Well Infrastructure Data System with Remote Sensor Validation
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Solution Overview
Problem
Existing data management systems for well infrastructure face challenges in securely collecting, processing, and analyzing large volumes of data from remote and potentially hostile environments, particularly in efficiently managing and controlling oil and gas well operations.
Innovation Solution
A data system comprising a network-enabled server and remote sensor devices that collect and validate condition data from well infrastructures, storing it in a database while facilitating user access and enabling decision processes to optimize operations, including communication with control devices to modify conditions based on analyzed data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is collected from remote and hostile environments using sensor devices, then monitoring capability is improved, but data security and reliable transmission become problematic
Solution Approach 1:
The patent introduces a server as an intermediary component that receives data from sensor devices in remote environments and stores it in a centralized database. This mediator architecture allows sensor devices to focus on data collection while the server handles secure storage, validation, and transmission, thereby maintaining data security without compromising monitoring capability.
Solution Approach 2:
The system divides the data management functionality into separate components: sensor devices for data collection, a server for data reception and validation, and a database for secure storage. This segmentation allows each component to be optimized for its specific function while maintaining overall system security and reliability.
2Quantity of substance
If large volumes of data are collected from well infrastructure, then comprehensiveness of information is improved, but processing speed and decision-making efficiency deteriorate
Solution Approach 1:
The server performs preliminary validation and processing of data before it is stored in the database. By pre-validating data formats, checking for errors, and organizing data structures in advance, the system reduces the time required for subsequent analysis and decision-making processes.
Solution Approach 2:
The system extracts and stores only the most relevant data fields from the raw sensor data in the database, while maintaining the ability to access detailed information when needed. This selective extraction approach reduces storage requirements and improves retrieval speed without losing critical information.
3Loss of information
If remote sensor devices are deployed to monitor well infrastructure, then operational awareness is improved, but system complexity increases
Solution Approach 1:
The server is designed as a universal platform that can receive data from multiple types of sensor devices, store various data formats, and support different user access methods. This multi-functionality reduces the need for separate systems for different monitoring tasks, thereby managing complexity while maintaining comprehensive operational awareness.
Solution Approach 2:
The centralized server acts as an intermediary that abstracts the complexity of data collection and management from the sensor devices. The sensors simply collect and transmit data, while the server handles the complex tasks of validation, storage, and retrieval, thereby reducing overall system complexity.
4Loss of time
If data is stored in a centralized database for easy access, then data retrieval efficiency is improved, but security risks increase
Solution Approach 1:
The system implements preliminary security measures including data validation, authentication protocols, and access control mechanisms before data is stored or retrieved. By establishing these security frameworks in advance, the system enables fast data retrieval while maintaining robust security protection.
Solution Approach 2:
The server implements feedback mechanisms that monitor access patterns and validate data integrity. This continuous monitoring and validation system allows efficient data retrieval while detecting and preventing unauthorized access or data corruption in real-time.
Data Source
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AI summary
There are described data system (200), devices and methods for use with well infrastructure (100). For example, such well infrastructure (100) may include oil and gas well structures, pipeline structures, and the like (110, 120, 130). In particular, there are described data systems (200), etc., for using data associated with monitored conditions at such well infrastructure (100). Such data systems (200) may comprise a data-storage facility (210) having stored data records associated with particular well infrastructures (100) (e.g. productions wells). The data system (200) may have one or more remote sensor devices (150) (e.g. gauges or distributed sensors) configured to monitor conditions at particular well infrastructures (100), and to collect condition data corresponding to those conditions. In some cases, a network-enabled server (220) is provided, in communication with the data-storage facility (210) and configured to receive from time to time,via a network (230), collected condition data from the one or more remote sensor devices (150), whereby the server (220) is configured to communicate that received condition data to the data-storage facility (210) for storing in appropriate data records. In such examples, the system (200) may be further configured to facilitate user access, via the network(230),to the data records comprising condition data stored at the data-storage facility (210).