DETAILED ACTION
Claim(s) 1,2,4,6,7,8 and 9,10,12,14,15,16 is/are rejected under 35 U.S.C. 103 as being unpatentable over CHOWHAN (CA 3088082 A1 WO 2019/087213 A1) in view of Brannigan et al. (US 2019/0003297 A1):
Claim(s) 3,5 and 11,13 is/are rejected under 35 U.S.C. 103 as being unpatentable over CHOWHAN (CA 3088082 A1 WO 2019/087213 A1) in view of Brannigan et al. (US 2019/0003297 A1) as applied in claims 1,2,4,6,7,8 and 9,10,12,14,15,16 further in view of Bertagnolli et al. (US 6,189,634 B1):
Response to Arguments
Objection to the Specification
Applicant’s arguments, see remarks, page 6, filed 8/12/2026, with respect to the specification objection have been fully considered and are persuasive. The objection of the specification has been withdrawn.
Claim Objection
Applicant’s arguments, see remarks, page 6, filed 8/12/2026, with respect to the objection of claim 5 have been fully considered and are persuasive. The objection of claim 5 has been withdrawn.
§IOI Rejection of the Claims
Applicant’s arguments, see remarks, pages 7-12, filed 8/12/2026, with respect to 35 USC 101 have been fully considered and are persuasive. The 35 USC 101 rejection of claims 1-16 has been withdrawn.
§102 Rejection of the Claims
Applicants state in page 14, 1st para:
Thus, Chowhan fails to provide an "output representing whether1 an image includes a visual representation of a cutter" via an object recognition model, as recited in independent claim 9 ( and similarly in independent claim I). Moreover, even if Chowhan did provide such an output, Chowan fails to provide an output that is "based on a cutter probability value", as claimed. This activity is fully supported by the Application, as-filed, at paragraphs [0025], [0026], and [0047], among others.
The examiner respectfully disagrees since CHOWHAN teaches “an image processed view of the front facing or23 top view” via [0094]:
[0094] FIG. 8 and FIG. 9 illustrates an image processed view of the front facing or top view of a worn/degraded drill tool where important parameters including centroid of the image, original image enclosing circle (scaled and overlaid), current worn cutter enclosing circle, centroid and differential wear reduction in outermost drill tool cutting edge are depicted. FIG. 8 presents the top or cutting face view, i.e. captured and processed image of a used/Worn/degraded drill bit. The image is processed matched and compared with the top face view of the original new image and its bounding circle. The earlier computed bounding circle of the new drill bit is match scaled and overlaid on the newly captured image of the worn drill tool.
Applicants state in page 14, 1st para:
Thus, Chowhan fails to provide an "output representing whether4 an image includes a visual representation of a cutter" via an object recognition model, as recited in independent claim 9 ( and similarly in independent claim I). Moreover, even if Chowhan did provide such an output, Chowan fails to provide an output that is "based on a cutter probability value", as claimed. This activity is fully supported by the Application, as-filed, at paragraphs [0025], [0026], and [0047], among others.
The examiner respectfully disagrees since CHOWHAN teaches a cutting probability value from a “regression5 neural network” via [0091] and fig. 4:410: “Machine Intelligence Based Engineering Analysis” with two output arrows from 410 to 404/414:
PNG
media_image1.png
375
962
media_image1.png
Greyscale
[0091] According to FIG. 6, 602 discloses the multiple cameras acquiring images of the drill tool and further send to 604, which is a neural network enhanced image processing module for object classification and image segmentation to identify the various objects and conditions of the drill tool. 606 discloses an overall block diagram presenting the coupling of neural network based algorithms for deformed drill tool analysis along with engineering analysis to provide predictive, prescriptive guidance, force models, bit simulation model, analysis results and field calibration. 608 and 610 discloses a regression neural network model to train and predict the cutter force interaction model for degraded drill tool and its cutting elements (as sensed).
Applicants state on page 14, 2nd para:
The Applicant respectfully submits that the Office has not made a proper prima facie case of anticipation because Chowhan does not teach each and every element of the independent claims, either expressly or inherently. In this particular instance, Chowhan fails to teach the existence of an" ... output representing an image that includes a visual representation of a cutter based on a cutter probability value ... " ( or similar language) as recited in the claims and described in the Application. Instead, Chowhan provides a" ... system [that] can visualize the drill tool on the field or in a test setup using its high-resolution cameras guided around the drill tool in a controlled, sensed, measured and pre-programmed trajectory ... ". See Chowhan, pg. 14. There is no explanation of how Chowhan operates to separate images that contain cutters from those that do not. Certainly, the operation of Chowhan is not inherently identical to that which is claimed, and Bertagnolli does nothing to remedy this deficiency. The Applicant therefore submits that every claim is novel over the cited references. Reconsideration and withdrawal of the rejection under 3 5 USC § I 02 is thus respectfully requested.
