DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Status
Claims 1-20 are currently pending and examined on the merits.
Priority
The instant application claims priority to U.S. Provisional Application 63/278,966 filed on 11/12/2021. At this point in examination, the effective filing date of claims 1-20 is 11/12/2021.
Information Disclosure Statement
No Information Disclosure Statement has been filed herein.
Claim Objections
Claims 9 and 15 are objected to because of the following informalities:
Claim 9, line 7 recites "second amount fluid", which should read "second amount of fluid".
Claim 15, line 5 recites “than”, which should be replaced with “that”.
These are typographical errors. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite: (a) mathematical concepts, (e.g., mathematical relationships, formulas or equations, mathematical calculations); and (b) mental processes, i.e., concepts performed in the human mind, (e.g., observation, evaluation, judgement, opinion).
Subject matter eligibility evaluation in accordance with MPEP 2106:
Eligibility Step 1: Claims 1-16 are directed to a method (process) of determining movement of carbon-based gas between microorganisms in the first wellbore and the second wellbore. Claims 17-20 are directed to a system (machine). Therefore, these claims are encompassed by the categories of statutory subject matter, and thus satisfy the subject matter eligibility requirements under Step 1.
[Step 1: YES]
Eligibility Step 2A: First, it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in Prong Two whether the recited judicial exception is integrated into a practical application of that exception.
Eligibility Step 2A, Prong One: In determining whether a claim is directed to a judicial exception, examination is performed that analyzes whether the claim recites a judicial exception, i.e., whether a law of nature, natural phenomenon, or abstract idea is set forth described in the claim.
Claims 1, 4-13, and 15-19 recite the following steps which fall within the mental processes and/or mathematical concepts groups of abstract ideas, as noted below.
Independent claim 1 further recites:
analyzing, by the computing system, the sequence reads to determine a first community of microorganisms that corresponds to one or more first subsurface geological features through which the first wellbore passes (i.e., mental processes);
analyzing, by the computing system, the sequence reads to determine a second community of microorganisms that corresponds to one or more second subsurface geological features through which the second wellbore passes (i.e., mental processes);
determining, by the computing system, that the second community of microorganisms includes an amount of one or more reference microorganism that correspond to at least a portion of the microorganisms of the first community of microorganisms (i.e., mental processes);
determining, by the computing system, an abundance of the one or more reference microorganisms present in the second community of microorganisms (i.e., mental processes);
determining, by the computing system and based on the abundance of the one or more reference microorganisms, an amount of movement of a carbon-based gas between the first wellbore and the second wellbore (i.e., mental processes).
Dependent claim 4 further recites:
wherein the individual subsurface geological features include at least one of a freshwater aquifer, a caprock layer, a rock formation, or a brine reservoir (i.e., mental processes).
Dependent claim 5 further recites:
analyzing, by the computing system, a first portion of the sequence reads that corresponds to one or more samples collected from a first individual subsurface geological feature to determine a first reference community of microorganisms that corresponds to a first individual subsurface geological feature (i.e., mental processes);
analyzing, by the computing system, a second portion of the sequence reads that corresponds to one or more additional samples collected from a second individual subsurface geological feature to determine a second reference community of microorganisms that corresponds to a second individual subsurface geological feature (i.e., mental processes).
Dependent claim 6 further recites:
analyzing, by the computing system, a first number of the sequence reads that corresponds to first genomic sequences of the first reference community of microorganisms present in the second community of microorganisms (i.e., mental processes);
determining, by the computing system and based on the first number of the sequence reads, a first abundance of the first reference community of microorganisms present in the second community of microorganisms (i.e., mental processes);
analyzing, by the computing system, a second number of the sequence reads that corresponds to second genomic sequences of the second reference community of microorganisms present in the second community of microorganisms (i.e., mental processes);
determining, by the computing system and based on the second number of the sequence reads, a second abundance of the second reference community of microorganisms present in the second community of microorganisms (i.e., mental processes).
Dependent claim 7 further recites:
determining, by the computing system, a microbial source log indicating: a first amount of the second community of microorganisms that corresponds to the first individual subsurface geological feature based on the first abundance of the first reference community of microorganisms present in the second community of microorganisms (i.e., mental processes);
determining, by the computing system, a microbial source log indicating: a second amount of the second community of microorganisms that corresponds to the second individual subsurface geological feature based on the second abundance of the second reference community of microorganisms present in the second community of microorganism (i.e., mental processes).
Dependent claim 8 further recites:
wherein: the first abundance of the first reference community of microorganisms present in the second community of microorganisms corresponds to a first amount of fluid displaced in the first individual subsurface geological feature in response to injection of one or more carbon-based gases at the first wellbore (i.e., mental processes);
wherein: the second abundance of the second reference community of microorganisms present in the second community of microorganisms corresponds to a second amount of fluid displaced in the second individual subsurface geological features in response to the injection of the one or more carbon-based gases at the first wellbore (i.e., mental processes).
Dependent claim 9 further recites:
determining, by the computing system, a first location of the one or more carbon-based gases in the first individual subsurface geological feature based on the first amount of fluid displaced in the first individual subsurface geological feature in response to injection of one or more carbon-based gases at the first wellbore (i.e., mental processes);
determining, by the computing system, a second location of the one or more carbon-based gases in the second individual subsurface geological features based on the second amount fluid displaced in the second individual subsurface geological features in response to the injection of the one or more carbon-based gases at the first wellbore (i.e., mental processes).
Dependent claim 10 further recites:
wherein the second individual subsurface geological feature is a freshwater aquifer (i.e., mental processes);
determining, by the computing system, that an amount of the one or more carbon-based gases is present in the freshwater aquifer based on the second location of the one or more carbon-based gases (i.e., mental processes).
Dependent claim 11 further recites:
wherein the first individual subsurface geological feature is located above a caprock layer and the second individual subsurface geological feature is located below a caprock layer (i.e., mental processes);
determining, by the computing system, that a breach of the caprock layer has occurred based on the first location of the one or more carbon-based gases and the second location of the one or more carbon-based gases (i.e., mental processes).
Dependent claim 12 further recites:
analyzing, by the computing system, the pressure measurements in conjunction with the first location of the carbon-based gases and the second location of the carbon-based gases to determine that a pressure threshold in at least one of the first individual subsurface geological feature or the second individual subsurface geological feature has been exceeded (i.e., mental processes);
determining one or more pressure mitigation operations to apply with respect to at least one of the first individual subsurface geological feature or the second individual subsurface geological feature (i.e., mental processes).
Dependent claim 13 further recites:
analyzing, by the computing system, the first location of the one or more carbon-based gases and the second location of the one or more carbon-based gases to determine a storage capacity for the one or more carbon-based gases in at least one of the first individual subsurface geological feature or the second individual subsurface geological feature (i.e., mental processes).
Dependent claim 15 further recites:
analyzing, by the computing system, the sequence reads with respect to genomic sequences of microorganisms to determine an amount of identity between individual sequence reads and the genomic sequences of the microorganisms (i.e., mental processes);
determining, by the computing system, than an individual sequence reads corresponds to a genomic sequence of a microorganism based on the amount of identity between the individual sequence read and the genomic sequence of the microorganism being at least a threshold amount of identity (i.e., mental processes).
