Digital Rock Modeling for Multiphase Flow Upscaling
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Solution Overview
Problem
Current methods for estimating flow unit properties of geological formations are limited in accuracy, leading to poor resource management and increased costs due to the need for multiple physical core samples and laboratory experiments, especially when simulating multiphase rock-fluid interactions.
Innovation Solution
A computing system that uses multiphase upscaling and machine learning to estimate relative permeability and capillary pressures by generating synthetic rock samples with varying volumetric distributions, allowing for automation and extrapolation of flow unit properties from core to reservoir scale, reducing the need for extensive physical sampling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical core samples are acquired and laboratory experiments are performed to determine multiphase rock-fluid interaction properties, then measurement precision is improved, but loss of time and productivity deteriorate due to the extensive sampling and experimentation required
Solution Approach 1:
The patent creates digital rock models that replicate the physical and chemical properties of actual rock formations. These digital copies allow virtual experimentation and multiphase flow simulation without requiring extensive physical core sampling and laboratory testing, thereby maintaining measurement precision while significantly improving productivity
Solution Approach 2:
The patent replaces physical laboratory experiments with computational simulations. Machine learning models and numerical algorithms substitute for physical rock-fluid interaction experiments, enabling rapid estimation of relative permeability and capillary pressure curves without the time-consuming nature of physical testing
2Measurement precision
If more core samples are acquired from the formation to obtain flow unit descriptions, then measurement precision is improved, but loss of substance and productivity worsen due to increased sampling requirements
Solution Approach 1:
The patent develops a universal digital rock modeling framework that can estimate flow unit properties for multiple rock types and formations using the same computational approach. This multi-functional system eliminates the need to acquire separate core samples for each formation type, reducing overall sample requirements while maintaining estimation accuracy across diverse geological settings
3Measurement precision
If physical laboratory experiments are performed on core samples, then measurement precision is improved, but device complexity and loss of time worsen due to the complex experimental setup and execution
Solution Approach 1:
The patent replaces complex physical experimental apparatus with computational models and algorithms. Digital rock models simulate multiphase flow behavior through numerical methods, eliminating the need for sophisticated laboratory equipment while maintaining the ability to accurately determine relative permeability and capillary pressure properties
Data Source
AI summary
A system can access geological data describing a plurality of rock types in a physical rock sample drilled from a reservoir. The system can generate synthetic rock samples and execute single phase upscaling to compute absolute permeabilities for the physical rock sample and the synthetic rock samples. The system can execute a first multiphase upscaling based on the single phase upscaling to determine relative permeabilities for the physical rock sample and the synthetic rock samples. The system can compare the relative permeability of the physical rock sample to the relative permeabilities for the synthetic rock samples and select a synthetic rock sample that varies the least from the physical rock sample. The system can perform at least one additional multiphase upscaling on the physical rock sample and the synthetic rock samples to determine a second multiphase upscaling result and to develop a plan for drilling operations.


