EA040908B1 - GLOBAL MANAGEMENT SYSTEM (GMS) USING PROTECTED DATA WITH ADDITIONAL ATTRIBUTES AND METHOD OF CREATING THEM - Google Patents

Description

Technical field

The present invention generally relates to a system and method for creating data compatible with an external system in the oil and gas supply chain and, in particular, to an interface and method for interacting with a secure intermediate platform to create secure and verifiable data to prevent falsification or input of unwanted data resulting from unauthorized access throughout the supply chain.

State of the art

The oil and gas industry is usually divided into three sectors; upstream, midstream and downstream as shown 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 raw 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.

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 related to resources in the upstream, midstream and downstream sectors by remotely monitoring, analyzing, predicting events for resources and providing data as an alert for decision making from any location. The term resource, as defined in this document, includes all oil and gas products and infrastructure.

The essence of the invention

The present invention, through one or more of its various aspects, embodiments, and/or specific features or ancillary components, provides various systems, servers, methods, media, and programs for interacting with compiled codes, such as, for example, Java or data mining algorithms, or a mixture of hardware and software elements to create data with additional attributes used in the global management system (GMS) related to the management of oil and gas resources. The data with additional attributes is extended data used to create events, applicable to create grouped events in a particular module of the GMS system.

The present invention generally relates to a system and method for collecting data from industrial control systems (ICS) and generating data compatible with an external system in an oil and gas supply chain, and in particular, to an interface and method for interacting with a secure intermediate platform to create secure and verifiable data to prevent falsification or introduction of unwanted data resulting from unauthorized access throughout the supply chain.

- 1 040908

In one embodiment, a method is provided for generating data in the oil and gas supply chain to be compatible with external systems, including receiving collected data from at least one of an industrial control system, a sensor, and a data acquisition device; storing the collected data in a secure intermediate hardware platform for interacting with at least one software component; and adding attributes to the collected data using a business rules engine to generate rich data, wherein at least a portion of the collected data sent to the secure intermediate platform is received from at least one of the secure/verified sensor and the secure/verified industrial control system ( ICS) connected to the first set of sensors and data acquisition devices located along the oil and gas supply chain.

In another embodiment, an interface is provided for creating data in the oil and gas supply chain for compatibility with external systems, including at least one of an industrial control system, a sensor, and a data acquisition device for receiving the collected data; a secure intermediate hardware platform for signing and storing collected data in order to interact with at least one software component; and a business rules engine for adding attributes to the collected data to create rich data, wherein at least a portion of the collected data sent to the secure intermediate platform is received from at least one of the secure/verified sensor and the secure/verified industrial control system (ICS) connected to the first set of sensors and data acquisition devices located along the oil and gas supply chain.

In yet another embodiment, a permanent computer-readable medium is provided storing a program for generating data in the oil and gas supply chain for compatibility with external systems, the program, when executed by the processor, comprising receiving collected data from at least one of an industrial control system, a sensor, and a collection device. data; signing and storing the collected data in a secure intermediate hardware platform for interacting with at least one software component; and adding attributes to the collected data using a business rules engine to generate rich data, wherein at least a portion of the collected data sent to the secure intermediate platform is received from at least one of the secure/verified sensor and the secure/verified industrial control system ( ICS) connected to the first set of sensors and data acquisition devices located along the oil and gas supply chain.

In one aspect, at least a portion of the rich data generated by the business rule engines is converted to events.

In another aspect, the extended data or events based on the extended data are signed or encrypted by at least one of the hardware or software security module(s).

In yet another aspect, the method includes securely capturing and verifying the collected data from at least one of an industrial control system, a sensor, and a data acquisition device using at least one of the secure/validated sensors and ICS.

In yet another aspect, the method includes checking the collected and verified data to confirm the accuracy of the information in the collected data prior to transmission to a secure intermediate hardware platform.

In another aspect, the method includes securing the secure intermediate hardware platform against at least one of tampering, unwanted input, and unauthorized access.

In another aspect, the additional extended data attributes include at least one protected attribute to detect modification or corruption of the extended data and to determine the authenticity of the extended data.

In one aspect, at least one software component securely sends extended data with additional attributes to a data integration module.

In yet another aspect, the business rules engine stores the extended data and queues it up in an encrypted and durable data store.

In yet another aspect, extended data with additional attributes communicates with an external system through an interface.

In another aspect, the method includes redundantly checking or deriving, averaging, and verifying the collected data from at least one of an industrial control system (ICS), a sensor, and a data acquisition device using at least one of the secure/verified sensors and the ICS to confirm the accuracy of the information. .

In another aspect, when receiving and transmitting the collected data, system drivers are used to collect data from at least one of a physical source, a sensor, a programmable logic controller, remote terminal devices, and ICS.

In yet another aspect, industrial control systems (ICS) are designed for the upstream, midstream, and downstream sectors of the oil and gas supply chain.

In yet another aspect, each of the upstream, midstream, and downstream industrial control systems is grouped into a single repository.

In yet another aspect, the collected data from each industrial control system is sent to a secure intermediate platform from at least one of the secure/validated sensors and ICS in the form of at least one of secure data, separately formatted data, jointly formatted data, data with protected attributes , read-only data, and tamper-proof data.

