Grid Cell Count Optimization for Reservoir Simulation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for selecting the number of grid cells in reservoir simulation models do not effectively optimize for simulation time and hardware constraints, leading to inefficient computational resource usage and increased costs.
Innovation Solution
A system that uses a trained neural network to predict the optimal number of grid cells based on CPU usage time and available processors, incorporating time and hardware constraints, to create earth, geomechanical, or petro-elastic models for reservoir simulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of grid cells is increased to improve model accuracy, then simulation precision is improved, but computational time and resource consumption increase
Solution Approach 1:
The system dynamically adjusts the number of grid cells (a key parameter) based on input conditions such as reservoir characteristics, simulation type, and hardware constraints. By changing this parameter adaptively rather than using a fixed high grid count, the system achieves optimal balance between model accuracy and computational efficiency for different simulation scenarios.
2Manufacturing precision
If the number of grid cells is increased to improve model detail, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The system employs dynamic adjustment of grid cell count based on simulation requirements and available computational resources. Rather than using a static high-detail model for all cases, the system adapts the level of detail to match the specific simulation needs and hardware constraints, reducing unnecessary computational complexity while maintaining required model detail.
3Productivity
If more computational resources are allocated to increase simulation speed, then productivity is improved, but cost increases
Solution Approach 1:
The system determines an optimal grid cell count that provides sufficient model detail without excessive computation. By avoiding overly refined grids that would require disproportionate computational resources, the system achieves adequate simulation speed using moderate computational resources, rather than allocating excessive resources to achieve marginal gains in simulation speed.
Data Source
AI summary
Systems, methods and computer readable storage media for optimizing a determination of a number of grid cell counts to be used in creating the geocellular grid of an earth, geomechanical or petro-elastic model for reservoir simulation. These may involve determining at least one processing time for a simulation; determining a grid cell count to be used in creating a geocellular grid for the simulation based on the at least one processing time and a number of processors to be used for creating the model; creating the geocellular grid using the grid cell count, and generating a model for the simulation using the geocellular grid.