CTNF 18/591,254 CTNF 100878 Notice of Pre-AIA or AIA Status, 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. DETAILED ACTION The following NON-FINAL Office Action is in response to application 18/591,254 filed on 02/29/2024. This communication is the first action on the merits. Information Disclosure Statement The information disclosure statement (IDS) submitted on 07/03/2024, 04/16/2025 has been considered by the examiner. Drawings 06-37 AIA The drawings were received on 02/29/2024 . These drawings are acceptable . Claim Objections 07-29-01 AIA Claim s 2, 9, and 16 objected to because of the following informalities: the abbreviation “BS&W” is an undefined abbreviation in the claims. The specification appears to define BS&W as “basic sediment and water (BS&W)” . Appropriate correction is required. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. A subject matter eligibility analysis is set forth below. See MPEP 2106. Specifically, representative Claim 1 recites: A computer-implemented method, comprising: extracting, automatically and in real-time as measured data from elements of a natural gas liquids (NGL) network, values for operating parameters and quality parameters; comparing the measured data against maximum limits; if the comparison indicated the measured data is within limit: continuing normal operations; and reporting performance; and if the comparison is not within limit: issuing an alert notification; conducting an investigation via trending and root-cause analysis; and performing corrective and mitigation actions. The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements.” Claim 8 and 15 comprise similar abstract idea limitations which performs the method of claim 1. Under Step 1 of the analysis, claim 1 belongs to a statutory category, namely it is a method claim. Likewise, claim 8 is a non-transitory, computer-readable medium claim, and claim 15 is a system claim. Under Step 2A, prong 1: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim. In the instant case, claim 1 is found to recite at least one judicial exception (i.e. abstract idea), that being a Mental Process and a Mathematical Concept. This can be seen in the claim limitations of “ comparing the measured data against maximum limits ”, “ if the comparison indicated the measured data is within limit: continuing normal operations; and reporting performance”, “if the comparison is not within limit: issuing an alert notification; conducting an investigation via trending and root-cause analysis; and performing corrective and mitigation actions” which is the judicial exception of a mental process because these limitations are merely data observations, evaluations, and/or judgements in order to evaluate whether measured process data is within predefined limits and determine an appropriate operational response” and is capable of being performed mentally and/or with the aid of pen and paper. Moreover, the limitations of “issuing an alert notification”, “conducting an investigation” and “performing corrective and mitigation actions” are also directed to managing operational responses to detect conditions, including notifying personnel, investigating causes, and therefore further recite certain methods of organizing human activity. See MPEP 2106.04(a)(2). Additionally, the aforementioned limitations recite mathematical calculations, e.g. see Spec. [0049]-[0063] describing the use of data analysis and predictive techniques, such as trending and root-cause analysis, to evaluate measured operating and quality parameter data and determine whether values exceed predefined limits, and to identify appropriate corrective or mitigation actions. Similar limitations comprise the abstract ideas of Claim 8 and 15 . Step 2A, prong 2 of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception(s) into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. In addition to the abstract ideas recited in claim 1, the claimed method recites additional elements including “A computer-implemented method, comprising: extracting, automatically and in real-time as measured data from elements of a natural gas liquids (NGL) network, values for operating parameters and quality parameters” however these elements are found to be data gathering and output steps, which are recited at a high level of generality, and thus merely amount to “insignificant extra-solution” activity(ies). See MPEP 2106.05(g) “Insignificant Extra-Solution Activity,”. Furthermore, the claim recites that the steps, e.g. “extracting”, are performed by the computer however this is found to be equivalent to adding the words “apply it” and mere instructions to apply a judicial exception on a general purpose computer does not integrate the abstract idea into a practical application. See MPEP 2106.05(f). The generic data gathering, processing, and output steps, are recited at such a high level of generality that it represents no more than mere instructions to apply the judicial exceptions on a computer. It can also be viewed as nothing more than an attempt to generally link the use of the judicial exceptions to the technological environment of a computer. Noting MPEP 2106.04(d)(I): “ It is notable that mere physicality or tangibility of an additional element or elements is not a relevant consideration in Step 2A Prong Two. As the Supreme Court explained in Alice Corp., mere physical or tangible implementation of an exception does not guarantee eligibility. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1983-84 (2014) ("The fact that a computer ‘necessarily exist[s] in the physical, rather than purely conceptual, realm,’ is beside the point") ”. Thus, under Step 2A, prong 2 of the analysis, even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception. No specific practical application is associated with the claimed system. For instance, nothing is done with the result of analyzing the measured operating and quality parameter data beyond determining whether the data is within predefined limits and as an example issuing an alert notification, reporting performance or indicating that normal operations should continue, rather than using the results to automatically control or modify operation of physical equipment (e.g., adjusting a valve position, regulating flow rate, or modifying pressure in a pipeline). Under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as described above with respect to Step 2A Prong 2, merely amount to a general purpose computer system that attempts to apply the abstract idea in a technological environment, limiting the abstract idea to a particular field of use, and/or merely performs insignificant extra-solution activit(ies) (claims 1, 8, and 15). Such insignificant extra-solution activity, e.g. data gathering and output, when re-evaluated under Step 2B is further found to be well-understood, routine, and conventional as evidenced by MPEP 2106.05(d)(II) (describing conventional activities that include transmitting and receiving data over a network , electronic recordkeeping, storing and retrieving information from memory, and electronically scanning or extracting data from a physical document). Therefore, similarly the combination and arrangement of the above identified additional elements when analyzed under Step 2B also fails to necessitate a conclusion that claim 1, as well as claim 8 and 15, amount to significantly more than the abstract idea. With regards to the dependent claims, claims 2-7, 9-14, and 16-20 , merely further expand upon the algorithm/abstract idea and do not set forth further additional elements that integrate the recited abstract idea into a practical application or amount to significantly more. Therefore, these claims are found ineligible for the reasons described for claims 1, 8, and 15. Specifically: With respect to dependent claims 2, 9, and 16 specifically , the claims further recite limitations directed to specifying operating parameters and quality parameters, including flow, pressure, temperature, level, and composition data. These limitations merely relate to the type of data being collected and analyzed as part of the abstract data analysis recited in claim 1. Such limitations constitute data gathering activity and do not impose any meaningful limits on how the abstract idea is performed. Accordingly, these limitations fail to integrate the abstract idea into a practical application. See MPEP 2106.05(g). With respect to dependent claims 3, 10, and 17 specifically , the claims further recite that the alert notification includes email or text messages. These limitations are directed to the format and transmission of output information, which constitute post solution activity and/or insignificant extra solution activity, such as transmitting data over a network. Such limitations merely represent conventional ways of communicating results and do not integrate the abstract idea into a practical application. See MPEP 2106.05(g)(h). With respect to dependent claims 4, 5, 11, 12, 18, and 19 specifically , the claims further recite limitations directed to performing investigation via trending and root-cause analysis using artificial intelligence algorithms, and providing an advisory including a proposed corrective action. These limitations merely expand upon the data analysis and evaluation underlying the abstract idea by further refining how the data is processed or interpreted. The use of artificial intelligence or advisory outputs amounts to mathematical concepts and mental processes, and the presentation of recommendations constitute output of the analysis. Furthermore, providing an advisory including a proposed corrective action constitutes managing conditions and directing decision-making regarding business or industrial operations. Accordingly, these limitations also recite certain methods of organizing human activity. See MPEP 2106.04(a)(2). Accordingly, these limitations fail to integrate the abstract idea into a practical application. See MPEP 2106.05(f)(g). With respect to dependent claims 6, 7, 13, 14, and 20 specifically , the claims further recite limitations directed to automatically performing corrective and mitigation actions, including adjusting preparations parameters such as temperature, pressure, valves, and injection. While these limitations reference real-world actions, they are triggered solely based on the results of the abstract data analysis and are recited at the high level of generality without any specific technological implementation. For instance, the claims do not specify how the system physically controls or modifies the industrial equipment, but instead merely indicate that an action is performed in response to the analysis. As such, these limitations amount to insignificant extra solution activity or instructions to apply the abstract idea, and therefore fail to integrate the abstract idea into a practical application. See MPEP 2106.05(f)(g)(h). Accordingly, for the reasons above and those discussed in relation to independent claim 1, 8, and 15, the dependent claims are insufficient to integrate the claimed abstract ideas into a practical application or significant more. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15 AIA Claim s 1, 3, 5-6, 8, 10, 12-13, 15, 17, and 19-20 are rejected under 35 U.S.C. 102( a)(1)/(a)(2 ) as being anticipated by US 20130304385 A1, Gillette, II (hereinafter Gillette) . Regarding Claim 1, 8, and 15, Gillette discloses a computer-implemented method ( Gillette, [0112] The server 150 or user computing device 160 may include any number and type of processors to retrieve and execute instructions stored in the memory storage device of the server to control its functionality. The server 150 may include any type of conventional computer, computer system, computer network, computer workstation, minicomputer, mainframe computer, or computer processor, such as an integrated circuit microprocessor or microcontroller in accordance with the present invention), comprising: extracting, automatically (Gillette, [0106] The central server 150 may receive data from the sensor devices 110 in any desired manner. In some embodiments, the server 150 is configured to automatically request data from one or more of the sensor devices 110 via the network 140, gateway 130, and coordinator 120. Alternatively, the sensor device 110, coordinator 120, gateway 130, or any other device operating in conjunction with embodiments of the invention can be configured to automatically request and/or transmit data in any suitable manner. For example, each sensor device 110 may be configured to collect and send data measured from a monitored asset (such as an internal combustion engine or compressor) and automatically transmit such data to the coordinator 120 at periodic intervals (e.g., every 15 seconds)) and in real-time as measured data from elements of a natural gas liquids (NGL) network ( Gillette, [0037] a holding tank monitoring system can include a sensor device configured to receive total dissolved solids (TDS) data of a stored fluid from a TDS sensor in real-time. The TDS sensor can be located near an input of a holding tank storing the stored fluid. In addition, the TDS sensor data can be used to determine water production of a natural resource well. For example, predictive analysis can be used to determine expected remaining production of the well based in part on the water production. Moreover, a holding tank monitoring method can include receiving, by a sensor device, total dissolved solids (TDS) data of a stored fluid from a TDS sensor in real-time, determining water production of a natural resource well based on the TDS sensor data, and determining expected remaining production of the well using predictive analysis based in part on the water production), values for operating parameters (Gillette, Fig. 29, [0038] In accordance with various embodiments, a logistics system can comprise a plurality of sensor devices providing data, a capacity module, an identification module, and a processor. Each of the plurality of sensor devices can be in communication with an individual holding tank. Further, the data can include flow rate of the individual holding tanks, and where the data identifies the individual holding tank locations. The capacity module can be configured to determine the time remaining until each of the individual holding tanks reaches capacity based on the flow rate and remaining capacity of the individual holding tanks. In addition, the identification module can be configured to identify a fleet of tanker trucks for draining the individual holding tanks. Moreover, the processor can implement a mathematical model populated by the data, where the mathematical model can comprise an objective function for minimizing tanker truck driven miles and preventing the individual holding tanks from reaching capacity) and quality parameters ( Gillette, [0035] a quality monitoring method can include receiving, by a sensor device, total dissolved solids (TDS) data of a stored fluid from a TDS sensor in real-time; transmitting, by the sensor device); comparing the measured data against maximum limits ( Gillette, Fig. 26, [0035] the TDS data to a coordinator; and comparing the TDS data to a TDS threshold level. A quality monitoring system can comprise a sensor device configured to receive total dissolved solids (TDS) data of a stored fluid from a TDS sensor, and a coordinator configured to receive the TDS data from the sensor device); if the comparison indicated the measured data is within limit (Gillette, [0425] comparing the TDS data to a TDS threshold level): continuing normal operations ( Gillette, [0021] A device or system according to the invention has the ability to enter into a learning mode by plotting data over time in order to establish the standard operating parameters of the machine. To initiate the learning mode, the device or system is activated to capture data from the machine over a specified time period (e.g., 10 seconds-60 minutes). The captured data can then be analyzed to determine the normal operating condition of a particular machine or device, Gillette’s determination that the machine or device is operating under normal operating conditions teaches continuing normal operations because the system maintains operation when the measured data corresponds to established operating parameters rather than indicating an abnormal condition requiring corrective action ); and reporting performance ( Gillette, [0114] Any computer system may be configured (i.e., using appropriate security protocols) to communicate instructions, software upgrades, data, and other information with components via network 140. In some embodiments, data received from the sensor devices 