In another aspect, the interaction includes the transfer of the collected data from the industrial control system to the data integration module through a secure intermediate hardware platform over a secure communication to ensure the integrity of the collected data.

In another aspect, the method includes securing at least one of the secure/verified sensors and the ICS from at least one of tampering, unwanted input, and unauthorized access.

In yet another aspect, at least one of the secure/verified sensors and ICS includes at least one of self-diagnosis, self-validation, alerting, and anomaly detection, and unique identifiers to securely encrypt collected data.

In one aspect, the method includes receiving securely collected and verified rich data in a data integration module from at least one of the secure/validated sensors and ICS, and secure intermediate platform, and collecting and/or organizing rich data and events generated from rich data, into grouped events in the global management system; performing in the control center at least one of monitoring alerts, generating alerts, and providing a solution based on the grouped events generated in the data management system; displaying, in the control center, a visual representation of the grouped events; and allowing interaction through the control center to establish a message with at least one of the data integration module, the external operational support service, personnel, and production equipment.

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 symbols represent like elements on several kinds of drawings.

In FIG. 1 shows an exemplary supply chain for use in the oil and gas industry, FIG. 2 is an exemplary system for use in accordance with the embodiments described herein, FIG. 3 is another exemplary diagram of a global control system according to the described embodiment, FIG. 4 is an exemplary embodiment of communication between a data management system and a control center according to an embodiment of the invention, FIG. 5 is an exemplary diagram of a global control system according to the described embodiment, FIG. 6 is an exemplary interface diagram according to one embodiment of the invention, FIG. 7A-7D show an exemplary sequence of events in which data acquisition occurs over time to determine probability, FIG. 8 is an exemplary interface diagram according to one embodiment of the invention, FIG. 9 is an exemplary embodiment of an interface process 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 in general terms and may include computer system 102, which is indicated in general terms. Computer system 102 may operate as a standalone device or may be attached to other systems or peripherals. For example, computer system 102 may comprise 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. Computer system 102 or portions thereof may be

- 3 040908 implemented in various devices or embedded in various devices such as a personal computer, tablet computer, set-top box, personal digital assistant, mobile device, pocket computer, laptop computer, desktop computer, communication device, wireless telephone, personal trusted device, 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 memory, or any combination thereof. Of course, those skilled in the art will appreciate that computer storage 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.

The 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 connected to a speech recognition engine, a camera such as a camcorder or camera, a cursor control device, a touch screen, or any combination of them. 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.

Computer system 102 may also include a media reader 112 and a network interface 114. In addition, computer system 102 may include any accessories, power supply, components, parts, peripherals, hardware, software, or any combination thereof that are well-known and are regarded as related 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.

All components of computer system 102 may be interconnected and communicate via bus 118. As shown in FIG. 2, all 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. 2 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 a device, a web device, a television with one or more processors built into it and/or attached to it, or any other device capable of executing a set of commands, serial or otherwise, that determines the actions performed by this device. Of course, it will be apparent to those skilled in the art that the above devices are exemplary devices only, and that device 120 can be any additional device or accessory that is well known and understood in the art, within the scope of this applications. 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 shows an exemplary global control system diagram according to the described embodiment. The diagram shows the data flow from initial detection and data collection in the upstream, midstream and downstream sectors, including any necessary intervention on the scene that can be carried out as a result of monitoring and warnings provided by the CCC command and 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. The integration of collected data interfaces between different technologies and systems provides communication between technologies and systems with different protocols, and integrates external systems such as ERP systems, etc. 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 monitoring the data provided by the data management system, alerting the control center (and personnel, if necessary) of events or the consequences of events, and performing diagnostics and data analysis. To the extent necessary, intervention by security and emergency personnel, UAVs (unmanned aerial vehicles), remote cameras and any other resource capable of interfering or implementing measures aimed at interfering, can be carried out after contact is established and the results are reported from the CCC control center . Data collected and extracted by UAVs or video cameras is stored in the system repository(s) for use in future analysis.

More specifically, the GMS (FIG. 5) manages oil and gas resources in a secure manner (or in an insecure manner, if desired) by monitoring illegal activity in the supply chain, alerting authorities and/or authorized personnel, and responding to illegal activity appropriately. For example, the system may alert authorities and/or authorized personnel, provide a written report to police or emergency personnel, predict or predict data, 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 GMS is not limited to the management of illegal activities, but can also be used for suspicious activity, emergencies, incidents, tampering, or for any other application normally envisaged by the management system. It should also be understood that in the course of monitoring, the system may discover that the activity does not appear to be illegal or suspicious at all, or is the result of a technical problem associated with the system or event. Additionally, as detailed below, the CCC control center uses data over time to detect and calculate trends and future events in grouped events. In this regard, the personnel in the control center of the CCC can be alerted before the occurrence of such events, when a certain level of probability is reached. Also, as detailed below, the CCC control center displays (eg, on an LCD display) alerts (in addition to normal activities) reflecting monitored events or incidents. Alerts may be used by personnel to contact emergency personnel or to intervene at the scene, and may be automatically issued by the CCC control center to emergency personnel if authorized personnel do not respond to such alerts within a specified time period or after repeated alerts.

