3D Seismic Fault Visualization via Double Radon Transform
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Solution Overview
Problem
Current software tools are unreliable in detecting and visualizing complex geological features like faults in 3D seismic survey data, often misrepresenting them due to sensitivity to strata patterns and incomplete characterization.
Innovation Solution
A method involving a double Radon Transform about two different axes of a seismic attribute volume, combined with exponentiation of characteristic parameters, to enhance the visibility of faults while suppressing unwanted features by integrating data within planes of interest and orienting enhancements based on angular orientation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current software tools are used to detect and visualize faults in 3D seismic survey data, then the detection process is simple and fast, but the reliability and accuracy of fault detection deteriorates due to sensitivity to strata patterns and incomplete characterization
Solution Approach 1:
The patent segments the fault detection process into multiple independent processing stages: initial fault attribute calculation, Radon transform processing, exponentiation enhancement, and inverse Radon transform. Each stage processes specific aspects of the data independently, improving reliability without requiring complete redesign of the entire system.
Solution Approach 2:
The patent applies Radon transform to convert the 3D seismic attribute volume into a different dimensional representation (Radon domain), where faults are enhanced through exponentiation of characteristic parameters. This dimensional transformation allows selective enhancement of fault features while suppressing strata patterns, resolving the contradiction between detection reliability and processing complexity.
2Loss of information
If multiple seismic attributes are combined to characterize faults, then the completeness of fault characterization improves, but the complexity of data processing and visualization increases
Solution Approach 1:
The patent merges multiple seismic attributes (coherence, dip/azimuth, structural orientation, semblance, volumetric curvature) into a unified processing framework using Radon transform. By combining these attributes in the Radon domain and applying exponentiation, the method achieves complete fault characterization while managing processing complexity through systematic integration rather than separate handling of each attribute.
Solution Approach 2:
The patent changes the parameter representation by applying exponentiation to characteristic parameters in the Radon domain. This parameter transformation enhances the contrast between fault features and background noise, allowing complete characterization of multiple attributes simultaneously while maintaining manageable processing complexity through a unified mathematical operation.
3Measurement precision
If traditional attribute algorithms are used to highlight faults, then the processing method is simple and fast, but the visualization accuracy deteriorates because only certain fault characteristics are captured
Solution Approach 1:
The patent performs preliminary Radon transform processing on the seismic attribute volume before applying exponentiation enhancement. This preliminary transformation prepares the data by converting it to a domain where fault features are more distinct, enabling subsequent enhancement operations to achieve higher visualization accuracy without significantly impacting processing efficiency.
Solution Approach 2:
The patent replaces traditional mechanical filtering methods with Radon transform-based processing. This substitution uses mathematical transformation and exponentiation operations instead of conventional filtering, achieving superior fault visualization accuracy while maintaining processing efficiency through computationally efficient transform algorithms.
Data Source
AI summary
A method of visually enhancing at least one geologic feature in 3D seismic survey data, comprising the steps of: (a) generating at least one attribute volume definable in Cartesian space and comprising at least one attribute derivable from said 3D seismic survey data; (b) generating a first Radon data volume from data resulting from a transaxial Radon Transform of said at least one attribute volume with respect to a first Cartesian axis; (c) generating a second Radon data volume from data resulting from a transaxial Radon Transform of said first Radon data volume with respect to a second Cartesian axis; (d) generating a third Radon data volume from data resulting from exponentiating a characteristic parameter of each one of a plurality of voxels forming said second Radon data volume to a predetermined first power value, and (e) applying a first Inverse Radon Transform to said third Radon data volume with respect to said second Cartesian axis, and a subsequent second Inverse Radon Transform to the resulting data from said first Inverse Radon Transform with respect to said first Cartesian axis.