Patent ID: 12190281

In the appended figures, similar components and/or features may have the same numerical reference label. Further, various components of the same type may be distinguished by following the reference label with a letter. If only the first numerical reference label is used in the specification, the description is applicable to any one of the similar components and/or features having the same first numerical reference label irrespective of the suffix.

DETAILED DESCRIPTION

Illustrative configurations are described with reference to the accompanying drawings. Wherever convenient, the same reference numbers are used throughout the drawings to refer to the same or like parts. While examples and features of disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the spirit and scope of the disclosed configurations. It is intended that the following detailed description be considered as exemplary only, with the true scope and spirit being indicated by the following claims.

It should be noted that the following description is related to characteristic-vectors merchant in a supply-chain. As mentioned earlier, the supply-chain in a market is a network of individuals, organizations, resources, activities, and technology, in which raw materials are converted to finished products delivered to a customer. However, the growth of the market has led to an increase in the visibility of gaps in the supply-chain. For example, digital commodities such as sensor data generated with or without operator intervention, for reporting of a regulation-mandated emission inventory, may be missed, or may not be reported, thereby creating a gap in tracking emissions between components involved in the supply-chain. Therefore, it is necessary to track the flow of commodities, to ensure integrity in the supply-chain.

A supply-chain characteristic-vectors method, and a supply-chain characteristic-vectors merchandising system are disclosed. Referring toFIG.1illustrating a schematic view100of an oil and gas supply-chain102. The oil and gas supply-chain102may include at least one upstream amenity, such as crude oil producing facility104a, and a natural gas facility104b(hereinafter collectively referred to as upstream amenity104), a midstream amenity, such as an oil processing plant106a, a natural gas processing plant106b, a refinery106c(hereinafter collectively referred to as midstream amenity106), and a downstream amenity such as a gas storage facility108a, or a households108b(hereinafter collectively referred to as downstream amenity108and a facility may be referred to as an amenity site).

The upstream amenity104, the midstream amenity106, and the downstream amenity108may be physically interconnected using at least one communication pathways, such as a road transport network110a, a rail transport network110b, and a pipeline network110c(hereinafter collectively referred to as communication pathways110). For example, with continued reference toFIG.1, the crude oil producing facility104amay be connected to the oil processing plant106aby pipeline network110c, and further connected to the natural gas processing plant106busing another branch of the pipeline network110c. Similarly, the natural gas processing plant106bmay be connected to the gas storage facility108avia the road transport network110a.

Referring now toFIG.2illustrating an exemplary layout200of the upstream amenity104. The upstream amenity104may include at least one air quality monitors202a,202b(hereinafter collectively referred to as air quality monitor202), at least one pumpjack204a,204b(hereinafter collectively referred to as pumpjacks204). The pumpjacks204may be fluidically coupled to a chemical tank206, a production tank208, a separator unit210, and/or a compressor212. Various systems assembled in the upstream amenity104may be tasked with the production of crude oil, or natural gas, which may be later refined in the refinery106cand further transported using communication pathways110to the gas storage facility108ain the downstream amenity108. Any airborne pollutants, or gases, and composition thereof in the atmosphere, produced in the oil and gas supply-chain102may be sensed by the air quality monitor202. The air quality monitor202may be installed throughout the oil and gas supply-chain102, i.e., the upstream amenity104, the midstream amenity106, and the downstream amenity108.

Now referring toFIG.3illustrating a perspective view300of the air quality monitor202. The air quality monitor202may be capable of measuring a target compound and at least one environmental parameter (e.g., a weather condition) in a collocated and contemporaneous manner. The measurement function of the air quality monitor202may be performed by the compound sensor or gaseous sensors embedded therein. These sensor(s) are point sensors, which means that their function is to measure a particular physical-chemical property of the target compounds to distinguish them from background atmospheric composition. Targeted compounds may include but are not limited to gases and aerosols emitted by industrial, anthropogenic, or natural activities. In particular, one configuration focuses on hydrocarbons and other greenhouse gases that absorb energy from radiation in the mid-IR region of the electromagnetic (EM) spectrum with a wavelength between 1 um and 5 um.

In one configuration, with continued reference toFIG.3, the air quality monitor202may be operated using a solar power system302. The solar power system302may be designed to provide sufficient power to the various other subsystems and to provide sufficient reserves and capacity to ensure the proper functioning of the air quality monitor202in most environmental conditions present in the field. The solar power system302may be replaced by wind-based or gas-based power generation or any other form of compact power generation system if the conditions warrant it. For instance, at high latitudes, wind-based power generation may be preferable to solar on account of low insolation.

With continued reference toFIG.3, the compound sensors or the gaseous sensors may be placed, or housed in an enclosure304. The enclosure304may be configured to protect the system from environmental hazards, or any tampering from unknown sources. Hazards may include but are not limited to precipitation, moisture, surface water and flooding, high temperature and insolation, low temperature, high wind, storms, hurricanes, typhoons, tornadoes, lightning, external impact and vibration, robbery, defacement, damage, earthquakes, light or electromagnetic interference, foreign agents or fauna and flora disturbance or intrusion. The enclosure304may also be highly visible by day and reflective at night to avoid accidental damage. The enclosure304may be directly on the ground, mounted on a foundation, or pole mounted.

In another configuration, with continued reference toFIG.3, sensor data corresponding to the compound gases sensed by the air quality monitor202may be transmitted to a remote location, using a communication module (not shown in the figure). The communication protocol may be wired as in a Supervisory Control and Data Acquisition system (referred to herein as a SCADA system) or wireless using Bluetooth®, Wi-Fi, LoRa, cellular, satellite, other radiofrequency, optical line of sight, or other wireless data-transmission protocol. If a wireless protocol is employed, the data may be relayed using a communication antenna306, if appropriate. In general, a communication system, which may include a communication antenna306, has a role that may include the communication of the measurement to a remote or centralized node and the receipt of communication related to settings and operations changes or firmware updates. The communication system may be used to relay messages to and from other air quality monitor202such as in a daisy chain, star, or mesh configuration to reduce the communication cost when relying on external communication infrastructure such as cellular or satellite communication networks.

Referring toFIG.4illustrating a system layout400of the air quality monitoring system414provided with representative components that may be included therein. The air quality monitoring system414may include an air quality data processing module406, air quality monitors202(illustrated as air quality monitors202a,202b, and202cin the figure), reference monitors402, and environmental monitors404. The air quality monitors202may include at least one chemical sensor configured to detect and measure chemicals such as ozone, nitrogen oxide, carbon dioxide, sulfur dioxide, volatile organic compounds, methane or other hydrocarbons and other chemicals in gaseous state (herein described as “gaseous chemicals”). The air quality monitors202may also include at least one particle sensor configured to detect and measure the presence of suspended particles in the air such as dust, smoke, pollen, or soot (herein collectively described as “particulate matter” or “PM”). With reference toFIG.2, the air quality monitor202may be located at multiple different locations within the upstream amenity104, such that measurements related to the gaseous chemicals may be measured within the upstream amenity104.

In one configuration, the reference monitors402may include precision gaseous chemical sensors configured to provide measurements for use in calibrating the gaseous sensors in the air quality monitor202. Further, the environmental monitors404may be configured to measure environmental conditions such as humidity, atmospheric temperature, atmospheric pressure, air density, ambient light, geographic location, wind speed and direction, and the like. In another configuration, the air quality data processing module406may be configured to communicate with the air quality monitor202, and reference monitors402. For example, air quality data processing module406may receive data from these monitors such as measurements related to the concentration of various particulates in the atmosphere. The air quality data processing module406may also transmit data to these monitors as calibration data, to generate or calculate cross-calibration factors. The air quality data processing module406may correct measurements from the air quality monitor202using the generated cross-calibration factors. Air quality data processing module406may be also configured to process the data from monitors and perform analysis to calculate or infer additional air quality data such as the amount of various gaseous chemicals in various locations, sources of those gaseous chemicals, and recommendations based on elicited requirements or preferences of end users. Air quality data processing module406may be configured to communicate with, computing devices408a, and mobile devices408b, to receive data and provide received, calculated, and inferred air quality data. For example, air quality data processing module406may receive user-input data and use that data to derive additional air quality data relevant to the area of analysis. Air quality data processing module406may also be configured to communicate with other sources of data such as reporting system410and weather station412. Air quality data processing module406may be implemented in any appropriate physical or virtual computing platform such as a networked server and may operate and act through any suitable interface such as a cloud computing platform.

In another configuration, the air quality monitoring system414may also be configured to process incoming data to provide a variety of outputs. For example, air quality monitoring system414may analyze measurements from the air quality monitor202to determine the sources of the gaseous chemicals being detected. Air quality monitoring system414may provide actionable steps to affect the chemical sources such as ways to reduce the release of those chemicals or ways to minimize exposure to those chemicals. It may do so by making use of stated preferences or user requirements and/or ancillary (e.g., topological, geological, meteorological, or demographic) datasets relevant to the area of investigation.

Referring toFIG.5illustrating another layout500of an example air quality monitor202provided with representative components that may be included therein. The air quality monitor202may include a processing module504, memory506, communication module508, and at least one gaseous chemical sensor such as chemical sensor510aor510b(hereinafter collectively referred to as “chemical sensors510”), and environmental sensor512. Processing module504may be configured to perform computing tasks and controls other components. For example, one of the computing tasks may include calibration. Memory506may be configured to store data such as measurement data from chemical sensors510and calibration data such as cross-calibration factors. Chemical sensors510are configured to measure gaseous substance or chemicals and airborne particulates, or airborne pollutants in analyte gas (sometime simply referred to herein as target substances). Environmental sensor512measures environmental conditions such as temperature, pressure, humidity, location, wind speed, and the like. Communication module508handles communication with other devices. For example, communication module508may handle communication between air quality monitor202and air quality data processing module406ofFIG.4, other air quality monitors, user devices such as mobile devices408band computing devices408a,408c, and the like. The communication module508may communicate through any of a variety of wired and wireless mechanisms such as Wi-Fi, Bluetooth, mobile networks, long-range radio, satellite, and the like. Air quality monitor202may also be configured to measure time, position, and other relevant information for computing devices. The components, functionality, and configuration of the sensor can be selected based on desired monitoring capabilities. At least one air quality monitor202may also measure a set of individual atmospheric readings. The set of individual atmospheric readings may include at least one of the following: barometric pressure, air temperature, or humidity level.

