SEM-EDS Mineral Map for Oil Recovery Prediction
Find Innovative SolutionsGenerate Solutions
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 fail to account for the critical role of rock composition in enhancing oil recovery processes.
Innovation Solution
The method combines standard scanning electron microscopy (SEM) images with energy dispersive spectrum (EDS) chemical spectra on an individual pixel basis to generate mineral maps, which are then used to improve the interpretation of fluid-rock interactions by focusing on the spatial distribution of minerals adjacent to pores, thereby predicting the response of reservoir rocks to enhanced oil recovery techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If bulk mineralogy estimates are used to analyze pore geometry and fluid-rock interactions, then the analysis process is simplified, but the precision and accuracy of predicting enhanced oil recovery response deteriorates
Solution Approach 1:
The patent segments the rock sample analysis into discrete pixel-level mineral identification units. Each pixel in the SEM image is individually analyzed by EDS to determine mineral composition, creating a detailed mineral map that captures spatial heterogeneity. This segmentation allows precise characterization of fluid-rock interaction zones without requiring complex bulk analysis procedures.
Solution Approach 2:
The patent introduces mineral maps as an intermediary between SEM imaging and enhanced oil recovery prediction. The mineral maps integrate spatial mineral distribution data with fluid-rock interaction observations, serving as a bridge that connects structural information with functional predictions. This intermediary layer enables accurate prediction without directly performing complex bulk mineralogy estimates.
2Reliability
If extensive laboratory testing is performed to evaluate rock sample responses to enhanced oil recovery processes, then the reliability of predictions improves, but the time and resources required increase significantly
Solution Approach 1:
The patent performs preliminary mineral mapping and spatial distribution analysis before conducting enhanced oil recovery experiments. By pre-characterizing the mineralogy and identifying critical fluid-rock interaction zones through SEM-EDS mineral maps, the methodology prepares the sample in advance, enabling more targeted and efficient laboratory testing that requires less extensive experimentation to achieve reliable predictions.
Solution Approach 2:
The patent replaces extensive mechanical laboratory testing with a combination of imaging-based mineral identification and spatial analysis. Instead of relying solely on time-consuming physical experiments to evaluate rock responses, the method uses SEM-EDS mineral maps to predict enhanced oil recovery behavior, substituting physical testing with information-based prediction that requires minimal laboratory intervention.
3Loss of information
If spatial distribution of minerals adjacent to pores is analyzed using SEM-EDS mineral maps, then the understanding of fluid-rock interactions improves, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent merges SEM imaging capability with EDS spectral analysis into an integrated mineral mapping system. The SEM provides high-resolution spatial information while EDS delivers mineral composition data at each pixel location. By combining these two techniques into a unified mineral map generation process, the system captures complete spatial and compositional information without requiring separate analysis devices or procedures.
Solution Approach 2:
The patent creates a universal mineral mapping approach that can be applied to various rock types and enhanced oil recovery scenarios using the same SEM-EDS methodology. The mineral map generation process serves multiple functions: identifying mineral composition, mapping spatial distribution, locating fluid-rock interaction zones, and predicting recovery responses. This multi-functionality reduces the need for specialized equipment for each specific analysis task.
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 rapid and robust evaluation of rock samples' potential responses to enhanced oil recovery processes, reducing the need for additional laboratory tests and enabling the prediction of responses for similar rock samples, thus saving time and resources.
Implementation Method 1
A scanning electron microscope is a type of electron microscope that produces images of a sample by scanning it with a focused beam of electrons. The electrons interact with atoms in the sample, producing various signals that can be detected and that contain information about the sample's surface topography and composition.
Implementation Method 2
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 3
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 4
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 5
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. Its characterization capabilities are due in large part to the fundamental principle that each element has a unique atomic structure allowing for a unique set of peaks on its X-ray emission spectrum.
Data Source
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.