Shallow Velocity Imaging Using SVIR and Travel-Time Inversion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional subsurface imaging techniques face challenges in complex shallow geology due to weak signals from near-surface noise, leading to low resolution and noise interference, especially at far-offset receivers, making it difficult to detect small-scale features and accurately pick first-arrival travel-times.
Innovation Solution
Applying super-virtual interferometric redatuming (SVIR) to enhance refracted signals and attenuate noise, followed by wave-equation travel-time inversion (WTI) to reconstruct high-resolution velocity models, improving signal-to-noise ratio and accuracy of first-break picks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional refraction tomography is used for subsurface imaging, then the method can handle near-surface issues, but the resolution and accuracy of first-break travel-time tomographic inversion are low, causing small-scale features to be undetected
Solution Approach 1:
The patent introduces an intermediate processing step (wavefield transformation/redatuming) between data acquisition and final imaging. This intermediary process transforms the raw seismic data into a different domain where small-scale features become more prominent and easier to detect, then uses this transformed data for high-resolution tomographic inversion.
Solution Approach 2:
The patent applies wavefield transformation that changes the parameter domain of the seismic data. By transforming from the time-space domain to a redatumed domain, the method enhances the visibility of small-scale features and improves the precision of travel-time measurements for tomographic inversion.
2Reliability
If conventional imaging methods are used, then the processing is straightforward, but noise interference with seismic signals is severe, especially at far offset where signal-to-noise ratio drops
Solution Approach 1:
The patent uses wavefield transformation as an intermediary process that acts as a filter between the noisy raw data and the final imaging. This intermediate step separates signal from noise by transforming the data into a domain where noise components are suppressed while preserving the useful seismic signals, particularly at far offsets.
Solution Approach 2:
The method extracts the useful seismic signals from the noisy data through wavefield transformation. By separating the signal components from the noise components in the transformed domain, the patent effectively removes noise interference while retaining the meaningful geological information.
3Measurement precision
If conventional methods are used, then first-break picks can be obtained, but it becomes difficult to pick first-arrival travel-times at far-offset receivers where the signal-to-noise ratio drops
Solution Approach 1:
The patent introduces wavefield transformation as an intermediary step that prepares the data for more accurate first-break picking. This intermediate processing enhances the signal characteristics at far offsets, making the first arrivals more distinct and easier to identify, thereby improving the accuracy of travel-time measurements.
Solution Approach 2:
The patent performs preliminary wavefield transformation before the actual first-break picking process. This preliminary action enhances the signal-to-noise ratio and clarifies the first-arrival events in advance, making the subsequent picking operation more accurate and reliable, especially for far-offset receivers.
Data Source
AI summary
A computer-implemented method and system for optimizing shallow subsurface imaging includes applying super-virtual interferometric redatuming (SVIR) to seismic wave data, and applying wave-equation travel-time inversion (WTI) to the redatumed seismic wave data.