Oil And Gas Flow Network Assessment From Steady-State Intervals
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Optimizing oil and gas flow network performance is challenging due to unpredictable variations in input conditions and the complexity of modeling multiple wells, leading to cumbersome simulations and suboptimal production settings, with existing methods requiring specific excitations and limited applicability.
Innovation Solution
A method that gathers historical and live data to identify steady state intervals in oil and gas flow networks, extracting statistical data to represent the data in a compact form, allowing for assessment and optimization without the need for specific excitations, and using local models to determine adjustments for improved performance.
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 and analyzes actual operational data from the flow network to identify steady-state intervals and their characteristics. Instead of relying on complex predictive models, the invention extracts meaningful patterns directly from measured data, thereby achieving prediction capability without the computational burden of complex simulations.
Solution Approach 2:
The patent creates simplified representations of the flow network behavior by copying and analyzing actual steady-state operating conditions from historical data. These simplified models capture essential system characteristics without requiring the computational resources of full-scale simulations, enabling efficient prediction and optimization.
2Productivity
If excitations are applied at control points to identify variations, then performance optimization is improved, but the method requires specific excitations and has limited applicability
Solution Approach 1:
The patent enables the flow network to assess itself by analyzing its own operational data without requiring external excitations or interventions. The system identifies steady-state intervals from its natural operation and uses this self-generated information for performance assessment and optimization, making the method universally applicable to any flow network with available operational data.
Solution Approach 2:
The patent develops a universal assessment method that can be applied to any oil and gas flow network regardless of its specific configuration or operating conditions. By focusing on identifying steady-state intervals from operational data rather than requiring network-specific excitations, the invention creates a broadly applicable methodology that works across diverse flow network topologies and operating scenarios.
3Loss of information
If large volumes of data are recorded for flow network monitoring, then data completeness is improved, but data processing and analysis become more cumbersome
Solution Approach 1:
The patent extracts only the essential information from large volumes of operational data by identifying and analyzing steady-state intervals. Instead of processing all recorded data, the invention selectively extracts meaningful steady-state periods and their characteristics, thereby maintaining data completeness for assessment purposes while dramatically reducing processing time and computational resources required.
Data Source
AI summary
A method for assessment of an oil and gas flow network comprises: 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; identifying time intervals in the data during which the control points and the flow parameters are in a steady state; and extracting statistical data representative of some or all steady state intervals identified in step to thereby represent the original data from step in a compact form.