The GMS receives information from sensor(s) and data collection device(s) located in various geographic locations and areas. These sensors may be any type of well-known sensor or data acquisition device capable of sensing or collecting data, provided it is designed to receive such data. The sensors are configured to receive and collect data related to oil and gas resources moving through the supply chain, the data including, without limitation, at least one of the following: temperature, density, humidity, volume, gravity, chemical composition, pressure, weight, pipeline pressure change, difference in vehicle weight or fuel volume, GPS positioning, vehicle position synchronization, geographic area, flow velocity, conductivity, rheology, turbidity, imaging, thermal imaging. Additionally, sensors can receive and collect information about the state of the sensor (i.e., malfunction, disconnection, etc.), strain gauge readings, weather data, road conditions, vehicle or road conditions, speed wind, barometric conditions, precipitation, maintenance data or maintenance date, personal location information (for example, the location of the nearest fire station or police station), data from radar, motion detectors, RF data, acoustic data, GPS location , data extracted from unmanned aerial vehicles (UAVs), the cost of oil reserves, etc. Information may also be collected by data collection devices. For example, information and data contained in a SAP™ or Oracle™ repository, which can be any data such as forecast, product purchase data, tax rate, etc.

Sensors and data acquisition devices (perceiving and collecting data in the form of secure (or non-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 transmitted to the gateway (FIG. 7). The gateway is a device for collecting data from various sources (for example, an ICS such as SCADA, while said ICS uses protocols such as MODBUS, AS-iOPC, EtherCAT, etc.) and includes a business rules engine (BRE). The gateway can also collect data directly from sensors, 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 a data management system where grouped events are generated from the data. It should also be understood that the collected data need not be obtained from the sources listed above, but may be obtained from any internal or external data source.

In some embodiments, additional secure and validated sensors and/or ICS, such as secure programmable logic controllers (PLCs) or secure SCADA systems, are used when receiving data in the upstream, midstream or downstream sectors of the oil and gas supply chain, and they can send their data directly to the gateway (or alternatively to the data integration module if there is no gateway). For example, data collected from upstream, midstream and downstream sensors (and/or data acquisition devices) processed by SCADA systems is also transmitted to secure and verified sensors and/or ICS and then to the gateway interface. In an alternative embodiment, secure and verified sensors and/or ICS replace the industrial control system (such as an unsecured SCADA system) and collect data directly from upstream, midstream and downstream sector sensors (FIG. 5). While all upstream, midstream and downstream sensors (and/or data acquisition devices) could be replaced in the system with protected/verified sensors and/or ICS, this would be very costly and time consuming. Accordingly, in one embodiment, secure/verified sensors and ICS replace existing sensors and/or data acquisition devices at predetermined points or nodes in the system. In another embodiment, secure/verified sensors and ICS are placed in new locations in the system. Newly added secure/validated sensors and ICS may collect or receive information from one or more existing sensors or data acquisition devices already installed in the system. Secured/Verified Sensors and ICS have attributes including, but not limited to, secure hardware, self-diagnostic capabilities, self-validation functions, alerting, anomaly detection and reporting capabilities, tamper protection, and a unique identifier that encrypts data in a secure manner, taken from standard or traditional sensors and data acquisition devices already used in the system.

A description of non-limiting examples of sensors and ICS that may be used in the system is provided below. It should be understood that the description is for explanatory purposes only, and that any number of commercially available sensors and/or ICS may be represented in a secure and validated manner with the capabilities of the attributes (all, some, and/or additional) listed above.

A programmable logic controller, PLC, or programmable controller can be used as an ICS. The PLC is an industrial application computer commonly used to automate industrial electromechanical processes such as controlling equipment in a factory. PLCs are used in various industries as well as in machines as an inexpensive and adaptable alternative to specialized microcontrollers. PLCs are designed for a variety of analog and digital input and output devices, extended temperature ranges, electrical noise immunity, vibration resistance, and shock resistance. The PLC continuously monitors the status of connected input devices and executes logic commands based on a customized program to control the status of output devices. PLC programs for controlling the operation of machines are usually stored in a back-up

- 6 040908 battery powered or non-volatile storage device. One type of PLC is the CX5010, CX5020 series controller with Intel® Atom™ processor built into the PC, manufactured by Beckhoff Automation GmbH. The CX5010 controller has a 1.1 GHz Intel® Atom™ Z510 processor and the CX5020 controller has an Intel® Atom™ Z530 processor

