Post-Stack Seismic Mapping for Near-Surface Feature Detection
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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 for quality control and lacking efficiency in detecting surface and near-surface features.
Innovation Solution
A method utilizing post-stack and post-processed reflected wave seismic cubes to map surface and near-surface features, generating 2D maps without the need for pre-stack gathers, refracted waves, or inversion steps, thereby enhancing processing speed and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional seismic data processing methods are used, then data quality control can be achieved through human intervention, but processing time and complexity increase significantly
Solution Approach 1:
The patent implements automated quality control algorithms that perform seismic data analysis without requiring human intervention. The system uses coherence calculations and statistical methods to automatically identify and flag data quality issues, replacing manual reviewer processes with self-service computational algorithms that maintain reliability while eliminating time-consuming human analysis steps
Solution Approach 2:
The patent transforms the quality control approach by changing from manual parameter assessment to automated computational parameters. It calculates coherence values, statistical metrics, and quality scores through mathematical operations on seismic data, converting subjective human evaluation into objective, rapidly computable parameters that maintain quality control standards while dramatically reducing processing time
2Difficulty of detecting and measuring
If traditional near-surface analysis methods are used, then surface features can be detected, but the process requires pre-stack gathers, refracted waves, and inversion steps that complicate the workflow
Solution Approach 1:
The patent extracts and eliminates unnecessary processing steps from the traditional workflow. It directly analyzes post-stack seismic data to detect surface features without requiring pre-stack gathers or refracted wave analysis. The method isolates the essential detection function from the complex sequence of traditional processing steps, removing redundant operations while maintaining detection capability
Solution Approach 2:
The patent inverts the traditional processing sequence by working backward from the final post-stack data rather than forward from raw acquisitions. Instead of using pre-stack gathers and performing inversion to obtain velocity models, the method directly interprets surface features from the already-processed post-stack seismic cube, reversing the conventional workflow logic to simplify the process
3Productivity
If post-stack seismic data is used for near-surface mapping, then processing speed increases, but traditional methods require additional modeling and inversion steps
Solution Approach 1:
The patent extracts and removes the unnecessary modeling and inversion steps from the processing workflow. It directly maps surface features from post-stack seismic data using coherence-based algorithms, eliminating the intermediate velocity modeling and inversion processes that traditionally preceded feature detection. This extraction maintains productivity gains while removing complexity
Solution Approach 2:
The patent makes the post-stack seismic data serve multiple functions simultaneously. The same post-stack cube used for primary imaging purposes is also directly utilized for near-surface feature detection without requiring separate processing streams. This multi-functionality eliminates redundant modeling steps while maintaining both imaging quality and detection accuracy
Data Source
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AI summary
Methods, apparatus, and systems for mapping surface and near surface features and processing artifacts from stacked and processed seismic data are disclosed. In some implementations, a computer system receives a three-dimensional (3D) seismic cube including seismic reflectivity data obtained at a geographical location. The computer system generates a vertical analysis window of the 3D seismic cube. The computer system extracts a second 3D seismic cube from the seismic reflectivity data based on the vertical analysis window. The second 3D seismic cube has multiple vertical amplitude traces associated with the seismic reflectivity data. The computer system generates 3D data comprising multiple frequency traces from the multiple vertical amplitude traces using a domain transform. The computer system generates a two-dimensional (2D) map from the 3D data. The 2D map represents geographical features of the geographical location.