Simultaneous Common-Offset Seismic Migration
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Solution Overview
Problem
Current seismic data processing methods are inefficient and computationally costly, particularly in generating seismic images for subsurface hydrocarbon reservoirs, as they often require expensive trace-by-trace migrations that do not provide image gathers for velocity analysis and noise attenuation.
Innovation Solution
The method involves simultaneous common-offset migration of seismic datasets, where entire common-offset sections are migrated and combined to produce stochastic image gathers, enabling efficient seismic imaging and velocity analysis, similar to more expensive trace-by-trace migrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If trace-by-trace migration is used to generate seismic images, then imaging precision is improved, but computational cost and processing time increase significantly
Solution Approach 1:
The seismic dataset is divided into multiple common-offset sections, each representing a specific offset range. These sections are processed independently through stochastic migration and then combined, allowing parallel computation while maintaining imaging precision. This segmentation enables the large-scale migration problem to be broken into manageable chunks that can be processed efficiently.
Solution Approach 2:
The patent uses stochastic migration to generate multiple realizations (copies) of the seismic image from the same input data. By generating numerous stochastic realizations and combining them, the method achieves deterministic-like precision without requiring expensive trace-by-trace deterministic migration for each realization, significantly reducing computational cost.
2Measurement precision
If trace-by-trace migration is used, then imaging precision is improved, but computational resources and cost increase
Solution Approach 1:
The dataset is segmented into common-offset sections that can be processed independently. This allows the computational workload to be distributed across multiple processors or computing nodes, reducing the computational burden on any single system while maintaining overall imaging precision through the combination of segmented results.
Solution Approach 2:
The patent employs stochastic migration with random realizations that are computationally inexpensive compared to deterministic trace-by-trace migration. Each stochastic realization is a 'cheap' computation that can be discarded after contributing to the final combined image, allowing many realizations to be generated within the same computational budget as a single deterministic migration.
3Productivity
If common-offset section migration is used, then processing efficiency is improved, but image quality and precision may deteriorate
Solution Approach 1:
Multiple common-offset sections are migrated separately and then merged through stacking and combination operations. This merging process integrates the results from different offset ranges, preserving the processing efficiency benefits of common-offset migration while recovering the image quality and precision that would be lost if individual sections were processed in isolation.
Solution Approach 2:
Stochastic migration generates multiple copies (realizations) of the migrated common-offset sections. By generating and combining numerous stochastic realizations, the method ensures that the final integrated image achieves precision comparable to trace-by-trace migration, compensating for the potential quality loss from processing smaller common-offset sections.
4Use of energy by moving object
If stochastic migration is used instead of deterministic migration, then computational cost is reduced, but traditional velocity analysis and noise attenuation capabilities are lost
Solution Approach 1:
The stochastic common-offset migration framework is designed to be multi-functional, serving both imaging and velocity analysis purposes. The migrated common-offset sections retain the offset information necessary for velocity analysis and noise attenuation, making the system universal enough to perform multiple seismic processing functions that were traditionally only available through deterministic trace-by-trace migration.
Data Source
AI summary
A system and method for forming a seismic image of a subterranean region of interest are provided. The method includes obtaining an observed seismic dataset for the subterranean region of interest and determining a plurality of common-offset sections from the observed seismic dataset. The method further includes determining stochastically migrated common-offset sections for each of the common-offset sections and forming a stochastic image gathers from the plurality of stochastically migrated common-offset sections. The method still further includes forming the seismic image by stacking each of the plurality of stochastically migrated common-offset sections.