DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 12 June 2026 have been fully considered but they are not persuasive.
The 112(a) rejections, 112(b) rejections, and drawing objections are withdrawn due to amendments.
Applicant argues steps (a) and (b) require physical sensor hardware integrated into the drilling equipment. Examiner respectfully disagrees. The steps merely require importing specific data from first/second databases. The type of data is the data that is collected by the physical sensors. Nothing in the claims requires the step of collecting the data or the actual positive structure of the sensors.
Applicant argues providing the information to an operator to support decision require physical drilling operations and cannot be abstract. Examiner agrees that providing the information is an additional element. However, the providing is an extra solution activity that is well-known, routine, and conventional as discussed below. The claim does not require any of the equipment related to the drilling decision. Instead, the claim merely recites that information is provided to an operator to support a decision (i.e., transmitting/displaying data).
Applicant argues the claims are patent eligible because they tie the abstract idea to a particular machine. Applicant argues the particular machines are the sensors and the drilling system. Examiner respectfully disagrees. The sensors are never positively recited. The sensors are merely disclosed in relation tot the type of data. The drilling system as it related to the step of “providing” information to the operator does not require any additional structures beyond the drill string which is merely a field of use limitation (see MPEP 2106.05(b)) as discussed below.
Applicant argues that the claimed technology should overcome the 101 because it provides an unconventional improvement with clear advancements of over the prior technologies and the specifications clearly lay out the practical applications and benefits the claimed technology. Examiner respectfully disagrees. The claimed invention does not integrate the abstract ideas into a practical application for the reasons discussed below. The claims limitations related to the additional elements (i.e., training machine learning, importing data, providing data) are not specific enough to integrate the abstract idea into a practical application.
Applicant argues that the claims involve more than performance of well-understood, routine, and conventional activities previously known in the industry because of the sensors, the training methodology, and the providing of information to the operator. Examiner respectfully disagrees. All of the limitations are well-understood, routine, and conventional as discussed below.
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 1-5, 7-15, and 17-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 of the Subject Matter Eligibility Test entails 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.
Claims 1-5, 7-15, and 17-21 are directed to a method (process), a system (machine or manufacture), and a non-transitory medium (manufacture), respectively. As such, the claims are directed to statutory categories of invention.
If the claim recites a statutory category of invention, the claim requires further analysis in Step 2A. Step 2A of the Subject Matter Eligibility Test is a two-prong inquiry. In Prong One, examiners evaluate whether the claim recites a judicial exception.
Claim 1 recites abstract limitations, including:
“(c) removing records within the second data of drilling parameters with ROP, WOB, RPM and torque values of less than or equal to zero by applying filters to drilling parameters in real time;
(d) converting second data in time to depth by calculating statistical attributes of said drilling parameters in time contained in specific intervals and having constant depth spacing;
(e) combining said drilling parameters converted to depth in step (d) with the LWD profile data imported in step (a) using depth as a reference;
(g) performing inferences to predict each said LWD profile with each LWD profile’s respective model using training features in an interval corresponding to a current depth of a drill up to the respective offset limits; and
(h) periodically checking whether there has been progress in drilling, if so repeating step (g), performing new inferences with respect to the new data.”
Claim 7 recites abstract limitations, including:
“(c) removing records within the second data of drilling parameters with ROP, WOB, RPM and torque values of less than or equal to zero;
(d) converting second data in time to depth by calculating statistical attributes of said drilling parameters in time contained in specific intervals and having constant depth spacing;
(e) combining said drilling parameters converted to depth in step (d) with the LWD profile data imported in step (a) using depth as a reference; and
(g) performing inferences to predict each said LWD profile using machine learning models.
These limitations, as drafted, are a process that, under its broadest reasonable interpretation, cover performance of the limitations in the mind, or by a human using pen and paper, and therefore recite mental processes. More specifically, other than reciting “a computer implemented method” nothing in the claim element precludes the aforementioned steps from practically being performed in the human mind, or by a human using pen and paper. The mere recitation of a generic computer does not take the claim out of the mental process grouping. Thus, the claim recites an abstract idea.
If the claim recites a judicial exception in step 2A Prong One, the claim requires further analysis in step 2A Prong Two. In step 2A Prong Two, examiners evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
Claim 1 recites the additional elements of:
(a) importing, by a drilling system comprising a drill string, first data of LWD profiles in depth from LWD sensors arranged at depth profile offsets on the drill string that acquire the first data in depth from an available first database;
(b) importing, by the drilling system, second data of drilling parameters from the surface sensors coupled to the drilling system that acquire the second data in real time from an available second database, the second data comprises drilling parameters with rate of penetration (ROP), weighted drill (WOB), and revolutions per minute (RPM);
(f) training, by the drilling system, machine learning models, based on supervised regressions, for each said LWD profile with the first database above each respective depth offset;
(h) periodically checking, by the drilling system, whether there has been progress in drilling, if so, repeating step (f) by training the models with any new data; and
(i) sending, by the drilling system, the results of each new prediction to a third database;
(j) continuously updating the machine learning models in real-time as new drilling data is received to maintain predictive accuracy despite changing geological conditions;
(k) displaying, by the drilling system, the predicted LWD profiles in a real-time visualization interface that displays the predicted LWD profiles in the offset interval from the drill tip to the limit of the depth profile offsets, enabling comparison between predicted and actual values to validate drilling decisions; and
(l) providing, by the drilling system, the predicted LWD profiles to an operator to support the drilling decisions comprising at least one of: geostopping for lithostratigraphic characterization, initiating a coring operation, or changing a drill bit base on predicted geological conditions in the offset interval.
