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 .
DETAILED ACTION
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 12 December 2023 and 16 May 2024 were filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Specification
The abstract of the disclosure is objected to because the words “For example” should be avoided. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
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 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1 (and dependent claims 2-19) recite “A method comprising: performing a first set of mathematical operations on a set of formation resistivity data to identify a set of formation values; evaluating a set of gamma ray (GR) formation log data collected to identify a set of formation GR values; performing a second set of mathematical operations on the formation resistivity data based on the set of formation GR values; and updating the set of formation values based on the performance of the second set of mathematical operations.”
Claims 1-19, in view of the claim limitations, recite the abstract idea of “performing a first set of mathematical operations on a set of formation resistivity data to identify a set of formation values; evaluating a set of gamma ray (GR) formation log data collected to identify a set of formation GR values; performing a second set of mathematical operations on the formation resistivity data based on the set of formation GR values; and updating the set of formation values based on the performance of the second set of mathematical operations.”
As a whole, in view of the claim limitations, but for the computer components and systems performing the claimed functions, the broadest reasonable interpretation of the recited “performing a first set of mathematical operations on a set of formation resistivity data to identify a set of formation values; evaluating a set of gamma ray (GR) formation log data collected to identify a set of formation GR values; performing a second set of mathematical operations on the formation resistivity data based on the set of formation GR values; and updating the set of formation values based on the performance of the second set of mathematical operations.”; therefore, the claims recite mental processes and mathematical concepts. Accordingly, the claims recite a mental process and mathematical concept, and thus, the claims recite an abstract idea under the first prong of Step 2A.
This judicial exception is not integrated into a practical application under the second prong of Step 2A. In particular, the claims recite the additional elements beyond the recited abstract idea of“[a] computer- implemented method” and “the method is carried out by one or more physical processors configured by machine-readable instructions” as recited in claims 20 and 21, individually and when viewed as an ordered combination, and pursuant to the broadest reasonable interpretation, each of the additional elements are computing elements recited at high level of generality implementing the abstract idea on a computer (i.e. apply it), and thus, are no more than applying the abstract idea with generic computer components. Moreover, aside from the aforementioned additional elements, the remaining elements of dependent claims 2-19 do not integrate the abstract idea into a practical application because these claims merely recite further limitations that provide no more than simply narrowing the recited abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception under Step 2B. As noted above, the aforementioned additional elements beyond the recited abstract idea, as an order combination, are no more than mere instructions to implement the idea using generic computer components (i.e. apply it), and further, generally link the abstract idea to a field of use, which is not sufficient to amount to significantly more than an abstract idea; therefore, the additional elements are not sufficient to amount to significantly more than an abstract idea. Additionally, these recitations as an ordered combination, simply append the abstract idea to recitations of generic computer structure performing generic computer functions that are well-understood, routine, and conventional in the field as evinced by Applicant’s Specification at [0084] (describing that the disclosure is not limited to the disclosed implementations, but, on the contrary, is intended to cover modifications and equivalent arrangements that are within the spirit and scope of the appended claims). Furthermore, as an ordered combination, these elements amount to generic computer components performing repetitive calculations, receiving or transmitting data over a network, which, as held by the courts, are well-understood, routine, and conventional. See MPEP 2106.05(d); July 2015 Update, p. 7. Moreover, aside from the aforementioned additional elements, the remaining elements of dependent claims 2-19 do not transform the recited abstract idea into a patent eligible invention because these claims merely recite further limitations that provide no more than simply narrowing the recited abstract idea. Looking at these limitations as an ordered combination adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use a generic arrangement of generic computer components and recitations of generic computer structure that perform well-understood, routine, and conventional computer functions that are used to “apply” the recited abstract idea. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amounts to significantly more than the abstract idea itself. Since there are no limitations in these claims that transform the exception into a patent eligible application such that these claims amount to significantly more than the exception itself, claims 1-21 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-21 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhu et al (US 2010/0326669).
Zhu et al disclose the following claimed features:
Regarding claim 1, a method comprising: performing a first set of mathematical operations on a set of formation resistivity data to identify a set of formation values; evaluating a set of gamma ray (GR) formation log data collected to identify a set of formation GR values; performing a second set of mathematical operations on the formation resistivity data based on the set of formation GR values; and updating the set of formation values based on the performance of the second set of mathematical operations (Abstract; Figure 3; [paragraphs [0025], [0040]).
