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 .
Status of Claims
Claims 1-20 are pending and are examined herein.
Claims 2-7, 10, 12-14 and 17-19 are rejected under 35 USC 112(b).
Claims 1-6, 8-18 and 20 are rejected under 35 USC 101 as being directed to an abstract idea without significantly more.
Claims 1-20 are rejected under 35 USC 103.
Information Disclosure Statement
The attached information disclosure statement(s) (IDS) is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the attached information disclosure statement(s) is/are being considered by the examiner.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2-7, 10, 12-14 and 17-19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 2 and 12 recite “estimating an uncertainty interval of the plurality of measurements and the mathematical dynamics model; and updating the uncertainty intervals for the mathematical dynamics model and the measurements, thereby producing an updated mathematical dynamics model.” The term “the uncertainty intervals” lacks proper antecedent basis. For the purposes of examination, the claim is being interpreted as requiring only a single uncertainty interval. The claims dependent on claims 2 and 12 do not resolve the issue and are rejected with the same rationale. In particular, claims 10 and 17 are also being interpreted as requiring only a single uncertainty interval.
Claim Rejections - 35 USC § 101 – Abstract Idea
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 1-6, 8-18 and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis
Each of the claims fall within one of the four statutory categories (i.e. process, machine, manufacture, or composition of matter).
Step 2 Analysis
Claim 1 includes the following recitation of an abstract idea:
modeling in real-time drilling mud flow dynamics in the drilling mud using a mathematical dynamics model; (This is a recitation of a mathematical concept.)
predicting physical states of the drilling mud with the mathematical dynamics model, thereby producing model physical state predictions; (This is a recitation of a mathematical concept.)
inputting the measurements into the mathematical dynamics model; and (This is a recitation of a mathematical concept.)
adapting the mathematical dynamics model based at least in part on discrepancies between the model physical state predictions and the measurements; and (This is a recitation of a mathematical concept.)
changing an operational parameter of the mud circulation system based on at least one value derived from the adapted mathematics dynamics model. (This is a recitation of a mathematical concept.)
Claim 1 recites the following additional elements which, considered individually and as an ordered combination, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
performing a plurality of measurements from a plurality of sensors coupled to the mud circulation system; (This is a recitation of performing mere data gathering, which is insignificant extra-solution activity. This does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. See MPEP 2106.05(g).)
Claim 1 does not reflect an improvement to computer technology or any other technology.
Claim 2 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
estimating an uncertainty interval of the plurality of measurements and the mathematical dynamics model; and (This is a recitation of a mathematical concept.)
updating the uncertainty intervals for the mathematical dynamics model and the measurements, thereby producing an updated mathematical dynamics model. (This is a recitation of a mathematical concept.)
Claim 2 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 2 does not reflect an improvement to computer technology or any other technology.
Claim 3 recites at least the abstract idea identified above in the claim upon which it depends, and further recites:
repeating foregoing steps:..., modeling, estimating, and inputting steps with the updated mathematical dynamics model. (This is a recitation of a mathematical concept.)
Claim 3 recites the following additional elements which, considered individually and as an ordered combination with the additional elements from the claim upon which it depends, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
performing (This is a recitation of performing mere data gathering, which is insignificant extra-solution activity. This does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. See MPEP 2106.05(g).)
Claim 3 does not reflect an improvement to computer technology or any other technology.
Claim 4 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
calculating a real-time downhole density of the drilling mud using the updated mathematical dynamics model. (This is a recitation of a mathematical concept.)
Claim 4 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 4 does not reflect an improvement to computer technology or any other technology.
Claim 5 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
calculating a real-time downhole viscosity of the drilling mud using the updated
mathematical dynamics model. (This is a recitation of a mathematical concept.)
Claim 5 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 5 does not reflect an improvement to computer technology or any other technology.
Claim 6 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
calculating a real-time downhole density, a real-time downhole viscosity, or both of the drilling mud using the updated mathematical dynamics model; and (This is a recitation of a mathematical concept.)
calculating an equivalent circulating density based on the real-time downhole density, the real-time downhole viscosity, or both. (This is a recitation of a mathematical concept.)
Claim 6 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 6 does not reflect an improvement to computer technology or any other technology.
Claim 8 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
wherein at least one of the model physical state predictions comprises a prediction of a density of the drilling mud or a prediction of a viscosity of the drilling mud. (This is a recitation of a mathematical concept.)
Claim 8 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 8 does not reflect an improvement to computer technology or any other technology.
Claim 9 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
wherein predicting the physical states of the drilling mud with the mathematical dynamics model, thereby producing the model physical state predictions comprises generating a fusion-determined drilling mud physical state value. (This is a recitation of a mathematical concept.)
