Seismic Velocity Model Estimation with Q Anomaly Correction
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Solution Overview
Problem
Conventional seismic data analysis and imaging techniques face challenges in accurately accounting for localized attenuation (Q) anomalies, leading to labor-intensive and error-prone identification of attenuating zones, and resulting in inaccurate velocity models that are too slow for imaging.
Innovation Solution
The proposed method involves iteratively updating physical property models using Full Wavefield Inversion (FWI) up to a first frequency threshold, extracting geobodies, obtaining a Q model, and incorporating it into the inversion process to refine the velocity model, with frequency continuation and full-band migration to achieve accurate imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional seismic data analysis techniques are used to identify attenuating zones, then the process is labor-intensive and error-prone, but the identification accuracy is poor
Solution Approach 1:
The patent replaces manual, labor-intensive identification of attenuating zones with an automated computerized system that uses seismic data processing and Q-factor analysis. The system automatically identifies geobodies with anomalous Q values, eliminating human error and reducing the complexity of the identification process while improving accuracy.
Solution Approach 2:
The system enables self-service by allowing the seismic data to speak for itself through automated analysis. The computerized system automatically processes the seismic data, calculates Q factors, identifies attenuating zones, and updates velocity models without requiring manual intervention, making the process both simpler and more accurate.
2Manufacturing precision
If velocity models are updated without accounting for Q anomalies, then the modeling process is simpler, but the velocity models are too slow for accurate imaging
Solution Approach 1:
The patent applies preliminary action by first identifying and characterizing Q anomalies before updating the velocity model. The system calculates Q factors, identifies attenuating geobodies, and incorporates this information into the velocity model update process. This preliminary characterization ensures that the velocity model accurately reflects the true subsurface velocity, preventing the model from being too slow for imaging.
Solution Approach 2:
The system applies local quality by updating the velocity model differently in different regions based on local Q characteristics. In areas with Q anomalies, the model incorporates attenuation effects, while in areas without anomalies, the standard modeling approach is used. This localized approach ensures accurate velocity models without unnecessarily complicating the entire model.
3Measurement precision
If Q anomalies are incorporated into the inversion process, then the velocity model accuracy is improved, but the processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the inversion process into distinct stages: first identifying Q anomalies and geobodies, then updating the velocity model with Q information, and finally performing imaging. This segmentation breaks down the complex inversion process into manageable steps, improving accuracy while controlling complexity through systematic processing.
Solution Approach 2:
The system uses Q-factor analysis as an intermediary between raw seismic data and velocity model updating. The Q-factor calculation serves as a mediator that characterizes attenuation properties, which then inform the velocity model update process. This intermediary step simplifies the overall complexity by providing a clear bridge between data and model.
Data Source
AI summary
Iterative methods for inversion of seismic data to update a physical property model are disclosed. Such methods may comprise iteratively updating the model until a first predetermined resolution is achieved, using full wavefield inversion of the seismic data up to a first frequency threshold and assuming the seismic data is free of attenuation effects; extracting geobodies from the updated model; obtaining a Q model using the geobodies; and updating the physical property model using an inversion process, wherein the Q model is incorporated into the inversion process. These steps may be repeated until a second predetermined resolution of the physical property model is achieved, wherein the first frequency threshold is progressively increased in each repetition. The Q model may be updated with seismic data at all available frequencies to obtain a full-band Q model; and the physical property model may be updated using full-band migration and the full-band Q model.