Relative Permeability Modeling from 3D Pore-Scale Flow Matching
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Solution Overview
Problem
Conventional methods for determining relative permeability of porous media are time-consuming, expensive, and challenging due to the need for experimental measurements with model fluids, especially for gases like CO2 and H2, and do not accurately integrate all experimentally measured quantities, such as saturation profiles.
Innovation Solution
A method involving 3D imaging, pore-scale flow simulation, and Darcy-scale modeling is used to determine relative permeability by segmenting a 3D image of a porous medium, simulating fluid flow at both scales, and iteratively updating the relative permeability model until a match within a predetermined tolerance is achieved.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the steady-state method is used to experimentally measure relative permeability, then the measurement is more robust against displacement instabilities and easier to interpret, but it requires injection of thousands of pore volumes of fluid at different fractional flow rates, which poses significant technical challenges and increases time and cost
Solution Approach 1:
The patent uses X-ray imaging to create digital copies (saturation profiles) of the physical fluid distribution in the rock sample. These digital saturation profiles are then integrated into the unsteady-state method, allowing accurate measurement without requiring the extensive fluid injection volumes needed by conventional steady-state methods.
Solution Approach 2:
The patent replaces the mechanical measurement approach (physical fluid injection and direct pressure/flow measurements) with an imaging-based approach. X-ray saturation monitoring provides non-intrusive measurement of fluid distribution, eliminating the need for complex mechanical injection systems and extensive pore volume injection.
2Loss of time
If the unsteady-state method is used to determine relative permeability, then the injection volumes are significantly reduced and it is better suited for handling the fluids of interest, but traditional interpretation methods make significant simplifications and do not integrate all experimentally measured quantities such as saturation profiles
Solution Approach 1:
The patent merges the unsteady-state method with X-ray saturation monitoring and capillary end-effect correction. By combining these elements, the method achieves both reduced injection volumes and high measurement precision, as the saturation profiles provide accurate data while the correction accounts for capillary effects that would otherwise reduce precision.
Solution Approach 2:
The patent incorporates capillary end-effect correction as a feedback mechanism. The correction uses the measured saturation profiles and flow data to iteratively refine the relative permeability calculation, ensuring that all experimentally measured quantities are properly integrated and the final results are accurate despite the simplified unsteady-state approach.
3Reliability
If conventional experimental methods are used to measure relative permeability with model fluids, then the measurement process is well-established, but it is time-consuming, expensive, and limits the number of samples that can be processed
Solution Approach 1:
The patent uses X-ray imaging to create digital representations of fluid saturation in rock samples. This copying approach allows rapid, non-destructive measurement that can be automated, significantly increasing the number of samples that can be processed compared to conventional methods that require physical fluid injection and manual measurement for each sample.
Solution Approach 2:
The patent replaces the time-consuming mechanical injection and measurement processes with automated X-ray imaging and computational analysis. This substitution eliminates the need for extensive fluid injection, pressure monitoring, and manual data collection for each sample, thereby dramatically increasing sample throughput while maintaining measurement reliability.
4Productivity
If pore-scale flow simulation is used to determine relative permeability, then computational cost is reduced and speed is improved, but it requires accurate 3D imaging and segmentation of the porous medium structure
Solution Approach 1:
The patent performs 3D imaging and segmentation of the porous medium structure as a preliminary step before conducting pore-scale flow simulations. By preparing the digital rock model in advance, the actual relative permeability determination can proceed rapidly through simulation, achieving high productivity while managing device complexity through upfront preparation.
Solution Approach 2:
The patent creates a digital copy of the porous medium structure through 3D imaging and segmentation. This digital replica can then be used repeatedly for pore-scale flow simulations without requiring physical sample preparation or modification, reducing the impact of imaging complexity on the overall determination process and enabling rapid iteration.
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 allows for faster, more accurate, and less computationally expensive determination of relative permeability, accounting for capillary end-effects and providing consistent capillary pressure-saturation functions for improved decision-making in hydrology, petroleum engineering, and carbon storage.
Implementation Method 1
simulating fluid flow on the segmented structural image with a pore-scale flow simulation to produce a pore-scale output
Implementation Method 2
generating a Darcy-scale flow model by simulating fluid flow based on boundary conditions of the pore-scale flow simulation using the initial relative permeability model
Data Source
AI summary
A method for determining a relative permeability of a porous medium uses a segmented structural image generated from a 3D image to produce a pore-scale output from a pore-scale flow simulation. A Darcy-scale flow model is generated by simulating fluid flow on boundary conditions of the pore-scale flow simulation and an initial relative permeability model. The Darcy-scale output is compared to the pore-scale output to determine a degree of match. The initial relative permeability model is updated and the Darcy-scale simulation and inverse modeling steps are repeated until the degree of match falls within a pre-determined tolerance.