Claim 7 recites the additional elements of:
(a) importing first data of LWD profiled in depth from an available first database;
(b) importing second data of drilling parameters in time from an available second database;
(f) training machine learning models for each LWD profile;
(h) periodically retraining the machine learning model as drilling progresses;
(i) providing the predicted LWD profiles to an operator to support drilling decisions comprising at least one of: geostopping for lithostratigraphic characterization, initiating a coring operation, or changing a drill bit.
The training of the machine learning models (originally in step (f) and in the repeat step (h)) and continuously updating the machine learning model (i.e., retraining in step (j)) are recited at a high level of generality, and, as applied, are a tool used in their ordinary capacity to perform the abstract idea, and therefore amount to “apply it.”
“Importing first data of LWD profiles in depth from an available first database,” “importing second data of drilling parameters in time from an available second database, the second data comprises drilling parameters with rate of penetration (ROP), weighted drill (WOB), and revolutions per minute (RPM),” “sending the results of each new prediction to a third database,” and “displaying the predicted LWD profiles in a real-time visualization interface that displays the predicted LWD profiles in the offset interval from the drill tip to the limit of the depth profile offsets, enabling comparison between predicted and actual values to validate drilling decisions” amount to insignificant extra-solution activity (i.e., activity incidental to the primary process or product that is merely a nominal or tangential addition to the claim, see MPEP 2106.05(g)).
“[A] drilling system comprising a drill string” merely links the method to a particular technical environment or field of use.
Examiner notes that the type of data being imported (i.e., from LWD sensors arranged at depth profiles offsets on the drill string that acquire the first data in depth and/or surface sensors coupled to ta drilling system) merely narrow the previously recited abstract idea. The limitation recited is for “importing” data. The fact that the data was collected by specific sensors is not relevant since the claim does not include the limitation of using the sensors to collect the data and then transmit the data to the first/second databases.
The additional element of a visualization interface is recited at a high level of generality, and, as applied, are a tool used in their ordinary capacity to perform the abstract idea, and therefore amount to “apply it.”
Examiner further notes that step (h) is conditional and not required since it would only be performed if there has been progress in drilling. However, for the purpose of compact prosecution the step will be fully analyzed under 101.
“[P]roviding, by the drilling system, the predicted LWD profiles to an operator to support the drilling decisions comprising at least one of: geostopping for lithostratigraphic characterization, initiating a coring operation, or changing a drill bit base on predicted geological conditions in the offset interval” amount to insignificant extra-solution activity (i.e., activity incidental to the primary process or product that is merely a nominal or tangential addition to the claim, see MPEP 2106.05(g)).
Accordingly, in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
If the additional elements do not integrate the exception into a practical application in step 2A Prong Two, then the claim is directed to the recited judicial exception, and requires further analysis under Step 2B to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself).
As discussed above, the additional elements amount to mere instructions to apply the exception (using additional elements of the machine learning model and the visualization interface). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Examiner notes that while step (f) requires the training of the machine learning model to be “based on supervised regression” the claim language does not define the relationship. “Based on” is an extremely broad and generic term and does not actually require supervised regression when training the model and does not define any relationship between the training of the machine learning model and the supervised regression.
Regarding the recited processes in steps (a), (b), and (i) (i.e., importing from a database and sending to a database), “importing” and “sending” are considered insignificant extra-solution activities as the limitations amount to selecting a particular data source or type of data to be manipulated and transmitting/receiving the data. As noted in Electric Power Group, selecting information, based on types of information and availability of information for collection, analysis, and display is considered insignificant extra-solution activity (see MPEP 2106.05(g)). Additionally, the Symantec, TLI, OIP Techs. and buySAFE court decisions cited in MPEP 2106.05(d)(II) indicate that mere receiving or transmitting data over a network is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here).
The “drill string” merely link the method to a particular technical environment or field of use. As it merely confines the use of the abstract idea to a particular technical field of use it fails add an inventive concept to the claim. This limitation represents a mere token acquiescence to limiting reach of the claim (see Flook and MPEP 2106.05(h)).
