Oil and Gas System Operating Point Segmentation
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Solution Overview
Problem
Conventional optimization methods for oil and gas producing systems typically generate a single operating point, which is limited by inaccuracies and uncertainties in the model, and fails to account for dynamic transients and safety margins, leading to suboptimal system control.
Innovation Solution
A method and system that simulate oil and/or gas producing systems to generate multiple operating points, allowing for a judicious choice of an optimum region and providing context for maneuvering between points, using independent variables such as flow rate and pressure settings, and dependent variables like flow rates and pressures, through a process involving genetic algorithms and operability mapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional optimization algorithms are used to deduce a single optimum operating point, then the system provides a specific control point, but the model inaccuracies and uncertainties lead to deviation between predicted and actual behavior
Solution Approach 1:
The patent segments the single optimum operating point into multiple candidate operating points by varying independent variables (flow rate, pressure, temperature) across different ranges. This segmentation allows the system to explore multiple regions of the operating space, each representing a potential optimal point under different conditions, thereby addressing model inaccuracies by providing alternatives rather than relying on a single predicted point.
Solution Approach 2:
The patent systematically changes multiple independent variables (flow rate, pressure, temperature) to generate different operating points. By varying these parameters across different ranges and combinations, the system creates a set of candidate operating points that account for model uncertainties, allowing operators to select the most reliable point based on actual system behavior rather than relying on a single model prediction.
2Ease of operation
If a single optimum operating point is deduced from optimization, then the control is simplified, but dynamic transients and safety margins are not accounted for
Solution Approach 1:
The patent segments the operating space into multiple discrete operating points, each representing a stable configuration. This segmentation allows the system to provide multiple reliable operating options rather than a single point, enabling operators to account for dynamic transients and safety margins by selecting appropriate points based on current system conditions and risk assessments.
Solution Approach 2:
The patent introduces dynamic considerations by allowing the set of candidate operating points to be updated based on changing system conditions, time, and operational requirements. This dynamic approach enables the system to adapt to transient conditions and maintain reliability by providing appropriate operating points for different operational phases and safety requirements.
3Adaptability or versatility
If multiple operating points are generated through systematic variation of independent variables, then the operability map provides comprehensive guidance, but the computational complexity increases
Solution Approach 1:
The patent segments the complex optimization problem into systematic variations of independent variables across defined ranges. By breaking down the multi-dimensional operating space into manageable segments (different flow rate ranges, pressure ranges, temperature ranges), the system generates multiple operating points through a structured process rather than exhaustive search, reducing computational complexity while maintaining comprehensive coverage.
Solution Approach 2:
The patent uses systematic parameter changes by varying independent variables in a structured manner across different ranges. This approach generates multiple operating points through controlled parameter variation rather than random search or exhaustive enumeration, providing comprehensive operating guidance while managing computational complexity through methodical parameter exploration.
Data Source
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AI summary
Embodiments of the invention identify a plurality of operating points for oil and/or gas producing systems, each operating point being characterised by a set of operating parameters which can be used to control components of the actual oil and/or gas producing system. These generated operating points may be collectively presented in a graphical manner to an operator of the oil and/or gas producing system, who can systematically configure the components of the oil and/or gas producing system to move, in an informed manner, through a path of operating points in order to reach what appears from the generated operating point data to be an optimal operating region. The oil and/or gas producing system may also be referred to as a hydrocarbon production system.