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 .
IDS
The information disclosure statement (IDS) submitted on March 26, 2024 is being considered by the Examiner.
Drawing
The drawing filed on August 9, 2023 is accepted by the Examiner.
Specification
The specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim rejection – 35 U.S.C. §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.
In reference to claims 1-20: the claimed invention is directed to a judicial exception (i.e., abstract idea) without significantly more.
The requirement for subject matter eligibility test for products and processes requires first, the claimed invention must be to one of the four statutory categories. 35 U.S.C. § 101 defines the four categories of invention that Congress deemed to be the appropriate subject matter of a patent: processes, machines, manufactures and compositions of matter. The latter three categories define "things" or "products" while the first category defines "actions" (i.e., inventions that consist of a series of steps or acts to be performed).
Second, the claimed invention also must qualify as patent-eligible subject matter, i.e., the claim must not be directed to a judicial exception unless the claim as a whole includes additional limitations amounting to significantly more than the exception. The judicial exceptions (also called "judicially recognized exceptions" or simply "exceptions") are subject matter that the courts have found to be outside of, or exceptions to, the four statutory categories of invention, and are limited to abstract ideas, laws of nature and natural phenomena (including products of nature).
In the first step, it is to be determined whether the patent claim under examination is directed to an abstract idea. If so, in the second step of analysis, it is to be determined whether the patent adds to the idea "something more" or "significantly more" that embodies an "inventive concept."
In the instant case, claim 1 is representative and it is reproduced here with the limitations that are part of the abstract idea in bold:
A method for drilling a hydrocarbon well in a subterranean formation based on channel thicknesses, the method comprising:
receiving seismic data for the subterranean formation;
extracting values for seismic attributes from the seismic data;
executing a machine learning model trained using synthetic seismic attribute values that are associated with true values of channel thicknesses for synthetic channels, the machine learning model receiving the extracted values for the seismic attributes as input values;
generating, based on the executing, at least one predicted value of a channel thickness for a channel in the subterranean formation;
generating, based on the at least one predicted value of the channel thickness for the channel, a map of the subterranean formation including the channel.
Step 2A:
Prong I: The claim recites the steps of “receiving seismic data for the subterranean formation”, “extracting values for seismic attributes from the seismic data”; “generating, based on the executing, at least one predicted value of a channel thickness for a channel in the subterranean formation; generating, based on the at least one predicted value of the channel thickness for the channel, a map of the subterranean formation including the channel”. These limitations could be carried out as a purely mental process (at least in a some relatively simple situations) and/or they could amount to a mathematical calculation (for example using input values to a functional model). Therefore, the recited method falls in the abstract idea grouping of mental processes and/or mathematical concepts at Prong I of the §101 analysis.
Prong II:
This abstract idea is not integrated into a practical application at Prong 2 of the §101 analysis because the claim does not recite sufficient additional elements to integrate the abstract idea into a practical application. The claim recites the method comprising “executing machine learning model trained using synthetic seismic attribute values that are associated with true values of channel thickness for synthetic channels, the machine learning model receiving the extracted values for the seismic attributes as input values”; however, the machine learning model is used to model a mathematical functional block that provides a channel thickness and creates a map or a plot of those variable relationship, in a sense, the machine learning model is act as a generic tool or routine computer implementation. Further, executing a standard machine learning model with a new data is not patentable. The instant application does not make a technical improvement to the algorithm per se. it only merely applies a generic machine learning technique to a new attribute or data.
The courts have found that adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea (such as a step of obtaining information about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694
(Fed. Cir. 2011 )) is not enough to integrate the abstract idea into a particular practical application or make the claim qualify as "significantly more" (see MPEP § 2106.05(g)).
The claim does not recite applying the abstract idea with, or by use of, any particular machine, nor does the claim affect a real-world transformation or reduction of a particular article to a different state or thing. The claim amounts to manipulating data: receives seismic data, extract values from those seismic data, trains the generic machine learning model using the extracted values, using the machine learning model, generate one predicted value of the channel thickness, and using the channel thickness, map or plot the subterranean formation. The claim does not recite any particular real-world actions that are taken as a result of the notification that is output.
The claim establishes a "a map of a subterranean formation'' as the general field-of-use, but does not recite a particular practical application being carried out within that field-of-use. Therefore, the claimed invention does not appear to be limited to the use of the mental process or math in a particular practical application, but instead the claim appears to monopolize the mental process or math itself, in any practical application where it might conceivably be used.
Step 2B:
Finally, at Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the abstract idea for the same reasons as discussed above with regard to Prong 2. Claim 1 is rejected as ineligible under 35 USC §101.
Claims 8 and 15 are analogous to claim 1, except that claims 8 and 15 are directed to a system and one or more non-transitory computer-readable media respectively, and include “at least one processor” and “a memory”. These additional elements are separate from the abstract idea that need to be considered at Prong 2 of the §101 analysis. However, these additional elements are merely generic computer processing components that are invoked as a tool to perform the abstract idea, which do not cause the claims as a whole to integrate the abstract idea into a particular practical application or provide significantly more than the recited abstract idea. Therefore, claims 8 and 15 are therefore rejected as ineligible under 35 USC §101 as well.
Dependent claim 2: the instant claim is directed to about controlling a depth of a drilling process based on a predicted value of a channel thickness, but does not describe how the controlling of the drilling process is connected with the analysis or the map obtained, and it would not be significantly more than the abstract idea.
