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 .
Response to Arguments
Applicant’s arguments, see Remarks, filed 30 January 2026, with respect to the rejections of claims 1, 3–7, and 15–18 under § 103 have been fully considered and are persuasive. The prior art rejections of claims 1, 3–7, and 15–18 have been withdrawn.
Applicant’s arguments, see Remarks, filed 30 January 2026, with respect to the rejection(s) of claims 8–15 under § 103 in view of Chakkalakal and Volponi 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 Therefore, the rejection has been withdrawn.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 Chakkalakal et al. (US Pub. 2018/0073685) and Fridley et al. (US Pub. 2022/0260988).
Specification
The specification is objected to as failing to provide proper antecedent basis for the claimed subject matter. See 37 CFR 1.75(d)(1) and MPEP § 608.01(o). Correction of the following is required:
Antecedent basis for the second alarm condition of claim 3, the third alarm condition of claim 4, and the second alarm fraction and second alarm condition of claim 10 should be added to the specification.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 8–12 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Chakkalakal in view of Fridley et al. (US Pub. 2022/0260988).
Claim 8: Chakkalakal discloses a control system (100) for use with a pipeline (102) that transports a process fluid (abstract, “process fluid”), the control system comprising:
a distributed temperature sensing system that records temperature data at a plurality of segments along the pipeline (¶ 30, “A fiber optic based DTS system (e.g., which may include one or more fluid temperature sensors) is used to measure temperature across pipe 102”; 108), wherein the plurality of segments make up a total length of the pipeline (necessarily and inherently; see also figs. 6 and 7);
a heating system (116) that heats the process fluid in the pipeline; and
a management system (120, 122) including a controller (122) in electronic communication with the distributed temperature sensing system and the heating system (see ¶¶ 29 and 30), the controller comprising a processor (120) and memory storing specific computer-executable instructions (¶ 29, “computer readable non-transitory memory that includes instructions”) that, when executed by the processor, cause the controller to:
receive the temperature data from the distributed temperature sensing system (see ¶ 30 discussing the DTS system and the processing circuitry 120);
determine a first alarm condition for each segment of the plurality of segments along the pipeline (the determination of the temperatures at the segments qualifies as a first alarm condition; alarms associated with temperature events are also mentioned in ¶ 32); and
display information (see e.g. fig. 3).
Chakkalakal does not disclose calculating a risk score of the pipeline based on the first alarm condition; and displaying, via a graphical user interface, a representation of the risk score.
However, Chakkalakal already provides general teachings about managing risks in the pipeline system (see ¶¶ 37 and 39). One of ordinary skill in the art would understand the physical aspects of the system that could cause risk to develop, and the record is clear that these risks in Chakkalakal are managed by an operator.
Furthermore, Fridley discloses a pipeline system (see ¶ 3) and discloses calculating a risk score of the pipeline based on an alarm condition (¶ 23, “In some implementations, the alert comprises a numerical risk score that indicates a likelihood that the anomaly will occur”; ¶ 81, “the system can transmit an alert that indicates that the system is experiencing an anomaly if the difference meets the threshold (340). The alert can additionally include a numerical risk score”); and displaying, via a graphical user interface, a representation of the risk score (clearly shown in at least figs. 4–7; see also at least ¶¶ 86 and 91).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to implement a risk score alike to the one associated with the alarm condition taught by Fridley, as well as to provide a graphical user interface to represent this score as shown in Fridley, to automate risk management and further aid an operator in risk management (see MPEP § 2144.04.III. regarding the obviousness of automating a manual activity), and otherwise to improve the reliability of the pipeline (see ¶ 3 of Fridley).
Claim 9: Chakkalakal does not disclose discloses that calculating the risk score includes: calculating an alarm fraction for the first alarm condition, the alarm fraction equating to a number of segments in which the first alarm condition is present over the total length of the pipeline; and when the alarm fraction is greater than a limit, adding a stored first alarm condition risk value to the risk score.
However, one of ordinary skill in the art would have understood that, and how, the degrees (at one or more locations) and extent (along the length of the pipeline) of temperature malfunctions would affect the risk of any particular system operating condition. Furthermore, one of ordinary skill in the art would have appreciated that some non-ideal temperature statuses would present a low risk (see e.g. the top of fig. 3 showing high and low temperatures, which necessitates an acceptability range, as well as this seemingly clearly reflected in fig. 5), and would have understood the relevance of adding only meaningful risks (i.e. those above a limit) to a risk score.