The examiner respectfully disagrees since CHOWHAN teaches a cutting probability value from a “regression neural network” via [0091] and fig. 3 : ~Previous Analysis Model~ with two output arrows from said Analysis Model (i.e., the regression neural network):
PNG
media_image2.png
363
962
media_image2.png
Greyscale
PNG
media_image3.png
1248
967
media_image3.png
Greyscale
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., remarks, page 14, 2nd para, 4th S: “ separate images that contain cutters from those that do not” ) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
§103 Rejection of the Claims
Applicant’s arguments, see remarks, page 15, 2nd para, filed 8/12/2026, with respect to rejected claim(s) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of 35 USC 103:
Claim(s) 1,2,4,6,7,8 and 9,10,12,14,15,16 is/are rejected under 35 U.S.C. 103 as being unpatentable over CHOWHAN (CA 3088082 A1 WO 2019/087213 A1) in view of Brannigan et al. (US 2019/0003297 A1):
wherein Brannigan teaches the claimed “context specific” (i.e., “information” from real-time “RT drill services”) via [0144]:
--[0144] As an example, RT drill services can include functionality to transmit and present information to individuals. In particular, the RT drill services can include functionality to transmit information to individuals involved according to roles and, for example, device types of each individual (e.g., mobile, desktop, etc.). In one or more embodiments, information presented by RT drill services can be context specific, and may include6 a dynamic display of information so that a human user may view details about items of interest--: as shown by the items in fig. 1:150:
PNG
media_image4.png
687
995
media_image4.png
Greyscale
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1,2,4,6,7,8 and 9,10,12,14,15,16 is/are rejected under 35 U.S.C. 103 as being unpatentable over CHOWHAN (CA 3088082 A1 WO 2019/087213 A1) in view of Brannigan et al. (US 2019/0003297 A1):
PNG
media_image5.png
578
544
media_image5.png
Greyscale
Re 1. (Currently Amended), CHOWHAN teaches A computer implemented method, the computer implemented method (likewise) comprising7:
acquiring a training set of images, wherein the training set of images comprise a set of images of cutters8 (or likewise “The artificial intelligence neural network that has been trained earlier on the various conditions and states of the drill tool is loaded and initialized”, pg. 9, ll. 30,31, i.e., “a software 3D training application can be used to classify mask and image segment in 3D, polygon bounding points and areas of interest for the drill tool marking out degradation, faults and wear and tear; and capable of generating mask and bounding box from 3D projection to 2D images; at various programmed or random orientation to train the artificial intelligence system for various drill bit faults.”. pg. 25, claim 29); and
training a <cutting9> machine learning system using the training set of images (or likewise “The artificial intelligence neural network that has been trained earlier on the various conditions and states of the drill tool is loaded and initialized.” [0057] 4th S & CHOWHAN’s claim 16: “training…augmented drill tool images”),
{{{1011
wherein the <cutting> machine learning system is transformed (or likewise “trained”12 [0057] 5th S) into a trained machine learning system that provides an output (or output arrow of fig. 5B:518) representing that includes a visual representation of a cutter (or likewise CHOWHAN teaches generating a visualization-output-geometric representation depending on a neural network-based machine-vision via “the artificial intelligence and neural network-based machine vision as applied to the electronic system for better …generating a geometric model13”, pg. 14, 5-14: fig. 4: “Geometric Model”/fig. 5B:514: “geometric model”) based14 on15 a cutter {{{probability}}} value16 (or likewise “evaluation…of drilling tool” [0050] 1st S: fig. 5B:516: “computation”) indicating a probability (via “a regression17 neural network model to train and predict the cutter force interaction model for degraded drill tool and its cutting elements (as sensed)” [0091] last S: fig. 4: 410: “Machine Intelligence Based Engineering Analysis”/fig. 5B:518 “Force”) of a cutter in the image (or likewise “images of the drill tool” [0091]: fig. 6:602/fig. 5A:502: “camera”),
to improve drilling operations18 (or likewise “improvement and addition to the drill tool” [0052] last S: fig. 2:220: “Enhanced New Drill Tool”) by providing context-specific information (“i.e. captured and processed image” [0094] 2nd S) for
drill bit1920 examination (or likewise fig. 8: “[0097] 812 represents an enclosing circle for the outermost cutting edge for the worn drill bit and is useful to compare with the original drill bit circle to examine wear and reduction in cutting radius and in the case of broken/chipped/ delaminated shoulder cutters”) {{{,
rotation, or
replacement2122}}}.
CHOWHAN does not teach the difference of claim 1 of:
context-specific (information)23.