In another configuration, the individual atmospheric readings at the upstream amenity104may be one of the set of environmental parameters from a set of environmental parameters (hereinafter referred to as set of upstream environmental parameters). The set of upstream environmental parameters may further include air quality index, biodiversity, hydrology parameters such as sediment transport and deposition, the intensity of solar radiation, and photosynthetically active radiation.

Referring toFIG.6illustrating a schematic view600of at least one device deployed at the upstream amenity104may be illustrated. The at least one device may include pressure sensors602, flow sensors604, temperature sensors606, level sensors608, and other discrete sensors610. The at least one device may be installed at the upstream amenity104, as illustrated byFIG.2. Again, referring toFIG.6and by way of an example, the pressure sensor602may include pressure switches, piezoelectric sensors, manometers, and the like. The pressure sensors may be deployed at a compressor or a wellhead pressure head and may be configured to generate a signal in response to the pressure of a fluid maintained in the aforementioned units. Similarly, flow sensors604, temperature sensors606, level sensors608, and other discrete sensors610may be configured to generate electric signals representative of the flow rate, temperature, level, and other parameters of the oil and/or gas, respectively. These parameters may be represented as set of physical parameters of the upstream amenity104(hereinafter referred to as set of upstream physical parameters).

Referring toFIG.7illustrating a side view700of the operation of a pumpjack204. The pumpjack204may include a motor708, a gearbox704, a walking beam706, a horse head710, a bridle716, a pump712, and a piston714positioned in the pump712. The pumpjack204may be connected to a control unit702. Further, the control unit702may include a user interface and a display. A site operator may access the user interface to manually adjust the operation of the pumpjack204. The operation of the pumpjack204may include output from the motor708, which may drive the gearbox704. Driving the gearbox704may further actuate the walking beam706. As illustrated byFIG.7, the horse head710may be connected to the walking beam706. Further, the bridle716may be extended from the horse head710, and bridle716may be connected to the pump712. Actuation of the walking beam706may further oscillate the horse head710in a vertical direction, thereby operating the pump712such that the piston714in the pump712may oscillate in tandem with the horse head. The actuation of the piston714may lift or excavate the emulsion from the oil well. The control unit702may be configured to control the operation of the pumpjack204via, for example, the output of the motor708, the gear ratio and output speed from the gearbox704, or the actuation speed of the walking beam706, which may further impact the oscillation speed of the horse head710, the bridle716and the pump712. Operational parameters such as speed (in RPM or meters/second) and frequency (cycles per second) may be acquired as set of upstream operational parameters. Further, a peak load on the walking beam706, a depth at which the pump712may be drilled into the oil well, and the diameter of the piston714may be included in the set of upstream operational parameters (either singular or a plurality thereof simply referred to herein as a set of upstream operational parameters).

Now referring toFIG.8, illustrating a side view800of an emission plume emitted from the pumpjack204,FIG.9illustrating a top view900of an emission plume emitted from the pumpjack204, andFIG.10illustrating a top view1000of an emission plume emitted from one or more pumpjack204.

With continued reference toFIGS.8-9, during drilling of the crude oil from an oil well, the pumpjack204may be operated in a manner explained in conjunction withFIG.7. Further, during operation, the pumpjack204may be configured to emit a gaseous plume802. The gaseous plume802may include gaseous chemicals, which may be sensed by the air quality monitor202. The air quality monitor202may be configured to generate a concentration signal representative of concentrations of particulate matter present in the gaseous plume802. The concentration signal may also be included in the set of upstream environmental parameters.

With continued reference toFIG.10, the upstream amenity104may include multiple potential emission sources from at least one pumpjack204a, and204b. Further, the upstream amenity104may include the air quality monitor202. In the scenario depicted inFIG.10, a target compound may be emitted from the pumpjack204aand may form an emission plume1002a. Similarly, another, or the same target compound may be emitted from the pumpjack204band may form another emission plume1002b. The emission plume1002amay be obstructed by the emission plume1002b, thereby forming a mixed emission plume1004. Therefore, for such a scenario, a confounding signal may be generated from each of the air quality monitors202, which may be representative of the concentration of one or more gaseous chemicals. The confounding signal may be later processed, and individual concentration profiles of each of the gaseous chemicals may also be obtained and included in the set of upstream environmental parameters.

Referring now toFIG.11illustrating an architecture1100of a supervisory-control-and-data-acquisition system (hereinafter referred to as SCADA system) connected to the upstream amenity104. In one configuration, the SCADA system may include an upstream SCADA system1102connected to the enclosure304and the at least one device deployed on the upstream amenity104. The upstream amenity104may include an input/output module1116. In an exemplary configuration, at least one device may include at least one sensor1104, at least one control valve1106, at least one solenoid1108, at least one alarm1110, and at least one discrete sensor1112. The at least one sensor1104may be configured to sense and determine one or more operational parameters of the one or more devices and may further transmit the operational parameters to an input/output module1116. Further, the upstream SCADA system1102may be connected to the output module1116. The input/output module1116may be further connected to the air quality monitor202via a master communication module1118. The master communication module1118may be further connected to the slave communication modules1114a, and1114b. Further, the slave communication modules1114a, and1114bmay be connected to a master communication units of other air quality monitors (not shown in the figure) positioned on upstream amenity104. Similarly, the upstream SCADA system1102may be configured to acquire concentration signals from the other air quality monitors202via the slave communication modules1114aand1114b.

The air quality monitor202may be configured to create historical data related to emissions given the topology of the upstream amenity104and may be configured to transmit the historical data to the input/output module1116. The upstream SCADA system1102may be configured to acquire both the historical data of the air quality monitor202, from the input/output module1116as a set of upstream environmental parameters. Further, each output from at least one device including at least one sensor1104, at least one control valve1106, at least one solenoid1108, at least one alarm1110, and the at least one discrete sensor1112may be transmitted to the input/output module1116. Further the upstream SCADA system1102may be configured to obtain the output from at least one device as an operational parameter. The operational parameter obtained by the upstream SCADA system1102may correspond to the upstream amenity104, and hence, may be included in the set of upstream operational parameters.

The upstream SCADA system1102may be configured to obtain a set of upstream physical parameters at the upstream amenity104. The set of upstream physical parameters may include a geological location of the installation site of the upstream amenity. Geological surveys may be conducted using various means from testing subsoil for onshore exploration to using seismic imaging for offshore exploration. Based on the survey, the geological location may be finalized for the installation of the upstream amenity104. Also, based on the energy reserves, energy companies compete for access to mineral rights granted by governments by either entering a concession agreement, as any discovered oil and gas are the property of the producers or a production-sharing agreement. Therefore, information corresponding to a landowner of the site may be obtained by the upstream SCADA system1102. Especially when the landowner may belong to the marginalized faction, various government initiatives have been undertaken to boost welfare for the marginalized faction, so that domestic production may also be boosted thereby reducing dependency on oil offshore locations. In some implementations, the landowner of the amenity site may be associated with, part of, characterized, etc. by other means such as (but not limited to) marginalized faction, race profile, location, procurement impact, processing impact, transportation means, transportation duration, term of land ownership, original land title lineage, proceeds usage/pledges, or any variable of similar identifying attributes (characteristic-vectors).

Referring toFIG.12illustrating a process layout1200of the oil and gas supply-chain102. The upstream amenity104may be connected to at least one pre-processing unit (referred to as pre-processing unit1304inFIG.13), which may be a part of the midstream amenity106. The pre-processing unit may include processing plants such as refinery106c. The upstream amenity104may be configured to transmit the crude oil to the pre-processing unit in the midstream amenity106, via the communication pathways110. The volumetric flow rate, and the pressure at which the crude oil may be transmitted to the downstream amenity108, may be obtained as upstream physical parameters. After obtaining the crude oil from the upstream amenity104, the pre-processing unit may be configured to gather and refine to initiate transportation of the crude oil to the downstream amenity108through the communication pathways110. The process of transfer of the crude oil to downstream amenity108may be illustrated in detail, in conjunction withFIGS.13-18.

Referring now toFIG.13, illustrating a transmission layout1300of the oil and gas supply-chain102from the upstream amenity104to the downstream amenity108. As explained earlier, and by way of an example, the upstream amenity104and the downstream amenity108may be connected by the communication pathways110. Referring back toFIG.13, crude oil may be extracted from a plurality of oil wells1302a,1302b, and1302c(hereinafter referred to as oil wells1302) in the upstream amenity104. The crude oil may be excavated from the using one or more pumpjack204, the process of which is already illustrated byFIG.7. Now, the crude oil may be collected by the pre-processing unit1304of midstream amenity106, and which, as illustrated earlier, may be configured to process and refine the crude oil into natural gas, or refined gas (hereinafter referred to as processed oil), to the downstream amenity108. Further, the processed oil may be transported through communication paths a1, b1, c1, c2 h2, and h4, which may be designated as the communication pathways110, to the downstream amenity108. However, it must be noted that based on the topological, economical, and environmental factors, the communication path a1, b1, c1, c2 h2, and h4 may be designed. As illustrated in the figure, each communication path may be formed between compressor stations A-B-C-D-E-F-G-H. Such as communication path a1 may be designed between compressor stations A and B, and communication path b1 may be designed between compressor stations B-C. It must be noted that the communication pathways110may not be limited to the communication paths a1, b1, c1, c2 h2, and h4, but may include more communication paths based on the location at which the downstream amenity108may be installed.

