EA042682B1 - SYSTEM AND METHOD FOR DATA MANAGEMENT BETWEEN FIRST SUBJECT AND SECOND SUBJECT IN OIL AND GAS SUPPLY CHAIN TO DETECT FRAUD OR THEFT OF OIL AND GAS RESOURCES - Google Patents

Description

The present invention generally relates to a system and method for managing and controlling data between entities in an oil and gas supply chain, and more specifically, to an excise tax management system and method for identifying and reconciling tax returns, enabling tax recollection in an efficient manner, production volumes and operational reports.

State of the art

The oil and gas industry is generally divided into three sectors: upstream, midstream, and downstream, as depicted in FIG. 1. The upstream sector is known as the upstream sector. The upstream sector includes the prospecting and exploration of potential underground or subsea deposits of crude oil and natural gas (for example, the identification of potential hydrocarbon reserves), the drilling of exploration wells and, subsequently, the drilling and completion of wells that recover and bring to the surface (produce) crude oil and / or crude natural gas. The midstream sector includes transportation (via pipeline, rail, truck, etc.), storage and wholesale of crude or refined petroleum products. Pipelines and numerous other transportation systems can be used to move crude oil from production sites to refineries and to supply various refined products to distributors in the downstream sector. The downstream sector refers to the refining of crude oil and the processing and refining of crude natural gas, as well as the marketing and distribution of products derived from crude oil and natural gas. The downstream sector provides consumers with products such as gasoline or motor fuel, kerosene, jet fuel, diesel fuel, heating oil, lubricants, waxes, asphalt, natural gas and LPG, as well as hundreds of petrochemical products.

In recent years, there has been a significant increase in illegal activities related to oil and gas resources. For example, the number of oil and gas thefts in regions like Texas and Mexico has increased about tenfold over the past ten years. Corruption, embezzlement, falsification, theft and other such illegal activities occur in all phases and sectors of the supply chain, including upstream, midstream and downstream. Illegal connections to pipelines, rerouting of crude oil, hijacking trucks, building underground tunnels and stealing oil from refineries are just some of the illegal activities that have become widespread in the industry. Due to this increase in activity, the oil and gas industry has faced several challenges. For example, occurring events are not always connected with each other geographically or otherwise, and form a chain of disparate events and incidents. Currently, there are many different solutions and technologies to assist in management, but they are not homogeneous or compatible systems. The lack of coordinated communication and transparency between regions, functions and teams creates various difficulties, and the lack of the ability to capture and track events hinders accounting. Thus, it becomes difficult or even impossible to respond to such events and incidents in a timely manner. Rerouting and material theft also make it more difficult for the tax authority to effectively collect taxes from subsidiaries or other suppliers in the oil and gas supply chain. Lack of data or unreliable data can lead to an underestimation of the true amount of taxes that should be levied at the state level.

Thus, there is a need to provide an intelligent control system capable of monitoring and sending reports or warnings of illegal activities targeting oil and gas resources while improving reliability, safety, compliance and environmental responsibility. Additionally, there is a need for a system that prescribes actions directed to resources in the upstream, midstream and downstream sectors by remotely monitoring, analyzing, predicting events on these resources and providing data as an alert to support decision making from any location. Additionally, there is a need for a system that allows the creation of secure and reliable data from the upstream, midstream and downstream sectors by remotely monitoring, analyzing, predicting resource events from these sectors, and providing data as an alert or report in order to allow the corporate level in the oil and gas supply chain to effectively control and manage all participants in the oil and gas supply chain. Additionally, there is a need for a system that allows editing of secure, accurate and reliable data from the upstream, midstream and downstream sectors, which allows for the efficient collection of taxes in the supply chain and allows the state level to correctly collect the amount of tax that must be paid by the entities participating in the chain oil and gas supplies. The term resource, as defined in this document, includes all oil and gas products and infrastructure.

Brief summary of the invention

The present invention, through one or more of its various aspects, embodiments and/or specific features or accessory components, provides

- 1 042682 various systems, servers, methods, media and programs for managing and controlling the excise tax management system and method for identifying and reconciling tax returns, production volumes and operational reports.

The present invention generally relates to a system and method for managing and controlling data between entities in an oil and gas supply chain, and more particularly to an excise tax management system and method for identifying and reconciling tax returns, production volumes, and operational reports.

In one embodiment, an integrity management system is provided that manages operation and control between at least one entity in an oil and gas supply chain, comprising a data integration management module that collects data from a plurality of production management systems that collects first data obtained from at least one from a sensor and a data acquisition device; at least one of a subsidiary, a franchisee, and a third party contractor collecting second data derived from the oil and gas supply chain; at least one gateway protecting and grouping first data collected from at least one of the sensor and the data collection device; and a data management system collecting first data obtained from at least one of the sensor and the data collection device and second data provided by at least one of a subsidiary, a franchisee, and a third party contractor, wherein the data management system protects and groups the first data to create at least one of the protected tax report, the tax assessment and the tax information related to the key performance indicator (KPI), and protects and groups the second data to create at least one of the protected data, the protected financial report, relating to at least one of a subsidiary, a franchisee, and a third-party oil and gas supply chain contractor.

In one aspect, a report on the protected and grouped first and second data is provided to a first entity to generate a first tax return from the protected and grouped first data and to a second entity to generate a second tax return from the protected and grouped second data, wherein the first and second tax returns are compared for verifying the accuracy of the second tax return corresponding to the first tax return.

In another aspect, the protected and grouped first and second data report is submitted to: an excise platform interface comprising a tax identification module for identifying taxable transactions for reconciliation; an operational reporting module that calculates and formats the secure and grouped first and second data; a tax compliance module for providing feedback on formatted secure and grouped first and second data; and a data construction module for combining the secure and grouped first and second data output from the tax identification module, the operational reporting module, and the tax compliance module.

In yet another aspect, the excise platform interface receives secure and grouped first and second data generated by the data management system, thereby allowing a third entity to compare and agree on at least one of excise tax, tax collection, and a KPI generated by at least one of the first and second subjects.

In another aspect, the data management system includes filtering and transforming the protected and grouped first and second data; extraction and annotation of filtered and transformed protected and grouped first and second data; performing a correlation of the extracted and annotated protected and grouped first and second data; and classifying the correlated protected and grouped first and second data; and sending the classified secure and grouped first and second data to the data store and the live data store.

In yet another aspect, the first entity is a corporate entity and the second entity is at least one of a subsidiary, a franchisee, and a third party contractor.

In another aspect, the integrity management system interfaces with the tax refund platform via an excise tax platform comprising a correlation handler receiving summary secure and grouped first and second data from an excise platform interface to identify and reconcile inconsistencies between the summary secure and grouped first and second data automatically generated. excise platform interface, and the corresponding declaration from the first and second tax declarations generated by the first and second entities, respectively.

In yet another aspect, the tax refund platform further includes a transaction repository storing identified and matched data from the correlation engine;

a transaction processor for linking the identified and matched data, a transaction archive storing the archived identified and matched data from the correlation processor;

and a data analysis module receiving processed and archived data for descriptive, diagnostic, predictive, and prescriptive analysis.

In another aspect, the collected first and second data include at least one of the following: invoice, payment, cash management, pump displacement, amount of fuel transported, and number of barrels of fuel.

In one aspect, the collected first and second data are marked as related to the tax event before being protected and grouped.

In another aspect, the first and second tax returns are one of the following: a tax report, a tax assessment, and KPI-related tax information, and are independently generated by the first and second entities, respectively.

In yet another aspect, a variety of production management systems are designed for the upstream, midstream and downstream sectors of the oil and gas supply chain.

In another aspect, each of the plurality of upstream, midstream, and downstream production management systems is grouped as a single data repository.