Regarding claim 2, wherein: the set of formation values include resistivity values that include one or more of a vertical resistivity value (Rv), a horizontal resistivity value (Rh), and a formation resistivity anisotropy value (Rvh), and the first set of mathematical operations includes a first computer modeling inversion calculation based on the set of resistivity data being collected by a multi-component induction (MCI) tool deployed in a wellbore (paragraphs [0014], [0018]).
Regarding claim 3, further comprising: aligning data points included in the set of formation resistivity data with data points included in the set of formation GR log data based on a span of wellbore locations where the set formation resistivity data and the set of formation GR log data was collected (paragraphs [0012], [0034], [0036]).
Regarding claim 4, further comprising: identifying a first speed associated with the set of formation resistivity data; identifying a second speed associated with the set of GR formation log data; and aligning data points included in the set of formation resistivity data with data points included in the set of formation GR log data based on the first speed and the second speed (paragraphs [0041], [0042], [0055]).
Regarding claim 5, further comprising: identifying one or more upper boundaries based on the set of formation GR values, wherein the one or more upper boundaries limit parameters of a computer inversion model that includes instructions of the second set of mathematical operations (paragraph [0032]).
Regarding claim 6, further comprising: generating a formation mapping that includes a shale section and a sand section, wherein the set of formation values are updated based on the formation mapping including the shale section and the sand section, wherein the mapping maps the set of formation GR values to one or more pseudo parameters (paragraphs [0046], [0068]).
Regarding claim 7, wherein the set of formation values include a vertical resistivity (Rv) value and an anisotropy ratio (Rv/Rh) value that corresponds to the Rv value divided by a horizontal resistivity (Rh) value (Figure 6; paragraph [0057]).
Regarding claim 8, wherein the first set of mathematical operations are implemented by instructions of an inversion model and execution of the instructions of the inversion model iteratively minimize a difference between the formation resistivity data and a synthetic response predicted by a forward model (paragraphs [0032], [0062]-[0064]).
Regarding claim 9, wherein the GR values include one or more pseudo parameters pertinent to formation anisotropy, and the one or more pseudo parameters include a pseudo vertical resistivity (Rv) value or a pseudo anisotropy ratio (Rv/Rh) value that corresponds to the Rv value divided by a pseudo horizontal resistivity (Rh) value (Figure 6; paragraph [0057]).
Regarding claim 10, wherein the pseudo Rv value or the pseudo Rv/Rh value are at least one of a soft constraint or regularization term (Figure 6; paragraph [0057]).
Regarding claim 11, wherein a strength of the regularization term is adjusted to increase a quality of an inversion as indicated by at least one indicator (paragraphs [0032], [0057], [0062]-[0064]).
Regarding claim 12, further comprising: estimating an initial pseudo vertical resistivity (Rv) value or an initial pseudo anisotropy ratio value that corresponds to the Rv value divided by a pseudo horizontal resistivity (Rh) value, wherein a second processing accesses an initial pseudo Rv value or the initial pseudo Rv/Rh value as part of the second mathematical operation (paragraphs [0032], [0057], [0062]-[0064]).
Regarding claim 13, wherein computing the pseudo Rv value or the pseudo Rv/Rh value includes identifying a shale section, a sand section, and constructing a mapping function to map GR log to a pseudo vertical resistivity (Rv) value or a pseudo anisotropy ratio (Rv/Rh) value that corresponds to the Rv value divided by a pseudo horizontal resistivity (Rh) value (paragraphs [0046], [0068]).
Regarding claim 14, wherein the set of formation GR log data is obtained from a wireline or logging while drilling (LWD) log during one or more sensing passes, and wherein a speed correction and a depth alignment are applied to align GR formation log data with the formation resistivity data based on the formation resistivity data being associated with a multi-component induction (MCI) tool (Figure 3; paragraphs [0025], [0034]).
Regarding claim 15, wherein a resolution matching algorithm is applied to match a vertical resolution of the set of GR formation log data and the set of formation resistivity data (Figure 3; paragraphs [0025], [0034]).
