Inflow Control Device Simulation Selection
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Solution Overview
Problem
Conventional tools and techniques fail to generate accurate simulations of in-flow control devices (ICDs) within well casings, limiting the accuracy of oil production simulations and not allowing for real-time updating or modification of these simulations based on changing reservoir properties.
Innovation Solution
A method and system that use a computing device to generate and select in-flow control device design simulations based on a reservoir simulation model, incorporating density and cross-sectional area parameters, and automatically update simulations in real-time to optimize ICD placements within well compartments, enabling efficient hydrocarbon extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional tools and techniques are used to generate simulations, then the simulation generation process is simple, but the accuracy of ICD placement simulations is insufficient
Solution Approach 1:
The patent introduces an automated case selection factor generation system that acts as an intermediary between the reservoir simulation model and the ICD placement simulations. This intermediary automatically generates case selection factors based on reservoir properties and well characteristics, enabling accurate simulation selection without requiring complex manual configuration by users.
Solution Approach 2:
The system enables self-service by automatically generating case selection factors and selecting appropriate simulations without user intervention. The automated process evaluates reservoir properties, generates relevant case selection factors, and selects the most appropriate ICD placement simulations, eliminating the need for users to manually configure complex simulation parameters.
2Adaptability or versatility
If manual simulation generation and selection is performed, then user control over simulation parameters is maintained, but real-time updating and modification of simulations is not possible
Solution Approach 1:
The patent implements dynamic simulation selection by enabling real-time updating of case selection factors when reservoir properties change. The system continuously monitors reservoir data and automatically regenerates case selection factors, allowing simulations to adapt dynamically to changing reservoir conditions without requiring manual reconfiguration.
Solution Approach 2:
The system incorporates feedback mechanisms where simulation results and updated reservoir properties feed back into the case selection factor generation process. This feedback loop enables the system to automatically adjust and select new simulations based on the latest reservoir data, maintaining adaptability while fully automating the selection process.
3Reliability
If multiple ICD configuration simulations are generated, then optimal ICD placement can be identified, but the time and computational resources required increase
Solution Approach 1:
The patent applies partial action by generating only the necessary case selection factors required for optimal ICD placement rather than exhaustively simulating all possible configurations. The automated system identifies and generates only the relevant case selection factors based on reservoir properties, reducing computational overhead while maintaining optimization accuracy.
Solution Approach 2:
The system performs preliminary action by pre-generating case selection factors based on reservoir properties before conducting detailed ICD placement simulations. This preliminary generation of selection factors filters and prepares the data in advance, enabling faster and more efficient optimization simulations without sacrificing reliability.
Data Source
AI summary
A method relates to generating and selecting in-flow control device design simulations. The method includes generating, based on a synthetic production logging profile and properties of a reservoir associated with a target well, a first design simulation and a second design simulation, the first design simulation including representations of a first plurality of in-flow devices and the second design simulation including different representations of a second plurality of in-flow devices, locations of the representations of the first plurality of in-flow devices and different locations of the different representations of the second plurality of in-flow devices is based on density parameters and cross-sectional area parameters, generating, automatically and without user intervention, case selection factors associated with each of the first design simulation and the second design simulation, ranking, automatically and without user intervention, the case selection factors; and selecting based on the ranking, automatically and without user intervention, at least one of the first design simulation or the second design simulation.