110 is processed into a report and electronically provided (i.e., via email) to multiple users in a ubiquitous data format such as Portable Document Format (PDF). Such reports can be created at the request of a user or generated automatically at predetermined times or in response to the occurrence of an event (such as a detected problem with a monitored asset)); and if the comparison is not within limit; issuing an alert notification ( Gillette, [0018] By setting upper and/or lower limit values to the meaningful attribute data being monitored, e.g. frequency, amplitude, high-temperature threshold, low-temperature threshold, or another parameter, condition alarms/alerts can be generated when the data exceeds or drops below a limit): conducting an investigation via trending and root-cause analysis ( Gillette, Fig. 25, [0020] The shorter the interval between data measurements (frequent measurements), the more likely the plotted data can be used to predict behavior that may lead to impending equipment failure. By creating a histogram (charted data values over time) of the collected data, and applying data trend modeling algorithms, systems and methods of the invention can predict certain characteristics that could lead to imminent failure if left unchecked, such as bearing seizer leading to a broken or bent valve); and performing corrective and mitigation actions ( Gillette, Fig. 27, Fig. 28, [0019] The value of being able to closely monitor the state of, for example, vibration in this example enables either a user or the system to take evasive or corrective action, such as dispatching a service technician, shutting down the equipment, or lowering engine RPM, thereby averting a potential costly failure). Regarding Claim 3, 10, and 17, Gillette discloses The computer-implemented method of claim 1, wherein the alert notification includes email (Gillette, [0222] data received from the sensor devices 1510 can be processed into a report and electronically provided (i.e., via email) to multiple users in a ubiquitous data format such as Portable Document Format (PDF). Such reports can be created at the request of a user or generated automatically at predetermined times or in response to the occurrence of an event (such as a detected problem with a monitored asset)) or text messages, wherein the text messages include short message service (SMS), multimedia messaging service (MMS), and rich communication services (RCS). Regarding Claim 5, 12, and 19, Gillette discloses the computer-implemented method of claim 1, comprising providing an advisory with the alert notification ( Gillette, [0018] By setting upper and/or lower limit values to the meaningful attribute data being monitored, e.g. frequency, amplitude, high-temperature threshold, low-temperature threshold, or another parameter, condition alarms/alerts can be generated when the data exceeds or drops below a limit [0114] Any of the components can be configured to communicate with each other (or with other additional systems and devices) for any desired purpose. For example, the server 150 or user computing device 160 may be used to upload software to sensor device 110 or other component, provide or update encryption keys, and to perform diagnostics on any of the components in systems 100 or 300. Any computer system may be configured (i.e., using appropriate security protocols) to communicate instructions, software upgrades, data, and other information with components via network 140. In some embodiments, data received from the sensor devices 110 is processed into a report and electronically provided (i.e., via email) to multiple users in a ubiquitous data format such as Portable Document Format (PDF). Such reports can be created at the request of a user or generated automatically at predetermined times or in response to the occurrence of an event (such as a detected problem with a monitored asset)), wherein the advisory provides a proposed corrective action ( Gillette, Fig. 27, Fig. 28, [0019] The value of being able to closely monitor the state of, for example, vibration in this example enables either a user or the system to take evasive or corrective action, such as dispatching a service technician, shutting down the equipment, or lowering engine RPM, thereby averting a potential costly failure). Regarding Claim 6, 13, and 20, Gillette discloses the computer-implemented method of claim 1, wherein performing corrective and mitigation actions are automatically ( Gillette, Fig. 27, Fig. 28, [0019] The value of being able to closely monitor the state of, for example, vibration in this example enables either a user or the system to take evasive or corrective action, such as dispatching a service technician, shutting down the equipment, or lowering engine RPM, thereby averting a potential costly failure) performed by software algorithms ( Gillette, Fig. 29, [0039] Furthermore, in various embodiments, a logistics method can comprise receiving data from a plurality of sensor devices, wherein each of the plurality of sensor devices can be in communication with an individual holding tank, and wherein the data can comprise a flow rate of the individual holding tanks, and wherein the data identifies the individual holding tank locations; determining a remaining time period until each of the individual holding tanks reaches capacity based on the flow rate and a remaining capacity of the individual holding tanks; identifying a fleet of tanker trucks for draining the individual holding tanks; and using the data to populate a mathematical model that can comprise an objective function for minimizing tanker truck driven miles and preventing the individual holding tanks from reaching capacity) . Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-21-aia AIA Claim s 2,4,7,9,11,14,16 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over US 20130304385 A1, Gillette, II (hereinafter Gillette), and further in view of US 20230083389 A1, PITCHUMANI et al. (hereinafter Pitchumani) . Regarding Claim 2, 9, and 16, Gillette discloses the computer-implemented method of claim 1, wherein the operating parameters include flow, pressure, temperature ( Gillette, [0085] The sensor unit 250 measures characteristics related to an asset. The sensor unit 250 may be configured to measure any number of desired characteristics, such as temperature, pressure, flow, vibration, strain, electrical parameters (such as voltage, resistance, and current)), and level (Gillette, [0034] In various embodiments, a method of selective holding tank draining can comprise receiving, by a sensor device, TDS data of a stored fluid from a TDS sensor; receiving, by the sensor device, volume data of the stored fluid from a volume sensor; determining, by a central server, a selected TDS level for disposal of the stored fluid; calculating an average TDS level of a drained volume of the stored fluid if draining from two or more tanks; and determining a stored fluid volume to drain from each of the two or more tanks to achieve a drained mixture have less than the selected TDS level) and quality parameters include moisture (Gillette, [0085] atmospheric characteristics (such as moisture and gas content), sound, a chemical, radiation, position, force, movement, and/or any other measurable characteristic), salt (Gillette, [0240] the electrical conductivity meter can be configured to measure a salt solution percentage of the stored fluid), and BS&W (Gillette, [0404] (a) the volume of liquid in the tank, [0405] (b) the composition of any water in the tank, [0406] (c) the amount of total dissolve solids (TSD) in the tank, [0407] (d) the amount of any crude oil in the tank, and [0408] (e) the chemical composition of any crude oil in the tank. 66) Gillette does not disclose parameters that include H2S, CO2, methane, and ethane. However, Pitchumani teaches parameters that include H2S, CO2, methane and ethane (Pitchumani, [0113] Natural gas is a general term that may refer to mixtures of light hydrocarbons and optionally other gases (nitrogen, carbon dioxide, helium) derived from natural gas wells. The main component of natural gas is methane. In addition to methane, natural gas may comprise higher hydrocarbons, such as ethane , propane and butane. In some cases (small) amounts of heavier hydrocarbons may be comprised in the natural gas, often indicated as natural gas liquids or condensates. When produced together with oil, the natural gas may be referred to as associated gas. Other compounds that may be present as contaminants in natural gas in varying amounts include carbon dioxide, hydrogen sulphide, and aromatic compounds). Before the effective filing date of the claimed invention, It would have been obvious to one of ordinary skill in the art to combine Gillette and Pitchumani teaching because Pitchumani teaches monitoring and controlling natural gas processes in which the composition of natural gas includes methane, ethane, carbon dioxide, and hydrogen sulfide, while Gillette teaches monitoring and analyzing fluid quality parameters including moisture, salt, and water content, crude oil content, and chemical composition of stored fluids. A person of ordinary skill in the art would have been motivated to integrate the additional parameters taught by Pitchumani into Gillette’s monitoring framework in order to provide a more comprehensive characterization of hydrocarbon fluids and improve monitoring process. Regarding Claim 4, 11, and 18, Gillette discloses the computer-implemented method of claim 1, wherein the investigation via trending and root-cause analysis (Gillette, Fig. 25, [0020] The shorter the interval between data measurements (frequent measurements), the more likely the plotted data can be used to predict behavior that may lead to impending equipment failure. By creating a histogram (charted data values over time) of the collected data, and applying data trend modeling algorithms, systems and methods of the invention can predict certain characteristics that could lead to imminent failure if left unchecked, such as bearing seizer leading to a broken or bent valve ) is performed by an artificial intelligence algorithm. Gillette does not disclose performed by an artificial intelligence algorithm. However, Pitchumani teaches performed by an artificial intelligence algorithm (Pitchumani, [0222] some of the most appropriate techniques that can be applied are decision tree, linear regression, random forest, neural network and gradient boosting tree). Before the effective filing date of the claimed invention, It would have been obvious to one of ordinary skill in the art to combine Gillette and Pitchumani teaching because Pitchumani teaches the use of artificial intelligence including decision trees, neural networks, and linear regression. A person of ordinary skill in the art would have integrated the artificial intelligence techniques taught by Pitchumani into Gillette’s framework in order to improve predictive analytics. Regarding Claim 7 and 14, Gillette discloses the computer-implemented method of claim 1, wherein corrective and mitigation actions (Gillette, [0019] The value of being able to closely