Regarding claim 16, further comprising: accessing a set of GR log data collected by a GR device; identifying that the GR log data collected by the GR device includes GR uranium data; removing the GR uranium data from the GR log data to generate the GR formation log data; and identifying a measure of shale in carbonates that are included in a wellbore formation based on the GR formation log data not including the GR uranium data (Figure 3; paragraphs [0025], [0034]).
Regarding claim 17, further comprising: estimating a volume of laminated shale versus dispersed shale included in a wellbore formation based on a combination of neutron log data and GR log data; and mapping the volume of laminated shale to a pseudo vertical resistivity (Rv) value or a pseudo anisotropy ratio (Rv/Rh) value that corresponds to the Rv value divided by a pseudo horizontal resistivity (Rh) value (paragraphs [0040], [0041], [0049], [0058]).
Regarding claim 18, further comprising: evaluating borehole imaging logs and GR logs to identify at least one zone with a laminated shale value that meets a threshold value; and generating a mapping function that maps the formation GR log data to a pseudo vertical resistivity (Rv) value or a pseudo anisotropy ratio (Rv/Rh) value that corresponds to the Rv value divided by a pseudo horizontal resistivity (Rh) value (paragraphs [0040], [0041], [0049], [0058]).
Regarding claim 19, further comprising: identifying a difference between a pseudo parameter and a second set of parameters pertinent to formation anisotropy; and identifying at least one of a measure of dispersed shale or a measure of carbonates included in a wellbore formation based on the identified difference limiting changes included in the updated set of formation values (paragraphs [0025], [0034], [0036]).
Regarding claim 20, a system (Figures 1-3) comprising: an electromagnetic (EM) sensing device that collects a set of formation resistivity data; a gamma ray (GR) sensing device that senses GR data, wherein at least a portion of the sensed GR data is included in a set of GR formation log data; a memory; one or more processors that execute instructions out of the memory to: perform a first set of mathematical operations on the set of formation resistivity data to identify a set of formation values; evaluate the set of gamma ray (GR) formation log data collected to identify a set of formation GR values; perform a second set of mathematical operations on the set of formation resistivity data based on the set of formation GR values; and update the set of formation values based on the performance of the second set of mathematical operations (Abstract; paragraphs [0025], [0040], [0079]).
Regarding claim 21, a non-transitory computer-readable storage medium (Figures 1-3) having embodied thereon instructions executable by one or more processors to perform a method comprising: performing a first set of mathematical operations on a set of formation resistivity data to identify a set of formation values; evaluating a set of gamma ray (GR) formation log data collected to identify a set of formation GR values; performing a second set of mathematical operations on the formation resistivity data based on the set of formation GR values; and updating the set of formation values based on the performance of the second set of mathematical operations (Abstract; paragraphs [0025], [0040], [0079]).
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Hou (US 11,230,922) discloses evaluation of formation and fracture characteristics based on multicomponent induction (MCI) and multipole sonic logging (MSL) data that includes automated calculation of inverted biaxial anisotropy (BA) parameters for the formation by performing an iterative BA inversion operation based on the MCI log data and using a BA formation model that accounts for transfers by axial formation anisotropy to resistivity. The inverted BA parameters and the processed MSL data can be used, in combination, to calculate a quantified value for an identification function, to indicate estimated presence or absence of a fracture in the formation. Wilson et al (US 11,016,209) disclose a system that includes a processor that generates a reservoir model of the earth formation based on additional data associated with the formation; converts the reservoir model to a resistivity model of the formation; generates simulated EM data based on the resistivity model of the formation; compares the EM data and the simulated EM data; generates an updated resistivity model based on the comparison between the EM data and the simulated EM data; and determines an operational parameter based on the updated resistivity model to manage production from a well. Zhang et al (US 2023/0375741) disclose a methods and a system for identifying formations that are clay-free or with minimal amount of clays, which have high hydrocarbon potential, by using both low frequency permittivity measurements (e.g., low-frequency permittivity measurements) and natural gamma ray flux measurements.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AN H DO whose telephone number is (571)272-2143. The examiner can normally be reached on M-F 7:00am-4:00pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ricardo Magallanes can be reached on 571-272-5960. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/AN H DO/Primary Examiner, Art Unit 2853
Prosecution Insights