Seismic Horizon Segmentation via Geometrical Probability
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Solution Overview
Problem
Seismic interpretation often results in errors during the manual identification of fault boundaries, leading to inconsistencies in constructing accurate geological models, as existing methods rely heavily on visual inspection and lack efficient automated processes for defining horizon segments and fault cuts.
Innovation Solution
A system and method that perform geometrical calculations using seismic horizon data to define horizon segments, assigning each point a probability of belonging to a segment, which aids in automated segmentation and classification, reducing the need for manual editing and enhancing the accuracy of fault boundary identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual identification of fault boundaries is used, then flexibility and adaptability to complex geological structures is maintained, but errors and inconsistencies increase due to reliance on visual inspection
Solution Approach 1:
The patent replaces manual visual inspection with automated geometrical calculations to identify fault boundaries. The system automatically computes horizon segments and fault cuts using mathematical operations on seismic data, eliminating human error while maintaining the ability to handle complex geological structures through algorithmic processing
Solution Approach 2:
The system performs self-validation by automatically calculating and verifying fault boundary positions through geometrical relationships. The automated process independently identifies and corrects inconsistencies without requiring manual review, allowing the system to service itself in ensuring interpretation accuracy
2Productivity
If automated segmentation methods are implemented, then efficiency and consistency are improved, but complexity of the processing system increases
Solution Approach 1:
The patent divides the seismic horizon into discrete horizon segments based on geometrical calculations. This segmentation allows the complex automated process to work with manageable units, where each segment can be independently processed and classified, reducing the overall system complexity while maintaining high productivity
Solution Approach 2:
The system transforms seismic data into different parameter representations through geometrical calculations, converting raw seismic traces into horizon segments with associated probabilities. This parameter transformation simplifies the automated processing by working with derived geometric parameters rather than raw seismic data
3Measurement precision
If probability-based classification is used, then accuracy of horizon segment assignment is improved, but computational requirements and processing time increase
Solution Approach 1:
The patent performs preliminary geometrical calculations to define horizon segments and their probabilities before final classification. By pre-computing the geometrical relationships and segment probabilities, the system reduces the computational burden during the actual classification process, maintaining high accuracy while minimizing processing time
Data Source
AI summary
One or more computer-readable media including computer-executable instructions to instruct a computing system to perform geometrical calculations using seismic horizon data; and define horizon segments based on the geometrical calculations where each defined horizon segment includes points and where each point has a corresponding probability of that point belonging to a defined horizon segment. Various other apparatuses, systems, methods, etc., are also disclosed.