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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 .
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 04/05/2024. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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. The claimed invention is directed to the abstract concept of performing abstract steps without significantly more. The claim(s) recite(s) the following abstract concepts in BOLD of
1. (Original) A method for identifying at least one mud motor stall event during a borehole drilling operation that is carried out using a drilling assembly comprising a downhole mud motor, the method comprising:
receiving, via a computing system, drilling sensor data that comprise a pressure measurement signal for a borehole drilling operation;
calculating, via the computing system, a smoothed pressure signal using the received pressure measurement signal;
calculating, via the computing system, a pressure fluctuation signal using the received pressure measurement signal and the calculated smoothed pressure signal;
determining, via the computing system, a pressure fluctuation distribution dataset using a subset of data for the calculated pressure fluctuation signal;
calculating, via the computing system, a set of statistical values from the determined pressure fluctuation distribution dataset, wherein the calculated set of statistical values comprises a pressure fluctuation value for a first selected percentile value and probability distribution parameters that characterize a selected theoretical probability distribution function;
calculating, via the computing system, a theoretical pressure fluctuation value for a second selected percentile value using the calculated probability distribution parameters for the selected theoretical probability distribution function;
identifying, via the computing system, at least one mud motor stall event when a pressure measurement value from the calculated pressure fluctuation signal is greater than the calculated pressure fluctuation value for the first selected percentile value and is greater than the calculated theoretical pressure fluctuation value for the second selected percentile value multiplied by a prescribed numerical value; and
utilizing the at least one identified mud motor stall event to manage the borehole drilling operation.
9. (Original) A method for identifying at least one mud motor stall event during a borehole drilling operation that is carried out using a drilling assembly comprising a downhole mud motor, the method comprising:
receiving, via a computing system, drilling sensor data that comprise a pressure measurement signal for a borehole drilling operation;
calculating, via the computing system, a smoothed pressure signal using the received pressure measurement signal;
calculating, via the computing system, a pressure fluctuation signal using the received pressure measurement signal and the calculated smoothed pressure signal;
determining, via the computing system, a pressure fluctuation distribution dataset using a subset of data for the calculated pressure fluctuation signal;
calculating, via the computing system, a set of statistical values from the determined pressure fluctuation distribution dataset, wherein the calculated set of statistical values comprises pressure fluctuation values for first selected percentile values and probability distribution parameters that characterize a selected theoretical probability distribution function;
calculating, via the computing system, theoretical pressure fluctuation values using second selected percentile values and the calculated probability distribution parameters for the selected theoretical probability distribution function;
identifying, via the computing system, at least one mud motor stall event when a pressure measurement value from the calculated pressure fluctuation signal is greater than a pressure cutoff value, where the pressure cutoff value is determined using the first selected percentile values, the second selected percentile values, the pressure fluctuation values, and the theoretical pressure fluctuation values; and
utilizing the at least one identified mud motor stall event to manage the borehole drilling operation.
16. (Original) A method for managing a borehole drilling operation that is carried out using a drilling assembly comprising a downhole mud motor, the method comprising:
receiving, via a computing system, drilling sensor data that comprise a pressure measurement signal for a borehole drilling operation;
calculating, via the computing system, a smoothed pressure signal using the received pressure measurement signal;
calculating, via the computing system, a pressure fluctuation signal using the received pressure measurement signal and the calculated smoothed pressure signal;
determining, via the computing system, a pressure fluctuation distribution dataset using a subset of the data for the calculated pressure fluctuation signal;
calculating, via the computing system, a pressure fluctuation value for a selected percentile value using the determined pressure fluctuation distribution dataset;
normalizing, via the computing system, the pressure fluctuation value using a selected weighting parameter value;
repeating the calculation and the normalization of the pressure fluctuation value a plurality of times for a plurality of selected percentile values to obtain a time-based or depth-based signal of normalized pressure fluctuation values; and
utilizing the normalized time-based or depth-based signal of normalized pressure fluctuation values to manage the borehole drilling operation.
Under step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. The above claims are considered to be in a statutory category.
Under Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitation the fall into/recite abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, it falls into the grouping of subject matter that, when recited as such in a claim limitation, covers performing mathematics or mental steps.
