Rock Fabric Imaging Workflow for Accurate Shale Flow Modeling
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Solution Overview
Problem
Current methods for characterizing nano-microscale fabrics in shale reservoirs, such as FIB-SEM imaging, are time- and resource-intensive, and do not effectively model fluid flow behavior due to limited field of view and high costs, making it difficult to optimize hydrocarbon production.
Innovation Solution
A method involving CT scanning to generate a digital image volume, segmentation to identify rock fabrics, machining to expose physical faces, and SEM imaging at multiple scales to determine material properties, followed by image processing to create statistically similar 3D models for fluid flow simulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If FIB-SEM imaging is used to characterize nano-microscale fabrics, then measurement precision is improved, but loss of time and cost increase significantly
Solution Approach 1:
The method segments the rock sample analysis into distinct phases: first acquiring a low-resolution 3D CT scan to identify fabric locations, then selectively imaging only those specific regions at high resolution with FIB-SEM. This segmentation approach maintains measurement precision for critical areas while dramatically reducing overall analysis time compared to full-sample high-resolution imaging.
Solution Approach 2:
The method creates a digital 3D model from the CT scan that serves as a virtual copy of the rock sample's internal structure. This digital replica allows identification of fabric locations and planning of FIB-SEM imaging without requiring direct high-resolution scanning of the entire physical sample, thereby reducing time and resource consumption.
2Measurement precision
If FIB-SEM imaging is used to characterize nano-microscale fabrics, then measurement precision is improved, but cost increases significantly
Solution Approach 1:
The method segments the rock sample analysis into distinct phases: first acquiring a low-resolution 3D CT scan to identify fabric locations, then selectively imaging only those specific regions at high resolution with FIB-SEM. This segmentation approach maintains measurement precision for critical areas while dramatically reducing overall analysis time compared to full-sample high-resolution imaging.
Solution Approach 2:
The method creates a digital 3D model from the CT scan that serves as a virtual copy of the rock sample's internal structure. This digital replica allows identification of fabric locations and planning of FIB-SEM imaging without requiring direct high-resolution scanning of the entire physical sample, thereby reducing time and resource consumption.
3Productivity
If direct numerical simulation is used to estimate physical properties, then productivity is improved, but measurement precision deteriorates due to limited field of view
Solution Approach 1:
The method performs preliminary low-resolution 3D CT scanning and fabric identification before conducting high-resolution FIB-SEM imaging. This preliminary action allows the subsequent numerical simulation to focus computational resources on accurately modeling only the identified fabric regions, improving both the precision of property estimates and the efficiency of the overall process.
Solution Approach 2:
The method applies high-resolution imaging and detailed numerical simulation only to specific regions where fabrics are identified, rather than uniformly processing the entire sample. This local quality approach concentrates computational and imaging resources on critical areas, improving measurement precision for fabric-related properties while maintaining productivity.
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
Provides a cost-effective and efficient characterization of nano-microscale fabrics in shale reservoirs, improving hydrocarbon production by accurately modeling fluid flow and reducing uncertainties in well production planning.
Implementation Method 1
a three-dimensional tomographic image of the rock sample is obtained, for example by way of a computer tomographic (CT) scan
Implementation Method 2
performing scanning electron microscope (SEM) imaging of the physical faces to generate two-dimensional (2D) SEM images of the physical faces
Data Source
Figure 1A
Figure 1B~1C
Figure 2A~2B
AI summary
A method for analyzing a rock sample includes segmenting a digital image volume corresponding to an image of the rock sample, to associate voxels in the digital image volume with a plurality of rock fabrics of the rock sample. The method also includes identifying a set of digital planes through the digital image volume. The set of digital planes intersects with each of the plurality of rock fabrics. The method further includes machining the rock sample to expose physical faces that correspond to the identified digital planes, performing scanning electron microscope (SEM) imaging of the physical faces to generate two-dimensional (2D) SEM images of the physical faces, and performing image processing on the SEM images to determine a material property associated with each of the rock fabrics.