Rock Classification Map Conversion for Consistent Lithologic Modeling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Converting rock classification maps for modeling is difficult and time-consuming due to non-interpolatable classification of rocks, which leads to inefficiencies and inconsistencies in lithologic modeling, particularly in basin modeling.
Innovation Solution
An automated lithologic model workflow that transforms rock classification maps into gridded index maps through image treatment and associates them with lithology values using a rock-lithology library, enhancing modeling efficiency and consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If rock classification maps are converted manually for modeling, then modeling accuracy can be maintained, but the conversion process becomes time-consuming and inefficient
Solution Approach 1:
The patent replaces manual mechanical conversion processes with automated image treatment and digital workflows. The system uses computer-based image processing to automatically convert rock classification maps into gridded index maps, eliminating the need for manual digitization while maintaining modeling accuracy through systematic color-to-lithology value mapping.
Solution Approach 2:
The system enables self-service conversion by allowing users to import rock classification maps and automatically generate gridded index maps through automated image treatment. The rock-lithology library automatically matches colors to lithology values without requiring manual intervention, making the conversion process independent and efficient.
2Productivity
If automated conversion methods are used, then processing efficiency improves, but consistency and accuracy of lithologic modeling may deteriorate
Solution Approach 1:
The patent transforms the rock classification map from its original format into a gridded index map with standardized parameters. By converting visual color information into discrete lithology values through a systematic mapping process, the system maintains consistency while enabling automated processing. The rock-lithology library provides standardized parameter mappings that ensure reliable and repeatable results.
Solution Approach 2:
The patent introduces a rock-lithology library as an intermediary between the imported rock classification map and the final gridded index map. This library acts as a standardized reference that systematically maps colors to lithology values, ensuring consistent and accurate conversion while enabling automated processing workflows.
3Measurement precision
If detailed image treatment is applied to rock classification maps, then lithology representation accuracy improves, but processing complexity increases
Solution Approach 1:
The patent segments the complex image treatment process into distinct automated steps: importing the rock classification map, treating the image to extract color information, matching colors to lithology values using the rock-lithology library, and generating the gridded index map. This segmentation simplifies the overall complexity while maintaining high lithology representation accuracy through systematic processing at each stage.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Non-interpolatable classification of rocks in a region as defined by rock classification maps may be digitized to generate gridded index map. For rock classification maps stored as raster images, image treatment may be applied to generate the gridded index map. The gridded index map may be associated with lithology values using a rock-lithology library, and the lithology values may be used to generate a lithologic representation of the region. Such conversion of rock classification maps for modeling the region may improve input lithologic data accuracy and consistency, while enhancing the efficiency of lithologic modeling (e.g., for basin modeling).