In an exemplary configuration, communication paths a1, b1, c1, c2 h2, h4 may include any one of the road transport network110a, rail transport network110b, or the pipeline network110c(refer toFIG.1). Again, referring toFIG.13, the compressor stations A-B-C-D-E-F-G-H may include a turbine, a motor, or a stationary engine. Processed oil may be transmitted through the communication paths a1, b1, c1, c2 h2, and h4, under high pressure to ensure mobility throughout the pipeline network110c. Therefore, the compressor stations A-B-C-D-E-F-G-H may be fluidically connected to, or stationed along, the communication paths a1, b1, c1, c2 h2, h4, such that transmission of the processed oil may be maintained under uniform pressure. Sometimes herein, the communication paths may be referred to as one or more of an energy supply pipeline.

In an exemplary configuration, with continuous reference toFIG.13, 6 metric tons (mT) of the processed oil from the pre-processing unit1304may be received at the compressor station A, which may be transferred to the compressor station B which may be situated at 200 miles from compressor station A. Further, as demanded by downstream amenities, from the compression station B, a portion of the processed oil (2 mT) may be diverted through communication path h1 to the compressor station H, and the remaining portion of the processed oil may be transmitted to the compression station C through the communication path b1. The demand of the downstream amenities may be best illustrated in the scenario, in which a demand for crude oil may be requested by a delivery station1306a. For example, when the delivery station1306a, based in Chicago, submits a demand of 1 metric ton of processed oil gas, the nearby compression station C may be configured to transmit the requisite demand from the processed oil received from the compressor station B to the delivery station1306athrough the communication path c2, and the remaining processed oil may be transmitted to a delivery station1306b, which may be stationed at Denver.

In one configuration, from initiation to delivery, and through transmission, the processed oil may be categorized and measured in terms of energy units, for example, MMBtu, which is a British thermal unit for defining the energy content of the processed gas. The crude oil extracted at the upstream amenity104may be measured in terms of upstream energy amount. For example, if 2 million gallons of crude oil may be extracted at the upstream amenity104, the upstream energy amount for the 2 million gallons of crude oil may range between 2,80,000 MMBtus to 3,00,000 MMBtus. This upstream energy amount may be acquired as the operational parameters by the upstream SCADA system1102.

However, the inclusion of such entities in the oil and gas supply-chain102may result in missing out on process parameters. For example, parameters corresponding to the gathering, boosting, and initiating transportation may be inevitably missed, or may not be recorded manually or automatically due to the processing of a large pool of data and information from the oil and gas supply-chain102.

In addition to missing data, some circumstances may also occur due to faults, or any anomalies occurring in the pipeline network110c. Circumstances such as line pack, commonly known as the phenomenon of storage of gas in the pipeline network110c, or malfunctioning of the compressor stations may cause temporal delays in the delivery of the processed oil to the downstream amenity108. Also, during transmission, due to leaks or damage in the communication pathways110may reduce pressure, or affect the flow rate of the processed oil through the communication pathways110. Such scenarios may reduce the integrity and data transparency of the oil and gas supply-chain102, thereby forming a genesis for efficient tracking of the processed oil throughout the oil and gas supply-chain102.

Therefore, to track the processed oil through each of the devices stationed in the oil and gas supply-chain102, a communication architecture may be installed throughout the upstream amenity104, the midstream amenity106, and the downstream amenity108. Now, referring toFIG.14illustrating a communication architecture1400installed at the communication pathways110. A communication module may be installed at each of the entities1402a-1402fstationed along the communication pathways110. The entities1402a-1402fmay include compressor stations, various sensors configured to sense flow rate or energy units associated with the processed oil transmitted through the communication pathways110. Iteratively, over a predefined time period, the entities1402a-1402fmay be configured to provide the midstream amenity physical parameters, such as the flow rate of the processed oil, or the pressure at which the processed oil may be transmitted. This set of process parameters may be communicated wirelessly, or through a hard-wired connection, to another SCADA system, which may be illustrated later in conjunction withFIG.15.

Now referring toFIG.15illustrating a communication architecture1500of a SCADA system connected with the communication pathways. In this configuration, the communication pathways110may be connected to another SCADA system, preferably a midstream SCADA system1502. Particularly, each of the entities1402may be connected to the midstream SCADA system1502. In another configuration, each of the entities1402may be connected to at least one data collection units1504a,1504b, and1504c(hereinafter referred to as data collection units1504), such as a Remote Terminal Units (RTUs) or a Programmable Logic Controllers (PLCs). The data collection units1504associated with entities1402may be configured to collect process parameters such as pressure, temperature, flow rate, and the like. As illustrated inFIG.15, the data collection units1504may also be connected to the pipeline network110c. In an exemplary configuration, the data collection units1504may be configured to accumulate and compile the process parameters as a set of midstream operational parameters, such as rate of flow of the processed oil, pressure at which the processed oil may be transmitted through pipeline network110c, the temperature of the processed oil in the pipeline network110c, and the like. The data collection units1504may also be configured to accumulate and compile a set of midstream operational parameters such as rate of flow of the processed oil, and the pressure at which the processed oil may be received at entities1402. The data collection units1504may be further connected to the midstream SCADA system1502via a satellite communication1506, through which the set of midstream operational parameters related to the pipeline network110cand the entities1402may be transmitted from the data collection units1504to the midstream SCADA system1502. Using the communication architecture illustrated inFIG.15, even a set of physical parameters from the pipeline network110cmay be easily obtained and processed, especially in scenarios such as locations in which immediate human intervention may be required, but accessibility to those locations may be limited. In another configuration, processed oil transmitted through the midstream amenity106communication pathways110may be measured in terms of midstream energy amount. For example, if 0.5 million gallons of processed oil may be transmitted through the midstream amenity106and the communication pathways110, the midstream energy amount for the 0.5 million gallons of processed oil may range between 168000 MMBtus to 180000 MMBtus. This midstream energy amount may be acquired as the operational parameter by the midstream SCADA system1502.

As discussed earlier, scenarios involving line pack delays or leaks may result in affecting the set of midstream physical parameters. For example, the pipeline involved in the leak may reduce the volumetric flow rate, and pressure at which the processed oil may be transmitted through the pipeline network110c. Also, factors such as the presence of uncontained water, or liquid petroleum in the gas supply may alter, or vary the compressibility of the processed oil during transmission. Also, leaks in the pipeline may affect the surrounding land, thereby disturbing the surrounding environment at which the pipeline network110cmay be installed. Therefore, a scarred land may be formed. These factors, such as rate of leaks, area or a predefined scarred land, variation of pressure, and volumetric flow rate, may be included in the set of midstream physical parameters, which may also be obtained by midstream SCADA system1502.

In another configuration, the midstream amenity106may also include air quality monitor202(refer toFIG.2). The air quality monitor202may be configured to sense a midstream environmental parameter such as individual atmospheric readings of the midstream amenity106, or emissions occurring at the midstream amenity106. Further, the midstream SCADA system1502may be configured to collect other environmental parameters such as air quality index, biodiversity, hydrology parameters such as sediment transport and deposition, and the like, to form a set of midstream environmental parameters.

Referring toFIG.16illustrating a layout1600of a communication architecture between multiple SCADAs, the midstream amenity106, and the downstream amenity108. The midstream SCADA system1502may be connected to the midstream amenity106, and as explained earlier, may be further connected to the communication pathways110. Similarly, the downstream amenity108may be connected to a downstream SCADA system1602. The downstream SCADA system1602may operate in a similar mechanism as the upstream SCADA system1102and the midstream SCADA system1502, i.e., the downstream SCADA system1602may be configured to obtain operational parameters related to at least one device in the downstream amenity108, which may include but not limited to a volumetric capacity of the gas storage units, industrial units, commercial complexes, or households; in addition to flow rate of the processed oil, the pressure of the processed oil received at the downstream amenity108, and the like. The processed oil transmitted at the downstream amenity108may be measured in terms of downstream energy amount. For example, if 12 gallons of processed oil may be delivered at the downstream amenity108, the downstream energy amount for the 12 gallons of processed oil may range between 67000 MMBtus to 80000 MMBtus. This downstream energy amount may be acquired as the operational parameter by the downstream SCADA system1602.

The downstream SCADA system1602may be configured to sense, and obtain the set of downstream environmental parameters, as well as the set of downstream physical parameters. The set of downstream environmental parameters may correspond to the concentration of gas, in the atmosphere, and individual atmospheric readings at the downstream amenity108, such as barometric pressure, temperature, humidity, temperature, atmospheric pressure, air density, ambient light, geographic location, wind speed, and direction. Further, the downstream SCADA system1602may also be configured to obtain the set of downstream physical parameters similar to the upstream SCADA system1102of the upstream amenity104, i.e., a volumetric flow rate and pressure at which the processed oil may be received at the downstream amenity108, as well as the information of landowner at which the downstream amenity108may be installed.

Referring now toFIG.17illustrating a layout1700of a networked SCADA system. The upstream SCADA system1102, the midstream SCADA system1502, and the downstream SCADA system1602may be configured as a networked SCADA system. Networked SCADA systems may be configured to allow access to the set of environmental parameters, the set of physical parameters, and the set of operational parameters from each of the upstream amenity104, midstream amenity106, downstream amenity108, and communication pathways110. Further, the transmission of data related to environmental, physical, and operational parameters from all the amenities may be achieved through widespread network architecture, which may include, but is not limited to, a local area network (LAN), a wide area network (WAN), or a combination of networks. The widespread network architecture may be implemented with hardware (e.g., silicon chipsets, antenna), software (e.g., protocol stacks, applications), or a combination thereof. In some scenarios, the oil and gas supply-chain102, the midstream amenity106, the downstream amenity108, and the communication pathways110may include more than one communication units to support different interfaces, protocols, and or communication standards with different devices and or network nodes.

