Foster Findlay Associates LimitedDownload PDFPatent Trials and Appeals BoardNov 17, 20212021004929 (P.T.A.B. Nov. 17, 2021) Copy Citation UNITED STATES PATENT AND TRADEMARK OFFICE UNITED STATES DEPARTMENT OF COMMERCE United States Patent and Trademark Office Address: COMMISSIONER FOR PATENTS P.O. Box 1450 Alexandria, Virginia 22313-1450 www.uspto.gov APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO. 16/462,111 05/17/2019 James Lowell 86011-332561 9302 23643 7590 11/17/2021 Barnes & Thornburg LLP (IN) 11 S. Meridian Street Indianapolis, IN 46204 EXAMINER ALKAFAWI, EMAN A ART UNIT PAPER NUMBER 2865 NOTIFICATION DATE DELIVERY MODE 11/17/2021 ELECTRONIC Please find below and/or attached an Office communication concerning this application or proceeding. The time period for reply, if any, is set in the attached communication. Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the following e-mail address(es): INDocket@btlaw.com PTOL-90A (Rev. 04/07) UNITED STATES PATENT AND TRADEMARK OFFICE BEFORE THE PATENT TRIAL AND APPEAL BOARD Ex parte JAMES LOWELL and DALE NORTON Appeal 2021-004929 Application 16/462,111 Technology Center 2800 Before JEAN R. HOMERE, MINN CHUNG, and MICHAEL J. STRAUSS, Administrative Patent Judges. HOMERE, Administrative Patent Judge. DECISION ON APPEAL I. STATEMENT OF THE CASE1 Pursuant to 35 U.S.C. § 134(a), Appellant appeals from the Examiner’s rejection of claims 1, 3–14, 16, and 19–22 all of the pending claims.2 Appeal Br. 1. Claims 15, 17, and 18 have been cancelled. Id. We have jurisdiction under 35 U.S.C. § 6(b). 1 We refer to the Specification filed May 17, 2019 (“Spec.”); the Final Office Action, mailed Oct. 13, 2020 (“Final Act.”); the Appeal Brief, filed Apr. 7, 2021 (“Appeal Br.”); the Examiner’s Answer, mailed Jun. 17, 2021 (“Ans.”); and the Reply Brief, filed Aug. 13, 2021 (“Reply Br.”). 2 “Appellant” refers to “applicant” as defined in 37 C.F.R. § 1.42(a). Appellant identifies Foster Findlay Associates Ltd., as the real party-in- interest. Appeal Br. 2. Appeal 2021-004929 Application 16/462,111 2 We affirm. II. CLAIMED SUBJECT MATTER According to Appellant, the claimed subject matter relates to a method and system for analyzing seismic trace data to allow interactive and adaptive tracking of geological objects. Spec. 1:3–7. Fig. 3, reproduced and discussed below, is useful for understanding the claimed subject matter: Figure 3 above illustrates an automated method and system for adaptively and interactively tracking geologic faults in 3D seismic data. In particular, upon receiving a predetermined data set from a 3D seismic data including 2D slices of seismic phase events, a user/interpreter picks a characteristic phase event as a seed point in the data set, determines and assigns a Appeal 2021-004929 Application 16/462,111 3 similarity score to an associated phase event within the data set. The interpreter then applies an optimization algorithm thereto to determine the likely contour of the horizon (or fault) starting from the seed point to an endpoint within the predetermined data set. The end point may be a phase event, having phase characteristics and/or a position within the predetermined data set suitable to provide an optimized path through the predetermined data set, or it may be a second seed point picked by the user. The generated optimum path of the tracked geological feature is that visually presented within the predetermined data set. Optionally, visual representations of alternate (but less optimal) paths may be provided. Id. at 11: 1–19. Independent claim 1, reproduced below with disputed limitations emphasized, is illustrative: 1. A computer-implemented method for detecting a natural contour of a geologic object represented in three-dimensional (3D) seismic data, the method comprising: identifying a first data set from within the 3D seismic data, the first data set comprising a plurality of phase events; selecting, from the plurality of phase events, a first seed phase event comprising a first phase characteristic; using a similarity calculation to determine a corresponding similarity score between the selected first seed phase event and each one of a predetermined number of candidate phase events included in the first data set; assigning each corresponding similarity score to each corresponding one of the predetermined number of candidate phase events; adjusting a particular similarity score of a particular one of the predetermined number of candidate phase events in accordance with a first boundary condition; generating a tracked path corresponding to a natural contour that is present between the first seed phase event and a second phase event, wherein the natural contour is determined utilizing