Claim 9 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 9 does not reflect an improvement to computer technology or any other technology.
Claim 10 recites at least the abstract idea identified above in the claim upon which it depends, and further recites:
wherein updating the uncertainty intervals for the mathematical dynamics model and the measurements, thereby producing the updated mathematical dynamics model comprises utilizing a feedback loop to improve an accuracy of the mathematical dynamics model. (This is a recitation of a mathematical concept.)
Claim 10 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 10 does not reflect an improvement to computer technology or any other technology.
Claim 11 recites substantially similar subject matter to claim 1 including substantially the same abstract idea.
Claim 11 recites the following additional elements which, considered individually and as an ordered combination with the additional elements identified in claim 1, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea:
A non-transitory computer-readable medium encoded with instructions that, when executed, cause a system comprising a mud circulation system having drilling mud flowing therethrough to perform a method comprising: (This is a high level recitation of generic computer components for performing the abstract idea. This does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea. See MPEP 2106.05(f).)
Claim 11 does not reflect an improvement to computer technology or any other technology.
Claims 12-15 recite substantially similar subject matter to claims 2, 4-5 and 9, respectively and are rejected with the same rationale, mutatis mutandis.
Claim 16 recites at least the abstract idea identified above in the claim upon which it depends, and further recites
merging, through probability-based techniques, the plurality of measurements from the plurality of sensors to account for redundancies in the measurements. (This is a recitation of a mathematical concept.)
Claim 16 does not recite further additional elements which might integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 16 does not reflect an improvement to computer technology or any other technology.
Claims 17-18 and 20 recite substantially similar subject matter to claims 10, 6, and 8, respectively, and are rejected with the same rationale, mutatis mutandis.
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 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 8-9, 11, 15 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Kulkarni (US 2014/0202772 A1) in view of Rasmus (US 2013/0049983 A1).
Examiner Remark: Kulkarni is prior art under 35 USC 102(a)(1) by virtue of its publication date.
Regarding claim 1, Kulkarni teaches
A method of operating a system comprising a mud circulation system having drilling mud flowing therethrough, the method comprising: (Kulkarni, Abstract and [0076-0078])
performing a plurality of measurements from a plurality of sensors coupled to the mud circulation system; (Kulkarni, [0015-0016, 0302] describes obtaining a plurality of measurement. In particular, [0302] indicates that the system may include a plurality of sensors. See also Figure 3, first step.)
modeling in real-time drilling mud flow dynamics in the drilling mud using a mathematical dynamics model; predicting physical states of the drilling mud with the mathematical dynamics model, thereby producing model physical state predictions; (Kulkarni, [0017-0018, 0027-0039] describes using a mathematical model to determine a mud weight. See also Figure 3, second and third steps)
inputting the measurements into the mathematical dynamics model; and (Kulkarni, [0017-0018, 0027-0039] describes using a mathematical model to determine a mud weight. This is based on the measurements as described at [0188]. Note that this step could be a second iteration through the loop of Figure 3 if this step and the previous steps were interpreted as being required to be distinct.)
...changing an operational parameter of the mud circulation system based on at least one value derived from the adapted mathematics dynamics model. (Kulkarni, Figure 3, bottom right step. See also [0020, 0041, 0120].)
Kulkarni does not appear to explicitly teach
adapting the mathematical dynamics model based at least in part on discrepancies between the model physical state predictions and the measurements; and
However, Rasmus—directed to analogous art--teaches
adapting the mathematical dynamics model based at least in part on discrepancies between the model physical state predictions and the measurements; and (Rasmus, Abstract, [0097, 0117] describe adjusting a mathematical model based on the difference between predicted values and measured values.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni by Rasmus because the techniques taught by Rasmus allow for improved accuracy as described by Rasmus at [0007].
Regarding claim 8, the rejection of claim 1 is incorporated herein. Furthermore, Kulkarni teaches
wherein at least one of the model physical state predictions comprises a prediction of a density of the drilling mud or a prediction of a viscosity of the drilling mud. (Kulkarni, [0017-0018, 0027-0039] describes using a mathematical model to determine a mud weight. See also Figure 3, second and third steps.)
Regarding claim 9, the rejection of claim 1 is incorporated herein. Furthermore, Kulkarni teaches
wherein predicting the physical states of the drilling mud with the mathematical dynamics model, thereby producing the model physical state predictions comprises generating a fusion-determined drilling mud physical state value. (Kulkarni, [0017-0018, 0027-0039] describes using a mathematical model to determine a mud weight. See also Figure 3, second and third steps. Figure 3, [0027-0039] indicate that the predication is computed by combining multiple measurements which is being interpreted as falling within the broadest reasonable interpretation of “fusion determined”.)