In yet another aspect, the collected first data from each of the plurality of production control systems is sent to the data integration control module in the form of at least one of unsecured data, secure data, separately formatted data, jointly formatted data, protected attribute data, read-only data and tamper-proof data.

In another aspect, the sensor is configured to sense data related to oil and gas resources moving through the supply chain, data related to at least one of the following: temperature, density, flow meter, humidity, volume, gravity, chemical composition, pressure, weight , pipeline pressure variation, difference in vehicle weight or fuel volume, GPS positioning, synchronization of vehicle location and geographic region, imaging, pump volumetric efficiency, amount of fuel transported, barrels of fuel, and thermal imaging; and the data collection device is configured to collect additional data related to oil and gas resources moving through the supply chain, and which is auxiliary and improves the interpretation of data from the sensor, including invoice, payment and cash management.

In a further aspect, the transmission of the collected data from the production control system to the data integration control module constitutes a secure communication to ensure the integrity of the collected first and second data.

In yet another aspect, the data integration control module comprises a data store for storing the collected first and second data; a data acquiring device for acquiring first and second data stored in the data store and creating a data structure containing key values from the acquired data; a data sorting device for sorting the structured data received from the device for obtaining data for analysis; and a data parser for parsing the structured data using computational models and algorithms for identifying events, checking the integrity of the structured data, and protecting the structured data to prevent tampering, wherein the data management module generates grouped events based on the parsed data.

In another embodiment, an integrity management system is provided that manages operation and control between a first entity and a second entity in a supply chain, comprising a plurality of production control systems collecting data obtained from at least one of a sensor and a data acquisition device; at least one gateway protecting and grouping data collected from at least one of the sensor and the data collection device; and a data integration module receiving data from at least one gateway and converting the secure collected data into at least one of the following: a secure tax report, a tax assessment, and tax information related to a key performance indicator (KPI) using the excise platform interface , thereby allowing the first entity to effectively compare and agree on at least one of the following: excise tax, tax collection, and KPIs from the second entity.

In yet another embodiment, a method is provided to manage operation and control between at least one entity in the oil and gas supply chain, including collecting first and second data in a data integration control module, including obtaining first data from at least one of a sensor and a device for data collection using a variety of production management systems; receiving second data provided by at least one of a subsidiary, a franchisee, and a third party contractor collected from the oil and gas supply chain; protecting and grouping the first data collected from at least one of the sensor and the data collection device by means of at least one

- 3 042682 locks; and collecting in the data management system the first data received from at least one of the sensor and the data collection device, and the second data provided by at least one of the subsidiary, the franchisee, and the third party contractor, while using the control system data, protect and group the first data to create at least one of the following: a protected tax report, tax assessment, and tax information related to a key performance indicator (KPI), and protect and group the second data to create at least one of the protected data, a protected financial statement relating to at least one of the following: a subsidiary, a franchisee, and a third-party oil and gas supply chain contractor.

Brief description of graphic materials

The present invention is further described in the following detailed description with reference to the aforementioned plurality of drawings, by way of non-limiting examples of preferred embodiments of the present invention in which like conventions represent like elements on several kinds of drawings.

In FIG. 1 shows an exemplary supply chain for use in the oil and gas industry.

In FIG. 2 shows an exemplary system for use in accordance with the embodiments described herein.

In FIG. 3 is an exemplary diagram of an integrity management system according to an embodiment of the invention.

In FIG. 4 shows another exemplary diagram of an integrity management system according to an embodiment of the invention.

In FIG. 5 shows an exemplary embodiment of communication between a data management system and a control center according to an embodiment of the invention.

In FIG. 6 is an exemplary diagram of an integrity management system according to an embodiment of the invention.

In FIG. 7 shows an exemplary interface diagram according to one embodiment of the invention.

In FIG. 8A-8D show an exemplary sequence of events in which data is collected over time to determine probability.

In FIG. 9 shows an exemplary interface diagram according to one embodiment of the invention.

In FIG. 10 shows an exemplary embodiment of an interface processing path according to one embodiment of the invention.

Detailed description

The present invention, through one or more of its various aspects, embodiments, and/or specific features or accessory components, is thus intended to provide one or more advantages, as specifically noted below.

In FIG. 2 shows an exemplary system for use in accordance with the embodiments described herein. System 100 is shown generally and may include computer system 102, shown generally. Computer system 102 may operate as a standalone device or may be attached to other systems or peripherals. For example, computer system 102 may include or be part of one or more of computers, servers, systems, communications networks, or a cloud environment.

The computer system 102 may operate as a server in a network environment or as a client user computer in a network environment. The computer system 102, or portions thereof, may be implemented in or embedded in various devices such as a personal computer, tablet computer, set-top box, personal digital assistant, mobile device, PDA, laptop computer, desktop computer, communication device, a wireless phone, a personal trusted device, a web device, or any other machine capable of executing a set of commands (serial or otherwise) that determines the actions performed by that device. In addition, although a single computer system 102 is depicted, additional embodiments may include any collection of systems or ancillary systems that individually or collectively execute instructions or perform functions.

As shown in FIG. 2, computer system 102 may include at least one processor 104, such as, for example, a CPU, a GPU, or both. Computer system 102 may also include computer storage 106. Computer storage 106 may include static storage, dynamic storage, or both. Computer storage 106 may optionally or alternatively include a hard drive, random access memory, cache, or any combination thereof. Of course, those skilled in the art will appreciate that computer storage device 106 may include any combination of known storage devices or a single storage device.

As shown in FIG. 2, the computer system 102 may include a computer display 108 such as a liquid crystal display, an organic light emitting diode display, a flat panel, a solid state display, a cathode ray tube, a plasma display, or any other known display.

Computer system 102 may include at least one computer input device 110 such as a keyboard, a remote control device including a wireless keypad, a microphone attached to a speech recognition engine, a camera such as a camcorder or camera, a cursor control device, or any combination thereof. . Those skilled in the art will appreciate that various embodiments of computer system 102 may include multiple input devices 110. Moreover, those skilled in the art will also appreciate that the above list of exemplary input devices 110 is not exhaustive and that computer system 102 may include any additional or alternative input devices 110.

The computer system 102 may also include a media reader 112 and a network interface 114. In addition, the computer system 102 may include any additional devices, components, parts, peripherals, hardware, software, or any combination thereof that are commonly known and contemplated. as pertaining to or included in a computer system, such as, for example, but not limited to, output device 116. Output device 116 may be, but is not limited to, a speaker, audio output, video output, remote control output, or any combination thereof.

Each of the components of computer system 102 may be interconnected and communicate via bus 118. As shown in FIG. 2, each of the components can be interconnected and communicate via an internal bus. However, it will be apparent to those skilled in the art that any of the components may also be connected via an expansion bus. Moreover, bus 118 may allow communication via any standard or other specification that is well known and understood, such as, but not limited to, PCI bus, PCI-express bus, PATA interface, SATA interface, and so on.

Computer system 102 may communicate with one or more additional computing devices 120 over network 122. Network 122 may be, but is not limited to, a local area network, a wide area network, the Internet, a telephone network, or any other network well known and understood in the art. . Network 122 shown in FIG. 2 is a wireless network. However, those skilled in the art will appreciate that network 122 may also be a wired network.

Additional computing device 120 is shown in FIG. 1 in the form of a personal computer. However, those skilled in the art will appreciate that, in alternative embodiments of the present application, device 120 may be a laptop computer, tablet PC, personal digital assistant, mobile device, PDA, desktop computer, communications device, wireless telephone, personal trusted device, a web device, a television with one or more processors built into and/or attached to it, or any other device capable of executing a set of commands, sequential or otherwise, that determines the actions performed by this device. Of course, it will be apparent to those skilled in the art that the devices listed above are exemplary devices only and that device 120 may be any additional device or accessory that is well known and understood in the art, within the scope of this application. Moreover, it will be similarly apparent to those skilled in the art that the device may be any combination of devices and fixtures.