an optimization algorithm; during generation of the tracked path, preventing the tracked path from tracking non-geological horizons by modifying one or more Appeal 2021-004929 Application 16/462,111 4 of the similarity scores of the candidate phase events to discourage the tracked path from jumping between peaks and troughs, wherein: discouraging the tracked path from jumping between peaks and troughs is performed by applying a sigmodal function to the similarity calculation used to determine said similarity scores of the candidate phase events, applying the sigmodal function operates to reduce similarity scores of specific candidate phase events that are determined to have a weak similarity relative to the first seed phase event, and reducing, using the sigmodal function, the similarity scores of the specific candidate phase events that are determined to have the weak similarity relative to the first seed phase event is performed irrespectively of a vertical path steepness existing between the first seed phase event and the specific candidate phase events such that said reducing is not performed based on the vertical path steepness but rather is based on the weak similarity determination; during generation of the tracked path and in response to determining the tracked path has entered an identified chaos area, using a defined chaos attribute to automatically exclude seed phase events that are associated with the identified chaos area from influencing the tracked path such that the tracked path is guided through the chaos area without reliance on said excluded seed phase events; during generation of the tracked path, causing the tracked path's generation to stop when the tracked path reaches a detected fault region corresponding to a geological fault represented within the 3D seismic data, wherein causing the tracked path's generation to stop at the fault region is based on a geological understanding that is encoded to programmatically stop the tracked path's generation, the geological understanding being encoded to cause the tracked path's generation to automatically stop at the fault region as a result of an encoded penalty that is potentially applied to tracked paths that cross into fault regions; and generating a visual representation of the natural contour using the tracked path. Appeal Br. 14–16 (Claims App.) (emphasis added). Appeal 2021-004929 Application 16/462,111 5 III. REFERENCES The Examiner relies upon the following references.3 Name Reference Date Chen US 2010/0040281 A1 Feb. 18, 2010 Imhof US 2010/0149917A1 Jun. 17, 2010 Haukas US 2014/0214328 A1 Jul. 31, 2014 Bas US 2014/0278115A1 Sep. 18, 2014 IV. REJECTIONS The Examiner rejects the claims on appeal as follows: Claims 1, 3, 6–11, 13, 14, 16, and 19–22 stand rejected under 35 U.S.C. § 103 as being unpatentable over the combined teachings of Purves, Chen, and Imhof.4 Final Act. 3–17.5 Claims 4 and 5 stand rejected under 35 U.S.C. § 103 as being unpatentable over the combined teachings of Purves, Chen, Imhof and Haukas. Final Act. 17–19. Claim 12 stands rejected under 35 U.S.C. § 103 as being unpatentable over the combined teachings of Purves, Chen, Imhof, and Bas. Final Act. 19–20. 3 All reference citations are to the first named inventor only. 4 The Examiner asserts that Imhof is cited as an evidentiary reference to buttress the official notice in the rejection, and not as part of the combination of references to reject the claims. Ans. 3. Because Appellant’s arguments do not challenge the reason for which Imhof is relied upon, we determine that the Examiner’s use of Imhof is immaterial to the pivotal issues before us. 5 Claim 22 is inadvertently omitted from the statement of the rejection. It is nonetheless discussed in the body of the rejection. Final Act. 16. Claim 15 has been cancelled. Appeal Br. 1. Appeal 2021-004929 Application 16/462,111 6 V. ANALYSIS We consider Appellant’s arguments, as they are presented in the Appeal Brief, pages 4–13 and the Reply Brief, pages 2–10.6 We are unpersuaded by Appellant’s contentions. Except as otherwise indicated herein below, we adopt as our own the findings and reasons set forth in the Final Action, and the Examiner’s Answer in response to Appellant’s Appeal Brief. Final Act. 2–20; Ans. 3–16. However, we highlight and address specific arguments and findings for emphasis as follows. a. Claim 1 Appellant argues, inter alia, that the Examiner errs in finding that the combination of Purves, Chen, and Imhof teaches or suggests applying a sigmoidal function to a similarity score calculation between candidate phase events to discourage a tracked path from jumping between peaks and troughs, as recited in independent claim 1. Appeal Br. 7. In