Regarding claim 11, this claim recites substantially similar subject matter to claim 1 and is rejected with the same rationale in view of Kulkarni further teaching
A non-transitory computer-readable medium encoded with instructions that, when executed, cause a system comprising a mud circulation system having drilling mud flowing therethrough to perform a method comprising: (Kulkarni, [0277])
Regarding claim 15, the rejection of claim 11 is incorporated herein. Claim 15 recites substantially similar subject matter to claim 9 and is rejected with the same rationale.
Regarding claim 20, the rejection of claim 11 is incorporated herein. Claim 20 recites substantially similar subject matter to claim 8 and is rejected with the same rationale.
Claims 2-7, 10, 12-14, and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Kulkarni (US 2014/0202772 A1) in view of Rasmus (US 2013/0049983 A1), further in view of “Stroud” (Sequential State and Variance Estimation within the Ensemble Kalman Filter).
Regarding claim 2, the rejection of claim 1 is incorporated herein. The combination of Kulkarni and Rasmus does not appear to explicitly teach
estimating an uncertainty interval of the plurality of measurements and the mathematical dynamics model; and updating the uncertainty intervals for the mathematical dynamics model and the measurements, thereby producing an updated mathematical dynamics model.
However, Stroud—directed to analogous art--teaches
estimating an uncertainty interval of the plurality of measurements and the mathematical dynamics model; and updating the uncertainty intervals for the mathematical dynamics model and the measurements, thereby producing an updated mathematical dynamics model. (Stroud, Abstract describes using Kalman filter methods to estimate parameters of models of dynamical systems. The model is presented in section 3 and includes an iterative update described by equations (6)-(11). Pages 3200, right hand column through page 3201 left hand column, and Figures 3 and 4 indicate that at each time period a credible interval (i.e., an uncertainty interval) is calculated using the posterior distribution computed using the posterior distribution (see page 3197, section 3).)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni and Rasmus by Stroud because the choice of Kalman filter method is robust with system nonlinearities, sparse observation networks, and the choice of initial parameter distribution as described by Stroud in the Abstract.
Regarding claim 3, the rejection of claim 2 is incorporated herein. Furthermore, Kulkarni teaches
repeating foregoing steps: performing, modeling,..., and inputting steps with the updated mathematical dynamics model. (Kulkarni, Figure 3 shows these operations (as mapped above with respect to claim 1) being performed in a loop.)
Kulkarni does not appear to explicitly teach
repeating...estimating
However, Stroud—directed to analogous art--teaches
repeating...estimating (Stroud, Abstract describes using Kalman filter methods to estimate parameters of models of dynamical systems. The model is presented in section 3 and includes an iterative update described by equations (6)-(11). Pages 3200, right hand column through page 3201 left hand column, and Figures 3 and 4 indicate that at each time period a credible interval (i.e., an uncertainty interval) is calculated using the posterior distribution computed using the posterior distribution (see page 3197, section 3).)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have combined these references in this way for the same reasons given above with respect to claim 2 and because both methods include running the models in an iterative fashion.
Regarding claim 4, the rejection of claim 2 is incorporated herein. Furthermore, Kulkarni teaches
calculating a real-time downhole density of the drilling mud (Kulkarni, [0017-0018, 0027-0039] describes using a mathematical model to determine a mud weight. See also Figure 3, second and third steps)
Kulkarni does not appear to explicitly teach
using the updated mathematical dynamics model.
However, Stroud—directed to analogous art--teaches
using the updated mathematical dynamics model. (Stroud, Abstract describes using Kalman filter methods to estimate parameters of models of dynamical systems. The model is presented in section 3 and includes an iterative update described by equations (6)-(11). Pages 3200, right hand column through page 3201 left hand column, and Figures 3 and 4 indicate that at each time period a credible interval (i.e., an uncertainty interval) is calculated using the posterior distribution computed using the posterior distribution (see page 3197, section 3).)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have combined these references in this way for the same reasons given above with respect to claim 2.
Regarding claim 5, the rejection of claim 2 is incorporated herein. Furthermore, Kulkarni teaches
calculating a real-time downhole viscosity of the drilling mud (Kulkarni, [0183-0184] indicates that the viscosity may be one of the computed values.)
Kulkarni does not appear to explicitly teach
using the updated mathematical dynamics model.
However, Stroud—directed to analogous art--teaches
using the updated mathematical dynamics model. (Stroud, Abstract describes using Kalman filter methods to estimate parameters of models of dynamical systems. The model is presented in section 3 and includes an iterative update described by equations (6)-(11). Pages 3200, right hand column through page 3201 left hand column, and Figures 3 and 4 indicate that at each time period a credible interval (i.e., an uncertainty interval) is calculated using the posterior distribution computed using the posterior distribution (see page 3197, section 3).)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have combined these references in this way for the same reasons given above with respect to claim 2.
