Seismic Attribute Gather Generation with Synthetic Data
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Solution Overview
Problem
Current seismic attribute generation methods, such as the expectation method, are inefficient and prone to bias when estimating attributes like surface-offset distance, especially in complex geological environments with multiple reflections or irregular surface geometries, leading to inaccurate subsurface imaging and hydrocarbon reservoir identification.
Innovation Solution
A method involving computing seismic images with a field dataset, generating synthetic data using a reflectivity model, and applying an expectation method to estimate seismic attribute gathers, which includes dividing the dataset into bins, performing migration using techniques like Kirchhoff or reverse time migration, and stacking the results to improve velocity modeling and hydrocarbon extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wave-based imaging algorithms (RTM, WEM) are used to image complex geology, then imaging accuracy is improved, but computational cost and time increase significantly
Solution Approach 1:
The patent pre-calculates and stores travel time and amplitude information in look-up tables before the main imaging process. This preliminary action allows the migration algorithm to retrieve pre-computed values instead of calculating them in real-time, significantly reducing computational time while maintaining imaging accuracy for complex geological structures
Solution Approach 2:
The patent divides the computational domain into discrete spatial bins and processes travel time and amplitude calculations separately for each bin. This segmentation allows parallel processing and optimization of different spatial regions, reducing overall computational time while preserving imaging quality
2Measurement precision
If surface-offset gathers are formed using wave-based migration, then accurate attribute estimation is achieved, but attributes become mixed and lost during shot record migration
Solution Approach 1:
The patent introduces an intermediate step where travel time and amplitude are calculated as separate auxiliary fields before being combined in the imaging process. This intermediary approach allows surface-offset attributes to be preserved and estimated accurately without being mixed during migration, as each attribute can be recovered from its corresponding intermediate field
Solution Approach 2:
The patent transforms the migration process to work in the travel time domain rather than directly in the offset domain. By changing the parameter space and using travel time as the primary variable, the method enables accurate recovery of surface-offset attributes after migration through the use of pre-computed look-up tables
3Measurement precision
If brute force method is used to generate wave-equation based surface offset gathers, then accuracy is maximized, but computational cost becomes prohibitively expensive
Solution Approach 1:
The patent creates simplified copy models of the seismic data with regularized acquisition geometry that preserve the essential wave propagation characteristics. These synthetic copies are used to generate look-up tables for travel time and amplitude, providing accurate attribute estimation at a fraction of the computational cost of processing the full brute force dataset
Solution Approach 2:
The patent uses computationally inexpensive synthetic data with idealized geometry as a disposable intermediate product to build look-up tables. These synthetic models are discarded after table generation, but they enable accurate attribute estimation for the actual data without requiring expensive brute force processing of the original complex dataset
Data Source
AI summary
A method for generating seismic attribute gathers, the method including: computing, with a computer, seismic images with a field dataset; generating, with a computer, synthetic data corresponding to the seismic images; computing, with a computer, an attribute volume by applying an expectation method to the synthetic data; mapping, with a computer, the attribute volume to the seismic images; and generating, with a computer, seismic attribute gathers by stacking the seismic images mapped to the attribute volume.