particular, Appellant argues that the Examiner erroneously finds Chen’s disclosure of performing a dimensionality reduction operation on a data set to preserve Euclidean distance between pairs of data teaches or suggests the disputed limitations. Id. at 8 (citing Chen ¶¶ 76–86). More particularly, Appellant states the following: Appellant notes that Chen makes no use of the term “phase event” at all. The Examiner's Answer attempts to remedy this deficiency by applying a concocted “linguistic interpretation” of “phase event,” and suggesting that the mention of different phases of processing data (e.g., an optional clustering phase, an evolutionary computation phase, a particles warm 6 We have considered in this Decision only those arguments Appellant actually raised in the Briefs. Arguments not made are waived. See 37 C.F.R. § 41.37(c)(1)(iv). Appeal 2021-004929 Application 16/462,111 7 optimization phase) described in Chen at paragraph [0036] are a disclosure of the "phase events" recited in claim 1. See Examiner's Answer at 5. But these teachings of Chen are plainly irrelevant to the “phase events” recited in Appellant's claims: namely, “characteristic events of a seismic trace” as defined in Appellant's specification. The processing phases taught in Chen, which are used in the transformation of data from a high- dimensionality data set to a low-dimensionality data set represent a sequence of operations, not characteristic events of a seismic trace. See Chen at ¶ [0036] (cited in Examiner's Answer). As such, with reference to the recitations of claim 1, it follows that the “phases” in Chen do not have a seed phase event, candidate phase events, or similarity scores to be used as the basis for generating a tracked path between the phases. Accordingly, Appellant respectfully submits that the discussion of different operations in performing a dimensionality reduction process in Chen does not pertain to the recited phase events in claim 1. As mentioned above, the Examiner's Answer offers another, equally flawed interpretation of the claimed “phase event”: specifically, pertaining to repeating signals having an amplitude and phase. See Examiner's Answer at 5–6. However, as explained above, Appellant's specification defines “phase event” as “characteristic events of a seismic trace,” and the Examiner’s interpretation ignoring this definition is unreasonably broad. As such, the disclosure in paragraphs [0075] and [0086] of Chen, cited by the Examiner, pertaining to the alignment or correlation between repeating signals based on their phase is inapposite to the adjustment of similarity scores in phase events (i.e., characteristic events of a seismic trace) based on a sigmoid function, as recited in claim 1. Furthermore, the sigmoid function referenced in Chen has nothing to do with adjusting similarity scores between two different phase events (i.e., characteristic events of a seismic trace). Rather, the sigmoid function in Chen is described as being used in a process of assigning weights to mismatch errors between sample pairs of data in an original input space and an Appeal 2021-004929 Application 16/462,111 8 output space having a lower dimensionality. See, e.g., Chen at ¶¶ [0076]-[0086] (cited in the Examiner's Answer). Reply Br. 4–5. In response, the Examiner finds that under the broadest reasonable interpretation “phase event” can be construed as a phase shift or phase change (i.e., affording the term a technical/mathematical interpretation), which is taught by Chen as a linear correlation approach. Ans. 5 (citing Chen ¶¶ 75, 86). Alternatively, the Examiner construes “phase event” as a certain event at a defined time/period/stage (a linguistic interpretation), which is taught by Chen as a “clustering phase, evolutionary computation (“EC” phase). Id. (citing Chen ¶¶ 45, 51–60). In particular, the Examiner the Examiner finds the following: [O]ne of ordinary skill in the art knows and recognizes the basic elements of correlation, the mathematical definition of “correlation” is “is a measure of similarity of two series as a function of the displacement of one relative to the other”, the displacement that is the phase shift by tao, wherein it is inherent that any signal is represented by its amplitude and phase as explained above. Note the terms (t and tao) do not necessarily refer to time aspect, they could reference radian aspect or any other aspect related to the compared signals, i.e. the correlation approach is applicable to any data type as long as the mathematical aspect is applied. Thus, the phase aspect is inherently applied in Chen. See OA page 8 “See [0086] “we can construct a multi-objective fitness function to minimize the distance mismatch between the