1.6 GHz.

Sensor types may include, but are not limited to, acoustic sensor, sound sensor, vibration sensor, automotive sensor, vehicle detection sensor, chemical sensor, electrical current sensor, electrical potential sensor, magnetic sensor, radio sensor, environmental sensor, weather sensor sensor, moisture sensor, humidity sensor, flow sensor, fluid velocity sensor, ionizing radiation sensor, subatomic particle sensor, navigation system sensor, position sensor, rotation angle sensor, displacement sensor, distance sensor, speed sensor, acceleration sensor, optical sensor, light sensor, imaging sensor, photon sensor, pressure sensor, force sensor, density sensor, level sensor, thermal sensor, thermal sensor, temperature sensor, proximity sensor, detection sensor, etc. One type of exemplary sensor is the di-soric™ RS 40 M 6000 G8L-IBS radar sensor. The sensor is designed to non-contact detection of approaching and receding objects, such as products on a conveyor, at a distance of up to 6 m. The detection range and pulse extension of the sensor are adjustable, and it is installed behind non-metallic materials, switching devices for proximity and distance detection can be used outdoors and housed in a durable metal case. In one exemplary embodiment, a PC-embedded CX5010 or CX5020 controller can be used to implement PLC or PLC/motion control (with or without visualization). Thus, the PLC is used in the exemplary embodiment to logically determine (verify) that the di-soric™ sensor is functioning properly and is correctly detecting objects moving along the conveyor. For example, the PLC can compare data received from a di-soric™ RS 40 M 6000 G8L-IBS radar sensor with data from an adjacent independent object detection sensor, such as the Tri-Tronics SMARTEYE® EZPRO photoelectric sensor, which detects objects as they pass through the emitted beam of light or provides a change in the characteristics of the reflected light as they pass through the beam. If the photoelectric sensor has detected objects but the radar sensor has not, then one or both of the sensors may be faulty or misconfigured and the appropriate alert system may be triggered. In the simplest exemplary embodiment, since the PLC is more or less a dedicated controller, it will repeatedly execute the internal program. One program cycle includes, for example, reading input from other modules (eg, a sensor), executing logic commands based on the input, and then updating the output accordingly. The memory device in the CPU stores the program and also maintains I/O state and provides a means to store values. As one skilled in the art would appreciate, any PLC can be used in the current system, and the present disclosure is not limited to the exemplary embodiments described above. Additionally, the information collected and output by the secure sensor or ICS can be digitally secured using, for example, symmetrical digital signatures. Symmetric key algorithms are a class of encryption algorithms that use the same cryptographic keys to both encrypt the plaintext and decrypt the ciphertext. In practical application, keys are a secret shared between two or more parties that can be used to keep a link of confidential information. Of course, the present disclosure is not limited to the use of symmetrical digital signatures. Rather, any known encryption method can be used. For example, the Freescale™ i.MX537 microprocessor is designed for advanced industrial and medical applications and includes the SAHARA (Random Number Generation and Symmetric/Asymmetric Hashing Accelerator) cryptographic accelerator. This microprocessor contains a random number generator, a secure storage device, supports the use of various standard ciphers and hash functions, and can also securely store AES keys and encrypt data using them.

In one non-limiting exemplary embodiment, secure/verified sensors and ICS are configured to create a symmetric digital signature for data. For the purposes of explanation, the specified devices (eg, secure/validated sensors and ICS) installed in the system are considered to be in a non-secure environment, with the central server installed in a secure environment. An AES key is generated before installation. The AES key is transmitted to the secure sensor or ICS and stored in a central server. Different keys can be generated for each device. Once the key is generated, the secure sensor or ICS can then be installed in a non-secure environment. To authenticate and prevent falsification of data sent by the secure sensor or ICS to the server, a data signature is generated by the secure sensor or ICS, where the signature may be a hash of the data to be signed. Said hash sum is generated in the SAHARA crypto processor using, for example, a standard hashing algorithm (eg SHA-224). The hash sum is then encrypted using the SAHARA crypto processor using the built-in AES key. The encrypted hashsum becomes a digital signature. The data is then sent to a central server with a digital signature and the ID of the device that signed the data. After the central server receives the AES key using the device ID, the digital signature is then decrypted using the specified AES key. The signature is authentic if the decrypted hash sum matches the hash sum re-created from the data to be authenticated. Once the data is signed, the authenticity and integrity of the data is guaranteed. In large-scale projects where the amount of data to be signed is too large to be processed in real time by a single processor, it is possible to distribute the computational load across multiple secure sensors or ICS, or store the data in a temporary buffer until it can be processed and delivered to more late time. However, it should be understood that any known encryption method can be applied and the system is not limited to the methods described herein.

The data integration module contains a data management system that stores data, retrieves data from storage, creates a data structure containing key values from the data, sorts the data structure, and analyzes the structured data using computational models and algorithms to identify events. Structured data is also checked for integrity and security in order to detect falsification. Groups of related events are created by the data management system for use by the CCC control center. CCC Control Center (which may include processor(s), software, interface(s) and multiple displays, and/or personnel to manage and dispose of information in the GMS global management system, and/or, for example, any of the components described on 2, and which may be located locally or remotely in any geographic location, mobile or otherwise) controls events and alerts, generates alerts, and provides solutions based on grouped events generated in the data management system. The control center also provides links to external operational support and personnel and resources.