Of course, it will be apparent to those skilled in the art that the above components of computer system 102 are exemplary only and should not be construed as exhaustive and/or all-encompassing. Moreover, the examples of the components listed above are also provided by way of example and should not be construed as exhaustive and/or all-encompassing.

In FIG. 3 is an exemplary diagram of an integrity management system according to an embodiment of the invention. The IMS integrity management system includes, but is not limited to, the CCC control center, the data management system, and the sensors used for secure measurement. The IMS Integrity Management System manages oil and gas resources securely (or insecurely, if desired) by monitoring tax-related activities in the supply chain, alerting corporate entities and their subsidiaries, future partners and franchisees, and/or informing the tax authority (also being the subject) of such activities in an appropriate manner. For example, the system may alert one of the entities that a taxable event has occurred, provide a tax report to one of the entities, forecast or predict tax data, and

- 5 042682 automatically provide recommendations and/or responses. It should be understood that the examples provided are non-limiting and that any number of responses may be provided as is contemplated in the art. It should also be understood that the IMS integrity management system is not limited to the management of tax-related activities, but can also be used as an alert and control system or for any other application normally intended by a management system. The system can equally be used to manage and control entities in the supply chain to identify and reconcile taxable events. Additionally, as detailed below, the CCC control center uses data over time to detect and calculate trends and future events.

The IMS Integrity Management System obtains information from sensor(s) and data collection device(s) located at various geographic locations and regions throughout the supply chain and in the form of any well-known sensor or data collection device capable of sensing or collecting data, provided that it is designed to collect this type of data. The sensors are configured to capture and collect data related to oil and gas resources moving through the supply chain, the data including, but not limited to, at least one of the following: temperature, density, humidity, volume of oil and/or gas recovered, volume transported oil and/or gas, volume of motor fuel sold at a filling station, gravity, chemical composition, pressure, weight, pressure change in the pipeline, difference in vehicle weight or fuel volume, GPS positioning, vehicle position synchronization and geographic region, flow rate, conductivity, rheology, turbidity, imaging, thermal imaging. Additionally, the sensors can receive and collect information about the state of the sensor (i.e. malfunction, disconnection, etc.), strain gauge readings, weather data, information about road conditions, vehicle or road conditions, wind speed, barometric conditions, rainfall, maintenance data or date of maintenance, personal location information (for example, the location of the nearest fire station or police station), data from radar, motion detectors, radio frequency data, acoustic data, GPS position information, data extracted from unmanned aerial vehicles, information about the cost of motor fuel reserves, pump volumetric efficiency, the amount of transported fuel and the number of barrels of fuel and thermal imaging, etc. Information may also be collected by data collection devices. For example, the information and data contained in a SAP™ or Oracle™ repository could be any data, forecast, product purchase, tax rate, invoice creation, payment, cash management, and so on.

Sensors and data acquisition devices (perceiving and collecting data in the form of secure measurements) may be located in the upstream sector, the midstream sector and/or the downstream sector of the oil and gas supply chain. The data is collected and sent to the gateway (depicted as part of the ICS production control system in Figure 6, although it can also be located separately from the ICS). The gateway is a device for collecting data from various sources (for example, an ICS such as SCADA, said ICS using protocols such as MODBUS, OPC, EtherCAT, etc.) and includes a business rules engine (BRE). The gateway can also collect data directly from a sensor, data collection devices, or any device that provides data from the upstream, midstream, and downstream sectors. The collected data can be converted into secure (or further secure) data, including, for example, a timestamp and various attributes. When the data is converted by the gateway, the data is sent (preferably in a secure manner) to the data integration module. Alternatively or alternatively, the collected data can be stored in a repository or multiple repositories and then sent to the IMS Integrity Management System where grouped events will be generated from the data. It should also be understood that the data collected does not have to come from the sources listed above, but can come from any internal or external data source.

The data integration module includes a data management system DMS that, in one embodiment, stores data, retrieves data from storage, and creates a data structure containing key values from the data, sorts the data structure, and parses the structured data using computational models and algorithms to identify events. Data is also checked for structured data integrity and structured data security to prevent falsification. Grouped events are created by the DMS data management system for use by the CCC control center. A CCC control center (which may include processor(s), software, interface(s) and multiple displays, and/or personnel to manage and dispose of information in an IMS integrity management system, and/or, for example, any of the components described on Fig. 2, and which may be located locally or remotely in any geographic location, mobile or otherwise) controls

- 6 042682 on tax-related events and alerts, creates alerts and provides solutions based on grouped events generated from the data management system. The control center also provides links to external operational support and personnel and resources. The DMS data management system is also described below in another embodiment with reference to FIG. 6.

The computational models and algorithms used in the IMS integrity management system are not limited to any particular model or algorithm. Instead, it should be understood that any number of solutions can be used in this system. However, as an example, a data mining algorithm, which is a set of heuristics and calculations, creates a data mining model from the data. To create a model, the algorithm first analyzes the provided data and looks for types of patterns or trends. The algorithm uses the results of the analysis to determine the optimal parameters for creating a data mining model. These settings are then applied to the entire dataset to extract actionable patterns and detailed statistics. The mining model generated by the algorithm from the collected data can take many forms, including a set of groups (eg, grouped events) describing the relationship between instances (eg, events) in the data set; a decision tree that predicts an outcome and describes how different criteria affect that outcome. Using data mined by algorithms, the system is able to apply historical data and improve accuracy over time. Accuracy can also be aided by human verification at the scene and the use of alerts generated by the system.

In FIG. 4 shows another exemplary diagram of an integrity management system according to an embodiment of the invention. The diagram shows the flow of data from initial detection and data collection in the upstream, midstream and downstream sectors throughout the excise tax refund, which can be carried out as a result of the monitoring and warnings provided by the CCC control center. Within each stream (sector) there are several technologies, resources and generations of resources. These technologies are not merged and therefore not tracked together. Integration of collected data interfaces between different technologies and systems provides communication between technologies and systems with different protocols and integrates external systems. The integrated data is formatted, stored and analyzed for use by the CCC (command and) control center. The CCC Control Center provides an overview of the collected data by exercising control over the data provided by the DMS data management system, acting as a GUI with functions for displaying reports on the screen and for displaying KPIs, tax reports and/or management functions.

In FIG. 5 shows an exemplary embodiment of communication between a data management system and a control center according to an embodiment of the invention. The DMS data management system, in one embodiment, provides real-time data, event classification, and recommendations to the CCC control center based on the analyzed collected data, as described above and will be described later. The CCC Control Center confirms the event classifications and responds by sending a notification to the DMS data management system, which can be securely logged with a timestamp. The CCC Control Center also manages events and alerts, generates alerts, and provides solutions based on grouped events generated by the DMS. Notifications and warnings can be sent, for example, to personnel located in the CCC control center or located remotely using any number of interfaces. Interfaces may convey information in the form of visual information, audio information, or in any other form, and may be transmitted by mobile devices as well as stationary devices. The control center also provides links to external operational support and personnel and resources. As described below, the DMS data management system can also be used in another embodiment to filter and transform data, extract/annotate data, perform data correlation, data reconciliation, and data classification.