Brannigan teach the difference of claim 1 of:
context-specific (information)24 (or likewise “information presented by RT drill services can be context specific…actionable information” via [0144]:
[0144] As an example, RT drill services can include functionality to transmit and present information to individuals. In particular, the RT drill services can include functionality to transmit information to individuals involved according to roles and, for example, device types of each individual (e.g., mobile, desktop, etc.). In one or more embodiments, information presented by RT drill services can be context specific, and may include a dynamic display of information so that a human user may view details about items of interest.
[0149] The OPTIDRILL™ technology can help to manage downhole conditions and BHA dynamics as a real-time drilling intelligence service. The service can incorporate a rigsite display (e.g., a wellsite display) of integrated downhole and surface data that provides actionable information to mitigate risk and increase efficiency. Such data can be simultaneously interpreted by remote experts, who may collaborate with a drilling team to improve performance. As an example, such data may be stored, for example, to a database system (e.g., consider a database system associated with the STUDIO™ framework).
Since CHOWHAN suggests in the background art using “real-time” as “assistance”25:
[0011] Further it can be of great use if the system can provide a guidance to the operator by inspecting the current state of the drill tool, look up the real-time history of the drilling operation so far, and provide the driller guidance on measuring the performance of drilling; analysis to verify if the current drill tool was right for the application; check the current state and health of the drill bit and a critical evaluation if a change in drill bit/tool is required. It will be also of great use if the system can provide analysis on the future performance of the drill bit/tool, guidance from history on the optimal drill bit for the session drilled so far; and evaluation/analysis for reason if the drill bit/tool has failed; and many more. Information collected about the drill bit in conjunction with various real-time logs and data acquired is also of great assistance to the drill bit manufacturer as feedback to evaluate and improve on his design ahead.
one of skill in the art could or would have done is look to other real-time art teachings making CHOWHAN’s be as Brannigan’s seeing in the change further reason/motivation (i.e., managing in real-time a drilling tool for fatigue is the reason/cause) to specifically combine CHOWHAN with Brannigan via Brannigan [0155]:
[0155] As an example, a framework can be implemented as a service that provides real-time tracking of steering and fatigue management in a time-depth log that can include rendering of graphical representation of a bottom hole assembly (BHA) of a tool string for drilling. As an example, such a framework can include a rig-state-detection engine that allows for analysis of drilling performance and continuous assessment of one or more factors. For example, consider assessment via one or more models such as a torque and drag model. As an example, a framework may organize and store data according to a format such as a comma separated values (CSV) format or one or more other formats.
via explicit, creative, routine, inferential Supreme Court Steps, A,B,C:
A) Create an Enhanced New Drill Tool Program based on CHOWHAN’s fig. 2:
A1) at step 214 create code calling/returning from an Input Logs Program:
PNG
media_image6.png
1135
1037
media_image6.png
Greyscale
B) Create the Input Logs Program based on Brannigan’s fig. 5 that shows double- headed arrows representing Log inputs/outputs:
PNG
media_image7.png
1321
864
media_image7.png
Greyscale
PNG
media_image8.png
588
338
media_image8.png
Greyscale
C) install CHOWHAN’s cutter fig. 12:1204 as Brannigan’s fig. 3:351 with associated logging equipment:336: “Logging and Control”; 352: Logging-While-Drilling (LWD):
PNG
media_image9.png
1423
754
media_image9.png
Greyscale
D) Drill creating log data (LWD) using the installation of Brannigan’s fig. 3;
E) Run Enhanced New Drill Tool Program calling the Input Logs Program receiving the log LWD data;
F) see what happens (I foresee a plurality of motives/causes/sparks (motivation) to combine references via said steps A-E:
[0011] Further it can be of great use if the system can provide a guidance to the operator by inspecting the current state of the drill tool, look up the real-time history of the drilling operation so far, and provide the driller guidance on measuring the performance of drilling; analysis to verify if the current drill tool was right for the application; check the current state and health of the drill bit and a critical evaluation if a change in drill bit/tool is required. It will be also of great use if the system can provide analysis on the future performance of the drill bit/tool, guidance from history on the optimal drill bit for the session drilled so far; and evaluation/analysis for reason if the drill bit/tool has failed; and many more. Information collected about the drill bit in conjunction with various real-time logs and data acquired is also of great assistance to the drill bit manufacturer as feedback to evaluate and improve on his design ahead.
[0155] As an example, a framework can be implemented as a service that provides real-time tracking of steering and fatigue management in a time-depth log that can include rendering of graphical representation of a bottom hole assembly (BHA) of a tool string for drilling. As an example, such a framework can include a rig-state-detection engine that allows for analysis of drilling performance and continuous assessment of one or more factors. For example, consider assessment via one or more models such as a torque and drag model. As an example, a framework may organize and store data according to a format such as a comma separated values (CSV) format or one or more other formats.).