The computational models and algorithms used in the GMS 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, a data mining algorithm, which is a set of heuristics and calculations that creates a data mining model from data, can be used as an example. To create a model, the algorithm first of all 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 data 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 cases (eg, events) in the dataset; a decision tree that predicts an outcome and describes how different criteria affect that outcome. Using data intelligently analyzed by algorithms, the system is able to apply historical data and improve accuracy over time. Accuracy can also be aided by human or UAV, such as drones, verification of warnings generated by the system.

In FIG. 4 shows an exemplary communication between a data management system and a control center according to an embodiment of the invention. The data management system 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 data management system, which can be securely logged with a timestamp. The CCC Control Center also provides control over events and alerts, generates alerts, and provides a solution based on grouped events generated by the data management system. 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. For example, external operational support and personnel can provide on-site intervention.

- 8 040908 to verify the accuracy of warnings (for example, to verify the fact of an explosion, theft of material), and UAVs can be mobilized and sent for the purpose of verification in a specific area related to warnings, and can provide a visual representation to improve the usefulness of the analysis of grouped events.

In FIG. 5 shows an exemplary global control system diagram according to the described embodiment. The GMS includes, without limitation, a CCC control center, a data management system, a data integration module, a user interface, a gateway interface, and sensors or data acquisition devices used to acquire data from the upstream, midstream, and downstream sectors. Additionally, the GMS contains secure/validated sensors and/or ICS that are used to further secure and verify data collected from sensors and data acquisition devices as described above. The GMS may also contain or cover external resources such as ERP systems, 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 GMS 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 GMS manages oil and gas resources securely (or insecurely, if desired) by monitoring illegal activity (which may also include, but not limited to, suspicious activity and/or technical problems) in the supply chain, alerting authorities and/or authorized personnel and responding to illegal activities in an appropriate manner. The GMS global 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. 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, as described above, data is sent to the CCC control center in order for personnel to respond to tampering, theft, or similar operational incidents. This process allows for a faster response than current systems, as well as the provision of an evidence base containing physical evidence that can be admitted in a court of general jurisdiction to prosecute offenders. For example, securely collected data from UAVs can be used to provide crime scene evidence that an event took place.

In particular, the collected data will be received and processed in real time and sent to the CCC control center (which may be in the form of a physical command and control center and / or an application that is functionally independent of the personnel or any combination thereof) for appropriate display to the personnel of the command center. The structured data will be analyzed according to computational models and/or algorithms to identify events, where the events may represent operational incidents such as the illegal activities described above, as well as operational issues that can be identified and displayed to operators in real time. In parallel with this (or at another time), structured data and events are entered into a predictive and prescriptive analysis module (a predictive and prescriptive analysis application) using machine learning, as described above, to identify a sequence of measurements (Fig. 7A) 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 GMS 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. Accuracy can also be aided by human or UAV on-site verification of warnings generated by the system.

The data management system, like the CCC control center, can also communicate with a predictive and prescriptive analysis module, which will apply machine learning based on structured data and events as training sets to classify events that can be regarded as a sequence of measurements. Proactive module

- 9 040908 and prescriptive analysis provides information to identify probable events (with a variable degree of probability) in the future or ongoing events that can be sent as events to the CCC control center. The predictive and prescriptive analysis module can also prescribe the response to an event that is most likely to result in a positive outcome based on the event history. Likewise, recognized (or known) trends over time can be used to improve grouped events to more accurately generate alerts in the CCC control center.

In FIG. 6 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 SCADA systems is transmitted to the gateway interface. In an alternative embodiment, secure/verified sensors and PLCs replace the industrial control system (such as SCADA) and collect data directly from upstream, midstream, and downstream sector sensors (FIG. 5). The gateway interface converts (eg, sorts, formats, and modifies) the collected data into secure and formatted data compatible with the system, and in particular with the data integration module, before sending it to the data management system for analysis by the global GMS.

In FIG. 7A-7D depict exemplary sensor measurements and sensors collecting data along a supply chain in accordance with an embodiment of the invention. The CCC control center, through an interface that provides interaction with the field and resource management system (Fig. 5), can perform several actions based on real-time data and events received from the data management system. Once a certain sequence of measurements (or sequence of events) associated with the description of events has become known (i.e. learned by the application for predictive and prescriptive analysis), events can be tagged in real time and sent to the CCC control center along with a probability score, denoting the probability that a sequence of unfolding measurements will result in an identifiable event In the figures, the shaded boxes represent the values obtained from a given sensor In Fig. 7A shows an exemplary number of sensors 1, ..., m, configured to receive a sequence Figures 7B, 7C, and 7D show an exemplary sequence of events in which the data obtained over time t represents a low probability, a medium probability, and a high probability, respectively, of the occurrence of an event (referred to here as the probability of an event I). The sensors depicted may consist of existing and/or newly added secure/validated sensors and ICS that have been added to the system at various locations.

The probability of the event is sent to the CCC control center along with a recommendation such as Theft possible on pipeline section 452, send a command to intervene in sector D. The CCC control center can respond in various ways, including, without exception, the following: request the display of additional data for the specified area , in which the event (incident) occurred; send drones (UAVs) to the affected area for reconnaissance or information or for visual representation; send first responders or people (such as police, firefighters, etc.) to the area to check for an event or incident at the site of operation; or give an order to evacuate personnel from the place of operation, depending on the incident (for example, an explosion at the work site during the selection of motor fuel).