In FIG. 6 is an exemplary diagram of an integrity management system according to an embodiment of the invention. An IMS integrity management system coupled to an excise tax refund platform via an excise platform interface (wherein said platform is primarily a software-based platform) includes, but is not limited to, a DMS data management system, a data integration module (or enterprise communications platform), gateway interface, and sensors or data collection devices used to collect data from the upstream, midstream and downstream sectors, along with various systems that store and provide data from future partners, franchisees and subsidiaries of the legal entity (not shown). An IMS integrity management system may also include or cover external resources, reservoir and resource management systems, predictive and prescriptive analysis applications, evidence-based event management systems, and existing legacy systems. It should be understood that the IMS integrity management system is not limited to the components described and is not required to include each of the components depicted in the non-limiting and exemplary embodiment. For example, a supervisory control and data acquisition system (ICS such as SCADA) may collect data instead of a gateway interface. As stated above, data can be stored in one repository or multiple repositories. The gateway can also be unmanned aerial vehicles having the same capabilities as a fixed gateway, coupled with supervisory control and data collection and collecting information directly from sensors or data collection devices at the upstream, downstream and midstream levels.

The IMS integrity management system monitors and manages or interfaces with at least one entity in the oil and gas supply chain. An entity may include, but is not limited to, a legal entity, future partners, franchisees, subsidiaries, and/or a tax authority. An excise tax management system and method for identifying and reconciling inconsistencies between tax documentation, production volumes and operational reports from various entities. The IMS integrity management system collects heterogeneous, unstructured and disparate data from sensors, data acquisition devices and auxiliary surveillance systems in the upstream, midstream and downstream sectors of the oil and gas infrastructure (pipelines), to store and process the collected data using the information of oil and gas infrastructure systems. Data is also collected through subsidiaries, franchisees and future partners, an enterprise resource planning system, or other financial management systems such as consumer-developed legacy applications. Data collected from subsidiaries, franchisees, and future partners may include, for example, invoice, payment, and cash management data. The data is structured for additional processing and analysis, and the integrity of the structured data is verified and protected to prevent falsification. Over time, the data is sent to the DMS in another embodiment for filtering/transformation, extraction/annotation, correlation, matching, classification, and storage.

In particular, the collected data will be received and processed in real time and sent to the DMS data management system. The DMS data management system in this embodiment includes a filtering and transformation module, an extraction/annotation module, a correlation execution module, and a classification module. Also in the DMS data management system is the data warehouse and the operational data warehouse. The DMS data management system is responsible for filtering and transforming data collected and captured by sensors, data collection devices, subsidiary, franchisee and/or future partners (which may be secure and grouped); extraction and annotation of filtered and transformed data; performing correlation of extracted and annotated data; and classification of correlated data. The classified data is then sent to the data warehouse and the live data warehouse for storage.

The DMS data management system is also responsible for transferring (and storing) the data stored in its data store and live data store to the interface of the excise platform. The excise platform interface includes, for example, a tax trigger identification module, a real-time reporting module, a key performance indicator (KPI) compliance module with tax law requirements, and a summary data building module. The excise platform interface is the boundary between the DMS data management system and the excise tax refund platform. The excise platform interface calculates and formats excise tax estimates based on a wide variety of data including, but not limited to, for example, large operational and financial data, or sales of fuels or derivative products by different entities along the oil and gas supply chain. The calculated and formatted data is identified as a taxable transaction for subsequent approval, and feedback on tax related KPIs is sent to the KPI dashboard (described below) in the excise tax refund platform. In particular, the excise platform interface identifies taxable transactions for reconciliation in the tax identification module, calculates and formats data in the operational reporting module, provides formatted data feedback in the tax compliance module, and generates summary data at the output of the tax identification module, the operational reporting module and the tax compliance module in the data construction module. Additionally, the excise platform interface receives data (which may be secure and grouped) generated by the DMS, thereby allowing an entity to compare and reconcile at least one of the following: excise tax, tax collection, and a KPI created by another entity/others. subjects. This interface allows the IMS integrity management system to provide built-in cross-checking and

- 8 042682 reconciliation of data relating to taxes between independent reporting sources. Ultimately, this provides transparency in the payment of taxes to ensure that fraud can be minimized. As an example, tax KPIs and related tax data are complex data and must be adapted in near real time, according to specific rules provided by government tax principles. For example, if the volume of oil sold is 5,000 barrels, the tax rate could be 5%. When the amount of oil sold is 500,000 barrels, the tax rate is only 3%. The tax refund platform complies with all the rules for processing the data provided by the DMS related to taxes in order to create, based on the provided rules, the corresponding taxes that must be paid. Another example occurs in the downstream sector, where a gas station may report a dollar amount of sales that does not match the amount of product distributed to the location.

The excise tax refund platform associated with the IMS includes, but is not limited to, a financial transaction correlation engine, a data analytics module (e.g., descriptive, diagnostic, proactive, and prescriptive analytics), a KPI or reporting dashboard, a discovery, reporting, and custom data publishing, another system interface module, web portal, mobile apps, workflow engine, deal archive, deal processing, and deal repository. The excise tax refund platform receives summary data from the excise platform interface (which received secure and accurate tax-related data from the DMS, which is part of the IMS) to identify and reconcile inconsistencies between the summary data automatically generated by the excise platform interface and the corresponding tax return, created independently or manually (for example, at the level of subsidiaries or corporate level or by any entity involved in the oil and gas supply chain). The excise tax refund platform also includes a transaction repository storing the identified and matched data from the correlation processor, a transaction processor for linking the identified and matched data, a transaction archive storing the archived identified and matched data from the correlation processor; and a data analysis module receiving processed and archived data for descriptive, diagnostic, predictive, and prescriptive analysis. The data sent to the data analysis module can be entered into a predictive and prescriptive analysis module (application for predictive and prescriptive analysis), using machine learning to identify a sequence of measurements (Fig. 8A) or calculated data classified as events requiring some action and /or reporting. The classification of an event previously provided by the data management system can be validated (by a human operator or machine) and the results sent to a predictive and prescriptive analysis module to improve the training data set for the learning algorithm, allowing it to learn over time. With the help of machine learning, the IMS integrity management system will learn to determine which sequence of event measurements, taken in aggregate, will indicate the occurrence of a particular event or group of events. With the help of learned events, the system is able to apply historical data and improve accuracy over time. Tax reports from the Excise Tax Refund Platform provided by oil and gas subsidiaries, partners, and franchisees may include information about past returns, their consolidations, and future projections. Accordingly, the excise tax refund platform allows tax management with an external interface for taxpayer access, unified tax documentation and a volume production and reconciliation repository, a built-in data analysis module and a reporting dashboard for the tax department, an integrated and centralized system for managing and collecting excise tax on oil and gas, and to identify and reconcile inconsistencies between tax documentation, production volumes and operational reports, thereby providing efficient excise tax collection. In particular, in one embodiment, during the tax reconciliation stage, the system automatically checks and rechecks the manually generated return against the automatically collected data (and securely converted and used to create applicable aggregated tax related data capable of creating a secure and legally valid tax return). tax return for verification purposes). It should be noted that one particular advantage of the IMS according to the present invention when interfaced with a tax refund platform via an excise tax platform lies in the quality of the data provided to said excise platform. IMS not only collects data in a secure manner from various sources, but also generates secure and accurate data, applicable to create secure and reliable aggregated data and report, applicable for effective tax retrieval and correction of discrepancies in the oil and gas supply chain. IMS also has the advantage of being able to effectively monitor and manage the activities of all participants in the supply chain (subsidiaries, franchises, etc.) at the corporate level. All secure collected data provided by the IMS system

- 9 042682 corporate level, will be used to create a secure and reliable report and KPI for effective comparison with reports and KPIs provided at the level of subsidiaries or at the franchise level. By comparing the reliable and secure reporting provided by IMS at the corporate level with reports from subsidiaries and franchisees, effective management within the oil and gas supply chain will allow the corporate layer to better see wrong or inefficient elements, as well as see ways to correct inconsistencies in the supply chain oil and gas.