Re 2. (Currently Amended), CHOWHAN of the combination of CHOWHAN-Brannigan teaches The method of claim 1, further comprising training the machine learning system based on a set of cutter positions (or likewise said “a software 3D training application can be used to classify mask and image segment in 3D, polygon bounding points and areas of interest for the drill tool marking out degradation, faults and wear and tear; and capable of generating mask and bounding box from 3D projection to 2D images; at various programmed or random orientation26 to train the artificial intelligence system for various drill bit faults.”, pg. 25, claim 29), wherein the trained machine learning system provides a predicted cutter position based on an image of the cutter (or likewise a neural network producing increasingly predictive-perception drill tool images in various orientations via “the … artificial intelligence-imaging neural network27 … generating… drill tool images from a 3D loaded CAD28 model29 … in various orientation”, pg. 23, claim 16).
Re 4. (Original), CHOWHAN of the combination of CHOWHAN-Brannigan teaches The method of claim 1, further comprising training the machine learning system using a set of training classifications (or likewise “classify mask and image segment in 3D, polygon bounding points and areas of interest for the drill tool marking out degradation, faults and wear and tear…to train the artificial intelligence system”, pg. 25, claim 29), wherein each of the set of training classifications correspond with one of a set of cutter characteristics (or likewise order a 3D image segment corresponding to/with a group by reason of common characteristics to train a neural network via “classify30 mask and image segment in 3D, polygon bounding points and areas of interest for the drill tool marking out degradation, faults and wear and tear…to train the artificial intelligence system”, pg. 25, claim 29).
Re 6. (Original), CHOWHAN of the combination of CHOWHAN-Brannigan teaches The method of claim 4, wherein training the machine learning system comprises training the machine learning system based on a primary characteristic 3132 (or likewise order a 3D image segment, comma33-listed first relative to the last comma-listed item “tear”, pg. 25, claim 29, corresponding to/with a group by reason of common characteristics, listed first relative to the feature of the last comma-listed item “tear”, to train a neural network via “classify34 mask and image segment in 3D, polygon bounding points and areas of interest for the drill tool marking out degradation, faults and wear and tear…to train the artificial intelligence system”, pg. 25, claim 29).
Re 7. (Currently Amended), CHOWHAN of the combination of CHOWHAN-Brannigan teaches The method of claim 1, further comprising revising a drilling operation based on the output from the trained machine learning system (or likewise “improve…drill tool run feedback35… of drill tool runs ( down hole and at surface) (Drilling Depth/UCS/CCS/WOB/TOB/RPM/ROPNibrations and others) with the current computed health/fault status and engineering analysis of the drill tool; computing, which part of cutting elements have worn or have been deformed at a higher rate than normal”, pg. 11, ll. 1-5).
Re 8. (Original), CHOWHAN of the combination of CHOWHAN-Brannigan teaches The method of claim 7, wherein the drilling operation is one of rotating a drill bit cutter (or likewise “rotation of the drill tool”, pg. 18,ll. 10-15) 3637.
Claim 9 rejected/interpreted like claim 1:
Re 9. (Currently Amended), CHOWHAN of the combination of CHOWHAN-Brannigan teaches An apparatus comprising:
a processor (or likewise “a smart phone38 camera”, pg. 8,ll.10-15 or “ a
customized electronic device, a smartphone device or a mobile device”, pg. 19, ll. 10-15); and
a non-transitory, computer-readable medium (or likewise “memory that enables the computer to store programs and data”) having instructions (or likewise “software”39, pg. 6,ll.20-25) stored thereon that are executable by the processor, the instructions including:
instructions to acquire a training set of images, wherein the training set of images comprise a set of images of cutters; and
instructions to train a machine learning system using the training set of images, wherein the machine learning system includes an object recognition model that comprises a set of weights corresponding to one or more nodes of a neural network of the machine learning system, and wherein the machine learning system transformed into a trained machine learning system that provides an output representing whether (i.e., if or “can”40, CHOWHAN, page 24, claim 17) an image includes a visual representation of a cutter based on a cutter probability value indicating a probability of a cutter in the image, to improve drilling operations by providing context-specific information for drill bit examination, rotation, or replacement.
Claim 10 is rejected like clam 2:
Re 10. (Currently Amended), CHOWHAN of the combination of CHOWHAN-Brannigan teaches The apparatus of claim 9, wherein the instructions to train the machine learning system are based on a set of cutter positions, wherein the trained machine learning system provides a predicted cutter position based on an image of the cutter.
Claim 12 is rejected like claim 4:
Re 12. (Original), CHOWHAN of the combination of CHOWHAN-Brannigan teaches The apparatus of claim 9, wherein the instructions to train the machine learning system include using a set of training classifications, wherein each of the set of training classifications correspond with one of a set of cutter characteristics.