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 (incidents) before sensors and data collection devices begin to register data. Using this proactive data, the CCC control center and personnel working in the CCC control center can be alerted to predicted areas of increased theft risk, identified by the system using data in the system, such as time of day, day of the week, month, or preset dates, weather conditions, previous sequences of events, etc. For example, based on a predicted high-risk area, UAVs may be directed to capture and display video, and intervention commands may be placed nearby to prevent the event. Otherwise, if, despite the above measures, an event occurs, the intervention time will be reduced due to the fact that the necessary resources are nearby. Additionally, the data management system can instruct the CCC control center to automatically display data from likely areas where events are likely to occur, so that personnel can inspect data and video from those areas for violations and activity, preventing the occurrence of any event. The GMS can also use a combination of data mining algorithms and human actions to update system data based on events and analysis, with person confirmation.

- 10 040908 la, located at the place of operation or at the place of occurrence of problems.

From the above it becomes clear that the global management system GMS is able to capture the development of events and connect them together to provide history for analysis and improve data analysis in the data management system. Based on previous knowledge of past events, historical data, and verification that events actually occurred, such as making a hole in a pipeline to steal fuel, future events can be more accurately predicted and the events themselves can be better interpreted. in the implementation of control and analysis. Additionally, due to the fact that the GMS is inherently based on forecasts and prescriptions, it is able to reduce the impact of human corruption, such as operating personnel in the CCC control center. Accordingly, it will become increasingly difficult for people involved in illegal activities to avoid detection by deleting data, changing data, bribing data controllers, and so on.

To a large extent, to prevent these types of situations, the global 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 illegal activity, while the specified activity will be displayed to the operator and recorded in the form of warnings, which are also not amenable to forgery and cannot be removed. Alternatively or in addition, the system itself can intervene instead of personnel to identify and send urgent information to external authorities such as the police, fire department, etc. Accordingly, the role of the system is to provide an alternative to human error and incompetence.

Further non-limiting examples of the global GMS are described below in relation to the midstream and downstream sectors. In the midstream sector, illicit activities typically involve re-routing or theft of materials. For example, a hole may be made in a supply chain pipeline to pump motor fuel out of the pipeline in order to steal the motor fuel, often successfully. As a countermeasure and in accordance with the objectives of the global GMS management system, several sensors and/or data acquisition devices can be installed on the pipeline, which will monitor and collect data from pipelines. For example, flow rate, temperature, pressure, volume, etc. can be monitored and collected. Collected data from sensors and data acquisition devices will be sent to the appropriate gateway (FIG. 5) or industrial control system ICS using secure/verified sensors and ICS and will be transmitted to the data management system and further to the CCC control center as described in this document. higher. 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 collector(s) only measure pipeline pressure every hour that fuel or crude oil is illegally extracted, the sensor(s) and data collector(s) may not detect illegal activity. On the other hand, if pipeline pressure is measured every minute, the sensor(s) and data acquisition device(s) will be able to measure any increase or decrease in pressure (or other types of data such as volume reduction, chemical presence of air or water) indicative of carrying out illegal activities. UAVs or personnel involved in locating the sensor(s) and data acquisition device(s) can be automatically sent to the regional area, images from the local camera can be captured, and police or emergency personnel can be notified that the activity is in implementation process.

Another non-limiting example of data in the midstream sector is a tanker truck transporting crude oil and oil product. In this example, the collected data 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 for longer than expected, or that the volume of the tanker's contents has changed, this may indicate ongoing or ongoing illegal activity. In another example, a tanker truck may stop at an overnight rest area. Since these zones are known, during a regular shutdown over a long period, the volume sensors on the tanker can be activated to monitor changes in the contents of the tank. In particular, it may be known that illegal activities are taking place in a particular area. Collectively, any change detected by the sensors can be sent through the data management system to the CCC control center, where it can be determined that the authorities should be sent to the specified location. In addition, data regarding the area and expectation of illegal activity in the specified zone will be passed to the learning mechanisms of the system, and such data will be used by the data analysis component in subsequent analyses. Content (resources) may also be marked with chemical or forensic markers to retrieve resources, such as those found in a retail store or authorities.

In the downstream sector, a non-limiting example is provided in which the collected data includes