Again referring toFIG.17, using the widespread network architecture, the upstream SCADA system1102, the midstream SCADA system1502, and the downstream SCADA system1602may be connected to a central SCADA system1702. The central SCADA system1702may be configured to obtain environmental, physical, and operational parameters associated with upstream amenity104, the midstream amenity106, and the downstream amenity108. Further, the environmental, physical, and operational parameters associated with the amenities may comply, with or be aggregated by the central SCADA system1702, and further transmitted to a remote server1704, using the widespread network architecture. The remote server1704may be installed onsite of the upstream amenity104, the midstream amenity106, and the downstream amenity108.

Referring now toFIG.18illustrating a layout1800of an overall communication architecture of the oil and gas supply-chain102. Sensing units1816aand1816b, which may or may not be the same as air quality monitor202described inFIG.2, may incorporate components such as a power system1820, weather sensors1826, compound sensors1828, a computing unit1824and a communication unit1822. Sensing unit1816amay relay sensor data to centralized computing unit1802using a network layer. The network layer may rely on existing communication infrastructure such as cellular or satellite, or it might use dedicated infrastructure such as custom wired or wireless systems including but not limited to Wi-Fi, Bluetooth, LoRa, and other telemetry and data-transmission systems. The data transmission may rely on other network infrastructures such as the internet or dedicated networks such as intranet or LAN.

Once data reaches centralized computing unit1802, processing may be performed to transform raw data into actionable data. To transform the raw compound measurements into speciation and concentrations, an external database1816such as the HiTRAN database may be queried for reference spectra of the target gas.

The centralized computing unit1802may be connected to the remote server1704. The centralized computing unit1802may be configured to obtain the set of environmental parameters, the set of operational parameters, and the set of physical parameters associated with the upstream amenity104, the midstream amenity106, the downstream amenity108, and the communication pathways110from the remote server1704. Once received, the centralized computing unit1802may be configured to execute a set of instructions, to generate a set of environmental characteristic-vectors, the set of operational characteristic-vectors, and the set of physical characteristic-vectors. Characteristic-vectors herein may be defined as data related to attributes, or inherent characteristics estimated by evaluating historical parameters, i.e., previously recorded parameters related to environment, machinery, or anomalies, averaged over a predefined time period which may be stored in remote server1704.

The centralized computing unit1802may be configured to obtain the set of environmental parameters, the set of operational parameters, and the set of physical parameters associated with the upstream amenity104, the midstream amenity106, the downstream amenity108, and the communication pathways110from the remote server1704iteratively, over a predefined time period. The set of environmental parameters, the set of operational parameters, and the set of physical parameters may be transmitted in batches corresponding to days, months, and years. For example, environmental characteristic-vectors may be calculated by analyzing historical data on the set of environmental parameters, such as emissions occurring over a predefined time period in the upstream amenity104, the midstream amenity106, and the downstream amenity108. The environmental characteristic-vectors may represent trends of the set of environmental parameters, or frequency and the magnitude of the frequency of emissions occurring in the upstream amenity104, the midstream amenity106, and the downstream amenity108. The environmental characteristic-vectors may include gross atmospheric readings, and emissions occurring at the upstream amenity104, the midstream amenity106, and the downstream amenity108. Similarly, the historical data corresponding to the set of physical parameters, such as volumetric flow rate and the corresponding pressure of the crude oil and the processed oil may be analyzed to generate the set of physical characteristic-vectors. Similarly, the centralized computing unit1802may be configured to calculate the set of operational characteristic-vectors of the upstream amenity104, the midstream amenity106, and the downstream amenity108, such as upstream operational characteristic-vectors, midstream operational characteristic-vectors, and the downstream operational characteristic-vectors by analyzing historical data of the set of operational parameters obtained from the remote server1704.

In another configuration, the centralized computing unit1802may be configured to calculate a gross average of each of the set of environmental characteristic-vectors, set of operational characteristic-vectors, and physical characteristic-vectors. For example, by obtaining environmental characteristic-vectors for a predefined time period occurring in years, in the upstream amenity104, the midstream amenity106, the downstream amenity108, and the communication pathways110, the centralized computing unit1802may be configured to calculate gross environmental characteristic-vectors occurring over the predefined time period. Similarly, the gross physical characteristic-vectors and the gross operational characteristic-vectors may be calculated by the centralized computing unit1802. The calculated characteristic-vectors may be stored in a memory1808.

Referring now toFIG.19illustrating another process layout1900of the oil and gas supply-chain102. Represented by block1902, the centralized computing unit1802may be configured to associate the upstream energy amount with the environmental characteristic-vectors of the upstream amenity104. For example, the upstream energy amount corresponding to the crude oil extracted may be correlated with the set of environmental characteristic-vectors and the set of physical characteristic-vectors, to estimate the energy content of the crude oil extracted under influence of the environmental characteristic-vectors. For example, 2 million barrels having an upstream energy amount ranging between 2,80,000 MMBtus to 3,00,000 MMBtus may be extracted by the pumpjack204, plurality of oil wells1302a,1302b, at an atmospheric pressure ranging between 29.6-30.2 inches Hg, temperature ranging between 122° F. and 200° F., and an emission ranging between 4 to 50 grams/megajoule measured using air quality monitor202. Any variation in the environmental characteristic-vectors may influence the extraction of crude oil.

At block1904, the midstream energy amount may be associated with the set of midstream environmental characteristic-vectors and the set of midstream physical characteristic-vectors. For example, the midstream energy amount from the processed oil may be associated with the set of midstream environmental and the set of midstream physical characteristic-vectors, such as the set of midstream physical characteristic-vectors related to refining i.e., density and sulfur content may be associated with the energy amount of the processed oil. Further, physical characteristic-vectors of the communication pathways110, such as the volumetric flow rate associated with the midstream energy amount may be associated with the content of uncontained water or uncontained liquid petroleum, and any leak caused in the communication pathways110may be correlated with the midstream energy amount. Environmental characteristic-vectors such as emissions occurring during transmitting through communication pathways110may be associated with the midstream energy amount, for example, the midstream energy amount for the 0.5 million gallons of processed oil ranging between 168000 MMBtus to 180000 MMBtus may be associated with a volumetric flow rate of 2000 ft3/second, through a pipe having a diameter ranging between 20-28 inches, with emissions ranging between 0.04-0.06 kg CO2per cubic foot.

Similarly, at block1906, the downstream energy amount may be associated with the downstream environmental characteristic-vectors and the set of downstream physical characteristic-vectors. For example, the set of downstream environmental characteristic-vectors such as the emissions occurring at the downstream amenity108may be associated with the downstream energy amount, i.e., the downstream energy amount for the 0.2-0.5 million gallons of processed oil ranging between 67000 MMBtus to 80000 MMBtus may be associated with a volumetric flow rate of 800 ft3/second, through a pipe having a diameter ranging between 12-18 inches, with emissions ranging between 0.04-0.06 kg CO2per cubic foot.

In another configuration, a successful merchandising, or a transacting, between the upstream amenity104and the midstream amenity106may be enabled, if the upstream energy amount associated with the upstream environmental characteristic-vectors may be calculated and co-related in the downstream energy amount associated with the downstream environmental characteristic-vectors. For example, the plurality of oil wells1302a,1302b, and1302cmay be configured to extract and transmit 2 million gallons of crude oil having an upstream energy amount ranging between 2,80,000 MMBtus to 3,00,000 MMBtus through the pipeline having an inner diameter ranging between 4 to 48 inches, at a pressure ranging between 200-3000 psi, and at a temperature ranging between 90° F. and 130° F. Further, the midstream amenity106may be configured to receive and process the crude oil to produce the processed oil having a downstream energy amount ranging between 40000 MMBtus to 55000 MMBtus, and further transfer the processed oil at a pressure ranging between 500-1400 psi, through the pipeline network110chaving an internal diameter ranging between 26-30 inches, and a temperature ranging between 100° F. to 120° F., to the downstream amenity108. At downstream amenity108, the processed oil may be received by various units, receiving units such as gas storage facility108areceiving 20000 MMBtus, and households108breceiving 30000 MMBtus. The transferring of the processed oil may be verified, for confirming that the gross volume energy amount may be equal (including losses, if any) throughout the oil and gas supply-chain102. If an equivalency may be established, thereby, the transaction may be completed. However, the existence of any error, or any functional anomaly between the upstream energy amount and the downstream energy amount, may indicate the loss of crude oil, or processed oil within the oil and gas supply-chain102, the location of which may be indicated by processing the set of environmental characteristic-vectors, the set of physical characteristic-vectors, and the set of operational characteristic-vectors which may be associated with the upstream energy amount and the downstream energy amount.

Referring toFIG.20illustrating an exemplary configuration, an emissions chart of the midstream amenity106. An anomaly that may lead to unsuccessful transactions may be determined based on tracking the characteristic-vectors associated with the upstream amenity104, the midstream amenity106, and the downstream amenity108, respectively. For example, emissions related to midstream amenity106may be monitored at time T, T+t (after a predefined time t), and T+2t (after a predefined time 2t). At any time, multiple sensors (Sensor 1, sensor 2, and sensor 3) may generate an emissions signal to indicate emissions against a predefined threshold occurring at the midstream amenity106. Referring to the figure, at time T, only sensor 1 may report an emission beyond the predefined threshold of 4 PPM. As time progresses, at time T+t, sensor 1 and sensor 2 may report an emission beyond the predefined threshold of 4 PPM, and at time T+2t, all the sensors may report emissions beyond the predefined threshold of 4 PPM. Therefore, the scenario at time T+2t may be accounted for the anomaly, i.e., a leak occurring at the midstream amenity106, which may eventually disrupt the transaction between the upstream amenity104and the downstream amenity108.