Claim 14 is rejected like claim 6:
Re 14. (Original), CHOWHAN of the combination of CHOWHAN-Brannigan teaches The apparatus of claim 12, wherein one of the set of training classifications corresponds with a primary characteristic
Claim 15 is rejected like claim 7:
Re 15. (Original), CHOWHAN of the combination of CHOWHAN-Brannigan teaches The apparatus of claim 9, further comprising instructions to revise a drilling operation based on the output from the machine learning system.
Claim 16 is rejected like claim 8:
Re 16. (Original), CHOWHAN of the combination of CHOWHAN-Brannigan teaches The apparatus of claim 15, wherein the drilling operation is one of rotating a drill bit cutter and replacing a drill bit cutter.
Claim(s) 3,5 and 11,13 is/are rejected under 35 U.S.C. 103 as being unpatentable over CHOWHAN (CA 3088082 A1 WO 2019/087213 A1) in view of Brannigan et al. (US 2019/0003297 A1) as applied in claims 1,2,4,6,7,8 and 9,10,12,14,15,16 further in view of Bertagnolli et al. (US 6,189,634 B1):
PNG
media_image10.png
578
715
media_image10.png
Greyscale
Re 3. (Original), CHOWHAN teaches The method of claim 1, further comprising training the machine learning system to determine a comparison value (or likewise “a neural network enhanced image processing module for…an image processed…and compared…image”,pg. 14,ll. 16 & pg. 15,ll.8-14) based on the training set of images, wherein at least one of the training set of images includes a visual representation of a portion of a cutter surface not covered (or non-occluded as shown in fig. 7 for at least a picture of the surface of the cutter) by41 polycrystalline diamond (“Total Segmental-Radial volumetric diamond table”- “Parameter”, pg. 10,ll. 21-23: fig. 7’s cutting elements implies that there is a diamond given the diamond table parameter) compact.
CHOWHAN does not teach the difference of claim 3:
(not covered) 42 by43 polycrystalline (diamond)44 compact.
Bertagnolli teach the difference of claim 3:
(not covered) 45 by46 polycrystalline (diamond)47 compact (or likewise “without a top polycrystalline diamond layer covering” a hole 503,624,625,626,627,628,629 via figs. 5,6a,6b,6c,6d,6e,6f:
PNG
media_image11.png
1405
989
media_image11.png
Greyscale
Since CHOWHAN suggests other types of cutting elements (i.e., PDC) and problems thereof, page 8, ll. 5-10:
--FIG 17 depicts the interaction plot of the various48 cutting elements and its wear profile processed by the electronic system used to further compute various engineering parameters.--:
PNG
media_image12.png
873
1023
media_image12.png
Greyscale
one of skill in the art of cutting elements could have or would have done is refer to others for a solution to the problem and thus make CHOWHAN’s be as Bertagnolli’s seeing in the change:
“improved wear and durability characteristics because it avoids failures due to stresses, delaminations and fractures caused by the differences in thermal expansion coefficient between the diamond and the substrate during sintering. Moreover, this invention may provide multiple polycrystalline diamond edges as the PDC wears. This exposure of multiple polycrystalline diamond edges slows the rate of wear flat surface development and reduces the weight on the bit required for acceptable drill penetration rates.”, Bertagnolli, abstract.
via explicit creative or even routine steps:
a) use a crowbar to pry out or a screw-driver or wrench to remove a worn-out cylinder as shown in CHOWHAN’s fig. 17 creating an empty spot:
PNG
media_image12.png
873
1023
media_image12.png
Greyscale
b) install Bertagnolli’s cylinder of fig. 5 in the same empty spot:
b1) use welding to fuse Bertagnolli’s cylinder of fig. 5 to the spot; or
b2) use screw-driver/tool inside the hole 503 to fasten via fasteners (e.g., screws) Bertagnolli’s cylinder of fig. 5 to the spot:
b2.1) if need be bust through 501 to fasten to the drill-bit:
PNG
media_image13.png
533
1000
media_image13.png
Greyscale
; and
c) starting mining (see what happens).
Claim 5 is rejected like claim 3:
Re 5. (Currently Amended) CHOWHAN of the combination of CHOWHAN, Bertagnolli teaches/already made obvious The method of claim 4, wherein the set of cutter characteristics comprises an indication that the cutter is worn (“worn”, pg. 2, ll.10-15: fig. 8 shows a worn cutter verses a new cutter circle-template) and is associated with one or more images of a cutter showing at least one portion of a cutter surface that is not covered (as in fig. 8, non-occluded cutter, for at least a picture of the surface) by [[a PDC]] polycrystalline diamond compact material (or likewise “PDC Drill Bit”, CHOWHAN: pg. 4,ll.5-10).
