Velocity Model Refinement via Ray Tomography and Waveform Inversion
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Solution Overview
Problem
Current methods for determining accurate velocity models in seismic exploration, especially for areas other than near surface, face challenges in complexity and resolution when using conventional techniques, leading to unreliable subsurface imaging.
Innovation Solution
A method employing ray-based tomography guided by waveform inversion, which iteratively adjusts velocity models using high-resolution velocity perturbations from depth migration or full waveform inversion, to create enhanced velocity models for geographical areas of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional velocity model building methods are used, then the process is simpler, but the resolution and structural conformity of the velocity model deteriorate
Solution Approach 1:
The velocity model building process is divided into multiple iterative steps: initial velocity model construction, depth migration, waveform inversion to obtain velocity perturbations, and updating the velocity model. Each step refines the model progressively, achieving high resolution through sequential processing rather than a single complex operation.
Solution Approach 2:
Depth migration is performed first to obtain an initial velocity model and migrated data before conducting waveform inversion. This preliminary action provides the foundation for subsequent high-resolution velocity perturbation analysis, enabling the final velocity model to achieve both high resolution and structural conformity.
2Reliability
If conventional velocity model building methods are used, then the computational process is faster, but the reliability of subsurface imaging deteriorates
Solution Approach 1:
The method employs iterative feedback where the velocity model is continuously refined: initial model → depth migration → waveform inversion → velocity perturbation → model update → repeat. Each iteration uses the results of the previous step to improve the model, ensuring high reliability through progressive optimization rather than single-pass processing.
Solution Approach 2:
Depth migration is performed as a preliminary step to establish an initial velocity model and migrated common image point gathers before the main waveform inversion process. This preliminary action reduces the complexity of the subsequent inversion by providing a better starting point, thereby improving reliability while managing computational time.
3Manufacturing precision
If conventional velocity model building methods are used, then the process is more straightforward, but the structural conformity of the velocity model deteriorates
Solution Approach 1:
The method merges depth migration and waveform inversion techniques into a unified velocity model building workflow. By combining the structural information from depth migration with the high-resolution velocity perturbations from waveform inversion, the final velocity model achieves superior structural conformity that neither method could achieve alone.
Solution Approach 2:
The method transforms the velocity model through multiple parameter changes: initial velocity parameters from depth migration are refined by incorporating velocity perturbation parameters from waveform inversion. This systematic parameter refinement ensures that the final velocity model accurately reflects subsurface structural features.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides improved resolution and structural conformity in velocity models, enhancing the accuracy of seismic imaging and reducing the risk of costly drilling missteps by providing more reliable subsurface data.
Implementation Method 1
seismic waves generated artificially have been used for more than 50 years to perform imaging of geological layers
Implementation Method 2
seismic signal that propagates in the form of a wave that is reflected at interfaces of geological layers
Implementation Method 3
geophones, or more generally receivers, which convert the displacement of the ground resulting from the propagation of the waves into an electrical signal
Implementation Method 4
Analysis of the arrival times and amplitudes of these waves make it possible to construct a representation of the geological layers
Data Source
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AI summary
Disclosed herein is a system and method for building a velocity model for a geographical area of interest (GAI). The system and method comprise determining a ray based tomography velocity image of said GAI using acquired data, determining a high resolution velocity guide (HRVG) image of said GAI, scaling said determined HRVG of said GAI, adding the scaled HRVG to the ray based tomography velocity image to determine an updated ray based tomography velocity image, and determining whether said updated ray based tomography velocity image has experienced convergence by determining whether a cost function of said ray based tomography velocity image does not improve compared to a previously determined cost function value of said ray based tomography velocity image.