In FIG. 7 shows an exemplary interface diagram according to one embodiment of the invention. As shown, the interface (gateway) receives data from one or more different sources. For example, data collected from sensors in the upstream, midstream and downstream sectors and processed by production control systems (such as SCADA) is transmitted to the gateway interface (shown here as part of the production control system). In an alternative embodiment, the gateway replaces the production control system and collects data directly from upstream, midstream and downstream sector sensors. The gateway interface converts (e.g., sorts, formats, and modifies) the collected data into secure and formatted data that is compatible with the system, and in particular the data integration module (or ERP), before sending it to the DMS for analysis by the integrity management system IMS. In an alternative embodiment, the gateway may be a construct, such as unmanned aerial vehicles, securely collecting and directly verifying data from sensors and data collection devices in the upstream, midstream, or downstream sectors.

In FIG. 8A-8D depict exemplary sensor measurements and sensors collecting data along a supply chain in accordance with an embodiment of the invention. The collected data is processed by the integrity management system, and the grouped and structured data is created or directly published as a tax report, financial report, KPI report, secure tax return form, or any report applicable to the preparation of the final tax return. Once a particular sequence of measurements (or sequence of events) associated with an event description has become known (i.e., learned by an application for predictive and prescriptive analysis), events can be tagged in real time with a probability score indicating the probability that the sequence of unfolding measurements will result in an identifiable event (such as a taxable event or a sequence of taxable events. In the figures, the shaded boxes represent the values obtained from a given sensor. Fig. 8A shows an exemplary number of sensors l...m, made with Figures 8B, 8C, and 8D show an exemplary sequence of events in which the data collected over time t represents a low probability, a medium probability, and a high probability, respectively, of an event occurring (herein referred to as probability events). The probability of the event is sent to the data management system DMS, whereby the excise platform interface and the excise tax refund platform identify a taxable event such as 500 barrels of fuel sold at location X on a given date.

To improve efficiency, with the help of a predictive and prescriptive analysis module, based on past events contained in historical measurement and event data, models can be created from historical data and used to help predict future events (i.e. taxable events) before how sensors and data collection devices will start logging data. By using this proactive data, the excise tax refund platform and personnel working on the excise tax refund platform can be alerted to predictable taxable event zones identified by the system using data in the system such as time of day, day of the week, month, or specific dates , previous sequences of events, etc. From the above it becomes clear that the IMS integrity management system is able to capture the development of events related to taxes, and connect them together to provide history for analysis and improve data analysis in the DMS data management system. Based on prior knowledge of past events, historical data, and verification that the events actually occurred, such as pump volumetric performance, fuel transported and barrels of fuel, payment and cash management data, and generation invoices, future events can be more accurately predicted and the events themselves can be better interpreted in monitoring and analysis. Additionally, due to the fact that the IMS integrity management system is inherently based on forecasts and prescriptions, it is able to mitigate the impact of human corruption, such as operating personnel in a subsidiary, a third-party company, a franchise enterprise, etc. less likely to provide falsified tax documents given the control and management of the excise tax refund platform. Accordingly, it will become increasingly difficult for people involved in illegal activities to avoid detection by deleting data, changing data, bribing data control personnel, and so on.

To a large extent, to prevent these types of situations, the integrity management system provides: secure and tamper-proof data that cannot be deleted alerts based on the correlation of grouped events notifying of a high probability of falsification (for example, falsification of information related to taxes ), while the specified falsification will be displayed to the operator and fixed in the form of warnings, which are also not amenable to forgery and cannot be deleted. Alternatively or in addition, the system itself can intervene instead of personnel to identify and send urgent information to external authorities such as the tax department, the legal entity that manages the corporation, etc. Accordingly, the role of the system is to provide an alternative to human error and incompetence when such fraudulent information is discovered.

Further non-limiting examples of the IMS integrity management system are described below in relation to the midstream and downstream sectors. In the midstream sector, illegal tax-related activities are typically carried out by modifying collected data and/or falsifying records and materials such as tax reports and tax returns. For example, when receiving a receipt in a taxable transaction, such as receiving a receipt for a purchase of 500 barrels of oil, the receipt can be forged in such a way that the excise tax is minimized. At the same time, during the preparation of the tax report, information related to a taxable transaction will reflect a forged receipt. As a countermeasure and in accordance with the objectives of the IMS integrity management system, several sensors and/or data collection devices can be installed on oil tanks, which will monitor and collect data from them. For example, each container of oil may include a sensor that detects the movement of the container of oil from the distribution center to the retail outlet, indicating the purchase of the container / containers of oil. The IMS Integrity Management System can be used to monitor and collect data related to a transaction as it progresses. The collected data from sensors and data acquisition devices will be sent to the appropriate gateway (FIG. 6) or ICS production control system and transferred to the data management system and further to the CCC control center, as described earlier in this document. Additional data collected should be updated so that they can be interpreted to provide conclusions and recommendations. For example, if the sensor(s) or data collection device(s) only detect the purchase of a container(s) of oil once a week, the sensor(s) and data collector(s) may not capture the purchase activity for the remaining six days in week. On the other hand, if the purchase of oil container(s) is measured daily, twice a day, the sensor(s) and data collection device(s) will be able to more accurately detect and calculate the purchase of oil container(s) (or any other type of data) indicating the implementation taxable transaction or activity. An unmanned aerial vehicle or personnel involved in locating the sensor/sensors and the data collection device/devices can alternately or simultaneously monitor the regional location, images from the local camera can be collected, and the system can be notified of the activity.

Another non-limiting example of data in the midstream sector is a tanker truck transporting crude oil and oil product. In this example, the data collected is the GPS information generated by the route traveled by the tanker and the volume of the tanker's contents. If data collected over time indicates, for example, that a tanker truck has been standing still longer than expected, or that the volume of the tanker truck has changed, this may indicate ongoing or ongoing illegal activity. For example, a change in the volume of the contents of a tanker truck may indicate that someone is trying to avoid reporting the event as a taxable transaction. In another example, a tanker truck may stop at an overnight rest area. Since these areas are known to be regularly shut down over an extended period, volume sensors on the tanker can be activated to monitor changes in the contents of the tanker. Any change detected by the sensors can be forwarded through the DMS data management system to the CCC control center after data analysis has been performed. The system learning processors will receive information about the area and the expected activity in that zone, and apply this information in further analysis. As before, such activity may indicate that someone is trying to avoid a certain event, the consequence of which is the payment of taxes.

In the downstream sector, a non-limiting example is provided in which the collected data includes the volume produced at the processing plant. The volume data can be related, for example, to the number of tank trucks needed to transport the contents of the tank trucks (fuel) to retail stores. It is understood that after the fuel arrives at retail stores, it is loaded into store tanks for storage. In this case, there is a transfer of volume and sale of fuel. Sensors and data collection devices can then be used to measure

- 11 042682 changes in the respective volumes and measurements of cash generated by the sale of fuel. If volumes and sales do not match, this may indicate illegal activity, such as creating falsified documents in order to evade or avoid a taxable event. This information may also be useful for re-levying or reconciling taxes, for estimating the amount of fuel required in a particular region, and so on. As it should be understood, data is not only collected but also stored in a repository and converted into a sum of grouped events that can be linked, used or analyzed for prescriptive or proactive action.

In FIG. 9 shows an exemplary interface diagram according to one embodiment of the invention. The interface, which in this application is also referred to as a gateway or gateway interface, connects data sensors located throughout the upstream, midstream and downstream sectors to external sources such as an ESB enterprise service bus or an IMS data integrity management system through a data integration module. As shown, the gateway is divided into three layers, including: (1) a computer (for signing and storage) communicating with production control systems (such as SCADA, OPC, AS-i MODBUS and Ethercat), drivers can be a combination of physical interfaces and software; (2) business rules engine (BRE) that performs correlation, security, authentication, filtering, negotiation, ensures the impossibility of forgery and creates data containing key values, BRE based on the collected data will create associations with data collected in objects, create events , based on the lack of integrity of objects, create warnings based on events, or events based on thresholds, or business rules, or trends; and (3) interfaces to external systems using, for example, HTTPS, SSL, or any other software or hardware protocol.