Dependent claim 3: the instant claim is directed to a convolution process of the synthetic seismic attributes and would be considered abstract idea of a computational nature.
Dependent claim 4: the instant claim is directed to a seismic reflector for seismic data and would be considered abstract idea of human thought and/or computational in form.
Dependent claim 5: the instant claim is directed to the characterization of seismic attributes and would be considered abstract idea of a human thought process and/or mathematical or computational analysis.
Dependent claim 6: the instant claim is directed to a generic machine learning model having a multiple regression model without specific modification as related to in drilling hydrocarbon well; and therefore, it would be considered a generic machine learning and would not be considered significantly more than the abstract idea.
Dependent claim 7: the instant claim is directed to validation of channel thickness by comparing the predicted channel thickness with the measured channel thickness which is a computational analysis process or method which reads on a human thought process.
Dependent claim 9: the instant claim is directed to about controlling a depth of a drilling process based on a predicted value of a channel thickness, but does not describe how the controlling of the drilling process is connected with the analysis or the map obtained, and it would not be significantly more than the abstract idea.
Dependent claim 10: the instant claim is directed to a convolution process of the synthetic seismic attributes and would be considered abstract idea of a computational nature.
Dependent claim 11: the instant claim is directed to a seismic reflector for seismic data and would be considered abstract idea of human thought and/or computational in form.
Dependent claim 12: the instant claim is directed to the characterization of seismic attributes and would be considered abstract idea of a human thought process and/or mathematical or computational analysis.
Dependent claim 13: the instant claim is directed to a generic machine learning model having a multiple regression model without specific modification as related to in drilling hydrocarbon well; and therefore, it would be considered a generic machine learning and would not be considered significantly more than the abstract idea.
Dependent claim 14: the instant claim is directed to validation of channel thickness by comparing the predicted channel thickness with the measured channel thickness which is a computational analysis process or method which reads on a human thought process.
Dependent claim 16: the instant claim is directed to about controlling a depth of a drilling process based on a predicted value of a channel thickness, but does not describe how the controlling of the drilling process is connected with the analysis or the map obtained, and it would not be significantly more than the abstract idea.
Dependent claim 17: the instant claim is directed to a convolution process of the synthetic seismic attributes and would be considered abstract idea of a computational nature.
Dependent claim 18: the instant claim is directed to a seismic reflector for seismic data and would be considered abstract idea of human thought and/or computational in form.
Dependent claim 19: the instant claim is directed to the characterization of seismic attributes and would be considered abstract idea of a human thought process and/or mathematical or computational analysis.
Dependent claim 20: the instant claim is directed to a generic machine learning model having a multiple regression model without specific modification as related to in drilling hydrocarbon well; and therefore, it would be considered a generic machine learning and would not be considered significantly more than the abstract idea.
Related Prior Art
In reference to claims 1-20: Denli et al. (U.S. Patent No. 11,520,077, hereon Denli) discloses a method for drilling a hydrocarbon well in a subterranean formation based on geological models (see Denli, column 6, lines 21-52), the method comprising: receiving seismic data or field seismic data for the subterranean formation (see Denali, column 7, lines 29-48); extracting values for seismic attributes from the seismic data; and Various types of geophysical and geological data are available to characterize the subsurface, including seismic data, well logs, petrophysical data, geo-mechanical data. In addition, various geological concepts, including environment of depositions (e.g., channel or turbidities complexes, etc.) are available. Further, various reservoir stratigraphic configurations, such as the number of channels, channel thicknesses, etc., may be inferred. The geophysical data, the geological concepts, and the reservoir stratigraphic configurations may be used to generate a reservoir model (or interpret one or more stratigraphic features), which in turn may be used to infer the values of their geological properties (e.g., V-shale, porosity, net-to-gross, etc.). (see Denali, column 1, lines 35-46). The method also performs machine learning in order to train machine learning model and generate, based on the machine learning model, one or more geological models for the respective stage of the life cycle (see Denali, Fig. 3).
The instant application differs in that it “executes a machine learning model trained using synthetic seismic attribute values that are associated with true values of channel thicknesses for synthetic channels, the machine learning model receiving the extracted values for the seismic attributes as input values; [generate], based on the executing, at least one predicted value of a channel thickness for a channel in the subterranean formation; generating, based on the at least one predicted value of the channel thickness for the channel, a map of the subterranean formation including the channel,” in combination with the rest of the claim limitations as claimed and defined by the Applicants.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Wang et al. (U.S. Patent No. 12,474,502) discloses systems and methods for generating synthetic borehole image logs include logging rate of penetration (ROP) data, resistivity data, and gamma ray data while drilling a borehole in a subsurface formation to generate logged data.
Utsuzawa et al. (U.S. Patent No. 11,091,997) discloses a system for drilling a borehole wherein the system includes drill string having a bottom hole assembly a nuclear magnetic resonance tool within the bottom hole assembly, and a surface control system including a nuclear magnetic resonance measurement quality map.
Donderici et al. (U.S. Patent No. 9,631,483) discloses apparatus and methods to process acoustic signals according to joint time-frequency processing. The joint time-frequency processing can combine features of both time-based processing and frequency-based processing. This processing is based on delay calculation from amplitude phases generated from the acoustic signals.
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/ELIAS DESTA/
Primary Examiner, Art Unit 2857