Dependent claim 16 further recites:
determining, by the computing system, taxonomic classifications for at least a portion of microorganisms included in the first community of microorganisms and the second community of microorganisms (i.e., mental processes).
Independent claim 17 further recites:
analyzing the sequence reads to determine a first community of microorganisms that corresponds to one or more first subsurface geological features through which the first wellbore passes (i.e., mental processes);
analyzing the sequence reads to determine a second community of microorganisms that corresponds to one or more second subsurface geological features through which the second wellbore passes (i.e., mental processes);
determining that the second community of microorganisms includes one or more reference microorganism that correspond to at least a portion of the microorganisms of the first community of microorganisms (i.e., mental processes);
determining an abundance of the one or more reference microorganisms present in the second community of microorganisms (i.e., mental processes);
determining, based on the abundance of the one or more reference microorganisms, an amount of movement of a carbon-based gas between the first wellbore and the second wellbore (i.e., mental processes).
Dependent claim 18 further recites:
determining that an additional abundance of one or more classifications of microorganisms present in the second community of microorganisms has decreased, the one or more classifications of microorganisms including microorganisms that are unable to survive in environments where greater than a threshold amount of the carbon-based gas is present (i.e., mental processes);
determining that a dissolution front of the carbon-based gas is present at a location of the second wellbore (i.e., mental processes).
Dependent claim 19 further recites:
determining locations of the one or more carbon-based gases in at least one of the one or more first subsurface geological features or the one or more second subsurface geological features based on one or more microorganisms originating in the one or more first subsurface geological features being present in the one or more second subsurface geological features (i.e., mental processes);
generating a model to predict the amount of movement of the carbon-based gas between the first wellbore and the second wellbore based on the locations of the one or more carbon-based gases in at least one of the one or more first subsurface geological features or the one or more second subsurface geological features (i.e., mental processes, mathematical concepts).
The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification. As noted in the foregoing section, the claims are determined to contain limitations that can practically be performed in the human mind with the aid of a pencil and paper, and therefore recite judicial exceptions from the mental process grouping of abstract ideas. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind.
Therefore, claims 1, 4-13, and 15-19 recite an abstract idea.
[Step 2A, Prong One: YES]
Eligibility Step 2A, Prong Two: In determining whether a claim is directed to a judicial exception, further examination is performed that analyzes if the claim recites additional elements that, when examined as a whole, integrates the judicial exception(s) into a practical application (MPEP 2106.04(d)). A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements are analyzed to determine if the abstract idea is integrated into a practical application (MPEP 2106.04(d)(I); MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the abstract idea, the claim fails to integrate the abstract idea into a practical application (MPEP 2106.04(d)(III)).
The judicial exceptions identified in Eligibility Step 2A, Prong One are not integrated into a practical application because of the reasons noted below.
Claim 14 recites performing one or more amplification and sequencing processes with respect to the first genetic material and the second genetic material to generate the sequence reads. It is notable that mere physicality or tangibility of an additional element or elements is not a relevant consideration in Step 2A Prong Two. As the Supreme Court explained in Alice Corp., mere physical or tangible implementation of an exception does not guarantee eligibility. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1983-84 (2014) ("The fact that a computer ‘necessarily exist[s] in the physical, rather than purely conceptual, realm,’ is beside the point"). See MPEP 2106.04(d)(I), citing Genetic Technologies Ltd. v. Merial LLC, 818 F.3d 1369, 1377, 118 USPQ2d 1541, 1547 (Fed. Cir. 2016) (steps of DNA amplification and analysis are not "sufficient" to render claim 1 patent eligible merely because they are physical steps). Therefore, the claimed additional element does not integrate the abstract ideas into a practical application.
Claims 1-3, 12, 14, and 20 recite the additional non-abstract elements of data gathering:
obtaining, by a computing system including one or more processors and memory, sequence reads that correspond to nucleic acids present in a plurality of samples, the plurality of samples including first samples collected from a first wellbore and second samples collected from a second wellbore (claim 1);
wherein: an amount of the carbon-based gas is injected into the first wellbore (claim 2);
wherein: the first samples are collected before the amount of carbon-based gas is injected into the first wellbore (claim 2);
wherein: the second samples are collected after the amount of carbon-based gas is injected into the first wellbore (claim 2);
wherein: the first samples are collected from a plurality of depths below a surface; and individual depths of the plurality of depths correspond to individual subsurface geological features (claim 3);
obtaining, by the computing system, pressure measurements from one or more pressure sensors present in at least one of the first individual subsurface geological feature or the second individual subsurface geological feature (claim 12);
extracting first genetic material from the first samples (claim 14);
extracting second genetic material from the second samples (claim 14);
causing a user interface to be generated that includes one or more graphics indicating the amount of movement of the carbon-based gas between the first wellbore and the second wellbore (claim 20).
Data gathering steps are not an abstract idea, they are extra-solution activity, as they collect the data needed to carry out the JE. The data gathering does not impose any meaningful limitation on the JE, or how the JE is performed. The additional limitation (data gathering) must have more than a nominal or insignificant relationship to the identified judicial exception. (MPEP 2106.04/.05, citing Intellectual Ventures LLC v. Symantee Corp, McRO, TLI communications, OIP Techs. Inc. v. Amason.com Inc., Electric Power Group LLC v. Alstrom S.A.).
Claim 17 recites the additional non-abstract element (EIA) of a general-purpose computer system or parts thereof:
a system comprising one or more hardware processors and a memory storing computer-readable instructions (claim 17).
The EIA do not provide any details of how specific structures of the computer elements are used to implement the JE. The claims require nothing more than a general-purpose computer to perform the functions that constitute the judicial exceptions. The computer elements of the claims do not provide improvements to the functioning of the computer itself (as in DDR Holdings, LLC v. Hotels.com LP); they do not provide improvements to any other technology or technical field (as in Diamond v. Diehr); nor do they utilize a particular machine (as in Eibel Process Co. v. Minn. & Ont. Paper Co.). Hence, these are mere instructions to apply the JE using a computer, and therefore the claim does not recite integrate that JE into a practical application.
Thus, the additionally recited elements merely invoke a computer as a tool, and/or amount to insignificant extra-solution data gathering activity, and as such, when all limitations in claims 1-20 have been considered as a whole, the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application. Claims 1-3, 12, 14, 17, and 20 contain additional elements that would not integrate a judicial exception into a practical application and are further probed for inventive concept in Step 2B.
[Step 2A, Prong Two: NO]
Eligibility Step 2B: Because the claims recite an abstract idea, and do not integrate that abstract idea into a practical application, the claims are probed for a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05). Identifying whether the additional elements beyond the abstract idea amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they amount to significantly more than the judicial exception (MPEP 2106.05A i-vi).
The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception(s) because of the reasons noted below.
With respect to claims 1-3, 12, 14, and 20: The limitations identified above as non-abstract elements (EIA) related to data gathering do not rise to the level of significantly more than the judicial exception. Activities such as data gathering do not improve the functioning of a computer, or comprise an improvement to any other technical field. The limitations do not require or set forth a particular machine, they do not affect a transformation of matter, nor do they provide an unconventional step (citing McRO and Trading Technologies Int’l v. IBG). Data gathering steps constitute a general link to a technological environment. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception are insufficient to provide significantly more (as discussed in Alice Corp.,).