Therefore, associating the energy amount at each stage in the upstream amenity104, the midstream amenity106, and the downstream amenity108with the physical and environmental characteristic-vectors may provide tracking of crude oil and processed oil throughout the oil and gas supply-chain102. Therefore, any anomaly or any other loss may be reported, and mitigated with prompt response accordingly, to ensure integrity in the oil and gas supply-chain102.

Referring now toFIGS.21A-21Billustrating a flow chart2100of a supply-chain characteristic-vectors merchant method for an environmental characteristic-vectors of a gas communicating from an upstream amenity104to a downstream amenity108. The supply-chain characteristic-vectors merchant method may be performed by processing the set of environmental parameters, the set of operational parameters, and the set of physical parameters associated with the upstream amenity104, the midstream amenity106, the downstream amenity108, and the communication pathways110.

At step2102, an air quality monitor202may be provided at the upstream amenity104(sometimes referred to herein as an upstream air quality monitor). As illustrated inFIGS.2-4, the air quality monitor202may include one or more sensors responsive to the gaseous chemical. At step2104, a set of upstream environmental parameters may be sensed by the air quality monitor202positioned at the upstream amenity104. The upstream environmental parameters may include the concentration of the target gaseous chemical. Additionally, the set of upstream environmental parameters may also include atmospheric characteristics such as barometric pressure, an air temperature, a humidity level, a wind-direction, or a wind-speed at the upstream amenity104.

At step2106, an upstream SCADA system1102may be provided at the upstream amenity104. The upstream SCADA system1102may be connected to at least one device in the upstream amenity104, which may include but is not limited to pressure sensors, pressure vessels, separators, drills, and the like. The upstream SCADA system1102may be configured to monitor and supervise at the least one device at the upstream amenity104.

At step2108, the set of upstream operational parameters from the at least one device may be sensed by the upstream SCADA system1102. The set of operational parameters may include operational parameter, such as pressure obtained from the pressure sensors, or an upstream energy amount, such as energy amount in thermal units associated with the crude oil extracted at the upstream amenity104.

At step2110, the set of upstream operational parameters and the set of upstream environmental parameters may be transmitted to the remote server1704. Particularly, the upstream SCADA system1102, after obtaining the set of upstream operational parameters and the set of downstream operational parameters from the upstream amenity104and the downstream amenity108, may be configured to transmit the associated parameters to a central SCADA system1702. The central SCADA system1702may further transmit the associated parameters to the remote server1704.

At step2112, an air quality monitor202may be provided at the downstream amenity108. At step2114, a set of downstream environmental parameters may be sensed by the air quality monitor202positioned at the downstream amenity108(the air quality monitor202may sometimes referred to herein as set of downstream air quality monitor). The set of downstream environmental parameters may include the concentration of the target gaseous chemical, from the emissions occurring at the downstream amenity108. Additionally, the set of downstream environmental parameters may also include atmospheric characteristics such as barometric pressure, an air temperature, a humidity level, wind direction, or wind speed at the downstream amenity108.

At step2116, processed oil such as gas may be communicated from the upstream amenity104to the downstream amenity108. The processed oil may be transmitted through communication pathways110(illustrated inFIG.1), using at least one of road transport network110a, rail transport network110b, or pipeline network110c.

At step2118, a downstream SCADA system1602may be provided at the downstream amenity108. The downstream SCADA system1602may be connected and may be configured to monitor and supervise at least one device in the downstream amenity108, which may include but is not limited to a volumetric capacity of the gas storage units, industrial units, commercial complexes, or households.

At step2120, downstream operational parameters from the at least one device may be sensed by the downstream SCADA system1602. The downstream operational parameters may include operational parameters, such as the rate of gas delivery to devices at the downstream amenity108, and a downstream energy amount, such as the energy amount in thermal units associated with the gas delivered at the downstream amenity108.

At step2122, the set of upstream operational parameters and the set of upstream environmental parameters may be transmitted to the remote server1704. Particularly, the upstream SCADA system1102, after obtaining the set of upstream operational parameters and the set of downstream operational parameters from the upstream amenity104, may be configured to transmit the associated set of parameters to a central SCADA system1702. The central SCADA system1702may further transmit the associated parameters to the remote server1704.

At step2124, a set of upstream environmental characteristic-vectors from the set of upstream environmental parameters may be calculated. The set of environmental characteristic-vectors may be calculated based on the historical data of the set of environmental parameters sensed in the upstream amenity104. For example, the atmospheric pressure, air temperature, and a humidity level, may be associated over time, to generate the set of upstream characteristic-vectors of the environment for the upstream amenity104. Further, at step2126, the set of upstream environmental characteristic-vectors may be associated with the upstream energy amount. In this step, each of the calculated upstream environmental characteristic-vectors from the set of upstream environmental characteristic-vectors may be associated with the energy amount of the extracted crude oil at the upstream amenity104. For example, the set of environmental characteristic-vectors such as emissions, air temperature, and a humidity level may be associated with the energy content of the extracted crude oil.

At step2128, a set of downstream environmental characteristic-vectors from the set of downstream environmental parameters may be calculated. The set of downstream environmental characteristic-vectors may be calculated based on the historical data of the set of downstream environmental parameters sensed in the downstream amenity108. For example, the atmospheric pressure, air temperature, and a humidity level, may be associated over time, to generate the set of downstream characteristic-vectors of the downstream amenity108. Further, at step2130, the set of downstream environmental characteristic-vectors may be associated with the downstream energy amount. In this step, each of the calculated downstream environmental characteristic-vectors from the set of downstream environmental characteristic-vectors may be associated with the energy amount of the processed oil received at the downstream amenity108. For example, the set of environmental characteristic-vectors such as emissions, air temperature, and a humidity level may be associated with the energy content of the processed oil.

At step2132, the presence of upstream energy amount may be confirmed in downstream amenity108. At the downstream amenity108, the processed oil may be received and verified such that the downstream energy amount associated with the set of environmental characteristic-vectors therein (i.e., the set of downstream environmental characteristic-vectors) may be equivalent to the upstream energy amount associated with the set of upstream environmental characteristic-vectors at the upstream amenity104. At step2134, after confirmation of the presence of the upstream energy mount and the upstream environmental characteristic-vectors associated therewith in the downstream amenity108, an equivalency may be established, and thereby, merchant may be completed.

Now, rising interest in the growth of the digital market, especially within the oil and gas supply-chain poses the risk of data tampering. For example, any competitor may unleash a cyber-attack to erase or tamper process data or manipulate information related to processes within the supply-chain. Therefore, to mitigate such events occurring in the oil and gas supply-chain102, various parameters and data related to characteristic-vectors may be secured using encryption, to maintain integrity and transparency of access to data in the oil and gas supply-chain102.

In an alternative configuration, a securing method, or encryption methods, such as cryptographic encryption, or multi-node encryption, may be implemented by executing relevant algorithms on the parameters obtained by the remote server1704. For example, encryption may be implemented before transmission of the characteristic-vectors to the remote server1704, by executing a set of algorithms such as the Noekeon Algorithm, as explained in “Network Data Encryption Transmission Method Based on the Noekeon Algorithm” authored by Jiong Tian et al. The Noekeon Algorithm may be configured to carry out the design and research of network data encryption transmission methods. Combined with the multi-node communication technology, a multi-node network data transmission model and a topological structure model may be established.

To this end, a supply-chain characteristic-vectors securing system and the supply-chain characteristic-vectors securing method is disclosed. Referring now toFIG.22illustrating a layout2200of a multi-node communication encryption model for the oil and gas supply-chain102. The multi-node communication encryption model may include an upstream amenity node2202, a midstream amenity node2204, and a downstream amenity node2206. As may be appreciated, the upstream amenity node2202may be configured to store and encrypt the set of parameters and the corresponding set of characteristic-vectors related to the upstream amenity104, such as the set of upstream physical parameters, the set of upstream physical characteristic-vectors, the set of upstream environmental parameters, and the set of upstream environmental characteristic-vectors. Additionally, analysis for transfer of the processed oil from the upstream amenity104and the downstream amenity108may be encrypted. Similarly, the midstream amenity node2204may be configured to store and encrypt parameters associated with the midstream amenity106, such as process parameters related to entities1402(refer toFIG.14). Again, refer toFIG.22, the downstream amenity node2206may be configured to store and encrypt parameters associated with the downstream amenity108, such as downstream physical parameters, downstream physical characteristic-vectors, downstream environmental parameters, and downstream environmental characteristic-vectors.

After establishing the multi-node communication encryption model for the oil and gas supply-chain102, for data transmission to the remote server1704, the model may be processed through three steps, namely: encapsulation, transmission, and decapsulation. The process of encapsulation may include adding a TCP header, IP header, and MAC header to the architecture, and then converting a bit stream composed of the parameters and characteristic-vectors of the model into electrical signals for transmission in the network. Further, after receipt of the multi-node communication encryption model by the remote server1704, the model may be distributed, or shared through a group of at least one user, private companies, or governmental organizations. Further, for decapsulation or decryption, a private node key associated with each of the upstream amenity node2202, midstream amenity node2204, and the downstream amenity node2206may be assigned, i.e., an upstream amenity node key may be assigned to the upstream amenity node2202, a midstream amenity node key may be assigned to midstream amenity node2204, and a downstream amenity node key may be assigned to the downstream amenity node2206. Each of the private node keys may be allocated to a higher hierarchy associate within the group of at least one user, private companies, or governmental organizations, and a secure communication may be established therebetween in case any access or modification may be required within the data encrypted in the multi-node communication encryption model. For example, if the governmental organization may require access to the multi-node communication encryption model, all the users, or other users of the group may be notified using a notification module, or any notification-generation tool known in the art. After acceptance of all the users in the group, the private node key may be shared with the party requesting access, for decrypting or decapsulating the data encrypted in the multi-node communication encryption model. Therefore, any change or access to the data may be tracked by the users of the group.