Claim 11 is rejected like claim 3:
Re 11. (Currently Amended), CHOWHAN of the combination of CHOWHAN, Bertagnolli teaches/already made obvious The apparatus of claim 9, wherein the instructions to train the machine learning system further include instructions to determine a comparison value based on the training set of images, wherein at least one of the training set of images includes a visual representation of a portion of a cutter surface not covered by polycrystalline diamond compact material.
Claim 13 is rejected like claim 5:
Re 13., CHOWHAN of the combination of CHOWHAN, Bertagnolli teaches/already made obvious The apparatus of claim 12, wherein the one of a set of cutter characteristics set of cutter characteristics comprises an indication that the cutter is worn and is associated with one or more images of a cutter showing at least one portion of a cutter surface that is not covered by [[a PDC]] polycrystalline diamond compact material.
Conclusion
The prior art “nearest to the subject matter defined in the claims” (MPEP 707.05) made of record and not relied upon is considered pertinent to applicant's disclosure.
The following table lists several references that are relevant to the subject matter claimed and disclosed in this Application. The references are not relied on by the Examiner, but are provided to assist the Applicant in responding to this Office action:
Citation
Relevance
Lehnherr et al. (US 2013/0083031 A1)
Lehnherr teaches “specific data context” in fig. 8:
PNG
media_image14.png
855
1165
media_image14.png
Greyscale
[0109] Advanced user computer(s) 704 can be configured to access the features associated with data source manager interface 706, layout manager interface 708, and visualization module interface 710 to generate customized viewers for storage in configured viewer library server 712. The viewers may be composed by the user(s) of advanced user computer(s) for a specific data context. For example, the context associated with the data and/or the composed viewer(s) can be any of, or a combination of, segment specific activity (e.g., wireline, drilling, well services, testing, etc.), workflow or service specific activity (e.g., resistivity logging, pressure/temperature monitoring, measurement and/or logging while drilling, stimulation, etc.), tools specific activity (e.g., down-hole tools, surface sensors, etc.), and/or client specific customizations. In some embodiments, the data context may be related to the segment(s), workflow, and/or tools specific activities discussed above with regard to the oilfield and drilling operations depicted in FIGS. 1-5. Advanced user computer(s) 704 may also be employed to generate viewers including contextual data from customer specific activities.
as the closest to the claimed “content-specific information” of claim 1.
Potash (US 2019/0145183 A1): previously cited in the previous Office action (6/30/2026) regarding teaching a neural network with training images
Potash also teaches a “confidence49 score…for each wear characteristic…on the…training images”:
[0028] In some embodiments, determining drill bit wear at step 410 includes steps 412, 414, and 416. At step 412, the machine learning modules included in the computer vision module identify wear characteristics in each drill bit image. At step 414, the computer vision module eliminates false positives from the wear characteristics identified in step 412. In one embodiment, the machine learning modules output a confidence score between zero and one associated with each identified wear characteristic and the computer vision module filters the identified wear characteristics based on the associated confidence score and a threshold confidence score. Different threshold confidence scores may be used for each wear characteristic, based on the number of training images for the wear characteristic, the uniqueness of the wear characteristic, and the like. For example, nozzles are a unique feature and a large number of training images are available so the nozzle characteristic is associated with a threshold confidence score of 0.95. In contrast, broken cutters and worn cutters look similar and the machine learning modules struggle to distinguish the two characteristics, so the broken cutters and worn cutters characteristics are associated with a threshold confidence score of 0.7 and 0.8, respectively. In some embodiments, the computer vision module presents the identified wear characteristics to a user to eliminate false positives. At step 416, the computer vision module eliminates overlapping features. Where the machine learning modules identify wear characteristics independently, the same portion of a drill bit image may be identified as multiple characteristics. In some embodiments, the computer vision module eliminates overlapping features by ranking the identified characteristics by confidence score, calculating the overlap ratio between the identified characteristics, and eliminating the identified characteristic associated with a lower confidence score when the overlap ratio exceeds a threshold value.
as the closest to the claimed “cutter probability value indicating a probability of a cutter” of claim 1.
THIS ACTION IS MADE FINAL. 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 DENNIS ROSARIO whose telephone number is (571)272-7397. The examiner can normally be reached Monday-Friday, 9AM-5PM EST.