Furthermore, Fridley discloses using “a clustering algorithm that clusters objects based on their proximity to other objects,” and teaches that “asset models can be combined together to represent a subsystem, and subsystem models can be combined together to represent a system.” One of ordinary skill in the art would have understood from that the “asset models” of Fridley are analogous to the pipeline segments of Chakkalakal, which join together to form a subsystem of a total pipeline, and would have appreciated that a level of risk in the pipeline segment assets would hierarchically affect the risk of the pipeline subsystem. Furthermore, Fridley teaches that risk scores can have certain categories (see ¶ 86, “e.g., low, medium, or high”), and one of ordinary skill in the art would have understood (as is clearly indicated throughout the rest of Fridley) that these are determined comparisons to limits. Therefore, before the effective filing date of the claimed invention, it would have been obvious to apply Fridley’s teachings by ascertaining when the temperatures at the pipeline segments of Chakkalakal exceeded a collective subsystem limit to arrive at a risk score.
Claim 10: Continuing from the discussion for claim 9, given Fridley’s teachings about the hierarchical effects of asset and subsystem risk scores, it further would have been obvious to one of ordinary skill in the art to calculate additional (second) alarm fractions for additional alarm conditions, and to add a further (second) alarm condition risk value to the risk score commensurate with the manner in which the further spread of the further asset conditions affected the risk of the pipeline subsystem.
Comment: The Office understands this “second alarm fraction” as corresponding to a different temperature-based alarm, although it’s unclear if this is also broad enough, or intended to read on non-temperature-based alarms. Both Chakkalakal and Fridley seem to acknowledge the importance of measuring other aspects of pipelines such as pressure and flow rate.
Claim 11: Continuing from the discussion for claims 9 and 10, it would have concomitantly been obvious to one of ordinary skill in the art to not add insignificant (i.e. below limit) alarm fractions to the risk score.
Claim 12: Modified as per claim 8 above, Fridley discloses that the representation of the risk score includes a numerical value (¶ 86, “a numerical risk score,” “the numerical risk scores can range from 0 to 100”).
Claim 13: Modified as per claim 8 above, Fridley discloses that the representation of the risk score includes an image of a colored gauge including a color based on the risk score (¶ 86, “The numerical risk scores can be color-coded to indicate the predicted severity of the corresponding anomaly. For example, the most severe anomalies can have red risk scores, while less severe anomalies can have yellow risk scores”).
Claim 14: Chakkalakal discloses that the first condition includes one of an out-of-range pipeline temperature condition, a pipeline alarm, a pump alarm, a heating system alarm, a temperature sensing system alarm, and a communication alarm (¶ 32, “DTS system 200 may provide alarms to indicate to an operator the position and intensity of any extreme temperature event which could jeopardize the flow of process fluid in the pipeline,” which qualifies as disclosing an out-of-range pipeline temperature condition alarm).
Allowable Subject Matter
Claims 1, 3–7, and 15–18 are allowed.
The following is a statement of reasons for the indication of allowable subject matter:
Applicant’s arguments against the rejection 1 (which now incorporates the limitations of claim 2) in view of Chakkalakal have been fully considered and found persuasive. With reference to the previous rejection, while it may have been obvious to present separate statements of “substation 1 is over-limit” and “substation 2 is over-limit” as “substations 1 and 2 are over-limit,” as Applicant persuasively argues, the claim appears to be more specific because the alarm condition would be specifically directed to adjacent segments that form an extended segment rather than the mere concise presentation of alarm conditions for segments that happen to be adjacent. While Fridley relevantly teaches clustering algorithms (¶ 54), this is different from and more complex (in a divergent way) than the claimed extended segment alarm.
Regarding claim 15, a reference such as Nixon et al. (EP 3156871 A1) discloses a graphical user interface displaying a condition of a virtual model of a system that includes pipes. However, analogous prior art does not seem to disclose or suggest a pipeline heating system that coordinates temperature data and distinguishes pipeline temperature data, ambient temperature data, and unusable temperature data along with the graphical display of virtual model pipeline conditions.
Conclusion
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/JOHN J NORTON/Primary Examiner, Art Unit 3761
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