Referring now toFIGS.23A-23Billustrating a flowchart2300of a supply-chain characteristic-vectors securing method for an environmental characteristic-vectors of a gas communicating from an upstream amenity to a downstream amenity. The supply-chain characteristic-vectors securing method may include encryption techniques illustrated in conjunction withFIG.22.

At step2302, an air quality monitor202may be provided at the upstream amenity104. As illustrated inFIGS.2-4, the air quality monitor202may include one or more sensors responsive to the gaseous chemical. At step2304, a set of upstream environmental parameters may be sensed by the air quality monitor202positioned at the upstream amenity104. The upstream environmental parameters may include the concentration of the target gaseous chemical. Additionally, the set of upstream environmental parameters may also include atmospheric characteristics such as barometric pressure, an air temperature, a humidity level, wind direction, or wind speed at the upstream amenity104.

At step2306, an upstream SCADA system1102may be provided at the upstream amenity104. The upstream SCADA system1102may be connected to at least one device in the upstream amenity104, which may include but is not limited to pressure sensors, pressure vessels, separators, drills, and the like. The upstream SCADA system1102may be configured to monitor and supervise the at least one device at the upstream amenity104.

At step2308, the set of upstream operational parameters from the at least one device may be sensed by the upstream SCADA system1102. The set of operational parameters may include operational parameters, such as pressure obtained from the pressure sensors, or an upstream energy amount, such as energy amount in thermal units associated with the crude oil extracted at the upstream amenity104.

At step2310, the set of upstream operational parameters and the set of upstream environmental parameters may be transmitted to the remote server1704. Particularly, the upstream SCADA system1102, after obtaining the set of upstream operational parameters and the set of downstream operational parameters from the upstream amenity104and the downstream amenity108, may be configured to transmit the associated parameters to a central SCADA system1702. The central SCADA system1702may further transmit the associated parameters to the remote server1704.

At step2312, an air quality monitor202may be provided at the downstream amenity108. At step2314, a set of downstream environmental parameters may be sensed by the air quality monitor202positioned at the downstream amenity108(the air quality monitor202may sometimes referred to herein as set of downstream air quality monitor). The set of downstream environmental parameters may include the concentration of the target gaseous chemical, from the emissions occurring at the downstream amenity108. Additionally, the set of downstream environmental parameters may also include atmospheric characteristics such as barometric pressure, an air temperature, a humidity level, wind direction, or wind speed at the downstream amenity108.

At step2316, processed oil such as gas may be communicated from upstream amenity104to downstream amenity108. The processed oil may be transmitted through communication pathways110(illustrated inFIG.1), using at least one of road transport network110a, rail transport network110b, or pipeline network110c.

At step2318, a downstream SCADA system1602may be provided at the downstream amenity108. The downstream SCADA system1602may be connected and may be configured to monitor and supervise at least one device in the downstream amenity108, which may include but is not limited to the volumetric capacity of the gas storage units, industrial units, commercial complexes, or households.

At step2320, the set of downstream operational parameters from the at least one device may be sensed by the downstream SCADA system1602. The downstream operational parameters may include operational parameters, such as the rate of gas delivery to devices at the downstream amenity108, and a downstream energy amount, such as the energy amount in thermal units associated with the gas delivered at the downstream amenity108.

At step2322, the set of upstream operational parameters and the upstream environmental parameters may be transmitted to the remote server1704. Particularly, the upstream SCADA system1102, after obtaining the set of upstream operational parameters and the downstream operational parameters from the upstream amenity104, may be configured to transmit the associated parameters to a central SCADA system1702. The central SCADA system1702may further transmit the associated parameters to the remote server1704.

At step2324, a set of upstream environmental characteristic-vectors from the set of upstream environmental parameters may be calculated. The set of upstream environmental characteristic-vectors may be calculated based on the historical data of the set of environmental parameters sensed in the upstream amenity104. For example, the atmospheric pressure, air temperature, a humidity level, may be associated over time, to generate the set of upstream environmental characteristic-vectors. Further, at step2326, the set of upstream environmental characteristic-vectors may be associated with the upstream energy amount. In this step, each of the calculated set of upstream environmental characteristic-vectors may be associated with the energy amount of the extracted crude oil at the upstream amenity104. For example, the set of environmental characteristic-vectors such as emissions, air temperature, and humidity level may be associated with the energy content of the extracted crude oil.

At step2328, a set of downstream environmental characteristic-vectors from the set of downstream environmental parameters may be calculated. The set of downstream environmental characteristic-vectors may be calculated based on the historical data of the set of environmental parameters sensed in the downstream amenity108. For example, the atmospheric pressure, air temperature, a humidity level, may be associated over time, to generate a set of downstream characteristic-vectors of the downstream amenity108. Further, at step2330, the set of downstream environmental characteristic-vectors may be associated with the downstream energy amount. In this step, each of the calculated downstream environmental characteristic-vectors from the set of calculated downstream environmental characteristic-vectors may be associated with the energy amount of the processed oil received at the downstream amenity108. For example, environmental characteristic-vectors such as emissions, air temperature, a humidity level may be associated with the energy content of the processed oil.

At step2332, the set of upstream environmental characteristic-vectors and the set of downstream environmental characteristic-vectors may be secured, using the encryption technique such as multi-node communication architecture, which is already explained in conjunction withFIG.22.

Other scenarios, as explained earlier, including the existence of any error, or any anomaly between the upstream environmental characteristic-vectors and the downstream environmental characteristic-vectors, may indicate the loss of crude oil, or processed oil within the oil and gas supply-chain102, the location of which may be indicated by processing the set of environmental parameters, the set of physical parameters, and the set of operational parameters from the remote server1704. Such anomalies may increase the likelihood of unsuccessful transactions. Therefore, such scenarios form a genesis for tracking commodities, to reduce increased characteristic-vectors due to the anomalies.

Therefore, in an alternative configuration, a digital twin, or a simulation model may be generated. Output from the simulation model may be analyzed for predicting insights on the set of environmental parameters or the characteristic-vectors, such that a scenario determining minimal environmental characteristic-vectors, and a communication path associated with the minimal environmental characteristic-vectors between the upstream amenity104and the downstream amenity108, may be determined accordingly.

Referring now toFIG.24illustrating a layout2400of a machine-learning model generation system for the oil and gas supply-chain102may be illustrated. The machine-learning model generation system may be embedded in the centralized computing unit1802, as an on-device machine-learning unit configured to enable on-device prediction, training, example collection, and/or other machine-learning tasks or functionality for determining minimal environmental characteristic-vectors, and a communication path associated with the minimal environmental characteristic-vectors between the upstream amenity104and the downstream amenity108.

The machine-learning model generation system may include a processor2402and a memory2404. The processor2402may include any suitable processing device (e.g., a processor core, a microprocessor, an ASIC, an FPGA, a controller, a microcontroller, etc.) and can be one processor or a plurality of processors that may be operatively connected. The memory2404can include one or more non-transitory computer-readable storage mediums, such as RAM, ROM, EEPROM, EPROM, flash memory devices, magnetic disks, etc., and combinations thereof. The memory2404may store data and instructions which are executed by the processor2402to cause the machine-learning model generation system to train models, using a variety of data. The machine-learning model generation system may also include a network interface2406that may enable communication over one or more networks (e.g., the Internet).

The machine-learning platform2410may be configured to generate an on-device prediction, training, example collection, and/or other machine-learning tasks or functionality, which may be hereinafter collectively referred to as “machine learning functions2408n”. The machine-learning functions may be in a form of machine-learning models stored locally on the machine-learning model generation system. The machine learning functions2408nmay include environmental-characteristic-vectors minimizing model2408b, and a communication path determining model2408a, in the oil and gas supply-chain102. The machine learning models may be based on a gradient tree-boosting algorithm. In particular, the machine learning models may utilize a FastTreeTweedie algorithm in the ML.NET framework. Alternative machine learning models such as simple-stress regression models could be used, but the gradient tree-boosting algorithm (decision tree) ensembles may provide better performance and may therefore be preferred. Further, other alternative machine learning models may include common regression models, linear regression models (e.g., ordinary least squares, gradient descent, regularization), decision trees and tree ensembles (e.g., random forest, bagging, boosting), generalized additive models, support vector machines, and artificial neural networks, among others. The machine learning models may be used to identify the emission sources and also to isolate the correlation between elevated concentrations and atmospheric variables. For example, a machine learning model configured as a tree-based model with a gradient tree-boosting algorithm may be trained with 10 leaves and 300 trees. The machine learning functions may be trained daily for each of the upstream amenity104, the midstream amenity106, and the downstream amenity108for up to 90 days of data.

The processor2402may be connected to the remote server1704and may be configured to obtain the upstream environmental characteristic-vectors, the midstream environmental characteristic-vectors, and the downstream environmental characteristic-vectors. Further, the machine-learning platform2410may be configured to train at least one model using a machine-learning engine2414, to minimize the environmental characteristic-vectors using the environmental characteristic-vectors minimizing model2408b, or determine a communication path using the communication path determining model2408a. For example, to minimize the environmental characteristic-vectors, the machine-learning platform2410may be configured to train the environmental characteristic-vectors minimizing model2408bby obtaining the upstream environmental characteristic-vectors, the midstream environmental characteristic-vectors, and the downstream environmental characteristic-vectors from the processor2402. As explained earlier, the machine learning function of environmental characteristic-vectors minimizing model2408bmay be based on the Regression model, which uses regression analysis. Regression analysis estimates relationships among variables. Intended for continuous data that can be assumed to follow a normal distribution, the analysis finds key patterns in large data sets and is often used to determine how much specific factors, such as emissions, influence the movement of the processed oil through the communication pathways110. With regression analysis, an emission, or any parameter from the upstream environmental characteristic-vectors or the downstream environmental characteristic-vectors may be predicted, and an independent variable may be used to determine an outcome, i.e., the influence of the predicted emission on the movement of the processed oil through the communication pathways110.