monitor the state of, for example, vibration in this example enables either a user or the system to take evasive or corrective action, such as dispatching a service technician, shutting down the equipment, or lowering engine RPM, thereby averting a potential costly failure [0085] The sensor unit 250 measures characteristics related to an asset. The sensor unit 250 may be configured to measure any number of desired characteristics, such as temperature, pressure, flow, vibration, strain, electrical parameters (such as voltage, resistance, and current), atmospheric characteristics (such as moisture and gas content), sound, a chemical, radiation, position, force, movement, and/or any other measurable characteristic, [0272] the server 1550 may issue a command to control, reconfigure, and/or update a software application operating on the gateway 1530, coordinator 1520, and/or sensor device 1510). Gillette does not disclose include increasing operating temperature, opening valves, increasing pressure, and methanol injection However, Pitchumani teaches include increasing operating temperature, opening valves ( Pitchumani, [0145] The valve 178 allows to control the flow rate of the liquefied ethane 176. The liquefied ethane can be combined with the stream of liquefied methane 150, to allow additional control of the temperature, composition and/or heating value of the LNG 160), increasing pressure (Pitchumani, [0277] FIG. 17 shows an example of the behavior of the controller over time (horizontal axis), for instance during a day, when AP-MCHE 650 was exceeding a safety threshold 652 longer than a predetermined time period. In FIG. 17, the top panel indicates LNG throughput 660, the mid-panel indicates refrigerant pressure drop 650 over the shell side of the main heat exchanger 22 (AP-MCHE), and the lower panel indicates power demand 670 by the refrigerant compressor (for instance compressor 80, or the combination of compressors 80 and 82). The horizontal line 652 in the mid-panel indicates a predetermined upper limit of ΔP-.sub.MCHE. When the constraint limit 652 for ΔP.sub.MCHE is exceeded, indicated by pressure peak 654, power demand 670 for the compressor increases, leading to power spike 672), and methanol injection (Pitchumani, [0156] One or more of streams 262 may, at least partly, be reinjected in the process stream 46 to be provided to the main heat exchanger 22 for condensation and liquefaction. Thus, in the example of FIG. 2, the composition of the process stream is conditioned before the process stream enters the main heat exchanger 22, instead of thereafter as in the example of FIG. 1 [0157] An additional separator 280 may be arranged in the flow path of the process stream, to control the methane content of the process stream 46) Before the effective filing date of the claimed invention, It would have been obvious to one of ordinary skill in the art to combine Gillette and Pitchumani teaching because Pitchumani teaches specific corrective and mitigation actions for controlling natural gas processes, including temperature, valve, pressure, and methane control. A person of ordinary skill in the art would have been motivated to integrate the process control actions taught by Pitchumani into Gillette’s monitoring and control framework in order to automatically respond to deterring operating conditions and improve performance while maintain operation within desired limits. Pertinent Prior Art The prior art made of record and not relied upon is considered pertinent to applicant’s disclose: -US 20210404858 A1, describing monitoring systems for fluid meter sets that utilize sensors(e.g., vibration, pressure, and oil condition sensors) to collect operational data, detect abnormal conditions such as leaks or systems failures based on the sensed data and generate alarm signals or responses for addressing the detecting conditions. -US 20140167969 A1 , describing systems and methods for monitoring conditions within a structure using sensor data, determining whether sensed data exceeds a threshold, and providing notifications or alerts when the threshold is exceeded, wherein sensed data is received from one or more sensors and processed to determine conditions and initiate responsive actions such as evacuation notification. -US 9613521 B2 , describing systems and methods for disseminating emergency notification content based on data received from one or more sensors configured to detect environmental conditions, wherein the sensed data is analyzed to determine whether a condition exceeds a threshold and in response an alert or notification is generated and transmitted to an intended audience, thereby providing responsive actions based on the monitored data. -US 10697947 B1, describing systems and methods for monitoring and detecting pollution and fugitive emissions at oil and gas facilities using one or more sensors configured to measure environmental parameters, wherein sensed data is analyzed to detect abnormal conditions, compare pollutant levels, and generate reports or alerts for initiating corrective actions to mitigate emissions. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to IBRAHIM NAGI SHOHATEE whose telephone number is (571)272-6612. The examiner can normally be reached 8am-5pm. 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, Shelby Turner can be reached at (571) 272-6334. 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. /IBRAHIM NAGI SHOHATEE/Examiner, Art Unit 2857 /SHELBY A TURNER/Supervisory Patent Examiner, Art Unit 2857
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