Next, under Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application. In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
This judicial exception is not integrated into a practical application because there is no improvement to another technology or technical field; improvements to the functioning of the computer itself; a particular machine; effecting a transformation or reduction of a particular article to a different state or thing. Examiner notes that since the claimed methods and system are not tied to a particular machine or apparatus, they do not represent an improvement to another technology or technical field. Similarly there are no other meaningful limitations linking the use to a particular technological environment. Finally, there is nothing in the claims that indicates an improvement to the functioning of the computer itself or transform a particular article to a new state.
Finally, under Step 2B, we consider whether the additional elements are sufficient to amount to significantly more than the abstract idea. Claims 1, 9, and 16 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because receiving drilling sensor data is considered necessary data gathering. As recited in MPEP section 2106.05(g), necessary data gathering (i.e. receiving data) is considered extra solution activity in light of Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). The additional limitation of Claims 1, 9, and 16 of a computing system is interpreted under broadest reasonable interpretation to be a generic computer. Generic computer elements are not considered significantly more than the abstract idea and do not integrate the abstract idea into a practical application. As recited in the MPEP, 2106.05(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94. The additional limitation of Claims 1 and 9 of utilizing the at least one identified mud motor stall event to manage the borehole drilling operation and the additional limitation of Claim 16 of utilizing the normalized time/depth based signal of normalized fluctuation values to manage the borehole drilling operation is considered to be mere instructions to apply an exception because the claim limitation amounts to the equivalent words of “apply it” as the claim limitations are only reciting the idea of a solution or outcome (i.e. managing the drilling operation) without any details to how the management of the drilling operation occurs. As recited in the MPEP, 2106.05(f), the recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015). Furthermore it is well known and understood in the art to manage drilling operations in response to a mud motor stall, as evidenced by Ng (US20210270097)in [0085] and Edbury (US20140291023) in Figure 2.
Claims 2-8, 10-15, and 17-20 further limit the abstract ideas without integrating the abstract concept into a practical application or including additional limitations that can be considered significantly more than the abstract idea.
Examiner’s Note
Claims 1-20 are not rejected under a prior art rejection (35 U.S.C. 102 or 35 U.S.C. 103).
In regards to Claims 1, 9, and 16, Ng (US20210270097) teaches the limitations “receiving, via a computing system, drilling sensor data that comprise a pressure measurement signal for a borehole drilling operation (System for the drilling of a wellbore with a plurality of sensors, including pressure sensor 202d – [0073], Figure 2; sensor readings sent to the computer 210 – [0076], Figure 2);
calculating, via the computing system, a smoothed pressure signal using the received pressure measurement signal (“Filtering and smoothing techniques may therefore be used to reduce the noise” – [0103]);
identifying, via the computing system, at least one mud motor stall event (“At block 435, stall detector 320 compares the signature of the potential mud motor stall to stored signatures of mud motor stalls. The stored signatures may be signatures of historic (i.e. real) or virtual mud motor stalls. The stored signatures may be generated based on drilling parameter data associated with the mud motor stalls. The comparison may be performed using any one of various suitable techniques. For example, according to some embodiments, dynamic time warping (DTVV) or symbolic aggregate approximation (SAX) may be used to determine a distance between the signature of the potential mud motor stall and the stored signatures. At block 440, stall detector 320 determines, based on the comparison, whether the distance is greater than a threshold distance” – [0092]); and
utilizing the at least one identified mud motor stall event to manage the borehole drilling operation (computer 210 takes sensor readings and outputs ROP and WOB setpoints to the automated drilling unit – [0085], Figure 2).”