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, Henok Shiferaw can be reached at 571-272-4637. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DENNIS ROSARIO/Examiner, Art Unit 2676
/Henok Shiferaw/Supervisory Patent Examiner, Art Unit 2676
1 whether: (coordinating) another word for either (Dictionary.com)
2 or: used to join alternatives: either of such choices
3 “whether” and “or” is an identity meaning the same thing: “either”
4 whether: (coordinating) another word for either (Dictionary.com)
5 regression: The relationship between the mean value of a random variable and the corresponding values of one or more independent variables, wherein random variable is defined: rv. statistics a quantity that may take any of a range of values, either continuous or discrete, which cannot be predicted with certainty but only described probabilistically . (Dictionary.com)
6 Include: to contain, as a whole does parts or any part or element, wherein contain is defined: to be equal to (“a dynamic display of information so that a human user may view details about items of interest”). (Dictionary.com)
7 BROAD CLAIM LANGUAGE: “-ing” (of “comprising”): a suffix of nouns formed from verbs, expressing the action of the verb or its result, product, material, etc. (the art of building; a new building; cotton wadding ), wherein etc. is defined: and others; and so forth; and so on (used to indicate that more of the same sort or class might have been mentioned, but for brevity have been omitted)., wherein so is defined: likewise or correspondingly; also; too.
8 cutter: a machine, tool, or other device for cutting. (Dictionary.com): <cutter> or <cutting)> is an “impact” via MPEP 2106.04(d) III, 1st para, last S: “Instead, the analysis should take into consideration all the claim limitations and how those limitations interact and impact each other when evaluating whether the exception is integrated into a practical application.”
9 <cutting> is the “impact”.
10 “cutter recognition” would give meaning and purpose to the manipulative steps of claim 1.
11 Each “wherein” clause in {{{triple brackets}}} is not “a limitation in a claim… where the clause gave ‘meaning and purpose to the manipulative steps’ ” via:
MPEP 2111.04 "Adapted to," "Adapted for," "Wherein," "Whereby," and Contingent Clauses [R-10.2019]
I. "ADAPTED TO," "ADAPTED FOR," "WHEREIN," and "WHEREBY"
Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure. However, examples of claim language, although not exhaustive, that may raise a question as to the limiting effect of the language in a claim are:
(A) "adapted to" or "adapted for" clauses;
(B) "wherein" clauses (“wherein the machine learning system includes an object recognition model that comprises a set of weights corresponding to one or more nodes of a neural network of the machine learning system”); and
(C) "whereby" clauses.
The determination of whether each of these clauses is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002) (finding that a "wherein" clause limited a process claim where the clause gave "meaning and purpose to the manipulative steps"[see claim 1 preamble’s lack of meaning and purpose and see MEANING AND PURPOSES I & II, below] and see: U.S. Constitution, setting forth the general principles of American government and beginning with the words, “We the people of the United States, in order to form a more perfect union. …” (Dictionary.com: preamble)).
12 train: to treat or manipulate so as to bring into some desired form, position, direction, etc.., wherein manipulate is defined: to adapt or change (accounts, figures, etc.) to suit one's purpose or advantage. (Dictionary.com)
13 model: a representation, generally in miniature, to show the construction or appearance of something. (Dictionary.com)
14 “based” is making a foundational contribution (and not necessarily the “cutter probability value”) to the claimed “provides an output” (mapped to the output arrow of CHOWHAN’s fig. 5B:518).
15 on: in connection, association, or cooperation with; as a part or element of. (Dictionary.com)
16 Regarding “cutter probability value” in view of applicant’s disclosure:
[0067] Plural instances may be provided for components, operations or structures described herein as a single instance. Finally, boundaries between various components, operations and data stores are somewhat arbitrary, and particular operations are illustrated in the context of specific illustrative configurations. Other allocations of functionality are envisioned and may fall within the scope of the disclosure. In general, structures and functionality presented as separate components in the example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements may fall within the scope of the disclosure.
17 regression: The relationship between the mean value of a random variable and the corresponding values of one or more independent variables, wherein random variable is defined: Statistics.
a quantity that takes any of a set of values with specified probabilities. (Dictionary.com)
18 MEANING AND PURPOSE I of claim 1 is “to improve drilling operations”.
19 bit: Machinery.
a. a removable drilling or boring tool for use in a brace, drill press, or the like.
b. a removable boring head used on certain kinds of drills, as a rock drill.
c. a device for drilling oil wells or the like, consisting of a horizontally rotating blade or an assembly of rotating toothed wheels. (Dictionary.com)
20 bit: a cutting or drilling tool, part, or head in a brace, drill, etc (Dictionary.com)
21 MEANING AND PURPOSE II of claim 1 is “for drill bit examination, rotation, replacement”.
22 Alternative language in triple brackets “does not limit the scope of a claim” via MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 3rd para:
As a general matter, the grammar and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
23 (italics) represent claim limitations already taught.
24 (italics) represent claim limitations already taught.