With respect to claim 17: The limitations identified above as non-abstract elements (EIA) related to general-purpose computer systems do not rise to the level of significantly more than the judicial exception. These elements do not improve the functioning of the computer itself, or comprise an improvement to any other technical field (Trading Technologies Int’l v. IBG, TLI Communications). They do not require or set forth a particular machine (Ultramercial v. Hulu, LLC., Alice Corp. Pty. Ltd v. CLS Bank Int’l), they do not affect a transformation of matter, nor do they provide an unconventional step. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception are insufficient to provide significantly more (as discussed in Alice Corp., CyberSource v. Retail Decisions, Parker v. Flook, Versata Development Group v. SAP America).
The additional element of performing one or more amplification and sequencing processes with respect to the first genetic material and the second genetic material to generate the sequence reads (claim 14) is conventional. The courts have recognized that amplifying and sequencing nucleic acid sequences is a laboratory technique that is well-understood, routine, conventional activity in the life science arts when they are claimed in a merely generic manner (e.g., at a high level of generality) or as an insignificant extra-solution activity. MPEP 2106.05(d)(II), citing University of Utah Research Foundation v. Ambry Genetics, 774 F.3d 755, 764, 113 USPQ2d 1241, 1247 (Fed. Cir. 2014).
[Step 2B: NO]
Therefore, claims 1-20 are patent ineligible under 35 U.S.C. § 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claims 1, 3-7, 14, and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (Water Resources Research, 2019, 56(2), 1-23), referred to as Zhang [A], in view of Trias et al. (Nature Communications, 2017, 8(1063), 1-14).
With respect to claim 1:
Regarding the recited obtaining, by a computing system including one or more processors and memory, sequence reads that correspond to nucleic acids present in a plurality of samples, the plurality of samples including first samples collected from a first wellbore and second samples collected from a second wellbore, Zhang [A] discloses sampling and sequencing fluids produced from EGS Collab boreholes (pg. 15, para. 5, lines 1-2; pg. 4, para. 2, lines 4-5). This teaches obtaining sequence reads from samples collected from multiple wellbores.
Regarding the recited analyzing, by the computing system, the sequence reads to determine a first community of microorganisms that corresponds to one or more first subsurface geological features through which the first wellbore passes, Zhang [A] discloses constructing a microbial community composition from sequence reads that correspond to boreholes from within the phyllite region of the Precambrian Poorman formation (pg. 4, para. 2, lines 4-6; pg. 4-5, para. 5, lines 1-5; Figures 2 and 4). This teaches analyzing sequence reads to determine communities of microorganisms that correspond to a rock formation through which a wellbore passes.
Regarding the recited analyzing, by the computing system, the sequence reads to determine a second community of microorganisms that corresponds to one or more second subsurface geological features through which the second wellbore passes, Zhang [A] discloses constructing a microbial community composition from sequence reads that correspond to boreholes from within the phyllite region of the Precambrian Poorman formation (pg. 4, para. 2, lines 4-6; pg. 4-5, para. 5, lines 1-5; Figures 2 and 4). This teaches analyzing sequence reads to determine communities of microorganisms that correspond to a rock formation through which a wellbore passes.
Regarding the recited determining, by the computing system, that the second community of microorganisms includes an amount of one or more reference microorganism that correspond to at least a portion of the microorganisms of the first community of microorganisms, Zhang [A] discloses that more than 70% of the OT and PST microbial families overlapped with similar abundances (pg. 10, para. 3, lines 1-4; Figure 4). This teaches a first and second community of microorganisms have a common portion of microorganisms.
Regarding the recited determining, by the computing system, an abundance of the one or more reference microorganisms present in the second community of microorganisms, Zhang [A] discloses normalizing counts of sequence reads to total sequence counts in a sample to determine relative abundances (pg. 7, para. 5, lines 3-5; Figure 4). This teaches determining an abundance of microorganisms present in a second community of microorganisms.
Zhang [A] does not disclose determining, by the computing system and based on the abundance of the one or more reference microorganisms, an amount of movement of a carbon-based gas between the first wellbore and the second wellbore.
However, Trias et al. discloses a small fraction of injected gas reached HN-04 monitoring well from the injection well through fast-flow pathway, which large changes in groundwater microbial community was also observed (pg. 8, col. 2, para. 4, lines 1-4; Fig. 2). This teaches that movement of carbon dioxide between wellbores was determined based on the amount of microorganisms in the wellbores.
It would have been prima facie obvious to one of ordinary skill in the art to modify the microbial community analysis in wellbores disclosed by Zhang [A] to incorporate determining carbon dioxide movement based on microorganisms disclosed by Trias et al. One would be motivated to incorporate analyzing carbon dioxide movement in wellbores because the microbial response to the arrival of CO2-charged water trends with DIC evolution and groundwater geochemical data, as supported by statistical analysis disclosed by Trias et al. (pg. 8, col. 2, para. 4, lines 4-7). This suggests that the relationship between microorganisms and carbon concentrations is strongly evidenced by statistical analysis. There is a likelihood of success, since both teachings are methods of microbial community analysis in wellbores, which are well known in the field of microbial ecology.
With respect to claim 3:
Regarding the recited wherein: the first samples are collected from a plurality of depths below a surface; and individual depths of the plurality of depths correspond to individual subsurface geological features, Zhang [A] discloses fluid samples collected from multiple depths beneath ground surface at the Sanford Underground Research Facility (SURF), where each depth corresponds to different parts of the Precambrian Poorman formation (pg. 4-5, para. 5, lines 1-5; pg. 5-6, para. 2, lines 1-17; Figure 2). This teaches samples collected from a plurality of depths below a surface, each depth corresponding to a subsurface geological feature.
With respect to claim 4:
Regarding the recited wherein the individual subsurface geological features include at least one of a freshwater aquifer, a caprock layer, a rock formation, or a brine reservoir, Zhang [A] discloses that the EGS Collab project involves drilling boreholes into a Precambrian Poorman formation (pg. 4-5, para. 5, lines 2-13). This teaches that an individual subsurface geological feature includes a rock formation.
With respect to claim 5:
Regarding the recited analyzing, by the computing system, a first portion of the sequence reads that corresponds to one or more samples collected from a first individual subsurface geological feature to determine a first reference community of microorganisms that corresponds to a first individual subsurface geological feature, Zhang [A] discloses constructing a microbial community composition from sequence reads that correspond to samples collected from boreholes within the phyllite region of the Precambrian Poorman formation (pg. 4, para. 2, lines 4-6; pg. 4-5, para. 5, lines 1-13; Figures 2 and 4). This teaches analyzing sequence reads to determine communities of microorganisms that correspond to a rock formation.
Regarding the recited analyzing, by the computing system, a second portion of the sequence reads that corresponds to one or more additional samples collected from a second individual subsurface geological feature to determine a second reference community of microorganisms that corresponds to a second individual subsurface geological feature, Zhang [A] discloses constructing a microbial community composition from sequence reads that correspond to samples collected from boreholes within the phyllite region of the Precambrian Poorman formation (pg. 4, para. 2, lines 4-6; pg. 4-5, para. 5, lines 1-13; Figures 2 and 4). This teaches analyzing sequence reads to determine communities of microorganisms that correspond to a rock formation.