original and output space, and to maximize the linear correlation between the output coding and the measured density values in the supervised data set.” Knowing that the same correlation approach is used in Purves OA page 6 “Moreover, [0088-0089] and fig 8, wherein the peak and trough features are part of the correlation consideration which is based on reference Appeal 2021-004929 Application 16/462,111 9 segments, such reference is “invariance to time shift and dilation”.” Third, the mathematical sigmoid function is well-known in the art and is applied in Chen. The sigmoid function: is a bounded differentiable, real function that is defined for all input values and has non negative derivative at each point and exactly one inflection point. This function is used to determine similarity as a weighting factor in order to present the degree of the similarity/ similarity score. One of its properties is, it provides the shortest distance of the data, avoiding and excluding mismatching, in other words this function provides an optimized/ weighted function to provide a better determination of the degree/ score of similarity. This aspect is applied in Chen as explained in the OA page 7-8 and recited her[e] for convenience “[0076-0086] wherein the similarity “matching” level/ weighing factor”, reads on “similarity” and wherein the sigmoid function is applied to determine such feature and wherein the distance between points to be minimized “short distance” which reads on “discouraging the tracked path from jumping between peaks and troughs is performed by applying a sigmodal function to the similarity'', knowing that mismatching points to be excluded (i.e. weak similarity to be excluded). See [0086] “we can construct a multi- objective fitness function to minimize the distance mismatch between the original and output space, and to maximize the linear correlation between the output coding and the measured density values in the supervised data set.”, also see [0057] “distance mismatch”. Not to mention that such technique sigmoid function/ weighing function is based on a short distance range, i.e. if the signal being steep, such feature does not make a difference as the steep distance is not within the range of consideration, as in [0077–0076] wherein the consideration of the relative distance range coefficient values, are based on the corresponding signal with the consideration of “short distance”. Ans. 7–8 (emphasis added) (alteration added). Appeal 2021-004929 Application 16/462,111 10 Appellant’s arguments are not persuasive of reversible Examiner error because they are tantamount to separate attacks against the references individually, and not as the combination proposed by the Examiner. One cannot show non-obviousness by attacking the references individually where the rejections are based on combinations of references. In re Merck & Co., 800 F.2d 1091, 1097 (Fed. Cir. 1986); see also In re Keller, 642 F.2d 413, 425 (CCPA 1981). As an initial matter, we note the disputed claim limitations recite applying a sigmoidal function to a similarity score calculation between candidate “phase events” to discourage a tracked path from jumping between peaks and troughs. We note, the cited claim language must be given its broadest reasonable interpretation consistent with Appellant’s disclosure, as explained in Morris: [T]he PTO applies to the verbiage of the proposed claims the broadest reasonable meaning of the words in their ordinary usage as they would be understood by one of ordinary skill in the art, taking into account whatever enlightenment by way of definitions or otherwise that may be afforded by the written description contained in the applicant’s specification. In re Morris, 127 F.3d 1048, 1054 (Fed. Cir. 1997); see also In re Zletz, 893 F.2d 319, 321 (Fed. Cir. 1989) (stating that “claims must be interpreted as broadly as their terms reasonably allow.”). Our reviewing court further states, “the proper … construction is not just the broadest construction, but rather the broadest reasonable construction in light of the specification.” In re Man Mach. Interface Techs. LLC, 822 F.3d 1282, 1287 (Fed. Cir. 2016). As noted by Appellant, the Specification refers to a “phase event” as a “trace extrema” or a “characteristic event of a seismic trace”. Reply Br. 3 (citing Spec. ¶¶ 72, 73). More broadly, the Specification also refers to a Appeal 2021-004929 Application 16/462,111 11 “phase event” as a “seed point anywhere within the predetermined data set” wherein the data set includes 3D seismic data. Spec. ¶ 73. Therefore, under the broadest reasonable consistent with the Specification, we construe a “phase event” as any data point referencing a seismic event within a