25 This is the initial motive/motorvation to look to others under 35 USC 103
26 orientation: the act or process of orienting or the state of being oriented, wherein orient is defined: to adjust or align (oneself or something else) according to surroundings or circumstances, wherein surroundings is defined: the conditions, scenery, etc, around a person, place, or thing; environment (Dictionary.com)
27 neural network: Also called neural net. Computers. a hardware or software system in which weighted connections between data nodes are refined to produce increasingly accurate results in information processing, as in pattern recognition or problem solving, with the goal of algorithmic computing that requires minimal human intervention., wherein accurate is defined: free from error or defect; consistent with a standard, rule, or model; precise; exact, wherein precise is defined: definitely or strictly stated, defined, or fixed, wherein definitely is defined: in a clear and definite manner; unambiguously, wherein definite is defined: positive; certain; sure, wherein sure is defined: confident, as of something expected: wherein expect is defined: to look forward to; regard as likely to happen; anticipate the occurrence or the coming of, wherein anticipate is defined: to realize beforehand; foretaste or foresee, wherein foresee is defined: to have prescience of; to know in advance; foreknow, wherein prescience is defined: knowledge of things before they exist or happen; foreknowledge; foresight, wherein foresight is defined: the act or power of foreseeing; prevision; prescience, wherein prevision is defined: wherein prevision is defined: a prophetic or anticipatory vision or perception, wherein prophetic is defined: predictive; presageful or portentous; ominous. (Dictionary.com).
28 CAD: computer-aided design, wherein computer-aided design is defined: CAD. the use of computer techniques in designing products, esp involving the use of computer graphics, wherein computer graphics is defined: pictorial computer output produced on a display screen, plotter, or printer. (Dictionary.com)
29 model: a simplified representation or description of a system or complex entity, esp one designed to facilitate calculations and predictions (Dictionary.com)
30 classify: to arrange or organize by classes; order according to class, wherein according is defined: agreeing, where agree is defined: to correspond; conform; resemble (usually followed by with ), wherein class is defined: a number of persons or things regarded as forming a group by reason of common attributes, characteristics, qualities, or traits; kind; sort. .
31 and: (used to connect alternatives). (Dictionary.com)
32 The crossed-out text “does not limit the scope of a claim [six]”: MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 3rd para:
As a general matter, the grammar (conjunction: “and”) and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language (conjunction: “and”) that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
33 comma: the sign (,), a mark of punctuation used for indicating a division in a sentence, as in setting off a word, phrase, or clause, especially when such a division is accompanied by a slight pause or is to be noted in order to give order to the sequential elements of the sentence. It is also used to separate items in a list, to mark off thousands in numerals, to separate types or levels of information in bibliographic and other data, and, in many European countries, as a decimal point. (Dictionary.com)
34 classify: to arrange or organize by classes; order according to class, wherein according is defined: agreeing, where agree is defined: to correspond; conform; resemble (usually followed by with ), wherein class is defined: a number of persons or things regarded as forming a group by reason of common attributes, characteristics, qualities, or traits; kind; sort. .
35 feedback: the furnishing of data concerning the operation or output of a machine to an automatic control device or to the machine itself, so that subsequent or ongoing operations of the machine can be altered or corrected. (Dictionary.com)
36 and: (used to connect alternatives). (Dictionary.com)
37 The crossed-out text “does not limit the scope of a claim [six]”: MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 3rd para:
As a general matter, the grammar (conjunction: “and”) and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language (conjunction: “and”) that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
38 smartphone: a device that combines a cell phone with a handheld computer, typically offering internet access, data storage, email capability, etc. (Dictionary.com)
39 software: Computers. the programs used to direct the operation of a computer, as well as documentation giving instructions on how to use them, wherein computer is defined: A programmable machine that performs high-speed processing of numbers, as well as of text, graphics, symbols, and sound. All computers contain a central processing unit that interprets and executes instructions; input devices, such as a keyboard and a mouse, through which data and commands enter the computer; memory that enables the computer to store programs and data; and output devices, such as printers and display screens, that show the results after the computer has processed data. . (Dictionary.com)
40 can: may; have permission to, wherein may is defined: (used to express contingency, especially in clauses indicating condition, concession, purpose, result, etc.), wherein condition is defined: Grammar. protasis, wherein protasis is defined: Grammar. the clause expressing the condition in a conditional sentence, in English usually beginning with if. (Dictionary.com)
41 by ADVERB over; past. (Dictionary.com)
42 (italics) represent claim limitations already taught
43 by ADVERB over; past. (Dictionary.com)
44 (italics) represent claim limitations already taught
45 (italics) represent claim limitations already taught
46 by ADVERB over; past. (Dictionary.com)
47 (italics) represent claim limitations already taught
48 various: of different kinds, as two or more things; differing one from another. (Dictionary.com)
49 confidence: full trust; belief in the powers, trustworthiness, or reliability of a person or thing, wherein trust is defined: confident expectation of something; hope, wherein expectation is defined: the degree of probability that something (“wear”) will occur. (Dictionary.com)
Prosecution Insights