Digital Rock Analysis REV Determination via Phase Partitioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for determining the representative elementary volume (REV) in digital rock analysis are subjective, prone to errors, and fail to accurately characterize anisotropic and heterogeneous materials, especially in multiphase fluid flow simulations.
Innovation Solution
The system employs high-resolution focused ion beam and scanning electron microscopy coupled with high-performance computing to analyze the porosity structure of samples, using phase-based partitioning and statistical analysis of subvolume parameters to determine the REV, enabling accurate characterization of multiphase flow properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional REV determination methods are used, then the process is simpler, but the results are subjective and prone to errors
Solution Approach 1:
The patent creates digital copies (virtual models) of rock samples through high-resolution scanning and imaging, allowing REV determination to be performed on digital representations rather than physical samples. This enables repeated, consistent analysis without subjective physical measurements, resolving the contradiction between measurement precision and complexity by automating the analysis process through computational methods.
Solution Approach 2:
The patent replaces manual, subjective REV determination methods with automated computational algorithms that analyze digital rock models. Statistical metrics and automated classification systems substitute for human judgment, eliminating subjectivity and errors while managing complexity through software-based solutions.
2Measurement precision
If high-resolution microscopy and high-performance computing are used, then REV determination accuracy is improved, but the computational resources and time required increase
Solution Approach 1:
The patent performs preliminary high-resolution scanning and digital model creation once, then reuses these digital models for multiple REV determination analyses. This preliminary action captures all necessary detail upfront, allowing subsequent statistical analyses to be performed efficiently on the existing digital data without repeated physical scanning, thus reducing overall time loss.
Solution Approach 2:
The patent analyzes multiple subvolumes and statistical metrics beyond the minimum required, using excessive computational effort to ensure robust REV determination. By performing more analyses than strictly necessary (multiple statistical tests, multiple subvolume classifications), the system achieves higher confidence and accuracy in REV identification, justifying the additional computational time through more reliable results.
3Reliability
If statistical analysis of multiple subvolumes is performed, then REV determination reliability is improved, but the computational complexity increases
Solution Approach 1:
The patent divides the digital rock model into multiple subvolumes and performs independent REV analysis on each segment. This segmentation allows statistical comparison across multiple regions, improving reliability by ensuring the REV determination is consistent throughout the entire sample rather than relying on a single potentially anomalous region.
Solution Approach 2:
The patent uses statistical feedback from multiple subvolume analyses to iteratively refine REV determination. By comparing results across subvolumes and using statistical metrics to guide further analysis, the system automatically adjusts and converges on the correct REV, improving reliability through self-correcting computational feedback loops.
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
This approach provides a robust and objective method for determining the REV, ensuring accurate representation of larger volumes and improved accuracy in multiphase fluid flow simulations by identifying the length scale at which distribution moments converge, thus addressing the limitations of existing methods.
Implementation Method 1
high resolution focused ion beam and scanning electron microscope
Implementation Method 2
high resolution focused ion beam and scanning electron microscope
Data Source
AI summary
The pore structure of rocks and other materials can be determined through microscopy and subject to digital simulation to determine the properties of multiphase fluid flows through the material. To conserve computational resources, the simulations are preferably performed on a representative elementary volume (REV). The determination of a multiphase REV can be determined, in some method embodiments, by deriving a porosity-related parameter from a pore-matrix model of the material; determining a multiphase distribution within the material's pores; partitioning the pore-matrix model into multiple phase-matrix models; and deriving the porosity-related parameter from each phase-matrix model. The parameter's dependence on phase and saturation can then be determined and analyzed to select an appropriate REV size.