The gateway interface provides, among other features, a mechanism for converting the collected data into a format that is more secure and compatible with an external system to which the converted data or objects or events or alerts generated in the gateway will be sent. For example, the gateway interface will secure the data collected from sensors and/or data collection devices, as well as format the collected data to make it compatible with the data integration system before it is used in the IMS integrity management system, especially at the DMS data management system level. The gateway interface interfaces with external systems using, for example, protocols such as HTTPS, SSL, etc. External interfaces include, but are not limited to, an ESB enterprise service bus or an ICS production management system such as the IMS Gateway Management System described herein.

At the driver level, drivers communicating with external systems, such as an ICS system, may be hardware, software, or a combination of the two. The hardware and software are preferably tamper-resistant and secure in order to prevent attacks on the physical hardware as well as malicious attacks on the software, such as by hackers, injecting unwanted data, and the like. The data that will be generated and created in the gateway interface will be more secure and will provide enhanced features in addition to data collected from various data repositories such as SCADA or ICS. The protected and enhanced data will then be provided to the IMS integrity management system and contribute to the creation of grouped events. The Gateway will also verify that the data received from the sensor(s) and data acquisition device(s) is authentic and not tampered with by external sources or otherwise. In other words, the gateway will first have the ability to authenticate received data before securing the data and adding additional properties. This will ensure that data to be protected and enhanced is authenticated before it enters the IMS integrity management system and prevents corrupted data from being sent to the IMS integrity management system. One disadvantage of existing systems in the oil and gas supply chain is the incredibly large amount of data. If the system becomes contaminated or infected with bogus, spurious, fabricated, or inaccurate data, the collected data will not be reliable and any events or grouping events generated in the IMS Integrity Management System could potentially compromise the reports generated by grouped events. Accordingly, any data intended to be accessed or used in the IMS integrity management system (via the data integration module) via the gateway should be as secure and accurate as possible. An example of performing authentication of the data that will be entered into the gateway is to collect several times more information from the sensors in a short period of time than they should collect, and to verify that the collected data always has the same essence (for example, temperature data are collected ten times within 30 s and the value does not change much, in which case the data appears to be correct). Another example of performing authentication or validation of data is to add an electronic system or mechanism to the sensor,

- 12 042682 protecting the data from falsification or rerouting of transport and protecting the sensor by any means, while the data collected from the sensor and then sent to the gateway will be as accurate as possible.

The gateway interface collects data through either physical interfaces leading to industrial sensors using industrial communication protocols such as OPC or Ethercat, or through virtual (i.e. software) interfaces leading to existing monitoring or control systems such as SCADA. Interfaces are driven, for example, by software drivers that can be dynamically loaded or unloaded depending on physical or virtual requirements. For example, if there are three OPC-driven devices and one Ethercat-driven device physically connected, there will be three OPC drivers and one Ethercat driver.

When the data reaches the gateway interface, the BRE business rules engine creates new control data by correlating the collected data, filtering non-essential data such as non-security events, validating access to read/write it/to the driver layer in the integration layer (in both directions), and applying security/access/authentication rules, using an external system if necessary. However, it should be understood that these functions are by way of example only and BRE is not limited to such functions.

At the interface level, the software in the gateway interface can also interact with external systems based on control requirements. For example, the interface may include an email interface, a web interface, and so on. The interface layer may also interface with the ESB as a messaging system (eg, using a protocol such as REST over HTTPS) to integrate data from all interfaces of the gateway and external systems into the storage component of the IMS integrity management system. It should also be understood that although the diagram shows an interface leading to a gateway interface, the gateway interface may also be directly connected or be part of an IMS integrity management system.

The ESB Enterprise Service Bus software is a messaging system similar to IBM™'s MQueue Series and BMC Control products. The ESB software, which in this embodiment is referred to as the data integration module that is part of the IMS integrity management system (although it should be understood that the ESB may also be a separate entity), may be an application such as Open ESB developed by Sun. Microsystems™, or WSO2 ESB. A programming language using JAVA technology may be used as a programming language for obtaining such software.

The BRE Business Rules Engine (second layer) acts as transformative processing of the collected data and applies rules that can be executed in such a way as to represent a specific element of interest, such as a potential security breach, or to regroup all data relevant and applicable for recharging taxes. BRE controls all activity and measurement points of loaded drivers, along with any physically or virtually attached devices. With real-time access to all these points, BRE can create new measurement points or data that can be used to create grouped events and grouped data in the IMS integrity management system. Based on collected data, BRE will also create associations with data collected in objects, create events based on the lack of integrity of objects, create event-based alerts or events based on thresholds or business rules or trends, create clusters tax-related data or a group of tax-related data. For example, measuring point A on a physically attached device (such as a temperature sensor) and measuring point B (such as a variable from an external SCADA software system) at certain thresholds can create new data based on both measuring point A and measuring point B. For example, new data C may be created, where the new data C is an addition to measurement points A and B and may constitute an event. This allows BRE to correlate data to better understand events as they occur. The events generated in the gateway are based on data collected from sensors, data collection devices, or ICS systems. Properties have been added to this data, which has been verified for accuracy before entering the gateway, to provide improved data.

As another possibility, if the sensors, data acquisition devices, or ICS systems are not reliable or unable to verify the accuracy of the data, the verification step is performed in the gateway. The events created in the gateway will be applicable in the DMS of the IMS system to create grouped events. Grouped events are used in IMS to create secure and reliable data related to taxes or KPI data or a secure and reliable report related to the management of entities in the oil and gas supply chain, and in the context of the present invention, allow effective control over activities of subsidiaries and franchisees, for example, at the corporate level, but also to reduce discrepancies in the oil and gas supply chain, but most importantly, allow efficient tax re-collection at the corporate level as well as at the state level.

BRE may also operate autonomously if sufficient physical and/or virtual information is available to determine, based on the collected data, the events applicable to create grouped events in the IMS integrity management system and secure and reliable tax-related data or KPI data, or a secure and reliable report related to the management of actors in the oil and gas supply chain without relying on any external system, while the grouped events will be applicable to define actions such as alerts, to identify or alert about security breaches and other actions, protected and reliable data related to taxes or KPI data or a secure and reliable report related to the management of entities in the oil and gas supply chain will be applicable to correct inconsistencies or inaccurate data from different sources that will affect revenues from tax recollection or on good governance in the oil and gas supply chain. The definition(s) of grouped events and secure and trusted tax related data or KPI data or secure and trusted report is managed by the data management module of the IMS integrity management system as part of the learning entity of the system. BRE stores and queues this data as needed, and encrypts or signs each data to ensure that the data is complete, authentic, accountable, irrefutable, and secure from external access, modification, tampering, and destruction. It should be understood that one or more features may be used, none or all of these features, in addition to another form of functionality. The encrypted data can then be accessed by external systems based on, for example, the security profiles of the system requesting the information.

In FIG. 10 shows an exemplary embodiment of an interface processing path according to one embodiment of the invention. Gateway interface drivers collect data from a variety of sources, including, but not limited to, physical sources, programmable logic controllers (PLCs) and remote terminals (RTUs), and any other type of source. The BRE business rules engine processes the data, correlates the data, and creates events or a sequence of events from the data, as detailed above. Data and events may optionally be signed by a hardware or software security module (HSM or SSM). Events and enhancements may be stored in a secure repository or data store. The gateway then checks to determine where the data will be sent (whether the IMS system is available), for example, to the IMS integrity management system or to another external system. If an IMS integrity management system is available, then the data or events are formatted and asserted for use by the integrity management system. Data sent to an external system can be formatted and validated, depending on the requirements of the external system. The data or events passing to the IMS integrity management system are sent to the data integration module, storing the data or events, retrieving the data from the storage, creating, for example, a data structure containing key values from the data, sorting the structured data, and parsing the structured data using computational models and algorithms for identifying correlations between data applicable to create grouped events in the IMS integrity management system. The data is also checked for structured data integrity and structured data security to prevent falsification. The data interface may be an independent interface or part of a data management system. If the interface is separate, the data then passes to the data management system for processing according to the embodiments described above.