Using the predicted parameter of the emission, or any parameter from the upstream environmental characteristic-vectors or the downstream environmental characteristic-vectors, a digital twin of the oil and gas supply-chain102, or a simulation model of the oil and gas supply-chain102may be generated by the centralized computing unit1802. The digital twin or the simulation model may represent environmental-characteristic-vectors-minimizing-simulation-model, configured to forecast the set of upstream environmental characteristic-vectors, the set of midstream environmental characteristic-vectors, and the set of downstream environmental characteristic-vectors to generate simulated set of upstream environmental characteristic-vectors, a simulated set of midstream environmental characteristic-vectors, and simulated set of downstream environmental characteristic-vectors which may be analyzed as such that mitigation of events related to the anomaly, such as a leak, may be prepared accordingly, thus minimizing or reducing the environmental characteristic-vectors.

In an exemplary configuration, the predicted values or the upstream environmental characteristic-vectors, the midstream environmental characteristic-vectors, the downstream environmental characteristic-vectors, and the simulation model associated therewith may be generated by the centralized computing unit1802. For example, the machine-learning platform2410may be configured to analyze the minimized environmental characteristic-vectors across the oil and gas supply-chain102, and train a communication-path-machine-learning-model for generating a communication-path-machine-learning-model parameter. Using the communication-path-machine-learning-model parameter, a communication-path-simulation-model may be generated, which may be configured to generate a simulated set of upstream environmental characteristic-vectors, a simulated set of midstream environmental characteristic-vectors, and simulated set of downstream environmental characteristic-vectors. These simulated set of environmental characteristic-vectors may be analyzed to determine a communication path with minimal characteristic-vectors. The communication-path-machine-learning-model may also be based on, as explained earlier, the regression analysis machine-learning model.

As may be appreciated, and explained earlier, the machine learning functions may be trained daily for each of the upstream amenity104, the midstream amenity106, and the downstream amenity108for up to 90 days, i.e., the training may be refined every passing day to reflect and record change in the environmental characteristic-vectors. Accordingly, the predicted parameter may also be refined, to generate updated set of upstream environmental parameters, updated set of midstream environmental parameters, and updated set of downstream environmental parameters. Using these updated set of parameters, the centralized computing unit1802may further generate a refined set of upstream environmental characteristic-vectors, a refined set of midstream characteristic-vectors, and a refined set of downstream environmental characteristic-vectors. Further, the digital twin or the simulation model may also be refined, i.e., to generate a refined communication-path-simulation-model, and refined environmental-characteristic-vectors-minimizing-simulation-model. The refined communication-path-simulation-model, and refined environmental-characteristic-vectors-minimizing-simulation-model may be configured to generate the refined set of simulated upstream environmental characteristic-vectors, the refined set simulated midstream environmental characteristic-vectors, and the refined set of simulated downstream environmental characteristic-vectors. Therefore, refining the simulation model, iteratively, may enhance the preparation for the mitigation of the anomalies occurring in the oil and gas supply-chain102. After refining, the refined simulated upstream environmental characteristic-vectors, the refined simulated midstream environmental characteristic-vectors, and the refined simulated downstream environmental characteristic-vectors, and any refined simulation model associated therewith may be stored in a database2412. Further, the trained machine-learning models may be stored in the machine-learning model repository2416.

Now referring toFIG.25A-25Billustrating a flow chart2500of a supply-chain characteristic-vectors minimizing method for minimizing environmental characteristic-vectors of a gas communicating from an upstream amenity104to a downstream amenity108, using the supply-chain characteristic-vectors minimizing system including the supply-chain characteristic-vectors model. At step2502, an air quality monitor202may be provided at the upstream amenity104. As illustrated inFIGS.2-4, the air quality monitor202may include one or more sensors responsive to the gaseous chemical. At step2504, a set of upstream environmental parameters may be sensed by the air quality monitor202positioned at the upstream amenity104. The set of upstream environmental parameters may include the concentration of the target gaseous chemical. Additionally, the set of upstream environmental parameters may also include atmospheric characteristics such as atmospheric pressure, an air temperature, a humidity level, wind direction, or wind speed at the upstream amenity104.

At step2506, an upstream SCADA system1102may be provided at the upstream amenity104. The upstream SCADA system1102may be connected to at least one device in the upstream amenity104, which may include but is not limited to pressure sensors, pressure vessels, separators, drills, and the like. The upstream SCADA system1102may be configured to monitor and supervise at the least one device at the upstream amenity104.

At step2508, a set of upstream operational parameters from the at least one device may be sensed by the upstream SCADA system1102. The set of operational parameters may include operational parameters, such as pressure obtained from the pressure sensors, or an upstream energy amount, such as energy amount in thermal units associated with the crude oil extracted at the upstream amenity104.

At step2510, the set of upstream operational parameters and the set of upstream environmental parameters may be transmitted to the remote server1704. Particularly, the upstream SCADA system1102, after obtaining the set of upstream operational parameters and the set of downstream operational parameters from the upstream amenity104and the downstream amenity108, may be configured to transmit the associated parameters to a central SCADA system1702. The central SCADA system1702may further transmit the associated parameters to the remote server1704.

At step2512, an air quality monitor202may be provided at the downstream amenity108. At step2514, a set of downstream environmental parameters may be sensed by the air quality monitor202positioned at the downstream amenity108(the air quality monitor202may sometimes referred to herein as set of downstream air quality monitor). The set of downstream environmental parameters may include the concentration of the target gaseous chemical, from the emissions occurring at the downstream amenity108. Additionally, the set of downstream environmental parameters may also include atmospheric characteristics such as barometric pressure, an air temperature, a humidity level, wind direction, or wind speed at the downstream amenity108.

At step2516, processed oil such as gas may be communicated from upstream amenity104to downstream amenity108. The processed oil may be transmitted through communication pathways110(illustrated inFIG.1), using at least one of road transport network110a, rail transport network110b, or pipeline network110c.

At step2518, a midstream SCADA system1502may be provided at the downstream amenity108. The downstream SCADA system1602may be connected and may be configured to monitor and supervise at least one device in the downstream amenity108, which may include but is not limited to the volumetric capacity of the gas storage units, industrial units, commercial complexes, or households.

At step2520, the set of downstream operational parameters from the at least one device may be sensed by the downstream SCADA system1602. The set of downstream operational parameters may include operational parameters, such as the rate of gas delivery to devices at the downstream amenity108, and a downstream energy amount, such as the energy amount in thermal units associated with the gas delivered at the downstream amenity108.

At step2522, the set of upstream operational parameters and the set of upstream environmental parameters may be transmitted to the remote server1704. Particularly, the upstream SCADA system1102, after obtaining the set of upstream operational parameters and the downstream operational parameters from the upstream amenity104and the downstream amenity108, may be configured to transmit the associated parameters to a central SCADA system1702. The central SCADA system1702may further transmit the associated parameters to the remote server1704.

At step2524, a set of upstream environmental characteristic-vectors from the set of upstream environmental parameters may be calculated. The set of upstream environmental characteristic-vectors may be calculated based on the historical data of the set of environmental parameters sensed in the upstream amenity104. For example, the atmospheric pressure, air temperature, and a humidity level, may be associated over time, to generate the set of upstream characteristic-vectors of the environment of the upstream amenity104. Further, at step2526, the set of upstream environmental characteristic-vectors may be associated with the upstream energy amount. In this step, each of the calculated set of upstream environmental characteristic-vectors may be associated with the energy amount of the extracted crude oil at the upstream amenity104. For example, the set of environmental characteristic-vectors such as emissions, air temperature, and humidity level may be associated with the energy content of the extracted crude oil.

At step2528, a set of downstream environmental characteristic-vectors from the set of downstream environmental parameters may be calculated. The set of downstream environmental characteristic-vectors may be calculated based on the historical data of the set of environmental parameters sensed in the downstream amenity108. For example, the atmospheric pressure, air temperature, and humidity level may be associated over time, to generate the set of downstream characteristic-vectors of the environment of the downstream amenity108. Further, at step2530, the set of downstream environmental characteristic-vectors may be associated with the downstream energy amount. In this step, each of the calculated set of downstream environmental characteristic-vectors may be associated with the downstream energy amount received at the downstream amenity108. For example, the set of downstream environmental characteristic-vectors such as emissions, air temperature, and humidity level may be associated with the energy content of the processed oil.

At step2532, an environmental-characteristic-vectors-minimizing machine-learning-model may be trained to generate a minimizing environmental-characteristic-vectors-minimizing-machine-learning-model parameter, such as predicted environmental-characteristic-vectors for the upstream amenity104, the midstream amenity106, and the downstream amenity108, respectively. As explained earlier, the environmental-characteristic-vectors-machine-learning model may be based on a linear regression model, configured to generate predicted environmental characteristic-vectors and an influence thereof, on the transportation of crude oil and processed oil throughout the oil and gas supply-chain102.

At step2534, an environmental-characteristic-vectors-minimizing simulation model may be generated, which may act as a digital twin of the oil and gas supply-chain102. The environmental-characteristic-vectors-minimizing simulation model may be configured to forecast any change in the trend of the environmental characteristic-vectors with respect to the upstream amenity104, the midstream amenity106, and the downstream amenity108. At step2536, the environmental characteristic-vectors for the upstream amenity104, the midstream amenity106, and the downstream amenity108may be minimized, such that mitigating events related to the anomaly, like a leak, may be prepared accordingly.