Regarding the recited process step in (k) (i.e., displaying data), instructions to display data on a display are considered insignificant extra-solution activities as the limits amount to selecting a particular type of data and displaying it. As noted in Electric Power Group, selecting information, based on types of information and availability of information for collection, analysis, and display is considered insignificant extra-solution activity (see MPEP 2106.05(g)). Additionally, the Symantec, TLI, OIP Techs. and buySAFE court decisions cited in MPEP 2106.05(d)(II) indicate that mere receiving or transmitting data over a network and then displaying the data after it is analyzed is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here).
Regarding the recited process step of “providing” the predicted LWD profiles, “transmitting” and “displaying” (i.e. providing) is considered insignificant extra-solution activities as the limitations amount to selecting a particular data source or type of data to be manipulated and transmitting/receiving the data. As noted in Electric Power Group, selecting information, based on types of information and availability of information for collection, analysis, and display is considered insignificant extra-solution activity (see MPEP 2106.05(g)). Additionally, the Symantec, TLI, OIP Techs. and buySAFE court decisions cited in MPEP 2106.05(d)(II) indicate that mere receiving or transmitting data over a network is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here).
Thus, even when viewed as an ordered combination, nothing in the claims add significantly more (i.e., an inventive concept) to the abstract idea.
Claims 2-3 recite “the target LWD profiles comprise layers (labels) in step (f)” and “in step (g) characteristics of statistical attributes of drilling parameters comprise torque, weight on drill (WOB), rate of penetration (ROP), revolutions per minute (RPM), MSE (mechanical specific energy), pumping pressure (SPP), drilled phase, drill type, drill run, or combination thereof” which merely narrow the previously recited abstract idea limitations.
Claim 4 recites the additional elements of a non-transitory computer-readable storage medium and a computer which are recited at a high level of generality, and, as applied, are a tool used in their ordinary capacity to perform the abstract idea, and therefore amount to “apply it” and mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Claim 5 recites “training of the models is supervised by Nuclear Magnetic Resonance (NMR) porosity profiles via regression, supervised by descriptions available in Exata via classification, or both” which is an abstract idea. These limitations, as drafted, are a process that, under its broadest reasonable interpretation, represent mathematical relationships, mathematical formulas or equations, and/or mathematical calculations and are therefore mathematical concepts. The mere recitation of a generic computer does not take the claim out of the mathematical concepts grouping. Thus, the claim recites an abstract idea.
Claims 7-9 recite “the constant depth spacing is approximately 0.1524 meters;” “the periodically checking in step (h) occurs approximately every minute;” and “the depth profile offsets range from approximately 3 meters to several dozen meters from the drill tip” which merely narrows the previously recited abstract idea limitations.
Claim 10 recites “the LWD profiles predicted include neutron (NEU) profiles” which is an abstract idea. These limitations, as drafted, are a process that, under its broadest reasonable interpretation, represent mathematical relationships, mathematical formulas or equations, and/or mathematical calculations and are therefore mathematical concepts. The mere recitation of a generic computer does not take the claim out of the mathematical concepts grouping. Thus, the claim recites an abstract idea.
Claims 11-14 recite “the method is applied to different LWD profiles in drilled phases of pre-salt reservoirs and salt phases” “the filters applied in step (c) include a drilling mode filter to preserve only data from drilling moments;” “the first database further comprises profiles acquired via wireline, gas chromatography, and categorical information including drill types, drilling fluid, and lithology;” and “the drilling parameters further include Mechanical Specific Energy (MSE) calculated from the drilling parameters” which merely narrows the previously recited abstract idea limitations.
Claims 15 and 17--18 recite “the machine learning models are based on a Gradient Boosting structure and utilize Light Gradient Boosting Methods (GBM) algorithms;” “the machine learning algorithm is retrained at each depth advance in a defined interval using Real Time Training (RTT);” and “the statistical attributes calculated in step (d) comprise mean, median, and standard deviation of the drilling parameters in time contained in the specific intervals” which are abstract ideas. These limitations, as drafted, are a process that, under its broadest reasonable interpretation, represent mathematical relationships, mathematical formulas or equations, and/or mathematical calculations and are therefore mathematical concepts. The mere recitation of a generic computer does not take the claim out of the mathematical concepts grouping. Thus, the claim recites an abstract idea.
Claim 19 recites the additional elements of a processor and a memory coupled to the processor. The additional elements of the processor and memory are recited at a high level of generality, and , as applied, are tools used in their ordinary capacity to perform the abstract idea, and therefore, amount to “apply it.”
Claim 20 recites “the Real Time Training (RTT) technique improves accuracy of results as the well advances and the model becomes more robust by using information acquired in the well being drilled as the most valuable data during training raining, and wherein when retraining the machine learning models after system interruptions or model adjustments, a drilling simulation routine is executed to prevent data leakage by ensuring that models are not trained with data from depths more recent than depths to which the models are applied.” which merely narrows the previously recited abstract idea limitations.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KRISTYN A HALL whose telephone number is (571)272-8384. The examiner can normally be reached M-F 9:00-5:00.
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/KRISTYN A HALL/Primary Examiner, Art Unit 3672
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