- 11 040908 is the volume produced at the processing plant. The volume data can be related, for example, to the number of tanker trucks needed to transport the contents of the tanker trucks (fuel) to retail stores. It is understood that after fuel arrives at retail stores, it is loaded into store tanks for storage. In this case, the volume is transferred and the fuel is sold. Sensors and data collection devices can then be used to measure changes in the respective volumes and measure the cash generated from the sale of the fuel. If volumes and sales do not match, this may indicate illegal activity such as embezzlement. 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. 8 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, allows data sensors located throughout the upstream, midstream and downstream sectors to interact with external sources, such as the ESB enterprise service bus or the GMS global data management system, through secure / verified sensors and ICS with data integration module. As shown, the gateway is divided into three layers containing: (1) a computer (for signing and storage) communicating with plant 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, protection, authentication, filtering, negotiation, prevents 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 that communicate with 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 collected data from sensors and/or data acquisition devices, and format the collected data to make it compatible with secure/validated sensors and ICS, and the data integration system before it is used in the global GMS, especially at the data management system (DMS) level. The gateway interface communicates with external systems using, for example, protocols such as HTTPS, SSL, etc. External interfaces include, but are not limited to, the ESB or the ICS plant control system. 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 extended features in addition to data collected from various data repositories such as SCADA or ICS. The secure and enhanced data will then be provided to the global GMS and will facilitate the creation of grouped events. The Gateway will also verify that data received from any secure/verified and unsecured/unverified 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 incoming data before securing the data and adding additional properties. This will ensure that data intended to be protected and enhanced properties is authenticated before it enters the GMS and prevents corrupted data from being sent to the GMS. 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 spoofed, spurious, fabricated or inaccurate data, the resulting data will not be reliable and any events or grouped events created in the GMS global management system could potentially compromise alerts generated from the grouped events. Accordingly, any data intended to be accessed or used in the global GMS (via the data integration module) via the gateway must be as secure and accurate as possible. An example of determining the authenticity of the data to be entered

- 12 040908 money to the gateway, is to receive several times more information from sensors in a short period of time than it is supposed to receive, and to verify that the collected data always have the same essence (for example, temperature data is received ten times during 30 s and the value practically does not change, in this case the data give the impression of being correct). Another example of data authentication is to add an electronic system or mechanism to the sensor to protect it from being tampered with by any means (e.g., entering erroneous data, making the sensor measure erroneously, etc.), whereby the data collected from the sensor and subsequently sent to the gateway will be as accurate as possible. Measurements from sensors reporting failures as a result of self-diagnostics or self-plausibility checks may be ignored. As an alternative or addition to the above authentications, measurement data can be compared with data from neighboring sensors measuring similar or related physical phenomena to ensure they are consistent. For example, if the temperature increased in one sensor, did it also increase in neighboring sensors? As a consequence, does the pressure change? And so on.

Machine learning methods for outlier detection can also be performed on historical and current data to detect inconsistent sensor readings.

The gateway interface collects data through either physical interfaces interacting with industrial sensors using industrial communication protocols such as OPC or Ethercat, or through virtual (i.e. software) interfaces interacting with existing monitoring or control systems such as SCADA. The 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 received data, filtering non-essential data such as non-security events, validating read/write access from/to the driver layer to 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 provided 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 interact 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 GMS. 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 to or be part of a global GMS.

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 global GMS 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) performs a transformational processing function on the received data and applies rules that can be executed in such a way as to represent a particular element of interest, such as a potential security breach. BRE controls all activity and measurement points of loaded drivers, along with any physically or virtually attached devices. With real-time access to all of these points, BRE can create new measurement points or data that can be used to create grouped events in the global GMS. Based on the collected data, BRE will also create associations with data collected into 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. 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

- 13 040908 values can create new data based on both measurement point A and measurement point B. For example, new data C can be created, where new data C is a function of the data from measurement points A and B and can be 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 collectors, or ICS systems. This data, which has been verified for accuracy before entering the gateway, is then appended with properties to obtain rich data.

In another embodiment, if the sensors, data collectors, or ICS systems are not reliable or unable to verify the accuracy of the data, the verification step is performed at the gateway. The events created in the gateway will be applicable in the DMS of the GMS system to create grouped events. Grouped events are used in the GMS to create and/or display warnings at the CCC level and in the context of the present invention will effectively mobilize the appropriate operational response at the scene (i.e. police in the event of theft of material, firefighters in the event of an explosion, etc.).

BRE can also operate autonomously if enough physical and/or virtual information is available to determine event-based collected data applicable to create grouped events in the global GMS without relying on data from any external system, actions such as alerts to identify or warning of security breaches, or taking other appropriate action. The definition(s) of grouped events is managed by the data management module of the global management system GMS 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. 9 shows an exemplary implementation of an interface process 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 terminal units (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 are not necessarily signed by a hardware or software security module (HSM or SSM). Events and extended data can be stored in a secure repository or data store. The gateway then checks to determine where the data will be sent, such as to the global GMS or to another external system. If the GMS is available, then the data or events can be formatted and validated for use by the global management system. Data sent to an external system can be formatted and validated based on the requirements of the external system.

The data is then sent to a data integration module, which can store data or events, retrieve data from storage, create from the data, for example, a data structure containing key values, sort the data structure, and analyze the structured data using computational models and algorithms to identify correlations between data. applicable to create grouped events in the global GMS. 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 one or more 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, encrypting, or containing a set of instructions for execution by a processor, or capable of executing by a computer system one or more of any of the embodiments described herein.