Now referring toFIG.26A-26B, a flowchart2600of a supply-chain communication path determining method for a gas communicating from an upstream amenity104to a downstream amenity108may be illustrated, using the supply-chain communication path determining system which may include supply-chain communication path machine-learning model. At step2602, an air quality monitor202may be provided at the upstream amenity104. As illustrated inFIGS.2-4, the air quality monitor202may include one or more sensors responsive to the gaseous chemical. At step2604, a set of upstream environmental parameters may be sensed by the air quality monitor202positioned at the upstream amenity104. The upstream environmental parameters may include the concentration of the target gaseous chemical. Additionally, the set of upstream environmental parameters may also include atmospheric characteristics such as barometric pressure, an air temperature, a humidity level, wind direction, or wind speed at the upstream amenity104.

At step2606, an upstream SCADA system1102may be provided at the upstream amenity104. The upstream SCADA system1102may be connected to at least one device in the upstream amenity104, which may include but is not limited to pressure sensors, pressure vessels, separators, drills, and the like. The upstream SCADA system1102may be configured to monitor and supervise at the least one device at the upstream amenity104.

At step2608, the set of upstream operational parameters from the at least one device may be sensed by the upstream SCADA system1102. The set of operational parameters may include operational parameters, such as pressure obtained from the pressure sensors, or an upstream energy amount, such as energy amount in thermal units associated with the crude oil extracted at the upstream amenity104.

At step2610, the set of upstream operational parameters and the set of upstream environmental parameters may be transmitted to the remote server1704. Particularly, the upstream SCADA system1102, after obtaining the set of upstream operational parameters and the set of downstream operational parameters from the upstream amenity104and the downstream amenity108, may be configured to transmit the associated parameters to a central SCADA system1702. The central SCADA system1702may further transmit the associated parameters to the remote server1704.

At step2612, an air quality monitor202may be provided at the downstream amenity108. At step2614, a set of downstream environmental parameters may be sensed by the air quality monitor202positioned at the downstream amenity108(the air quality monitor202may sometimes referred to herein as set of downstream air quality monitor). The set of downstream environmental parameters may include the concentration of the target gaseous chemical, from the emissions occurring at the downstream amenity108. Additionally, the set of downstream environmental parameters may also include atmospheric characteristics such as barometric pressure, an air temperature, a humidity level, wind direction, or wind speed at the downstream amenity108.

At step2616, processed oil such as gas may be communicated from upstream amenity104to downstream amenity108. The processed oil may be transmitted through communication pathways110(illustrated inFIG.1), using at least one of road transport network110a, rail transport network110b, or pipeline network110c.

At step2618, a downstream SCADA system1602may be provided at the downstream amenity108. The downstream SCADA system1602may be connected and may be configured to monitor and supervise at least one device in the downstream amenity108, which may include but is not limited to the volumetric capacity of the gas storage units, industrial units, commercial complexes, or households.

At step2620, the set of downstream operational parameters from the at least one device may be sensed by the downstream SCADA system1602. The set of downstream operational parameters may include operational parameters, such as the rate of gas delivery to devices at the downstream amenity108, and a downstream energy amount, such as the energy amount in thermal units associated with the gas delivered at the downstream amenity108.

At step2622, the set of upstream operational parameters and the set of upstream environmental parameters may be transmitted to the remote server1704. Particularly, the upstream SCADA system1102, after obtaining the set of upstream operational parameters and the set of downstream operational parameters from the upstream amenity104, may be configured to transmit the associated parameters to a central SCADA system1702. The central SCADA system1702may further transmit the associated parameters to the remote server1704.

At step2624, a set of upstream environmental characteristic-vectors from the set of upstream environmental parameters may be calculated. The set of environmental characteristic-vectors may be calculated based on the historical data of the set of environmental parameters sensed in the upstream amenity104. For example, the atmospheric pressure, air temperature, and a humidity level, may be associated over time, to generate the set of characteristic-vectors of the environment at the upstream amenity104. Further, at step2626, the set of upstream environmental characteristic-vectors may be associated with the upstream energy amount. In this step, each of the calculated upstream environmental characteristic-vectors from the calculated upstream environmental characteristic-vectors may be associated with the energy amount of the extracted crude oil at the upstream amenity104. For example, the set of environmental characteristic-vectors such as emissions, air temperature, and a humidity level may be associated with the energy content of the extracted crude oil.

At step2628, a set of downstream environmental characteristic-vectors from the set of downstream environmental parameters may be calculated. The set of downstream environmental characteristic-vectors may be calculated based on the historical data of the set of environmental parameters sensed in the downstream amenity108. For example, the atmospheric pressure, air temperature, and a humidity level, may be associated over time, to generate the set of characteristic-vectors of the environment at the downstream amenity108. Further, at step2630, the set of downstream environmental characteristic-vectors may be associated with the set of downstream energy amount. In this step, each of the calculated set of downstream environmental characteristic-vectors may be associated with the energy amount of the processed oil received at the downstream amenity108. For example, the set of environmental characteristic-vectors such as emissions, air temperature, and a humidity level may be associated with the energy content of the processed oil.

At step2632, a communication-path-machine-learning-model may be trained to generate a communication-path-machine-learning-model parameter, such as predicted environmental characteristic-vectors for the upstream amenity104, the midstream amenity106, and the downstream amenity108, respectively. As explained earlier, the communication-path-machine-learning model may be based on a linear regression model, configured to generate predicted environmental characteristic-vectors and an influence thereof, on the transportation of crude oil and processed oil throughout the oil and gas supply-chain102.

At step2634, a communication-path simulation model may be generated, which may act as a digital twin of the oil and gas supply-chain102. The communication-path simulation model may be configured communication-path-simulation-model is configured to generate a simulated set of upstream environmental characteristic-vectors and a simulated set of downstream environmental characteristic-vectors. At step2636, the communication path with communication path with minimal upstream environmental characteristic-vectors and a minimal downstream environmental characteristic-vectors, by analyzing the simulated set of upstream environmental characteristic-vectors and the simulated set of downstream environmental characteristic-vectors may be determined.

In another alternative configuration, the present supply-chain may be configured for other commodities in physical form (e.g. gas, liquid, or solid). Non-limiting examples may include the movement of ice that may be in solid form or contained in a mixture of liquid water with ice distributed therein. Or, the supply-chain may be moving produce (such as apples from growing regions of the US, bananas from tropical regions to markets in Europe, fish from net-farms in the pacific ocean for consumption in Chicago, Illinois, or any of an infinitely larger number of applications). When alternatively configured (outside the illustrated application to oil and/or natural gas), the items travelling through the supply-chain may benefit from tracking/trading/reporting characteristic-vectors such as an atmospheric pressure, an atmospheric temperature, a humidity level, composition of airborne pollutants in atmosphere, volume of uncontained water in the gas, volume of uncontained liquid petroleum in the gas, a predefined scarred land of an amenity site of the upstream amenity, a usage of water, a usage of topsoil, a usage of nutrients, a type of nutrients, a grade of slope of the land, proximity of a river, depth of a water table (e.g. aquifer), proximity of endangered species, proximity of human habitat/domicile, etc. In some configurations, air quality monitors might not be utilized and/or be replaced with other monitors contiguously dispersed, intermittently dispersed, or terminally located (at end or beginning points) along the supply-chain. Along similar lines, a SCADA system may be replaced by other analog or digital monitoring/reporting/controlling systems.

The methods, systems, devices, graphs, and/or tables discussed herein are examples. Various configurations may omit, substitute, or add various procedures or components as appropriate. For instance, in alternative configurations, the methods may be performed in an order different from that described, and/or various stages may be added, omitted, and/or combined. Also, features described with respect to certain configurations may be combined in various other configurations. Different aspects and elements of the configurations may be combined in a similar manner. Also, technology evolves and, thus, many of the elements are examples and do not limit the scope of the disclosure or claims. Additionally, the techniques discussed herein may provide differing results with different types of context awareness classifiers.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly or conventionally understood. As used herein, the articles “a” and “an” refer to one or to more than one (i.e., to at least one) of the grammatical object of the article. By way of example, “an element” means one element or more than one element. “About” and/or “approximately” as used herein when referring to a measurable value such as an amount, a temporal duration, and the like, encompasses variations of ±20% or ±10%, ±5%, or ±0.1% from the specified value, as such variations are appropriate to in the context of the systems, devices, circuits, methods, and other implementations described herein. “Substantially” as used herein when referring to a measurable value such as an amount, a temporal duration, a physical characteristic-vectors (such as frequency), and the like, also encompasses variations of ±20% or ±10%, ±5%, or ±0.1% from the specified value, as such variations are appropriate to in the context of the systems, devices, circuits, methods, and other implementations described herein.

As used herein, including in the claims, “and” as used in a list of items prefaced by “at least one of” or “one or more of” indicates that any combination of the listed items may be used. For example, a list of “at least one of A, B, and C” includes any of the combinations A or B or C or AB or AC or BC and/or ABC (i.e., A and B and C). Furthermore, to the extent more than one occurrence or use of the items A, B, or C is possible, multiple uses of A, B, and/or C may form part of the contemplated combinations. For example, a list of “at least one of A, B, and C” may also include AA, AAB, AAA, BB, etc.

While illustrative and presently preferred embodiments of the disclosed systems, methods, and/or machine-readable media have been described in detail herein, it is to be understood that the inventive concepts may be otherwise variously embodied and employed, and that the appended claims are intended to be construed to include such variations, except as limited by the prior art. While the principles of the disclosure have been described above in connection with specific apparatuses and methods, it is to be clearly understood that this description is made only by way of example and not as limitation on the scope of the disclosure.