Accordingly, the present invention provides various systems, servers, methods, media, and programs. Although the invention has been described with reference to several exemplary embodiments, it should be understood that the words used are descriptive and illustrative, but not limiting. Changes may be made within the scope of the appended claims, as currently claimed and as modified, without departing from the scope and spirit of the invention in its aspects. Although the invention has been described with reference to specific means, materials, and embodiments, the invention is not intended to be limited to the disclosures; instead, the invention embraces all functionally equivalent structures, methods, and uses falling within the scope of the appended claims.

Although a computer-readable medium may be described as a single medium, the term computer-readable medium includes a single medium or multiple media such as a centralized or distributed database and/or associated caches and servers storing one or more instruction sets. The term computer-readable medium should also include any medium capable of storing a thread, encrypting, or containing a set of instructions for execution by a processor or causing a computer system to execute one or more of any of the embodiments described herein.

The computer-readable medium may comprise a permanent computer-readable medium or media and/or comprise a temporary computer-readable medium or media. In a certain non-limiting exemplary embodiment, the computer-readable medium may include a mass storage device, such as a memory card or other module, accommodating one or more non-volatile read-only storage devices. In addition, the computer-readable medium may be random access memory or other volatile, writable storage device. Additionally, the computer-readable medium may include a magneto-optical or optical medium such as a disk or magnetic tapes or other data storage device for the purpose of collecting carrier signals, such as signals sent over a transmission medium. Accordingly, the description is intended to include any computer-readable medium or other equivalents and future generations of media in which data or instructions may be stored.

Although the present application describes specific embodiments that may be implemented as code segments in computer-readable media, it should be understood that dedicated hardware implementations such as ASICs, programmable logic arrays, and other hardware devices may be built to implement one or more embodiments described in this document. Applications, which may include the various embodiments set forth herein, may include a wide variety of electronic and computer systems. Accordingly, the present application may cover software, firmware, and hardware implementations, or combinations thereof.

Although this technical description describes the components and functions that may be implemented in certain embodiments, with reference to certain standards and protocols, the invention is not limited to these standards and protocols. Such standards are periodically superseded by faster or more efficient equivalents that have essentially the same functionality. Accordingly, superseding standards and protocols that have the same or similar functionality are considered to be their equivalents.

The illustrations of the embodiments described herein are intended to provide a general understanding of the various embodiments. It is intended that the images will not serve as a complete description of all elements and features of the device and systems using the structures or methods described in this document. Many other embodiments may become apparent to those skilled in the art upon consideration of the invention. Other embodiments may be used and derived from the present invention so that structural and logical substitutions and changes may be made within the scope of the invention.

Additionally, the images are for representational purposes only and may not be drawn to scale. Some proportions in images may be exaggerated, while other proportions may be minimized. Accordingly, the description and figures are to be regarded as illustrative and not restrictive.

One or more embodiments of the invention may be referred to herein, individually or collectively, by the term invention for convenience only and without intending to voluntarily limit the scope of this application to any particular invention or novel idea. Moreover, although certain embodiments have been depicted and described herein, it should be understood that any subsequent construction intended to achieve the same or similar purpose may be replaced by the depicted specific embodiments. This invention is intended to cover any and all subsequent adaptations or variations of the various embodiments. Combinations of the above embodiments and other embodiments not specifically described herein will become apparent to those skilled in the art upon review of the description.

The abstract of the invention is provided in order to satisfy the requirements of 37 C.F.R. §1.72(b) and is filed with the understanding that it will not be used to construe or limit the scope or meaning of the claims. In addition, in the foregoing detailed description, various features may be grouped together or described in one embodiment to simplify the invention. This invention should not be construed as implying that the claimed embodiments require more features than are expressly stated in each claim. Instead, as reflected in the following claims, patentable subject matter may address less than all of the features of the described embodiments. Thus, the following claims are included in the detailed description, with each claim standing alone as it defines a separately claimed

- 15 042682 object of the invention.

The foregoing subject matter is to be regarded as illustrative and non-limiting, and the appended claims are intended to cover all such modifications, improvements, and other embodiments falling within the true spirit and scope of the present invention. Thus, to the maximum extent permitted by law, the scope of the present invention shall be determined by the broadest possible interpretation of the following claims and their equivalents, and shall not be limited by the foregoing detailed description.

Claims (24)

