Midpoint-Offset Domain Full Waveform Inversion for Seismic Data
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Solution Overview
Problem
Conventional seismic data processing methods are inadequate for handling the increased data volumes from modern seismic acquisition systems, particularly in near-surface analysis, requiring time-consuming human intervention and struggling with quality control and accurate subsurface imaging.
Innovation Solution
The implementation of full waveform inversion (FWI) methods in the midpoint-offset domain, using a computer system to sort seismic traces into common midpoint-offset bins, apply linear moveout corrections, determine surface-consistent residual static corrections, and perform one-dimensional FWI to generate robust and accurate velocity models of the subsurface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional seismic data processing methods are used, then human intervention is required for quality control, but this increases processing time and reduces productivity
Solution Approach 1:
The system performs automatic quality control through computational algorithms that independently analyze and process seismic data without requiring human intervention. The method automatically sorts traces into bins, applies corrections, and generates velocity models, making the system self-sufficient in quality control tasks.
Solution Approach 2:
Manual human intervention in quality control is replaced by computational algorithms and automated processing systems. The mechanical/manual operations of analysts are substituted with electronic data processing, mathematical transformations, and computer-based waveform inversion techniques.
2Quantity of substance
If the number of seismic acquisition channels is increased, then more data is available, but conventional methods struggle to handle the increased data volumes
Solution Approach 1:
The large volume of seismic data is divided into smaller manageable units by sorting traces into common midpoint-offset bins (XYO bins). This segmentation allows the processing system to handle data in organized groups rather than as a single large dataset, reducing processing complexity while maintaining full utilization of available data.
Solution Approach 2:
The method transforms the processing approach by organizing data into a three-dimensional midpoint-offset domain (XYO space), adding structural organization to the data handling process. This dimensional organization enables more efficient processing of large datasets compared to conventional two-dimensional approaches.
3Adaptability or versatility
If traditional interactive analysis methods are used, then analyst input is required, but this reduces automation and increases time consumption
Solution Approach 1:
The system performs automatic near-surface analysis through computational algorithms that independently execute the full workflow from data sorting to velocity model generation without requiring analyst intervention at each step, achieving high automation while maintaining analytical capability.
Solution Approach 2:
The method automatically adjusts processing parameters such as bin sizes, correction amounts, and inversion settings through computational optimization, replacing manual parameter selection by analysts with automated parameter tuning based on the data characteristics.
4Productivity
If full waveform inversion is performed in the midpoint-offset domain, then computation time is reduced, but specialized processing steps are required
Solution Approach 1:
The method performs preliminary sorting of seismic traces into common midpoint-offset bins and applies linear moveout corrections before conducting waveform inversion. These preparatory steps organize the data in advance, enabling more efficient inversion processing and reducing the overall computation time despite adding initial processing steps.
Solution Approach 2:
The method combines multiple processing operations (sorting, moveout correction, stacking, static correction, and waveform inversion) into an integrated workflow that processes data through all stages in a unified manner, improving computational efficiency compared to separate discrete processing steps.
Data Source
AI summary
Methods for full waveform inversion (FWI) in the midpoint-offset domain include using a computer system to sort seismic traces into common midpoint-offset bins (XYO bins). For each XYO bin, a linear moveout correction is applied to a collection of seismic traces within the XYO bin. The collection of seismic traces is stacked to form a pilot trace. The computer system determines a surface-consistent residual static correction for each seismic trace. The computer system determines that the surface-consistent residual static correction for each seismic trace is less than a threshold. Responsive to the determining that the surface-consistent residual static correction is less than the threshold, the computer system stacks the collection of seismic traces to provide the pilot trace. The computer system groups the pilot traces for the XYO bins into a set of virtual shot gathers. The computer system performs one-dimensional FWI based on each virtual shot gather.