Seismic Survey Merging via Edge-Based Reflector Continuity
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Solution Overview
Problem
Conventional methods for combining already-processed seismic datasets result in discontinuous, nonsmoothed merged datasets, requiring reprocessing and significant time and resources, especially when dealing with overlapping geographic regions and complex fault patterns.
Innovation Solution
The method involves calculating edges between survey datasets to generate modified datasets with seamless, continuous reflectors across boundaries, allowing for direct merging of already-processed data into a unified, processed dataset using techniques like dynamic time warping and graph optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If already-processed seismic datasets are directly combined, then processing time is reduced, but the merged dataset becomes discontinuous and nonsmoothed
Solution Approach 1:
The patent applies preliminary action by performing edge calculations and reflector matching between datasets before the actual merging process. This preparatory step establishes continuous reflector relationships across dataset boundaries, ensuring smooth transitions in the final merged dataset without requiring time-consuming post-processing adjustments
2Manufacturing precision
If datasets are reprocessed to achieve smooth merging, then data quality is improved, but computational expense and time increase significantly
Solution Approach 1:
The patent extracts and processes only the critical boundary regions (edges) where datasets overlap, rather than reprocessing entire datasets. By focusing computational resources on calculating edges and matching reflectors at boundaries, the method achieves smooth merging while avoiding the prohibitive computational cost of full dataset reprocessing
3Loss of energy
If conventional merging methods are used, then resource consumption is reduced, but the merged dataset requires reprocessing
Solution Approach 1:
The patent implements self-service by making the merging process inherently produce usable, smooth output data through built-in edge calculation and reflector matching mechanisms. The method embeds quality assurance directly into the merging workflow, eliminating the need for subsequent reprocessing steps and ensuring the merged dataset is immediately analyzable
Data Source
AI summary
A method for generating a merged survey dataset, that includes obtaining a plurality of survey datasets, calculating edges between survey datasets of the plurality of survey datasets, modifying the plurality of survey datasets, based on the edges, to obtain a plurality of modified survey datasets, and generating the merged survey dataset using the plurality of modified survey datasets.