Material Strain Decomposition for Reservoir Simulation
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Solution Overview
Problem
Inaccurate estimation of material strain leads to inaccurate modeling of materials, such as rocks, resulting in unreliable predictions of hydrocarbon recovery from subsurface regions.
Innovation Solution
A system and method for decomposing material strain into classical, hysteretic, and residual components, allowing for more accurate modeling of materials by facilitating the determination of effective moduli of elasticity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional strain approximation methods are used, then the modeling process is simple, but the accuracy of material modeling and hydrocarbon recovery predictions is poor
Solution Approach 1:
The patent segments the total material strain into three distinct components: elastic strain (reversible), plastic strain (irreversible), and hysteretic strain (energy-dissipating). This segmentation allows each component to be modeled with appropriate constitutive laws, significantly improving strain measurement accuracy while providing a structured framework that manages modeling complexity through systematic decomposition of the strain tensor.
Solution Approach 2:
The patent transforms the single-parameter strain approximation into a multi-parameter strain decomposition model. By introducing additional parameters (elastic modulus, plastic yield stress, hysteretic damping coefficients) and establishing their relationships through constitutive equations, the model achieves higher accuracy in predicting material behavior under cyclic loading conditions while maintaining tractability through parameter identification from experimental data.
2Reliability
If strain is decomposed into multiple components, then modeling accuracy improves, but the decomposition process becomes more complex
Solution Approach 1:
The strain decomposition process is segmented into distinct computational steps: (1) calculate elastic strain using Hooke's law from stress and elastic modulus, (2) determine plastic strain through yield criterion and flow rules, and (3) compute hysteretic strain as the residual component. This stepwise segmentation improves modeling reliability by ensuring each component satisfies its governing physical laws while managing decomposition complexity through a systematic algorithmic approach.
Solution Approach 2:
The patent implements feedback mechanisms in the strain decomposition process by using experimental stress-strain data to identify and update material parameters (elastic modulus, yield stress, hardening coefficients) iteratively. This feedback loop ensures that the decomposed strain components accurately reflect the actual material behavior, improving modeling reliability while the automated parameter identification algorithms keep the decomposition process manageable despite its complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The decomposition of material strain into its components enables more accurate modeling of materials, leading to improved predictions of hydrocarbon recovery, with a demonstrated 20% difference in estimated ultimate recovery compared to traditional strain approximation methods.
Implementation Method 1
The decomposition component may be configured to decompose the strain of the material into classical strain, hysteretic strain, residual strain, and/or other strain
Data Source
AI summary
Strain information may define strain of a material to stress. The strain of the material may be decomposed into classical strain, hysteretic strain, and residual strain. The classical strain, the hysteretic strain, and the residual strain may be used to facilitate modeling of the material. For example, the classical strain, the hysteretic strain, and the residual strain of a rock may be used to facilitate modeling of a subsurface region that includes the rock such as a reservoir simulation to predict hydrocarbon recovery.