Seismic Velocity Model Building for Subsalt Imaging
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Solution Overview
Problem
Current seismic exploration methods, particularly those using ray-based systems, struggle to provide reliable Common Image Gathers for high velocity contrast geo-bodies like subsalt or salt overhung deep mini basins, as reverse time migration angle gathers do not converge with residual moveout curvatures, especially at large angles, limiting accurate identification of these complex geological structures.
Innovation Solution
A computer-implemented method and system that generates velocity models, stack images, and angle gathers using seismic reflection data, enabling perfect convergence of reverse time migration angle gathers with residual moveout curvatures across the full angle range, including large angles, by employing a novel algorithm that decomposes tomographic models into azimuthal sectors and uses curvature analysis and semblance picking, combined with distributed incremental least-squares algorithms and Gaussian smoothing for real-time tomography inversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reverse time migration angle gathers are used for imaging, then imaging capability in complex structures is improved, but convergence with residual moveout curvatures fails at large angles
Solution Approach 1:
The patent transforms the angle gathers from offset-domain to true-angle-domain by changing the parameter space. This transformation allows the residual moveout curvatures to converge properly with the migration angle gathers across the full angle range, resolving the convergence failure that occurred at large angles in the offset-domain approach.
2Productivity
If conventional ray-based methods are used, then computational efficiency is maintained, but identification accuracy of high velocity contrast geo-bodies deteriorates
Solution Approach 1:
The patent replaces conventional ray-based mechanical methods with wave-equation-based Reverse Time Migration (RTM). This substitution enables accurate imaging of high velocity contrast geo-bodies by properly handling wave propagation physics, including diffraction and reflection, which ray-based methods cannot adequately capture.
3Measurement precision
If tomography inversion is performed to improve velocity model accuracy, then identification precision is improved, but computational resource requirements increase
Solution Approach 1:
The patent segments the tomography inversion process into distributed incremental least-squares steps. By dividing the inversion into smaller incremental updates and distributing computations, the method achieves accurate velocity model building while reducing the computational burden on any single processing unit and enabling parallel processing.
4Adaptability or versatility
If manual interpretation methods are used, then flexibility in analysis is maintained, but subjectivity and time consumption increase
Solution Approach 1:
The patent implements automated curvature analysis and semblance picking that perform velocity analysis and geo-body identification without manual intervention. The system automatically extracts curvature information from angle gathers, performs semblance calculations, and identifies high velocity contrast geo-bodies, eliminating subjective manual interpretation while maintaining analytical flexibility.
Data Source
AI summary
A computer-implemented method and computing system apparatus programmed to perform operations of the computer-implemented method for obtaining a subsurface stack image, subsurface angle gathers, and a subsurface velocity model over an entire survey region having high velocity contrast geo-bodies. Particularly, user inputs, input velocity models, and surface-seismic data are obtained by fixed source and receiver pairs and then used by the computer program product embedded within the computing system apparatus to minimize the number of iterations, required to obtain a final velocity model, a final stack image, and final angle gathers wherein their flatness deviation is equal to, or less than, a user-defined flatness value. Therefore, the attributes developed by said computer-implemented method and system can help solve the imaging problem of sub high velocity contrast geo-bodies like subsalt, or salt overhung deep mini basins.