With respect to claim 6:
Regarding the recited analyzing, by the computing system, a first number of the sequence reads that corresponds to first genomic sequences of the first reference community of microorganisms present in the second community of microorganisms, Zhang [A] discloses a sequence table, which is a matrix that gives the number of counts of each sequence variant in each sample, was generated from quality-filtered reads (pg. 7, para. 5, lines 1-2). Also, further discloses using these counts to visualize the microbial community composition in each sample (pg. 7, para. 5, lines 3-5; Figure 4). This teaches analyzing a number of sequence reads that corresponds to a community of microorganisms present in a second community of microorganisms.
Regarding the recited determining, by the computing system and based on the first number of the sequence reads, a first abundance of the first reference community of microorganisms present in the second community of microorganisms, Zhang [A] discloses normalizing counts of sequence reads to total sequence counts in a sample to determine relative abundances (pg. 7, para. 5, lines 3-5; Figure 4). This teaches determining an abundance of microorganisms present in a second community of microorganisms based on a number of sequence reads.
Regarding the recited analyzing, by the computing system, a second number of the sequence reads that corresponds to second genomic sequences of the second reference community of microorganisms present in the second community of microorganisms, Zhang [A] discloses a sequence table, which is a matrix that gives the number of counts of each sequence variant in each sample, was generated from quality-filtered reads (pg. 7, para. 5, lines 1-2). Also, further discloses using these counts to visualize the microbial community composition in each sample (pg. 7, para. 5, lines 3-5; Figure 4). This teaches analyzing a number of sequence reads that corresponds to a community of microorganisms present in a second community of microorganisms.
Regarding the recited determining, by the computing system and based on the second number of the sequence reads, a second abundance of the second reference community of microorganisms present in the second community of microorganisms, Zhang [A] discloses normalizing counts of sequence reads to total sequence counts in a sample to determine relative abundances (pg. 7, para. 5, lines 3-5; Figure 4). This teaches determining an abundance of microorganisms present in a second community of microorganisms based on a number of sequence reads.
With respect to claim 7:
Regarding the recited determining, by the computing system, a microbial source log indicating: a first amount of the second community of microorganisms that corresponds to the first individual subsurface geological feature based on the first abundance of the first reference community of microorganisms present in the second community of microorganisms, Zhang [A] discloses that more than 70% of the OT and PST microbial families overlapped with similar abundances and that a major component of such “signature” community in the two families is the family Rhodocyclaceae (21.5% in OT and 36.4% in PST) (pg. 10, para. 3, lines 1-6; Figure 4). This teaches that a number of microorganisms corresponds to OT based on its abundance also being present in PST. Therefore, both communities of microorganisms in OT and PST subsurface geological features have a common portion of microorganisms.
Regarding the recited determining, by the computing system, a microbial source log indicating: a second amount of the second community of microorganisms that corresponds to the second individual subsurface geological feature based on the second abundance of the second reference community of microorganisms present in the second community of microorganism, Zhang [A] discloses that more than 70% of the OT and PST microbial families overlapped with similar abundances and that a major component of such “signature” community in the two families is the family Rhodocyclaceae (21.5% in OT and 36.4% in PST) (pg. 10, para. 3, lines 1-6; Figure 4). This teaches that a number of microorganisms corresponds to PST based on its abundance also being present in OT. Therefore, both communities of microorganisms in OT and PST subsurface geological features have a common portion of microorganisms.
With respect to claim 14:
Regarding the recited extracting first genetic material from the first samples, Zhang [A] discloses DNA extraction first performed on each filter of samples to isolate and purify the genomic DNA from impurities (pg. 7, para. 3, lines 1-2). This teaches extracting genetic material from samples.
Regarding the recited extracting second genetic material from the second samples, Zhang [A] discloses DNA extraction first performed on each filter of samples to isolate and purify the genomic DNA from impurities (pg. 7, para. 3, lines 1-2). This teaches extracting genetic material from samples.
Regarding the recited performing one or more amplification and sequencing processes with respect to the first genetic material and the second genetic material to generate the sequence reads, Zhang [A] discloses amplifying and sequencing the extracted DNA (pg. 7, para. 3, lines 2-6). This teaches performing amplification and sequencing processes on genetic material to generate sequence reads.
With respect to claim 16:
Regarding the recited determining, by the computing system, taxonomic classifications for at least a portion of microorganisms included in the first community of microorganisms and the second community of microorganisms, Zhang [A] discloses assigning taxonomy to each sequence, which are then visualized in the microbial community composition for each sample (pg. 7, para. 5, lines 2-5; Figure 4). This teaches determining taxonomic classifications for portions of microorganisms included in communities of microorganisms.
With respect to claim 17:
Claim 17 recites a computing system comprising one or more hardware processors and memory storing computer-readable instructions.
Broadly claiming an automated means to replace a manual function to accomplish the same result does not distinguish over the prior art. See Leapfrog Enters., Inc. v. Fisher-Price, Inc., 485 F .3d 1157, 1161, 82 USPQ2d 1687, 1691 (Fed. Cir. 2007) (“Accommodating a prior art mechanical device that accomplishes [a desired] goal to modern electronics would have been reasonably obvious to one of ordinary skill in designing children’s learning devices. Applying modern electronics to older mechanical devices has been commonplace in recent years.”); In re Venner, 262 F. 2d 91, 95, 120 USPQ 193, 194 (CCPA 1958); see also MPEP § 2144.04. Furthermore, implementing a known function on a computer has been deemed obvious to one of ordinary skill in the art if the automation of the known function on a general purpose computer is nothing more than the predictable use of prior art elements according to their established functions. KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 417, 82 USPQ2d 1385, 1396 (2007); see also MPEP § 2143, Exemplary Rationales D and F. Likewise, it has been found to be obvious to adapt an existing process to incorporate Internet and Web browser technologies for communicating and displaying information because these technologies had become commonplace for those functions. Muniauction, Inc. v. Thomson Corp., 532 F.3d 1318, 1326-27, 87 USPQ2d 1350, 1357 (Fed. Cir. 2008).
Regarding the recited obtaining sequence reads that correspond to nucleic acids present in a plurality of samples, the plurality of samples including first samples collected from a first wellbore and second samples collected from a second wellbore, Zhang [A] discloses sampling and sequencing fluids produced from EGS Collab boreholes (pg. 15, para. 5, lines 1-2; pg. 4, para. 2, lines 4-5). This teaches obtaining sequence reads from samples collected from multiple wellbores.
Regarding the recited analyzing the sequence reads to determine a first community of microorganisms that corresponds to one or more first subsurface geological features through which the first wellbore passes, Zhang [A] discloses constructing a microbial community composition from sequence reads that correspond to boreholes from within the phyllite region of the Precambrian Poorman formation (pg. 4, para. 2, lines 4-6; pg. 4-5, para. 5, lines 1-5; Figures 2 and 4). This teaches analyzing sequence reads to determine communities of microorganisms that correspond to a rock formation through which a wellbore passes.
Regarding the recited analyzing the sequence reads to determine a second community of microorganisms that corresponds to one or more second subsurface geological features through which the second wellbore passes, Zhang [A] discloses constructing a microbial community composition from sequence reads that correspond to boreholes from within the phyllite region of the Precambrian Poorman formation (pg. 4, para. 2, lines 4-6; pg. 4-5, para. 5, lines 1-5; Figures 2 and 4). This teaches analyzing sequence reads to determine communities of microorganisms that correspond to a rock formation through which a wellbore passes.
