Porous Medium Model Generation Using Fourier Series and Collision Detection
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Solution Overview
Problem
Current methods for generating porous medium models, such as CT scanning and random field models, face challenges in efficiently creating diverse models for geological reservoirs, particularly in low porosity scenarios and accurately representing complex particle configurations, with high computational costs and storage requirements.
Innovation Solution
A method utilizing Fourier series to generate irregular particle shapes, combined with particle filling and collision detection algorithms, enables the creation of interconnected porous media with near-zero porosity, employing grid mapping and the Floyd-Warshall algorithm for efficient collision detection and parameter updating.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CT scanning is used to create porous medium models, then measurement precision is improved, but cost and efficiency deteriorate
Solution Approach 1:
The patent creates digital copies of porous medium structures through mathematical modeling rather than physical CT scanning. The Fourier series generates particle configurations that replicate real porous media geometry, while the particle accumulation model simulates the stacking process, producing virtual models that substitute for expensive physical scanning while maintaining structural fidelity.
Solution Approach 2:
The patent replaces the mechanical CT scanning system with a computational system using Fourier series transformation and particle accumulation algorithms. This substitution transitions from physical measurement equipment to mathematical modeling, dramatically improving efficiency while preserving the essential geometric characteristics of porous media.
2Adaptability or versatility
If random field model is used to generate porous media, then model diversity is improved, but connectivity in low porosity models deteriorates
Solution Approach 1:
The patent performs preliminary particle placement using Fourier series to generate candidate particle positions and configurations before final model assembly. This preliminary arrangement ensures that particles are positioned to maintain connectivity pathways, and the accumulation process is guided to preserve continuous porous structures even at low porosity levels.
Solution Approach 2:
The patent employs a dynamic particle accumulation process where particles are added iteratively with adjustments to maintain connectivity. The model evolves through controlled accumulation steps that adapt particle placement to preserve continuous pore networks, allowing the system to dynamically adjust configurations to maintain reliability while achieving diversity.
3Manufacturing precision
If level set function is used for particle shape representation, then manufacturing precision is improved, but computational cost and storage space deteriorate
Solution Approach 1:
The patent uses simplified particle shape representations that are computationally inexpensive compared to level set functions. While individual particles have less geometric detail, the overall model achieves sufficient precision through the collective arrangement of many particles, trading individual particle complexity for overall model efficiency and reduced computational burden.
Solution Approach 2:
The patent applies partial detail to particle shapes - using simplified geometries that capture essential morphological features without the full complexity of level set representations. This partial representation is sufficient for pore-scale simulation purposes while dramatically reducing computational costs and storage requirements.
4Manufacturing precision
If single particle method is used with closed curves, then manufacturing precision is improved, but collision detection difficulty increases
Solution Approach 1:
The patent introduces an intermediary collision detection mechanism that simplifies the detection process. Rather than directly checking complex closed curve intersections, the system uses bounding box or distance-based preliminary checks as intermediaries to quickly identify potential collisions, reducing the computational complexity of detecting interactions between irregularly shaped particles.
Data Source
AI summary
Provided are a method and a system for randomly generating a porous medium model. The method includes following steps: setting a porosity, resolution and a size of a pre-generated porous medium model; initializing the porous medium model and generating position information of particles; extracting particle profile edges; obtaining filled particles; carrying out a collision detection on the filled particles and preset particles, and determining effectiveness of a particle generation position; presetting a cyclic pop-up condition, and if a judgment result meets the cyclic pop-up condition, continuing; otherwise, updating Fourier parameters; adding a particle configuration meeting the cyclic pop-up condition to a model generation area, and storing parameters; determining whether the generated model meets preset generation requirements, and if so, outputting a porous medium model.