Petrophysical Modeling with CT Texture and NMR Heterogeneity Mapping
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Solution Overview
Problem
Existing laboratory techniques fail to accurately characterize the heterogeneity of carbonate reservoirs due to the trade-off between resolution and field of view in high-resolution imaging, leading to incomplete representation of pore-scale features and broader reservoir-scale properties.
Innovation Solution
A method involving CT imaging, texture classification, and NMR scanning is employed to segment and analyze rock samples, integrating deep learning algorithms to generate a petrophysical model that accounts for both microscopic and macroscopic heterogeneities, using a combination of micro-CT, CNN, and NMR techniques to estimate permeability and porosity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution imaging techniques are used to capture detailed pore-scale features, then measurement precision of pore structure is improved, but field of view is reduced limiting reservoir-scale characterization
Solution Approach 1:
The patent divides the rock sample into multiple sections or regions, imaging each section at high resolution using micro-CT. By segmenting the sample, the system can maintain high measurement precision for pore-scale features in each segment while collectively covering the entire reservoir-scale sample through multiple segments, thus resolving the contradiction between detailed imaging precision and overall field of view coverage.
2Ease of operation
If core samples are screened visually to ensure homogeneity, then ease of operation is improved, but measurement precision of heterogeneity is reduced
Solution Approach 1:
The patent replaces the manual visual inspection method with automated CT imaging and computational analysis. The CT scanning system automatically captures three-dimensional images of the core sample, and software algorithms analyze the images to identify and characterize heterogeneity patterns. This substitution maintains ease of operation while dramatically improving measurement precision of heterogeneity by providing objective, quantitative data throughout the entire sample volume.
Solution Approach 2:
The patent introduces CT imaging as an intermediary between sample selection and analysis. Instead of directly visually inspecting samples, the system uses CT scans as an intermediate step to create detailed internal images, which then guide the selection and characterization process. This intermediary enables precise heterogeneity measurement while maintaining operational efficiency through automated image analysis.
3Device complexity
If traditional permeability estimation methods are used, then device complexity is reduced, but measurement precision of permeability is worsened due to incomplete pore structure representation
Solution Approach 1:
The patent creates a digital copy or virtual model of the rock's pore structure through CT imaging. Instead of using physical models or simplified assumptions, the system generates accurate three-dimensional digital representations of the actual pore networks. These digital copies can then be used for computational permeability estimation, maintaining relatively simple physical device requirements while achieving high measurement precision through sophisticated image analysis and modeling algorithms.
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 comprehensive understanding of reservoir properties by reconciling detailed pore-scale information with broader reservoir-scale characteristics, enhancing the accuracy of permeability and porosity estimation, and improving reservoir characterization and management.
Implementation Method 1
imaging, using a computed tomography (CT) imaging device to generate a CT image of a rock sample from a reservoir
Implementation Method 2
scanning the rock sample using an nuclear magnetic resonance (NMR) device to provide NMR data for the rock sample, the NMR data characterizing relaxation times across different regions of the rock sample
Data Source
AI summary
Systems and methods are disclosed relating to reservoir characterization. A computed tomography (CT) imaging device is used to generate a CT image of a rock sample from a reservoir and segmented into CT slices. The CT slices are processed to identify textures of the rock sample to provide texture data. The rock sample is scanned using nuclear magnetic resonance (NMR) to provide NMR data. The NMR data is segmented to provide NMR segments. The NMR segments and texture data are analyzed to determine a contribution of each texture in each CT slice to one or more relaxation times in a corresponding NMR segment for each CT slice. A petrophysical property is predicted for each texture of each CT slice based on a contribution of each texture and the corresponding NMR segment for each CT slice. A petrophysical model for the reservoir is generated based on the predicted petrophysical property.