FWI-Guided Seismic Arrival-Time Picking
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Solution Overview
Problem
Existing methods for picking the arrival-time of the first seismic event in seismic data sets, especially those with low signal-to-noise ratios, often fail to provide accurate results due to noise interference and varying seismic wave velocities with depth and horizontal position.
Innovation Solution
A method combining the Modified Energy Ratio (MER) technique with full waveform inversion (FWI) to determine an updated seismic velocity model, simulating arrival-times, and defining a predicted time-window for accurate picking of arrival-times, using a computer system to iteratively update and refine the seismic velocity model and simulate seismic wave propagation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional arrival-time picking methods are used in seismic data sets with low signal-to-noise ratios, then the processing is simpler and faster, but the accuracy of arrival-time picking deteriorates due to noise interference
Solution Approach 1:
The method performs preliminary full waveform inversion to generate an updated velocity model and simulates expected arrival times before conducting the actual arrival-time picking. This preliminary action creates a predicted time-window that guides the subsequent picking process, enabling accurate identification of first arrivals even in low signal-to-noise ratio conditions by establishing expected temporal boundaries before examining the noisy data.
Solution Approach 2:
The patent introduces an intermediary predicted time-window derived from full waveform inversion simulations as a mediator between the velocity model and the actual arrival-time picking. This intermediary structure filters noise interference by providing a temporal framework within which to search for arrivals, effectively separating signal identification from noise without requiring complex denoising procedures.
2Measurement precision
If full waveform inversion is performed to update the seismic velocity model, then the accuracy of arrival-time prediction is improved, but the computational complexity and processing time increase
Solution Approach 1:
The method segments the seismic processing into distinct stages: first performing full waveform inversion to obtain an updated velocity model, then using that model to simulate arrival times and define predicted time-windows, and finally conducting arrival-time picking within those windows. This segmentation allows the computationally intensive FWI to be performed once on the full data set, while subsequent picking operations are simplified and accelerated by the pre-computed time-windows.
Solution Approach 2:
The full waveform inversion is performed as a preliminary step to establish the velocity model and predicted arrival times before the actual picking process. This preliminary computation, while intensive, needs to be done only once per seismic line or survey, after which the derived time-windows can be applied efficiently to numerous traces without repeating the full inversion computation.
3Ease of operation
If a fixed time-window is used for picking first arrivals, then the picking process is simpler, but the accuracy deteriorates when seismic wave velocities vary with depth and horizontal position
Solution Approach 1:
The patent replaces fixed, static time-windows with dynamic predicted time-windows that are computed based on the updated velocity model from full waveform inversion. These dynamic windows adapt to local velocity variations by simulating expected arrival times for each trace based on its specific geometry and position, allowing the picking process to automatically adjust to velocity changes without manual intervention or complex adaptive algorithms.
Solution Approach 2:
The method changes the time-window parameter from a fixed constant to a dynamically computed value based on the velocity model and trace geometry. By calculating predicted arrival times using the updated velocity model and using these as the basis for defining time-windows, the system adapts the picking parameters to match the actual subsurface velocity structure, maintaining accuracy across varying geological conditions.
Data Source
AI summary
A method of determining an arrival-time of a first seismic event in a seismic data set including, obtaining the seismic data set and an initial seismic velocity model, and determining an updated seismic velocity model based on the seismic data set. Furthermore, the method includes determining a simulated arrival-time of the first seismic event based on the updated seismic velocity model and defining a predicted time-window based on the simulated arrival-time of the first seismic event, and picking the arrival-time of the first seismic event in the seismic data set based on the predicted time-window.