Regarding the recited determining that the second community of microorganisms includes one or more reference microorganism that correspond to at least a portion of the microorganisms of the first community of microorganisms, Zhang [A] discloses that more than 70% of the OT and PST microbial families overlapped with similar abundances (pg. 10, para. 3, lines 1-4; Figure 4). This teaches a first and second community of microorganisms have a common portion of microorganisms.
Regarding the recited determining an abundance of the one or more reference microorganisms present in the second community of microorganisms, Zhang [A] discloses normalizing counts of sequence reads to total sequence counts in a sample to determine relative abundances (pg. 7, para. 5, lines 3-5; Figure 4). This teaches determining an abundance of microorganisms present in a second community of microorganisms.
Zhang [A] does not disclose determining, based on the abundance of the one or more reference microorganisms, an amount of movement of a carbon-based gas between the first wellbore and the second wellbore.
However, Trias et al. discloses a small fraction of injected gas reached HN-04 monitoring well from the injection well through fast-flow pathway, which large changes in groundwater microbial community was also observed (pg. 8, col. 2, para. 4, lines 1-4; Fig. 2). This teaches that movement of carbon dioxide between wellbores was determined based on the amount of microorganisms in the wellbores.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (Water Resources Research, 2019, 56(2), 1-23), referred to as Zhang [A], and Trias et al. (Nature Communications, 2017, 8(1063), 1-14) as applied to claims 1, 3-7, 14, and 16-17 above, in view of Peet et al. (Applied and Environmental Microbiology, 2015, 81(8), 2881-2892).
Zhang [A] and Trias et al. are applied to claims 1, 3-7, 14, and 16-17 above.
With respect to claim 2:
Zhang [A] and Trias et al. do not disclose wherein: an amount of the carbon-based gas is injected into the first wellbore.
However, Peet et al. discloses that for sample collection, 10 to 20 liters of formation fluids were collected from sequestration sites before, during, and after CO2 injection (pg. 2882, col. 1, para. 2, lines 5-7). This teaches that an amount of carbon dioxide was injected into a wellbore.
Zhang [A] and Trias et al. do not disclose wherein: the first samples are collected before the amount of carbon-based gas is injected into the first wellbore.
However, Peet et al. discloses that for sample collection, 10 to 20 liters of formation fluids were collected from sequestration sites before, during, and after CO2 injection (pg. 2882, col. 1, para. 2, lines 5-7). This teaches that samples were collected before carbon dioxide injection.
Zhang [A] and Trias et al. do not disclose wherein: the second samples are collected after the amount of carbon-based gas is injected into the first wellbore.
However, Peet et al. discloses that for sample collection, 10 to 20 liters of formation fluids were collected from sequestration sites before, during, and after CO2 injection (pg. 2882, col. 1, para. 2, lines 5-7). This teaches that samples were collected after carbon dioxide injection.
It would have been prima facie obvious to one of ordinary skill in the art to modify the microbial community analysis in wellbores disclosed by Zhang [A] and Trias et al. to incorporate sample collection from wellbores disclosed by Peet et al. One would be motivated to incorporate the different sample collection methods from wellbores because Peet et al. discloses that the 16S rRNA gene was amplified and cloned from DNA extracted from passage 3 of Otway core 3, yielding 26 clones of a single ribotype matching B. subterraneus with 98.5% identity (1,502/1,521 nucleotides) (pg. 2885, col. 2, para. 1, lines 9-12). This means that the method effectively amplifies and clones the 16S rRNA gene, producing precise clones with high percentage of identity. Therefore, methods of sample collection will also be as effective to support microbial community analysis in wellbores. There is a likelihood of success, since microbial growth analysis and overall microbial community analysis in wellbores are well known techniques in the field of microbial ecology.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (Water Resources Research, 2019, 56(2), 1-23), referred to as Zhang [A], and Trias et al. (Nature Communications, 2017, 8(1063), 1-14) as applied to claims 1, 3-7, 14, and 16-17 above, in view of Morozova et al. (International Journal of Greenhouse Gas Control, 2010, 4(6), 981-989).
Zhang [A] and Trias et al. are applied to claims 1, 3-7, 14, and 16-17 above.
With respect to claim 8:
Zhang [A] and Trias et al. do not disclose wherein: the first abundance of the first reference community of microorganisms present in the second community of microorganisms corresponds to a first amount of fluid displaced in the first individual subsurface geological feature in response to injection of one or more carbon-based gases at the first wellbore.
However, Morozova et al. discloses active numbers of bacterial cells corresponding to fluid probes taken from an observation well in response to carbon dioxide injection (pg. 985-986, Fig. 3 and 4). This teaches a number of microorganisms present in a community of microorganisms that correspond to fluid displaced in response to carbon dioxide injection.
Zhang [A] and Trias et al. do not disclose wherein: the second abundance of the second reference community of microorganisms present in the second community of microorganisms corresponds to a second amount of fluid displaced in the second individual subsurface geological features in response to the injection of the one or more carbon-based gases at the first wellbore.
However, Morozova et al. discloses active numbers of bacterial cells corresponding to fluid probes taken from an observation well in response to carbon dioxide injection (pg. 985-986, Fig. 3 and 4). This teaches a number of microorganisms present in a community of microorganisms that correspond to fluid displaced in response to carbon dioxide injection.
It would have been prima facie obvious to one of ordinary skill in the art to modify the microbial community analysis in wellbores disclosed by Zhang [A] and Trias et al. to incorporate corresponding microorganisms to displaced fluids disclosed by Morozova et al. One would be motivated to incorporate relating amounts of microorganisms to displaced fluids because the study disclosed by Morozova et al. uses the fluorescence in situ hybridization (FISH) technique to assess the influence of CO2 exposure on the composition of microbial communities, which allows for direct visualization, identification, and localization of bacterial cells from selected phylogenetic groups in environmental samples (pg. 982, col. 1, para. 2-3, lines 4-21). This means that the FISH technique will be able to clearly visualize, identify, and localize bacterial cells in samples. Therefore, this will also clearly connect microorganisms to displaced fluids under the influence of carbon dioxide for microbial community analysis in wellbores. There is a likelihood of success, since both teachings are microbial community analyses in wellbores, which are well known methods in the field of microbial ecology.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (Water Resources Research, 2019, 56(2), 1-23), referred to as Zhang [A], Trias et al. (Nature Communications, 2017, 8(1063), 1-14), and Morozova et al. (International Journal of Greenhouse Gas Control, 2010, 4(6), 981-989) as applied to claims 1, 3-8, 14, and 16-17 above, in view of Zhang et al. (Water Resources Research, 2018, 55(1), 856-867); refer to as Zhang [B].
Zhang [A], Trias et al., and Morozova et al. are applied to claims 1, 3-8, 14, and 16-17 above.
With respect to claim 9:
Zhang [A], Trias et al., and Morozova et al. do not disclose determining, by the computing system, a first location of the one or more carbon-based gases in the first individual subsurface geological feature based on the first amount of fluid displaced in the first individual subsurface geological feature in response to injection of one or more carbon-based gases at the first wellbore.
