Hyperspectral Geological Mapping for Consistent ROI Detection
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Solution Overview
Problem
Existing geological mapping methods are laborious, prone to variation, and require manual review and adjustment by geologists, leading to inconsistencies and inefficiencies.
Innovation Solution
An automated geological mapping method using hyperspectral imaging and machine learning to generate geo-spatially accurate maps of geological structures, identifying regions of interest without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review and adjustment of hyperspectral data is performed by geologists, then mapping accuracy can be improved, but productivity decreases and consistency deteriorates
Solution Approach 1:
The system performs preliminary automated processing of hyperspectral data to generate initial geological maps before any human review. The automated classification and mineral identification are completed in advance, providing a ready-to-review foundation that significantly reduces the time geologists need to spend on initial map generation while maintaining consistent quality standards.
Solution Approach 2:
The patent replaces the manual mechanical process of geological map creation with an automated computational system. Machine learning algorithms and hyperspectral analysis software automatically classify minerals and generate maps, substituting the manual review and adjustment process with automated digital processing that maintains accuracy while dramatically increasing productivity.
2Measurement precision
If manual review and adjustment of hyperspectral data is performed by geologists, then mapping accuracy can be improved, but consistency deteriorates due to variation between different geologists
Solution Approach 1:
The system performs self-service through automated algorithms that independently analyze hyperspectral data and generate geological maps without requiring human intervention. The machine learning models consistently apply the same classification criteria and mineral identification algorithms to all datasets, ensuring uniform results regardless of which geologist would have performed the manual review, thereby eliminating inter-geologist variability.
Solution Approach 2:
The patent transforms the subjective parameters of manual geological assessment into objective, quantifiable parameters through hyperspectral analysis. By converting visual geological judgments into measurable spectral signatures and mineral abundance percentages, the system enables consistent, repeatable results that are independent of individual geologist expertise or interpretation styles.
3Productivity
If automated processing is implemented, then productivity increases and consistency improves, but device complexity increases
Solution Approach 1:
The patent implements a universal hyperspectral analysis platform that handles multiple geological mapping tasks through a single integrated system. The same automated processing pipeline performs mineral identification, classification, abundance estimation, and map generation across different geological settings and mine types, reducing the need for multiple specialized tools and simplifying the overall system architecture despite the advanced capabilities.
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
The method enables rapid, accurate, and consistent generation of geological maps, reducing the need for manual review and ensuring repeatable results, enhancing workflows such as mine planning and automation.
Implementation Method 1
The method may involve capturing the scan data using a hyperspectral imaging device. The method may involve forming a hyperspectral data cube. The hyperspectral data cube may include two or more spatial dimensions (representing location in 2D or 3D space) and one spectral dimension.
Data Source
AI summary
The present invention relates to a geological mapping method. The method includes receiving scan data relating to a geological structure. The data is processed to determine one or more regions of interest. The method further includes displaying a geo-spatially accurate map of the geological structure showing the regions of interest. Advantageously, the map showing the regions of interest may be rapidly generated, without the need for manual review and adjustment by a geologist. The mapping method may be accurate, consistent and repeatable without the need for manual review and adjustment by a geologist.