SEM-EDS Mineral Mapping for EOR Response Prediction
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Solution Overview
Problem
Current methods for analyzing pore geometry and fluid-rock interactions in reservoir rocks are limited, relying on bulk mineralogy estimates and requiring extensive laboratory testing, which is time-consuming and imprecise, and do not adequately account for the mineral composition at the critical regions where fluid interactions occur.
Innovation Solution
Combining standard scanning electron microscopy (SEM) images with energy dispersive spectrum (EDS) chemical spectra on an individual pixel basis to generate mineral maps, which provide spatial distribution information of mineral types adjacent to void spaces in reservoir rocks, and integrating this data with laboratory test results to predict the effectiveness of enhanced oil recovery processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If bulk mineralogy estimates are used to analyze fluid-rock interactions, then the analysis process is simplified, but the precision and accuracy of predicting enhanced oil recovery responses deteriorates
Solution Approach 1:
The patent segments the rock sample analysis into distinct spatial regions (pore spaces vs. grain interiors) and analyzes mineral composition separately in each region. This segmentation allows identification of critical pore wall mineralogy that controls fluid-rock interactions, resolving the contradiction by providing detailed precision where needed while maintaining overall process efficiency.
Solution Approach 2:
The patent applies local quality analysis by focusing computational and analytical resources specifically on pore wall regions where fluid-rock interactions occur, rather than uniformly analyzing the entire rock volume. This targeted approach improves prediction accuracy for EOR responses while avoiding unnecessary analysis of non-critical regions.
2Measurement precision
If extensive laboratory testing is performed to evaluate rock samples, then the accuracy of predicting enhanced oil recovery responses is improved, but the time required and resources consumed increase significantly
Solution Approach 1:
The patent performs preliminary analysis of pore wall mineralogy using SEM-EDS imaging before conducting full-scale laboratory testing. This preliminary characterization identifies key mineralogical controls on fluid-rock interactions, allowing optimization of subsequent laboratory test designs and reducing the number of tests needed to achieve accurate predictions.
Solution Approach 2:
The patent replaces extensive mechanical laboratory testing with a computational modeling approach that uses SEM-EDS derived pore wall mineralogy as input parameters. This substitution significantly reduces testing time while maintaining prediction accuracy by using physics-based models to simulate fluid-rock interaction outcomes.
3Productivity
If standard SEM imaging is used without EDS spectral analysis, then the imaging speed and simplicity are maintained, but the ability to identify mineral composition at critical regions deteriorates
Solution Approach 1:
The patent merges standard SEM imaging with EDS spectral analysis into an integrated workflow. The SEM provides high-speed morphological imaging to identify pore spaces and grain structures, while EDS analysis is automatically applied to determine mineral composition at identified pore wall locations, preserving both imaging speed and mineralogical information.
Solution Approach 2:
The patent uses automated image processing and mineral identification algorithms as intermediaries between SEM imaging and EDS analysis. These intermediaries rapidly process SEM images to locate pore walls, then trigger targeted EDS analysis only at critical regions, maintaining overall workflow efficiency while capturing essential mineral composition data.
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 enables rapid and robust evaluation of rock samples' potential responses to enhanced oil recovery processes, reducing the need for additional laboratory tests and allowing for the prediction of fluid-rock interactions, thereby improving the accuracy and efficiency of hydrocarbon recovery techniques.
Implementation Method 1
One type of detected energy is associated with secondary electrons that are emitted from surface or shallow interactions of the electron beam with the material
Implementation Method 2
Another type of detected energy is associated with backscattered electrons that are emitted after elastic scattering interactions with the electron shell of atoms that respond to differences in atomic number
Implementation Method 3
Yet another type of detected energy are characteristic X-Rays that are produced when the incident electron beam excites ground-state electrons in an atom to another state. The change in energy states results in a distinct X-Ray spectrum for each element
Implementation Method 4
Energy-dispersive X-ray spectroscopy (EDS) is an analytical technique used for the elemental analysis or chemical characterization of a sample. It relies on an interaction of some source of X-ray excitation and a sample
Data Source
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AI summary
Methods of combining mineral composition and laboratory test results for reservoir rock samples to predict future responses to secondary and tertiary oil recovery treatments are disclosed. Particular, SEM and EDS will be combined to produce a mineral map, including mineral distribution around the rock's pore space, for comparison with laboratory data to predict and/or interpret how certain mineral distributions will respond to various fluid-rock interactions.