However, Zhang [B] discloses a well-known adsorption-induced swelling phenomenon in clay-rich rocks that is considered a naturally generated “saturation footprint” that tracks CO2 migration through reservoirs, and testing this idea of tracking these footprints to monitor migration of CO2 plumes by measuring strain changes during dynamic CO2/brine displacements in a clay-rich rock (pg. 856, para. 2, lines 3-9; Figure 1(a)). This teaches tracking carbon dioxide locations in reservoirs based on fluid displaced in response to carbon dioxide injection.
Zhang [A], Trias et al., and Morozova et al. do not disclose determining, by the computing system, a second location of the one or more carbon-based gases in the second individual subsurface geological features based on the second amount fluid displaced in the second individual subsurface geological features in response to the injection of the one or more carbon-based gases at the first wellbore.
However, Zhang [B] discloses a well-known adsorption-induced swelling phenomenon in clay-rich rocks that is considered a naturally generated “saturation footprint” that tracks CO2 migration through reservoirs, and testing this idea of tracking these footprints to monitor migration of CO2 plumes by measuring strain changes during dynamic CO2/brine displacements in a clay-rich rock (pg. 856, para. 2, lines 3-9; Figure 1(a)). This teaches tracking carbon dioxide locations in reservoirs based on fluid displaced in response to carbon dioxide injection.
It would have been prima facie obvious to one of ordinary skill in the art to modify the microbial community analysis in wellbores disclosed by Zhang [A], Trias et al., and Morozova et al. to incorporate determining carbon dioxide locations disclosed by Zhang [B]. One would be motivated to incorporate determining carbon dioxide locations because the study disclosed by Zhang [B] straightforwardly demonstrated that the DFOSS technique accurately measures the distributed strain signals in rocks during supercritical CO2/brine displacement (pg. 864, para. 2, lines 1-3). This means that the DFOSS technique will accurately measure locations of carbon dioxide based on displaced fluids. There is a likelihood of success, since microbial community analysis in wellbores and tracking carbon dioxide migration through reservoirs are well known techniques in the field of earth science.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (Water Resources Research, 2019, 56(2), 1-23), referred to as Zhang [A], Trias et al. (Nature Communications, 2017, 8(1063), 1-14), Morozova et al. (International Journal of Greenhouse Gas Control, 2010, 4(6), 981-989), and Zhang et al. (Water Resources Research, 2018, 55(1), 856-867), referred to as Zhang [B], as applied to claims 1, 3-9, 14, and 16-17 above, in view of Fahrner et al. (International Journal of Greenhouse Gas control, 2012, 9, 262-271).
Zhang [A], Trias et al., Morozova et al., and Zhang [B] are applied to claims 1, 3-9, 14, and 16-17 above.
With respect to claim 10:
Zhang [A], Trias et al., Morozova et al., and Zhang [B] do not disclose wherein the second individual subsurface geological feature is a freshwater aquifer.
However, Fahrner et al. discloses detection of CO2 intrusion in freshwater aquifers (pg. 270, col. 1, para. 3, lines 1-8). This teaches that a freshwater aquifer is the subsurface geological feature.
Zhang [A], Trias et al., Morozova et al., and Zhang [B] do not disclose determining, by the computing system, that an amount of the one or more carbon-based gases is present in the freshwater aquifer based on the second location of the one or more carbon-based gases.
However, Fahrner et al. discloses site specific monitoring strategies at CO2 injection sites to detect leakage events, including identifying total inorganic carbon concentrations, and to ensure the safety of freshwater aquifers (pg. 270, col. 1, para. 3, lines 1-8). This teaches determining an amount of carbon dioxide is present in freshwater aquifer based on carbon dioxide injection sites.
It would have been prima facie obvious to one of ordinary skill in the art to modify the microbial community analysis in wellbores disclosed by Zhang [A], Trias et al., Morozova et al., and Zhang [B] to incorporate determining the presence of carbon dioxide in freshwater aquifers disclosed by Fahrner et al. One would be motivated to incorporate determining the presence of carbon dioxide because the study disclosed by Fahrner et al. clearly identifies the pH, TIC, and EC as suited monitoring parameters for the detection of CO2 intrusion in freshwater aquifers (pg. 270, col. 1, para. 3, lines 3-6). This means that detection of carbon dioxide in freshwater aquifers will be reliably identified using clear monitoring parameters. There is a likelihood of success, since microbial community analysis in wellbores and carbon dioxide monitoring strategies in freshwater aquifers are well known techniques in the field of earth science.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (Water Resources Research, 2019, 56(2), 1-23), referred to as Zhang [A], Trias et al. (Nature Communications, 2017, 8(1063), 1-14), Morozova et al. (International Journal of Greenhouse Gas Control, 2010, 4(6), 981-989), and Zhang et al. (Water Resources Research, 2018, 55(1), 856-867), referred to as Zhang [B], as applied to claims 1, 3-9, 14, and 16-17 above, in view of Siriwardane et al. (Energy & Fuels, 2013, 27(8), 4232-4243).
Zhang [A], Trias et al., Morozova et al., and Zhang [B] are applied to claims 1, 3-9, 14, and 16-17 above.
With respect to claim 11:
Zhang [A], Trias et al., Morozova et al., and Zhang [B] do not disclose wherein the first individual subsurface geological feature is located above a caprock layer and the second individual subsurface geological feature is located below a caprock layer.
However, Siriwardane et al. discloses a figure that shows the CO2 transport in the reservoir and overburden layers as a result of injection of CO2 with and without the presence of a simulated fractured zone at the end of a 5 year injection period (pg. 4236, col. 1, para. 1, lines 7-22; Figure 4). This teaches that there is a monitoring layer, which is a subsurface geological feature located above a caprock layer, and a reservoir layer, which is a subsurface geological feature located below a caprock layer.
Zhang [A], Trias et al., Morozova et al., and Zhang [B] do not disclose determining, by the computing system, that a breach of the caprock layer has occurred based on the first location of the one or more carbon-based gases and the second location of the one or more carbon-based gases.
However, Siriwardane et al. discloses that the injection of CO2 causes the reservoir pressure to increase with time, and the pressure increase in the monitoring layer is significant in the presence of a breach in the caprock (pg. 4236, col. 1, para. 1, lines 7-22; Figure 4). This teaches that a breach of the caprock layer has occurred based on the increase in pressure and carbon dioxide migration from the reservoir layer to the monitoring layer, as depicted in Figure 4.
It would have been prima facie obvious to one of ordinary skill in the art to modify the microbial community analysis in wellbores disclosed by Zhang [A], Trias et al., Morozova et al., and Zhang [B] to incorporate determination of a breach of caprock layer disclosed by Siriwardane et al. One would be motivated to incorporate determining a breach of caprock layer because results of the study disclosed by Siriwardane et al. show that the presence of a fault/fractured zone in the caprock layer can significantly change the pressure response in the monitoring layer and the overburden ground response (pg. 4240, col. 2, para. 1, lines 18-27). Numerical models throughout the study, such as Figure 12, also clearly depict highest pressure at the fracture location (pg. 4238). This means that determining a breach of the caprock layer using numerical modeling makes it obvious when there is a breach present at a caprock layer. There is a likelihood of success, since microbial community analysis in wellbores and modeling of carbon dioxide migration in the presence of a caprock fracture are well known techniques in the field of earth science.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (Water Resources Research, 2019, 56(2), 1-23), referred to as Zhang [A], Trias et al. (Nature Communications, 2017, 8(1063), 1-14), Morozova et al. (International Journal of Greenhouse Gas Control, 2010, 4(6), 981-989), and Zhang et al. (Water Resources Research, 2018, 55(1), 856-867), referred to as Zhang [B], as applied to claims 1, 3-9, 14, and 16-17 above, in view of Jeong et al. (International Journal of Greenhouse Gas Control, 2018, 71, 278-292) and Nielsen et al. (Energy Procedia, 2017, 114, 4787-4796).
