Rock Permeability Estimation via Aspect Ratio Pore Segmentation
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Solution Overview
Problem
Current methods for determining rock permeability in subterranean formations are inadequate as they fail to account for varying pore types with different aspect ratios, leading to insufficient characterization of complex geometrical characteristics and inaccurate estimation of rock permeability.
Innovation Solution
A process involving acquiring rock samples, determining volume-based aspect ratio distributions, grouping into pore types, obtaining mercury injection capillary pressure data, creating forward models, deriving initial pore size distributions, and optimizing these distributions using combinations of pore type models to accurately estimate rock permeability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a single aspect ratio is used to model pore systems, then the model is simple and easy to implement, but it fails to accurately represent the complex geometrical characteristics of multiple pore types in real rock formations
Solution Approach 1:
The patent divides the continuous aspect ratio distribution into discrete pore types (e.g., vug pores, moldic pores, intercrystalline pores) with specific aspect ratio ranges. This segmentation allows the complex pore system to be modeled as multiple simpler sub-systems, each characterized by representative aspect ratios, thereby maintaining modeling simplicity while improving characterization accuracy.
Solution Approach 2:
The patent assigns different aspect ratio values to different pore types within the same rock formation. Each pore type is given local quality characteristics (specific aspect ratios) that reflect its geometrical properties, allowing the model to capture spatial variability in pore geometry without requiring a completely complex unified model.
2Ease of operation
If experimental-based analytical equations are used to describe mercury injection capillary pressure data, then the fitting process is straightforward, but the fitting parameters are insufficient to quantitatively describe the complex geometrical characteristics for different pore size distribution types
Solution Approach 1:
The patent extends the traditional single-parameter pore size distribution model by adding the aspect ratio dimension. Instead of modeling pores as simple cylindrical tubes (one-dimensional radius), the invention incorporates two-dimensional geometrical characteristics (radius and aspect ratio) to describe pore throat geometry, thereby preserving geometrical information that would be lost in conventional models.
Solution Approach 2:
The patent introduces aspect ratio as an additional fitting parameter alongside traditional pore size parameters. By changing the parameter set from single-dimensional to multi-dimensional, the model gains the ability to quantitatively describe complex geometrical characteristics while maintaining the straightforward fitting approach through extended analytical equations.
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 a more precise estimation of rock permeability by accounting for multiple pore types, improving the accuracy of permeability assessments and informing drilling operations such as well placement and production planning.
Implementation Method 1
obtaining mercury injection capillary pressure data of the rock sample
Data Source
AI summary
Process for determining rock permeability. In some embodiments, the process can include determining a volume-based aspect ratio distribution of pores in a rock sample from a digital image of the sample, grouping the volume-based aspect ratio distribution into two or more pore types, selecting an initial pore type from the two or more pore types, obtaining mercury injection capillary pressure (MICP) data of the sample, creating a volume forward model and a frequency forward model using the MICP data, deriving an initial volume-based pore size distribution and an initial frequency-based pore size distribution for the initial pore type using the volume and the frequency forward models, respectively, selecting either the initial volume-based or the initial frequency-based distribution based on the forward models, and optimizing the selected distribution using an inversion of the MICP data with combinations of two or more pore type distributions to create an optimized distribution.