received set of seismic data points. The Examiner finds, and Appellant does not dispute, that Purves discloses a method and system for detecting a natural contour of a geologic object represented in three-dimensional (3D) seismic data, including applying an algorithm to a similarity score of predetermined number of candidate phase events. Final Act. 3–7 (citing Purves ¶¶ 4, 9, 12–15, 21–, 24, 39–46, 50–57, 60, 71, 73, 84–93, 96). Further, the Examiner finds that Chen teaches applying a sigmodal function to a similarity score calculation between candidate data. Id. at 7–8 (citing Chen ¶¶ 76–87). Further, the Examiner reasons that: It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the well-known technique of sigmoid function in determining the similarity/matching degree of Chen to the similarity degree calculation of similarity degree of Purves in order to attain the expected results yet with higher accuracy ([0081] “accurate distance mapping” Chen). Moreover, the teaching of Purves does not specify a particular similarity/ matching calculation technique, thus, any well-known approach/ technique applied within the art would be applicable as long as the matching/ similarity degree to be attained. Id. at 8–9. We find the Examiner’s proposed combination of the cited teachings of Purves and Chen is no more than a simple arrangement of old elements with each performing the same function it had been known to perform, Appeal 2021-004929 Application 16/462,111 12 yielding no more than what one would expect from such an arrangement. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 416 (2007). Therefore, the ordinarily skilled artisan, being “a person of ordinary creativity, not an automaton,” would have been able to fit the teachings of the cited references together like pieces of a puzzle to predictably result in system that applies a sigmoidal function to a similarity score calculation between candidate “phase events” to reduce the similarity scores of the specific candidate phase events. Id. at 420–21. Because Appellant has not demonstrated that the Examiner’s proffered combination would have been “uniquely challenging or difficult for one of ordinary skill in the art,” we agree with the Examiner that the proposed modification would have been within the purview of the ordinarily skilled artisan. See Leapfrog Enters., Inc. v. Fisher-Price, Inc., 485 F.3d 1157, 1162 (Fed. Cir. 2007) (citing KSR, 550 U.S. at 418). Consequently, we are satisfied that, on the record before us, the Examiner has established by a preponderance of the evidence that the combination of Purves and Chen teaches the disputed claim limitations. Because we are not persuaded of Examiner error, we sustain the Examiner’s rejection of claim 1 as being unpatentable over the combination of Purves and Chen. b. Claim 10. Appellant argues that the combination of Purves, Chen, and Imhof does not teach or suggest “an alternate natural contour that is an alternate solution provided by the optimization algorithm” as recited in claim 10. Appeal Br. 9. According to Appellant, Purves’s disclosure of a user being able to stop an adaptation process or solution produced by an algorithm does not teach the disputed limitations. Id. (citing Purves ¶¶ 102, 104). Appeal 2021-004929 Application 16/462,111 13 Appellant’s arguments are not persuasive of reversible Examiner error. Appellant fails to provide evidence that or explain why the modification or alteration of the deformation parameters does not result or otherwise teach or suggest an alternate solution by an optimization algorithm. We thus agree with the Examiner that Purves’s disclosure of modifying the optimal solution by altering the deformation parameters therein to yield another solution teaches or suggests an alternate solution as recited in claim 10. Final Act. 12 (citing Purves ¶¶ 100–102). Because we are not persuaded of Examiner error, we sustain the Examiner’s rejection of claim 10 as being unpatentable over the combination of Purves and Chen. c. Claim 4 Appellant argues that the combination of Purves, Chen, Imhof, and Haukas does not teach or suggest a similarity score projected from a second data set included in the 3D seismic data. Appeal Br. 9. According to Appellant, Purves’s disclosure of identifying weak phase events, which are subsequently linked to the guide reflector using constraints dependent on actual weakness of each event, does not teach or suggest the weakness of an event related to a similarity score. Id. (citing Purves ¶¶ 24, 35–39). Appellant’s arguments are not persuasive of reversible Examiner error. We note claim 4 recites the following: A method according to claim 3, wherein the variable is (i) a relative position of the