Edge Computing for Local Well Test Triggering
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Solution Overview
Problem
Current systems for monitoring and controlling hydrocarbon production at well sites face challenges in presenting complex data in a usable form for real-time decision-making, leading to inefficiencies in hydrocarbon extraction and production optimization.
Innovation Solution
A monitoring system that includes a multi-selector valve, separator, and sensors to determine virtual flow rates of liquid and gas components, allowing for real-time data analysis and automatic adjustment of operating parameters, as well as the initiation of well tests when flow rates do not match historical data, enabling efficient hydrocarbon production and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is collected and transmitted to off-site personnel for analysis, then data processing capability is improved, but response time and real-time decision-making capability deteriorate
Solution Approach 1:
The system segments data processing functions by deploying edge computing devices at remote locations to perform local data analysis, while central servers handle aggregate data processing. This segmentation enables simultaneous local real-time decision-making and centralized comprehensive analysis, resolving the contradiction between data processing capability and response time.
Solution Approach 2:
Edge computing devices serve as intermediaries between remote sensors and central servers. These intermediaries perform preliminary data processing, filtering, and analysis locally, then transmit only essential results to central servers, enabling both real-time local response and comprehensive centralized processing.
2Loss of information
If complex raw data is presented to well site personnel, then data completeness is improved, but ease of interpretation and decision-making deteriorate
Solution Approach 1:
The system creates simplified copies and visual representations of complex raw data through dashboards, graphs, and alerts. These visual copies present essential information in intuitive formats while maintaining linkage to complete underlying data, enabling easy interpretation without losing data completeness.
Solution Approach 2:
The system replaces manual data interpretation with automated edge computing algorithms that analyze raw sensor data and generate actionable insights. This substitution transforms complex mechanical/data processing tasks into automated computational processes that maintain data completeness while improving interpretability.
3Device complexity
If manual analysis and decision-making processes are used, then system simplicity is improved, but productivity and optimization capability deteriorate
Solution Approach 1:
The system implements self-service automation where edge computing devices autonomously monitor well site parameters, detect anomalies, and trigger alerts without requiring constant human intervention. This self-service capability maintains operational simplicity while significantly improving productivity through continuous automated monitoring and faster response to production issues.
Solution Approach 2:
The system changes operational parameters dynamically based on real-time data analysis. Edge computing devices continuously adjust production parameters such as flow rates and pressure settings to optimize hydrocarbon extraction, improving productivity while maintaining system simplicity through automated parameter management.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides real-time or near real-time data analysis and control of hydrocarbon production, allowing for immediate adjustments to operating parameters, thereby enhancing the efficiency and optimization of hydrocarbon extraction and production.
Implementation Method 1
a separator that couples to the output pipe and separates the hydrocarbons into gas and liquid components
Data Source
AI summary
A method for locally performing a well test may include receiving, at a processor, data associated with a flow of hydrocarbons directed into an output pipe via a multi-selector valve configured to couple to one or more hydrocarbon wells. The method may also include determining one or more virtual flow rates of the liquid and gas components based on the data. The method may then send a signal to a separator configured to couple to the output pipe, wherein the signal is configured to cause the separator to perform a well test for a respective well when the virtual flow rates of the liquid and gas components do not substantially match well test data associated with the respective well, wherein the well test data comprises one or more flow rates of the liquid and gas components determined during a previous well test for the respective well.