1. A system for managing data transferred between the first entity and the second entity in the oil and gas supply chain relating to taxes to detect fraud or theft of oil and gas resources moving along the supply chain, the first entity being a corporate entity and the second entity representing is at least one of a subsidiary, a franchisee, and a third party contractor associated with but independent of the first entity, comprising a data integration module configured to collect data from a first plurality of production management systems configured to collect first data obtained from a plurality of sensors and related to oil and gas resources owned by the first entity or under the control of the first entity; and a second plurality of production management systems configured to collect second data obtained from a plurality of sensors associated with the oil and gas resources of the first entity, the second data being obtained when the oil and gas resources are under the control of the second entity, the second data being collected at points in the oil supply chain and gas of oil and gas resources that are downstream in the supply chain and follow the receipt of the first data, while the sensors are configured to perceive data related to oil and gas resources moving along the supply chain and related to at least one of the following: temperature , density, flow meter, humidity, volume, gravity, chemical composition, pressure, weight, pipeline pressure change, difference in vehicle weight or fuel volume, GPS positioning, vehicle position synchronization, geographic region, imaging, pump displacement, amount of fuel transported, barrels of fuel, and thermal imaging; at least one gateway configured to convert first data collected from the first set of production control systems into secure first data and group said first data and convert second data collected from the second set of production control systems into secure second data and group said second data, wherein the first and second data are protected using at least a timestamp and attributes of said data, wherein the first and second data are grouped according to a sequence of events, in which each event contains a measurement taken over time in the chain supplying a plurality of sensors to first and second plurality of production control systems, wherein each of the first and second data relates to tax-related events that require action or reporting; and a data management system configured to receive secure and grouped first data from at least one gateway and further transform it to create, for a corporate entity, at least one of the following: tax assessment and tax information related to a key performance indicator ( KPI), and receiving second data from at least one gateway and further transforming it to create at least one of the following: tax assessment and tax information related to a key performance indicator (KPI) related to at least one of the following: a subsidiary, a franchisee, and a third-party contractor, wherein the tax-related data management system is configured to report the secure and grouped first and second data generated by the data management system to a control system configured to generate a first tax return from protected and grouped first or second data based on tax-related events, wherein the system for managing tax-related data receives from the second subject a second tax return based on the same tax-related events, wherein the system for managing the data related to taxes is configured to compare the first and second tax returns to verify the accuracy of the second tax return corresponding to the first tax return and reconcile events related to the taxes on which the first and second tax returns are based to detect possible fraud or theft. 2. The system according to claim 1, characterized in that the protected and grouped first and second data are additionally to be sent to the interface of the excise platform, containing a tax identification module for identifying taxable transactions for approval; an operational reporting module configured to calculate and format secure and grouped first and second data; a tax compliance module to provide feedback on the formatted secure and grouped first and second data; and a data builder to combine the secure and grouped first and second data output from the tax identification module, the operational reporting module, and the tax compliance module. 3. The system according to claim 2, characterized in that the interface of the excise platform is configured to receive secure and grouped first and second data generated by the data management system, thereby allowing the third entity to compare and agree on at least one of the following: excise tax, tax collection and KPI created by at least one of the first and second entities. 4. The system according to claim 3, characterized in that the data management system includes filtering and converting protected and grouped first and second data; extraction and annotation of filtered and transformed protected and grouped first and second data; performing a correlation of the extracted and annotated secure and grouped first and second data; and performing a classification of the correlated secure and grouped first and second data and sending the classified protected and grouped first and second data to the data store and the live data store. 5. The system according to claim 3, characterized in that the system is configured to interface with the tax refund platform by means of an excise tax platform containing a correlation processor that receives summary protected and grouped first and second data from the interface of the excise platform to identify and reconcile inconsistencies between the summary protected and grouped first and second data automatically generated by the excise platform interface, and the corresponding declaration from the first and second tax declarations. 6. The system of claim 5, wherein the tax refund platform further comprises a transaction repository configured to store identified and matched data from the correlation engine; transaction processor for linking identified and matched data; a transaction archive configured to store the archived identified and matched data from the correlation processor; and a data analysis module receiving the processed and archived data for descriptive, diagnostic, predictive, and prescriptive analysis. 7. The system according to claim 1, characterized in that the first and second data collected are to be marked as related to a tax event before being protected and grouped. 8. The system according to claim 1, characterized in that a plurality of production management systems are designed for the upstream, midstream and downstream sectors of the oil and gas supply chain. 9. The system of claim 8, characterized in that each of the plurality of production management systems for the upstream, midstream and downstream sectors is grouped as a single data repository. 10. The system according to claim 8, characterized in that the collected first data from each of the plurality of production control systems are to be sent to the data integration module in the form of at least one of the following: data formatted separately, data formatted jointly, data with protected attributes, read-only data, and tamper-proof data. 11. The system according to claim 1, characterized in that the transmission of the collected data from the production control system to the data integration module is carried out via secure communication to ensure the integrity of the collected first and second data. 12. The system according to claim 1, characterized in that the data integration module contains a data store for storing the collected first and second data; a data acquiring device for acquiring first and second data stored in the data store and creating a data structure containing key values from the acquired data; data sorting device for sorting structured data, - 17 042682 received from the device for data acquisition, for analysis and a data analyzer designed to analyze structured data to identify events, check the integrity of structured data and protect structured data in order to prevent falsification, while the data integration module is configured to create grouped events on based on the analyzed data. 13. A method for managing data transmitted between a first entity and a second entity in an oil and gas supply chain related to taxes to detect fraud or theft of oil and gas resources moving along the supply chain using the system according to any one of claims 112, wherein the first the subject is a corporate entity, and the second entity is at least one of a subsidiary, a franchisee, and a third party contractor associated with but independent of the first entity, including collecting first and second data in a data integration module, including obtaining first data, associated with oil and gas resources owned by the first entity or which are under the control of the first entity of the plurality of sensors using the first plurality of production management systems; and collecting second data obtained from a plurality of sensors associated with the oil and gas resources of the first entity using a second plurality of production management systems, the second data being obtained when the oil and gas resources are under the control of the second entity, the second data being collected at points in the oil supply chain, and gas of oil and gas resources that are downstream in the supply chain and follow the receipt of the first data, while the sensors are configured to perceive data related to oil and gas resources moving along the supply chain and related to at least one of the following: temperature, density, flow meter, humidity, volume, gravity, chemical composition, pressure, weight, pipeline pressure change, difference in vehicle weight or fuel volume, GPS positioning, vehicle position synchronization, geographic region, imaging, volumetric pump performance, amount of fuel transported, barrels of fuel, and thermal imaging; at at least one gateway, converting said first data collected from a first plurality of production control systems into secure first data and grouping said first data and converting second data collected from a second plurality of production control systems into secure second data and grouping said second data , wherein the first and second data are protected using at least a timestamp and attributes of said data, wherein the first and second data are grouped according to a sequence of events, in which each event contains a measurement taken over time in the supply chain by a set sensors of the first and second sets of industrial control systems, while each of the first and second data relate to events related to taxes that require action or reporting; in the data management system, receiving from at least one gateway secure and grouped first data and additionally converting them to create, for a corporate entity, at least one of the following: tax assessment and tax information related to a key performance indicator (KPI), and receiving second data from at least one gateway and further transforming them to create at least one of the following: tax assessment and tax information related to a key performance indicator (KPI) related to at least one of the following: a subsidiary, the franchisee and the third party contractor, the method further comprising sending reports from the tax related data management system about the protected and grouped first and second data generated by the data management system to the control system configured to generate the first tax return from the protected and grouped first or second data based on tax related events, wherein the system for managing tax related data receives from the second subject a second tax return based on the same tax related events, wherein the system for managing tax related data taxes, is configured to compare the first and second tax returns to verify the accuracy of the second tax return corresponding to the first tax return, and reconcile events related to the taxes on which the first and second tax returns are based to detect possible fraud or theft. 14. The method according to claim 13, further comprising sending secure and grouped first and second data to the interface of the excise platform, whereby using the interface of the excise platform, taxable transactions are identified for reconciliation using the tax identification module; calculating and formatting secure and grouped first and second data using the operational reporting module; providing feedback on formatted secure and grouped first and second data using the tax compliance module, and combining protected and grouped first and second data output from the tax identification module, operational reporting module and tax compliance module using the data construction module . 15. The method according to claim 14, characterized in that the interface of the excise platform receives secure and grouped first and second data generated by the data management system, thereby allowing the third entity to compare and agree on at least one of the following: excise tax, tax collection and KPI created by at least one of the first and second entities. 16. The method according to claim 15, characterized in that, using the data management system, filtering and converting the protected and grouped first and second data; extraction and annotation of filtered and transformed protected and grouped first and second data; correlation of extracted and annotated protected and grouped first and second data; classifying the correlated secure and grouped first and second data; and sending the classified secure and grouped first and second data to the data store and the live data store. 17. The method according to claim 15, further comprising receiving from the tax refund platform containing the correlation handler, the consolidated secure and grouped first and second data from the interface of the excise platform to identify and reconcile inconsistencies between the consolidated protected and grouped first and second data automatically generated by the excise platform interface and the corresponding declaration from the first and second tax declarations. 18. The method of claim 17, wherein the tax refund platform writes the identified and matched data from the correlation handler to the transaction repository; linking identified and matched data with a transaction processor; storing archived identified and matched data from the correlation processor in the transaction archive and receiving processed and archived data for descriptive, diagnostic, predictive and prescriptive analysis in the data analysis module. 19. The method according to claim 13, characterized in that the collected first and second data are marked as related to the tax event before being protected and grouped. 20. The method according to claim 13, characterized in that a plurality of production management systems are designed for the upstream, midstream and downstream sectors of the oil and gas supply chain. 21. The method of claim 20, wherein each of the plurality of upstream, midstream, and downstream production management systems is grouped as a single data repository. 22. The method according to claim 20, characterized in that the collected first data from each of the plurality of production control systems is sent to the data integration module in the form of at least one of the following: data formatted separately, data formatted together, data with protected attributes , read-only data, and tamper-proof data. 23. The method according to claim 13, characterized in that the transmission of the collected data from the production control system to the data integration module is a secure communication to ensure the integrity of the collected first and second data. 24. The method according to claim 13, characterized in that using the data integration module to store the collected first and second data in a data store; obtaining first and second data stored in the data store, and creating a data structure containing key values from the obtained data using the device for obtaining data; sorting the structured data received from the data acquisition device for analysis by the data sorting device; and performing structured data analysis to identify events, verify structured data integrity, and protect structured data to prevent tampering, while - 19 042682 using the data integration module, grouped events are created based on the analyzed data.