerira, JR et al. and Pop et al. of the orientation of a drill hole of the drill plan can be recalculated in real-time to accommodate for on-site drilling limitations and wherein the on-site drilling limitations are any one of drill site accessibility, drill hole geometry, drill hole timing limitations, a requirement for movement of the drill rig, setup availability, or any combination thereof by incorporating wherein a completion constraint is used to identify a point at which sufficient drilling has been completed, and wherein the point at which sufficient drilling has been completed is a point at which further increase in drill hole density provides additional value which is below a specified threshold as taught by Thore for the purpose of determining an optimal trajectory for reaching a target in a situated medium.
Sequerira, JR et al. in view of Pop et al. in further view of Thore teaches wherein a completion constraint is used to identify a point at which sufficient drilling has been completed, and wherein the point at which sufficient drilling has been completed is a point at which further increase in drill hole density provides additional value which is below a specified threshold.
The motivation for doing so would have been because Thore teaches that by the driller knowing a target volume to be reached, the driller can create an optimal trajectory for reaching a target in a situated medium, without doing excess drilling (Thore Col. 3 lines 5-10, “The subject of the present invention, etc.”).
Conclusion
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/BERNARD E COTHRAN/Examiner, Art Unit 2188
/RYAN F PITARO/Supervisory Patent Examiner, Art Unit 2188
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