particular one candidate phase event with respect to any other one of the predetermined number of candidate phase events or a predetermined geological object, (ii) an angular inclination of the natural contour with respect to the 3D seismic data, (iii) the particular similarity score of the particular one candidate phase event, or (iv) a similarity score projected from Appeal 2021-004929 Application 16/462,111 14 a second data set said that is also included within the 3D seismic data. Id. at 16 (Claims App.) (emphasis added). Because the claim recites a variable that can be alternatively one of four elements, the Examiner need only show that the proposed combination of references teaches or suggests any one of the four recited items. In this case, the Examiner finds the following: As to claim 4, Purves as modified teaches “the variable is (i) a relative position of the particular one candidate phase event with respect to any other one of the predetermined number of candidate phase events or a predetermined geological object,” ([0025] “each of the event linking reflective surface position”. Moreover, [0082] “30 seismic volume aligned in accordance with the natural position of the strata surveyed, i.e. the stratigraphic layers are substantially horizontal within that volume and a vertical direction within that volume indicates a direction towards a position within that volume that is either above or below a referenced stratigraphic layer”. Also see [0089] and [0093] “position”, “distance”.) Purves is silent in regards to angular inclination. Haukas teaches “(ii) an angular inclination of the first natural contour with respect to the 3D seismic data,” ([0013] “gradient of the amplitude”. See [0054-0062] the directional “gradient' reads on “angular inclination”. Also see [0066], [0075] and [0081].) It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the directional gradient determination of Haukas to the determination of the event characteristics of Purves, as such technique is well-known in the art and applicable and would provide the expected results with higher accuracy (KSR). Appeal 2021-004929 Application 16/462,111 15 Purves as modified teaches “(iii) the particular similarity score of the particular one candidate phase event,” (Moreover, [0084-0089] “applies probability function based on the determined attribute characteristics and respective local waveform characteristics in order to determine, whether or not, a candidate event meets an acceptance criteria and can be selected to be part of the tracked horizon.”, if the first selected event matches the defined threshold/acceptance criteria, then it is taken, otherwise another event/data set to be selected “move vertically”; “similarity', “semblance”,. Moreover, [0039] and [0090] “steer”, “poor', “weak” wherein crossing weak events is applied based on the identified similarity degree of [0024] and claim 3, also see [0092-0093] “according to a value of probability'. See claim 1-3 “degree of similarity' reads on score. Also see [0038-0039].) Purves as modified teaches “and (iv) a similarity score projected from a second data set said that is also included within the 3D seismic data.” ([0035-0039], claim 11, 13 and 25 “second region of interest', see [0024] and claim 3 “degree of similarity'.) Final Act. 17–18. Because the Examiner finds that the combination of Purves, Chen, Imhof, and Haukas teaches all four elements that can alternatively correspond to the claimed variable, Appellant’s allegation that the combination does not teach one of the elements (even if true) does not overcome the Examiner’s prima facie case of obviousness. Accordingly, we are not persuaded of error in the Examiner’s rejection of claim 4. Regarding the rejections of claims 3, 5–9, 11–14, 16, and 19–22, Appellant has not presented separate patentability arguments or has reiterated substantially the same arguments as those previously discussed for the patentability of claims 1, 4, and 10. As such, claims 3, 5–9, 11–14, 16, and 19–22, fall therewith. See 37 C.F.R. § 41.37(c)(1)(iv). Appeal 2021-004929 Application 16/462,111 16 VI. CONCLUSION For the above reasons, we affirm the Examiner’s rejections of claims 1, 3–14, 16, and 19–22. VII. DECISION SUMMARY In summary: Claims Rejected 35 U.S.C. § References s Affirmed Reversed 1, 3, 6–11, 13, 14, 16, 19–22 103 Purves, Chen, Imhof 1, 3, 6–11, 13, 14, 16, 19–22 4, 5 103 Purves, Chen, Imhof, Haukas 4, 5 12 103 Purves, Chen, Imhof, Bas 12 Overall Outcome 1, 3–14, 16, 19–22 No time period for taking any subsequent action in connection with this appeal may be extended under 37 C.F.R. § 1.136(a)(1). See 37 C.F.R. § 1.136(a)(1)(iv). AFFIRMED Copy with citationCopy as parenthetical citation