Zhang [A], Trias et al., Morozova et al., and Zhang [B] are applied to claims 1, 3-9, 14, and 16-17 above.
With respect to claim 12:
Zhang [A], Trias et al., Morozova et al., and Zhang [B] do not disclose obtaining, by the computing system, pressure measurements from one or more pressure sensors present in at least one of the first individual subsurface geological feature or the second individual subsurface geological feature.
However, Jeong et al. discloses downhole pressure gauges that takes pressure measurements from caprock formations (pg. 280, col. 1, para. 3, lines 3-9; pg. 280, col. 2, para. 1, lines 1-7; pg. 290, col. 1, para. 3, lines 2-5). This teaches obtaining pressure measurements from pressure sensors at a subsurface geological feature.
Zhang [A], Trias et al., Morozova et al., and Zhang [B] do not disclose analyzing, by the computing system, the pressure measurements in conjunction with the first location of the carbon-based gases and the second location of the carbon-based gases to determine that a pressure threshold in at least one of the first individual subsurface geological feature or the second individual subsurface geological feature has been exceeded.
However, Jeong et al. discloses that leakage is detected in wells at caprock formations if pressure buildup is measured to be greater than a predefined pressure threshold (pg. 280, col. 2, para. 1, lines 1-7; pg. 284-285, col. 2, para. 3, lines 1-4). This teaches analyzing pressure measurements in wells to determine that a pressure threshold has been exceeded.
Zhang [A], Trias et al., Morozova et al., Zhang [B], and Jeong et al. do not disclose determining one or more pressure mitigation operations to apply with respect to at least one of the first individual subsurface geological feature or the second individual subsurface geological feature.
However, Nielsen et al. discloses selecting model boundary conditions and modelling mitigation of pressure development by use of a large regional model with local structural traps in the Bunter Sandstone Formation in the UK Southern North Sea (pg. 4787, para. 1, lines 8-16; pg. 4791, para. 4, lines 1-2; pg. 4793, para. 3, lines 1-2). This teaches pressure mitigation operations to apply with respect to a subsurface geological feature.
It would have been prima facie obvious to one of ordinary skill in the art to modify the microbial community analysis in wellbores disclosed by Zhang [A], Trias et al., Morozova et al., and Zhang [B] to incorporate pressure measurements from pressure sensors disclosed by Jeong et al. and pressure mitigation operations disclosed by Nielsen et al. One would be motivated to incorporate pressure measurements taken from sensors because the optimal solution produced by the study disclosed by Jeong et al. is regarded as a solution that minimizes total costs across all scenarios (pg. 291, col. 1, para. 4, lines 5-7). This means that obtaining pressure measurements from sensors will be less costly for microbial community analysis in wellbores. Nielsen et al. also discloses optimizing computational time when assessing the effect of pressure management from water production on two neighboring storage sites by using only a smaller part from the regional model (pg. 4791, para. 3, lines 1-4). This means that determining pressure mitigation operations could take less computational time. There is a likelihood of success, since microbial community analysis, pressure-based monitoring networks, and modeling pressure management for large scale carbon capture and storage are well known techniques in the field of earth science.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (Water Resources Research, 2019, 56(2), 1-23), referred to as Zhang [A], Trias et al. (Nature Communications, 2017, 8(1063), 1-14), Morozova et al. (International Journal of Greenhouse Gas Control, 2010, 4(6), 981-989), and Zhang et al. (Water Resources Research, 2018, 55(1), 856-867), referred to as Zhang [B], as applied to claims 1, 3-9, 14, and 16-17 above, in view of Hsu et al. (Separation and Purification Technology, 2012, 94, 146-153).
Zhang [A], Trias et al., Morozova et al., and Zhang [B] are applied to claims 1, 3-9, 14, and 16-17 above.
With respect to claim 13:
Zhang [A], Trias et al., Morozova et al., and Zhang [B] do not disclose analyzing, by the computing system, the first location of the one or more carbon-based gases and the second location of the one or more carbon-based gases to determine a storage capacity for the one or more carbon-based gases in at least one of the first individual subsurface geological feature or the second individual subsurface geological feature.
However, Hsu et al. discloses ranking various reservoir sites in terms of potential storage capacity to help evaluate how much CO2 may be stored to enable effective control of atmospheric CO2 concentrations (pg. 147, col. 1, para. 3, lines 1-12; pg. 147-148, col. 2, para. 6, lines 1-11). This teaches analyzing carbon dioxide storage locations to estimate storage capacity for carbon dioxide in a subsurface geological feature or reservoir.
It would have been prima facie obvious to one of ordinary skill in the art to modify the microbial community analysis in wellbores disclosed by Zhang [A], Trias et al., Morozova et al., and Zhang [B] to incorporate determining storage capacity from carbon dioxide locations disclosed by Hsu et al. One would be motivated to incorporate determining storage capacity because the presented framework of site selection for CO2 geological storage from Hsu et al. not only overcomes the limitations in field data in pre-screening potential sites, but also reduces resource investment (pg. 152, col. 1-2, para. 3, lines 16-19). This means that determining storage capacity in the overall microbial community analysis in wellbores will take less materials and become more resourceful. There is a likelihood of success, since microbial community analysis and site-selection for carbon dioxide storage are well known techniques in the field of earth science.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (Water Resources Research, 2019, 56(2), 1-23), referred to as Zhang [A], and Trias et al. (Nature Communications, 2017, 8(1063), 1-14) as applied to claims 1, 3-7, 14, and 16-17 above, in view of Petti et al. (Clinical Infectious Diseases, 2007, 44(8), 1108-1114).
Zhang [A] and Trias et al. are applied to claims 1, 3-7, 14, and 16-17 above.
With respect to claim 15:
Zhang [A] and Trias et al. do not disclose analyzing, by the computing system, the sequence reads with respect to genomic sequences of microorganisms to determine an amount of identity between individual sequence reads and the genomic sequences of the microorganisms.
However, Petti et al. discloses classification of gene sequences to a particular genus or species requiring analysis with a reference library and this analysis reports nucleotide sequences in terms of “percent identity”, which refers to the number of identical nucleotide bases shared by the query and reference sequences divided by the number of nucleotide bases sequenced (pg. 1109, col. 2, para. 2, lines 1-5; pg. 1110, col. 1, para. 2, lines 1-4). This teaches analyzing sequence reads with respect to genomic sequences to determine an amount of identity.
Zhang [A] and Trias et al. do not disclose determining, by the computing system, than an individual sequence read corresponds to a genomic sequence of a microorganism based on the amount of identity between the individual sequence read and the genomic sequence of the microorganism being at least a threshold amount of identity.