Hopwood (US20250059876) teaches the limitations “utilizing the at least one identified mud motor stall event to manage the borehole drilling operation (detecting stall condition on mud motor during drilling based on the differential pressure of the drilling mud, and performing operations 1104-1116 in response – Figure 11)”
Edbury (US20140291023) teaches the limitations “receiving, via a computing system, drilling sensor data that comprise a pressure measurement signal for a borehole drilling operation (“ FIG. 8 illustrates assessing a relationship of weight on bit that includes a determination of weight on bit induced side load torque using measurements of surface torque and differential pressure. At 214 , pressure is measured to determine a differential pressure across a mud motor while drilling. The measurement may be, for example, as described above relative to FIG. 3. At 216 , a motor output torque is determined based on the differential pressure. In some embodiments, the torque at bit and motor output torque are assumed to be the same. The determination of torque at bit may be, for example, as described above relative to FIG. 3” – [0112]); utilizing the at least one identified mud motor stall event to manage the borehole drilling operation (Figure 2 details control system for controlling the drilling with the sensor data as input and analysis thereof)”
Shen (US20240003241) teaches the limitations “receiving, via a computing system, drilling sensor data that comprise a pressure measurement signal for a borehole drilling operation (architecture for real time mud motor health monitoring with data preparation and processing for pressure – Figure 50); calculating, via the computing system, a smoothed pressure signal using the received pressure measurement signal (differential pressure with differential pressure statistics including mean, standard deviation, percentiles – Figure 17)”
Jeffryes (US20180135402) teaches the limitations “receiving, via a computing system, drilling sensor data that comprise a pressure measurement signal for a borehole drilling operation (“The differential pressures across the downhole tool 130 may be measured using one or more pressure sensors 132, 134 coupled to the downhole tool 130 (see FIG. 1). For example, one pressure sensor 132 may be positioned above the mud motor 160, and another pressure sensor 134 may be positioned below the mud motor 160. In another implementation, the differential pressures across the downhole tool 130 may be measured at the standpipe 118” – [0034]; methods are executed by a computing system – [0045]); calculating, via the computing system, a pressure fluctuation signal using the received pressure measurement signal and the calculated smoothed pressure signal (“Thus, the pressure variation [i.e. pressure fluctuation] seen above the mud motor 160 (e.g., at the standpipe 118) due to the pressure variation across the mud motor 160 may be viewed as a low-pass filtered version [i.e. calculated smoothed pressure signal] of the actual pressure variation across the mud motor 160. There may also be additional attenuation mechanisms between the mud motor 160 and the surface that may cause the pressure variation seen at surface (e.g., at the standpipe 118) to be reduced even further” – [0026]); utilizing the at least one identified mud motor stall event to manage the borehole drilling operation (“ In some implementations, computing system 600 contains one or more pre/post stall action module(s) 608. In the example of computing system 600, computer system 601A includes the pre/post stall action module 608. In some implementations, a single pre/post stall action module may be used to perform some or all aspects of one or more implementations of the methods 400 or 500. In alternative implementations, a plurality of pre/post stall action modules may be used to perform some or all aspects of methods 400 or 500” – [0048]; Figure 4 details method 400 and Figure 5 details method 500)”
In regards to Claims 1 and 9, Ng, Shen, Hopwood, Jeffryes, and Edbury are silent with regards to the language of “determining, via the computing system, a pressure fluctuation distribution dataset using a subset of data for the calculated pressure fluctuation signal;
calculating, via the computing system, a set of statistical values from the determined pressure fluctuation distribution dataset, wherein the calculated set of statistical values comprises a pressure fluctuation value for a first selected percentile value and probability distribution parameters that characterize a selected theoretical probability distribution function;
calculating, via the computing system, a theoretical pressure fluctuation value for a second selected percentile value using the calculated probability distribution parameters for the selected theoretical probability distribution function;
identifying, via the computing system, at least one mud motor stall event when a pressure measurement value from the calculated pressure fluctuation signal is greater than the calculated pressure fluctuation value for the first selected percentile value and is greater than the calculated theoretical pressure fluctuation value for the second selected percentile value multiplied by a prescribed numerical value.”
In regards to Claim 16, Ng, Shen, Hopwood, Jeffryes, and Edbury are silent with regards to the language of “determining, via the computing system, a pressure fluctuation distribution dataset using a subset of the data for the calculated pressure fluctuation signal;
calculating, via the computing system, a pressure fluctuation value for a selected percentile value using the determined pressure fluctuation distribution dataset;
normalizing, via the computing system, the pressure fluctuation value using a selected weighting parameter value;
repeating the calculation and the normalization of the pressure fluctuation value a plurality of times for a plurality of selected percentile values to obtain a time-based or depth-based signal of normalized pressure fluctuation values; and
utilizing the normalized time-based or depth-based signal of normalized pressure fluctuation values to manage the borehole drilling operation.”
Conclusion
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/YOSSEF KORANG-BEHESHTI/Primary Examiner, Art Unit 2857
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