Oil And Gas Flow Network Assessment Using Steady-State Data
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Solution Overview
Problem
Existing methods for assessing oil and gas flow networks are cumbersome, requiring significant computing power and often provide only a computer-assisted guess for optimal settings due to unpredictable variations in flow networks, especially when multiple wells supply single or multiphase fluids, making it difficult to optimize production settings.
Innovation Solution
A method that identifies steady state intervals in flow networks by gathering historical and live data, extracting statistical data representative of these intervals to compactly represent the original data, allowing for efficient assessment and optimization without the need for additional excitations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If simulations and models are used to predict flow network response, then prediction capability is improved, but computing power requirements and model complexity increase significantly
Solution Approach 1:
The patent extracts only the essential steady-state characteristics from complex flow network data, separating the critical performance parameters from the overwhelming volume of raw measurements. This extraction approach maintains prediction capability while eliminating unnecessary computational complexity by focusing only on steady-state intervals where meaningful assessments can be made.
Solution Approach 2:
The patent employs simple statistical methods and basic data processing techniques instead of complex simulations, using readily available historical and live data that can be processed with minimal computational resources. This approach provides sufficient assessment capability without requiring significant computing power or complex modeling infrastructure.
2Measurement precision
If comprehensive data collection is performed to assess flow network performance, then assessment accuracy is improved, but data volume and processing time increase
Solution Approach 1:
The patent performs preliminary identification of steady-state intervals before detailed assessment, filtering the data stream to isolate only those periods suitable for meaningful evaluation. This preliminary action prevents wasteful processing of transient data and enables focused analysis on relevant intervals, reducing overall processing time while maintaining assessment accuracy.
Solution Approach 2:
The patent extracts statistical characteristics from identified steady-state intervals, pulling out only the essential performance metrics needed for assessment rather than processing entire data sets. This extraction of relevant information from comprehensive data maintains accuracy while dramatically reducing processing requirements.
3Loss of information
If excitations are applied to identify flow network variations, then system response information is improved, but operational disruption and complexity increase
Solution Approach 1:
The patent utilizes naturally occurring steady-state intervals that arise during normal flow network operation, allowing the system to provide its own assessment opportunities without external intervention. This self-service approach captures system response information during routine operation, eliminating the need for deliberate excitations and associated operational disruptions.
Solution Approach 2:
The patent converts the typically problematic transient variations and unpredictable well inputs into identifiable steady-state intervals that can be used for assessment. By recognizing and utilizing these intervals rather than treating them as disruptions, the method transforms operational variability from a hindrance into a source of assessment information.
Data Source
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AI summary
A method for assessment of an oil and gas flow network comprises: (1) gathering historical data and/or live data relating to the status of multiple control points at different branches within the flow network and to one or more flow parameter(s) of interest in one or more flow path(s) of the flow network d; (2) identifying time intervals in the data during which the control points and the flow parameters are in a steady state; and (3) extracting statistical data representative of some or all steady state intervals identified in step (2) to thereby represent the original data from step (1) in a compact form.