The computer-readable medium may include a permanent computer-readable medium or media and/or include 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 memories. 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 receiving 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 designed 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 depictions 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, such 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 aspect ratios in images may be increased while other aspect ratios may be reduced. 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 be 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 refer to at least all of the features of the described embodiments. Thus, the following claims are included in the detailed description, with each claim

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Claims (19)

of the claims is independent, since it defines a separately claimed 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. CLAIM 1. A method for creating secure data with additional attributes used in a global management system (GMS) related to the management of oil and gas resources, including receiving, through a gateway, data related to oil and gas resources collected from at least one sensor located along the oil supply chain and gas; receipt by the gateway of at least a portion of oil and gas related data collected from at least one secure/verified sensor located adjacent to at least one sensor, wherein at least one secure/verified sensor is configured to collect and verify data; checking by the gateway the data collected from the at least one sensor and the data collected from the at least one secure/validated sensor to confirm the accuracy of the information in the collected data before being transmitted to the secure server; recording by means of the gateway the received data on a secure server containing at least one software component; and adding, via the gateway, attributes to the data stored on the secure server using a business rules engine configured to apply security/access/authentication rules to generate rich data, the additional rich data attributes including at least one secure attribute allowing detect modification or corruption and authenticate the extended data used in the GMS and protect by the secure server gateway from at least one of falsification and input of unwanted data, as well as unauthorized access; characterized in that the verification of the collected data to confirm the accuracy of the information in the collected data is carried out by comparing the data collected from at least one sensor with the data collected from at least one protected/verified sensor located adjacent to at least one sensor, and measuring similar or related physical phenomena to ensure they are consistent. 2. The method of claim 1, wherein at least a portion of the extended data generated by the business rules engine is converted to events. 3. The method according to claim 1 or 2, characterized in that the extended data or events based on the extended data are signed or encrypted by at least one of the hardware or software security modules of the gateway. 4. The method according to any one of the preceding claims, characterized in that at least one software component securely sends extended data with additional attributes to the GMS data integration module. 5. A method according to any one of the previous claims, characterized in that the business rules engine stores the extended data and creates a queue of it in an encrypted and long-term data store. 6. The method according to any one of the previous claims, characterized in that the extended data with additional attributes is transmitted to the external system via an interface. 7. The method of claim 1, wherein the collected data is sent to a secure server as at least one of secure data, separately formatted data, jointly formatted data, data with protected attributes, read-only data, and data , protected from forgery. 8. The method according to any one of the preceding claims, further comprising receiving the collected and verified rich data securely in the data integration module and collecting and/or organizing the rich data and events generated from the rich data into grouped events in the global control system; performing at the control center at least one of monitoring alerts, generating alerts, and providing decisions based on the grouped events generated in the data management system; - 16 040908 displaying by the control center a visual representation of grouped events and providing interaction through the control center to exchange data with at least one of the data integration module, external operational support, personnel and production equipment. 9. Global Management System (GMS), which manages the oil and gas supply chain and contains a gateway to create secure data with additional attributes used in the GMS; at least one sensor located along the oil and gas supply chain, configured to collect data related to oil and gas resources; at least one secure/verified sensor located adjacent to at least one sensor configured to collect at least a portion of data related to oil and gas resources, wherein at least one secure/verified sensor is configured to collect and verify data ; a secure server containing at least one software component configured to store data received from the gateway, and protected by the gateway from at least one of falsification and input of unwanted data, as well as unauthorized access; and a gateway business rules engine configured to add attributes to the data stored on the secure server to create rich data, configured to apply security/access/authentication rules, the additional extended data attributes including at least one protected attribute, capable of detecting modification or corruption and authenticating extended data used in the GMS, wherein the gateway is configured to verify data collected from at least one sensor and data collected from at least one secure/validated sensor to confirm the accuracy of the information in the collected data before transmission to a secure server, characterized in that the verification of the collected data to confirm the accuracy of the information in the collected data is carried out by comparing the data collected from at least one sensor with the data collected from at least one secure / verified th sensor located adjacent to at least one sensor and measuring similar or related physical phenomena to ensure they are consistent. 10. The system of claim 9, wherein the rich data generated by the business rules engine is converted into events. 11. The system according to any one of claims 9 or 10, characterized in that the extended data or events based on the extended data are signed or encrypted by at least one of the hardware or software security modules of the gateway. 12. The system according to claims 9 to 11, characterized in that at least one software component securely sends extended data with additional attributes to the GMS data integration module. 13. The system according to claims 9 to 12, characterized in that the business rules engine stores and queues extended data in an encrypted and long-term data store. 14. The system according to claims 9 to 12, characterized in that the business rules engine stores events created from the extended data and queues them in an encrypted and long-term data store. 15. The system according to claims 9 to 14, characterized in that the extended data with additional attributes is transmitted to the external system via an interface. 16. The system according to claims 9 to 15, characterized in that the events generated from the extended data are sent via an interface to an external system. 17. The system according to claims 9 to 16, further comprising a data integration module receiving extended data and events generated from the extended data into grouped events in the global management system; and a control center performing at least one of monitoring alerts, generating alerts, and providing decisions based on the grouped events generated in the data management system, wherein the control center displays a visual representation of the grouped events, and wherein the control center cooperates to exchange data over with at least one of the data integration module, external operational support, personnel and production equipment. 18. The system of claim 9, wherein the collected data is transmitted to a secure server 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. 19. A permanent machine-readable medium that contains a program executable by a process -