Seismic Convolution Gathers for Surface-Related Multiple Removal
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Solution Overview
Problem
Conventional seismic processing techniques struggle with efficiently predicting and removing surface-related multiples from seismic data, which can contaminate migrated seismic images and lead to erroneous geological interpretations.
Innovation Solution
A method and system that utilize a convolution gather approach to iteratively determine predicted surface-related multiples by arranging seismic traces into offset gathers, generating a trace index map, and applying a convolution function to identify and remove coherent noise using adaptive multiple subtraction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional seismic processing techniques are used to predict and remove surface-related multiples, then the processing can be performed with standard methods, but the efficiency and accuracy of multiple removal is insufficient leading to noise contamination in migrated seismic images
Solution Approach 1:
The seismic data is segmented into offset gathers sorted by offset domain, and the multiple prediction process is divided into iterative convolution steps. Each convolution gather processes a specific pair of offset gathers, breaking down the complex multiple removal task into manageable segments that can be processed efficiently and then combined.
Solution Approach 2:
The method performs preliminary organization of seismic traces into offset gathers and creates trace index maps before the actual convolution process. The convolution gathers are pre-computed by pairing offset gathers based on predetermined multiple surface locations, preparing the data structure in advance to enable efficient iterative processing and accurate multiple prediction.
2Reliability
If surface-related multiples are not removed from seismic data, then the processing workflow is simpler, but the migrated seismic images contain noise that leads to erroneous geological interpretations
Solution Approach 1:
The method introduces convolution gathers as an intermediary structure that facilitates the multiple removal process. By creating predicted surface-related multiples through convolution of offset gathers and then subtracting these predictions from the original data, the system provides a systematic intermediary step that enhances interpretation reliability without requiring overly complex processing equipment.
Solution Approach 2:
The approach transforms the multiple removal problem by working in the offset domain and using trace index maps to organize data along different dimensional axes. By processing pairs of offset gathers with predetermined multiple surface locations and accumulating convolution gathers, the method adds dimensional organization to the processing workflow that systematically eliminates multiples while maintaining interpretability.
Data Source
AI summary
A method may include obtaining seismic data regarding a geological region of interest. The seismic data may include an offset gather that includes various seismic traces sorted into an offset domain. The method may further include determining a pair of offset gathers based on a predetermined multiple surface location and the offset gather. The method may further include determining a trace index map for the pair of offset gathers. The method may further include generating, iteratively, a convolution gather that includes various convolution traces and based on a convolution function and the trace index map. A respective convolution trace among the convolution traces may be determined using a first trace and a second trace from the pair of offset gathers. The method may further include determining a predicted surface-related multiple using the first convolution gather.