Automated Reservoir Simulation Resource Configuration
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Solution Overview
Problem
Reservoir simulations are computationally expensive and can fail due to inadequate computer resource configuration, which is beyond the expertise of some users, leading to wasted time and resources.
Innovation Solution
A method and system that automate the configuration of computing resources for reservoir simulations using a simulation engine to identify the minimum necessary resources based on past performance data and objectives, reducing the likelihood of simulation failure and simplifying the user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automated resource configuration is implemented, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The simulation engine automatically configures computing resources by analyzing simulation objectives, constraints, and historical performance data without requiring user expertise in resource configuration. The system self-determines optimal CPU cores, memory, and storage allocation based on simulation parameters and past performance patterns.
Solution Approach 2:
The system performs preliminary analysis of simulation objectives and constraints before the actual simulation runs. It pre-configures the computing resources by evaluating historical performance data and simulation requirements, preparing the optimal resource allocation in advance to avoid configuration errors during execution.
2Device complexity
If manual resource configuration is used, then device complexity is reduced, but reliability deteriorates due to misconfiguration
Solution Approach 1:
The simulation engine incorporates feedback loops that monitor simulation performance and resource utilization. It continuously adjusts resource allocation based on actual simulation behavior and historical performance data, learning from past configurations to improve reliability and prevent misconfiguration errors.
Solution Approach 2:
The system automatically detects and corrects configuration issues by analyzing simulation objectives and constraints. It self-validates resource allocations against predefined criteria and historical performance patterns, ensuring reliable configuration without requiring manual verification.
3Productivity
If adequate computing resources are allocated, then productivity is improved, but loss of energy increases
Solution Approach 1:
The simulation engine dynamically adjusts computing resource allocation during simulation execution based on actual performance needs. It monitors simulation progress and resource utilization in real-time, scaling resources up or down as required to maintain productivity while minimizing energy waste from over-provisioning.
Solution Approach 2:
The system optimizes resource allocation parameters by analyzing historical performance data and simulation characteristics. It adjusts CPU cores, memory, and storage parameters dynamically to achieve the minimum necessary resources for completing simulations within target time frames, reducing energy consumption while maintaining productivity.
Data Source
AI summary
A method and system for automating a reservoir simulation. The method includes identifying a simulation parameter associated with a simulation resource to perform a computer-based reservoir simulation using reservoir data associated with a subterranean reservoir and configuring the simulation resource using a simulation engine to include the simulation parameter for performing the reservoir simulation with a reduced likelihood of simulation failure. The method also includes performing the reservoir simulation using the configured simulation resource and the reservoir data to generate reservoir simulation data and evaluate the reservoir.