However, Petti et al. discloses that for bacteria identified by the 16S rRNA gene using the classification analysis, most taxonomists accept a percent identity score of
≥
97% and
≥
99% to classify a microorganism to genus and species, respectively (pg. 1110, col. 1, para. 2, lines 1-4; pg. 1110, col. 1, para. 2, lines 9-12; Figure 3). This teaches that a sequence corresponds to a genomic sequence of a microorganism based on an amount of identity greater than a threshold score of either 97% or 99%.
It would have been prima facie obvious to one of ordinary skill in the art to modify the microbial community analysis in wellbores disclosed by Zhang [A] and Trias et al. to incorporate identifying sequence reads corresponding to genomic sequence reads of a microorganism based on percent identity disclosed by Petti et al. One would be motivated to incorporate determining sequence reads based on percent identity because Petti et al. discloses that 16S rRNA gene sequencing allows for reliable identification of Inquinilus limosus from respiratory samples (pg. 1111, col. 2, para. 1, lines 3-5). This suggests that determining sequence reads based on percent identity for microbial community analysis in wellbores will be very reliable. There is a likelihood of success, since microbial community analysis and gene sequencing are well known techniques in the field of microbial ecology.
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (Water Resources Research, 2019, 56(2), 1-23), referred to as Zhang [A], and Trias et al. (Nature Communications, 2017, 8(1063), 1-14) as applied to claims 1, 3-7, 14, and 16-17 above, in view of Yanagawa et al. (The ISME Journal, 2012, 7(3), 555-567) and Seyyedi et al. (Scientific Reports, 2020, 10(3624), 1-14).
Zhang [A] and Trias et al. are applied to claims 1, 3-7, 14, and 16-17 above.
With respect to claim 15:
Zhang [A] and Trias et al. do not disclose determining that an additional abundance of one or more classifications of microorganisms present in the second community of microorganisms has decreased, the one or more classifications of microorganisms including microorganisms that are unable to survive in environments where greater than a threshold amount of the carbon-based gas is present.
However, Yanagawa et al. discloses a decrease in number of microbes with respect to increasing sediment depth and CO2 concentration (pg. 555, Abstract, lines 9-10; pg. 560, col. 1, para. 2, lines 7-12). Also, further discloses that the decrease in microbes due to increase in CO2 indicates that CO2 extremes are critical geochemical constraints for biomes in the marine sedimentary habitat, where CO2 concentrations are measured to be several tens of mol
m
-
3
(pg. 564, col. 1, para. 3, lines 4-11; pg. 564, col. 2, para. 2, lines 8-11). This teaches that a number of one or more classifications of microorganisms has decreased, which are also microorganisms that are unable to survive in carbon dioxide concentrations greater than several tens of mol
m
-
3
.
Zhang [A], Trias et al., and Yanagawa et al. do not disclose determining that a dissolution front of the carbon-based gas is present at a location of the second wellbore.
However, Seyyedi et al. discloses that during CO2 injection into saline aquifers or depleted oil fields, a CO2-saturated brine (carbonated brine) front will be formed ahead of the CO2 front (pg. 2, para. 2, lines 1-2). This teaches that a dissolution front of carbon dioxide will be present at a location of a wellbore.
It would have been prima facie obvious to one of ordinary skill in the art to modify the microbial community analysis in wellbores disclosed by Zhang [A] and Trias et al. to incorporate a decrease in microorganisms based on a threshold disclosed by Yanagawa et al. and a dissolution front of carbon dioxide disclosed by Seyyedi et al. One would be motivated to incorporate a decrease in microorganisms based on a threshold amount of carbon dioxide because Yanagawa et al. discloses that the number of microbes in the upper 10 cm of sediment for MUC8, MUC10, and Dive 201 PC28 samples from CO2-seep sites were consistent with the number found in samples from MUC23 at the reference site (pg. 560, col. 1, para. 2, lines 1-6). This means that determining the decrease in microorganisms will be consistent in microbial community analysis in wellbores. Seyyedi et al. also discloses that their novel core flooding approach examines effects from pore to continuum scales (pg. 2, para. 2, lines 1-2). This suggests that the method for detecting the presence of dissolution front can be examined in a broad range, from microscopic to macroscopic changes, which provides certainty for detection in all aspects. There is a likelihood of success, since microbial community analyses and investigating pore structure changes in reservoirs are well known techniques in the field of earth science.
Claims 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (Water Resources Research, 2019, 56(2), 1-23), referred to as Zhang [A], and Trias et al. (Nature Communications, 2017, 8(1063), 1-14) as applied to claims 1, 3-7, 14, and 16-17 above, in view of Würdemann et al. (International Journal of Greenhouse Gas Control, 2010, 4(6), 938-951).
Zhang [A] and Trias et al. are applied to claims 1, 3-7, 14, and 16-17 above.
With respect to claim 19:
Zhang [A] does not disclose determining locations of the one or more carbon-based gases in at least one of the one or more first subsurface geological features or the one or more second subsurface geological features based on one or more microorganisms originating in the one or more first subsurface geological features being present in the one or more second subsurface geological features.
However, Trias et al. discloses analyzing the groundwater community in the control well HN-01 being present or absent in the monitoring well HN-04 to determine carbon dioxide arrival in a location (pg. 2, col. 2, para. 1, lines 4-6; pg. 10, col. 2, para. 2, lines 16-18; pg. 10, col. 1, Figure 7, lines 2-7). This teaches the monitoring well as the location of carbon dioxide where microorganisms originating from the control well is also present in the monitoring well, which is also depicted in Figure 2.
Zhang [A] and Trias et al. do not disclose generating a model to predict the amount of movement of the carbon-based gas between the first wellbore and the second wellbore based on the locations of the one or more carbon-based gases in at least one of the one or more first subsurface geological features or the one or more second subsurface geological features.
However, Würdemann et al. discloses performing simulations to predict the arrival of CO2 from the injection well to the observation wells and the amount of CO2 needed to arrive at the wells (pg. 944-945, col. 2, para. 2, lines 1-18; pg. 948, col. 2, para. 4, lines 1-4). This teaches generating models to predict the amount of carbon dioxide that was moved between the injection well and the observation well, where the location of carbon dioxide is beneath a caprock.
It would have been prima facie obvious to one of ordinary skill in the art to modify the microbial community analysis in wellbores disclosed by Zhang [A] and Trias et al. to incorporate the predictive simulations for carbon dioxide movement disclosed by Würdemann et al. One would be motivated to incorporate a predictive model because Würdemann et al. discloses that a Gas Membrane Sensor (GMS) was used to monitor changes in the reservoir gas composition in the observation wells in near real time, as a low cost, high resolution alternative to U-tube sampling (pg. 939, col. 2, para. 3, lines 7-10). This means that the predictive model using this sensor is less costly if implemented in the microbial community analysis in wellbores disclosed by Zhang [A] and Trias et al. There is a likelihood of success, since microbial community analyses and exploration of monitoring technologies in CO2 storage are well known techniques in the field of earth science.
With respect to claim 20:
Zhang [A] and Trias et al. do not disclose causing a user interface to be generated that includes one or more graphics indicating the amount of movement of the carbon-based gas between the first wellbore and the second wellbore.
However, Würdemann et al. discloses Figure 7, which depicts the amount of CO2 injected into the injection well whose migration in the injection and observation wells is monitored in Figures 5 and 9 (pg. 944-945 and 947). This teaches graphics indicating the amount of carbon dioxide migration between two wellbores.
Conclusion
No claims are allowed.
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/J.N.L./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686
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