Regarding claim 6, the rejection of claim 2 is incorporated herein. Furthermore, Kulkarni teaches
calculating a real-time downhole density, a real-time downhole viscosity, or both of the drilling mud (Kulkarni, [0017-0018, 0027-0039] describes using a mathematical model to determine a mud weight. See also Figure 3, second and third steps. [0183-0184] indicates that the viscosity may be one of the computed values.)
...calculating an equivalent circulating density based on the real-time downhole density, the real-time downhole viscosity, or both. (Kulkarni, [0019, 0088, 0250] teaches estimating the equivalent circulation density based on the estimated mud weight.)
Kulkarni does not appear to explicitly teach
using the updated mathematical dynamics model; and
However, Stroud—directed to analogous art—teaches
using the updated mathematical dynamics model; and (Stroud, Abstract describes using Kalman filter methods to estimate parameters of models of dynamical systems. The model is presented in section 3 and includes an iterative update described by equations (6)-(11). Pages 3200, right hand column through page 3201 left hand column, and Figures 3 and 4 indicate that at each time period a credible interval (i.e., an uncertainty interval) is calculated using the posterior distribution computed using the posterior distribution (see page 3197, section 3).)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have combined these references in this way for the same reasons given above with respect to claim 2.
Regarding claim 7, the rejection of claim 6 is incorporated herein. Furthermore, Kulkarni teaches
changing a composition of the drilling mud of the mud circulation system based on the equivalent circulating density. (Kulkarni, Figure 3, bottom right step, [0020, 0041])
Regarding claim 10, the rejection of claim 2 is incorporated herein. Kulkarni and Rasmus does not appear to explicitly teach
wherein updating the uncertainty intervals for the mathematical dynamics model and the measurements, thereby producing the updated mathematical dynamics model comprises utilizing a feedback loop to improve an accuracy of the mathematical dynamics model.
However, Stroud—directed to analogous art--teaches
wherein updating the uncertainty intervals for the mathematical dynamics model and the measurements, thereby producing the updated mathematical dynamics model comprises utilizing a feedback loop to improve an accuracy of the mathematical dynamics model. (Stroud, Abstract describes using Kalman filter methods to estimate parameters of models of dynamical systems. The model is presented in section 3 and includes an iterative update described by equations (6)-(11). Pages 3200, right hand column through page 3201 left hand column, and Figures 3 and 4 indicate that at each time period a credible interval (i.e., an uncertainty interval) is calculated using the posterior distribution computed using the posterior distribution (see page 3197, section 3). The equations (6)-(10) are applied in a feedback loop based on new observations/measurements Y_t at each time step.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni and Rasmus by Stroud because the choice of Kalman filter method is robust with system nonlinearities, sparse observation networks, and the choice of initial parameter distribution as described by Stroud in the Abstract.
Regarding claims 12-14 and 17-19, the rejection of claim 11 is incorporated herein. Claims 12-14 and 17-19 recite substantially similar subject matter to claims 2, 4-5, 10, and 6-7, respectively, and are rejected with the same rationale.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Kulkarni (US 2014/0202772 A1) in view of Rasmus (US 2013/0049983 A1), and further in view of Hackett (Multi-Sensor Fusion: A Perspective).
Regarding claim 16, the rejection of claim 15 is incorporated herein. Kulkarni and Rasmus does not appear to explicitly teach
merging, through probability-based techniques, the plurality of measurements from the plurality of sensors to account for redundancies in the measurements.
However, Hackett—directed to analogous art--teaches
merging, through probability-based techniques, the plurality of measurements from the plurality of sensors to account for redundancies in the measurements. (Hackett, Abstract describes a field of techniques called sensor fusion for combining different measurements. Section 3.1, starting on page 1325 and continuing onto page 1326, describes Bayesian (i.e., probability based) approaches for performing this.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni and Rasmus by Hackett because “Bayesian statistics is very useful in combining multiple sensor values since sensor uncertainty can easily be incorporated” (Hackett, section 3.1., first sentence.)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Liu (US 2017/0138137 A1) – Liu, Abstract describes a technique for managing the drilling of a well by monitoring downhole conditions.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Markus A Vasquez whose telephone number is (303)297-4432. The examiner can normally be reached Monday to Friday 9AM to 4PM PT.
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, Li Zhen can be reached on (571) 272-3768. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MARKUS A. VASQUEZ/ Primary Examiner, Art Unit 2121
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