Seismic Reflection Pattern Matching for Sparse Structural Style Detection
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Solution Overview
Problem
Conventional seismic data processing techniques struggle to accurately determine geological structural styles in frontier exploration scenarios with sparse or low signal-to-noise ratio seismic data, particularly in remote basins for hydrocarbon exploration or CO2-sequestration, where there is limited or no prior knowledge of subsurface geological structure.
Innovation Solution
A data processing system isolates large amplitude signals in seismic reflection measurements and identifies a best fit with structural geology geometric primitives, such as extension, compression, and strike-slip, using scale-invariant features to determine the geological structural style, even with sparse or noisy data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional seismic data processing techniques are used, then the processing method is simple and well-established, but the accuracy of determining geological structural styles deteriorates in sparse or low signal-to-noise ratio data
Solution Approach 1:
The patent replaces conventional mechanical/geological interpretation methods with a computational image processing approach. Seismic reflection measurements are treated as images, and geological structural styles are identified through automated image analysis algorithms that detect geometric patterns, thereby improving accuracy in sparse data conditions where traditional methods fail.
Solution Approach 2:
The patent transforms the problem from direct geological interpretation to parameter-based image analysis. By changing the approach from analyzing geological parameters directly to analyzing image parameters (amplitude, continuity, geometry of seismic reflections), the system achieves more reliable structural style identification in low signal-to-noise ratio conditions.
2Productivity
If sparse seismic data with low signal-to-noise ratio is used, then the data acquisition cost and time are reduced, but the ability to correctly determine geological structure type deteriorates
Solution Approach 1:
The patent extracts and isolates the most relevant geometric features from seismic images using image processing techniques. By extracting key structural characteristics (fault patterns, fold geometries, stratigraphic arrangements) from noisy or sparse data, the system maintains high accuracy in structural style identification without requiring complete or high-quality datasets.
Solution Approach 2:
The patent introduces image processing as an intermediary step between raw seismic data and geological interpretation. This intermediary layer processes and enhances the data, extracting meaningful geometric patterns that bridge the gap between sparse/ noisy measurements and reliable structural style determination.
3Device complexity
If single lines of section are processed without intersecting cross-sections, then the data processing complexity is reduced, but the system fails to correctly determine geological structure type
Solution Approach 1:
The patent creates a universal image processing approach that can determine geological structural styles from single seismic lines with the same accuracy as multi-line or 3D datasets. The method is designed to be scale-independent and applicable to various data configurations (single line, multiple lines, 2D, or 3D), making the system universally effective without requiring complex multi-line processing.
Data Source
AI summary
Methods and systems for determining a geological structural style of a subterranean formation include acquiring seismic reflection measurements of the subterranean formation; isolating one or more signals in the acquired measurements, the one or more signals having larger amplitudes relative to one or more other signals in the acquired measurements; obtaining a set of structural geology geometric primitives wherein each structural geology geometric primitive comprises geometric data representing a known structural geological style; identifying at least one best fit between a set of the one or more isolated signals and a structural geology geometric primitive from the set of structural geology geometric primitives; determining a degree of confidence for at least one best fit identified; and determining a geological structural style of the subterranean formation based on the identified at least one best fit and based on the determined degree of confidence for that best fit.