Seismic Displacement Field Calculation via Feature Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for processing time-lapse seismic data struggle to effectively discriminate between amplitude changes and time shifts, which is crucial for monitoring changes in subsurface reservoirs, particularly in hydrocarbon reservoirs, to optimize hydrocarbon production and minimize costs.
Innovation Solution
A method involving the selection of seismic traces from baseline and monitor surveys, extraction of features such as local curve maxima and minima, matching these features using algorithms like the Needleman-Wunsch algorithm, and calculating a displacement field to align and compare the data sets, thereby enhancing the difference image and understanding of subsurface changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional seismic data processing methods are used to compare time-lapse surveys, then the processing is computationally simpler and faster, but the ability to discriminate between amplitude changes and time shifts is insufficient
Solution Approach 1:
The patent segments the seismic trace comparison process into distinct feature extraction steps (amplitude, frequency, phase features) that can be independently analyzed and matched, allowing precise discrimination between amplitude changes and time shifts while managing computational complexity through modular processing
Solution Approach 2:
The patent introduces a new dimension of analysis by extracting and comparing multiple feature types (amplitude, frequency, phase) simultaneously rather than relying on single-trace amplitude comparison, enabling differentiation between amplitude variations and temporal shifts through multi-dimensional feature space analysis
2Measurement precision
If feature extraction and matching algorithms are applied to seismic traces, then the discrimination between amplitude and time shifts is improved, but the computational time and processing complexity increase
Solution Approach 1:
The patent extracts specific diagnostic features (amplitude, frequency, phase characteristics) from the full seismic traces, analyzing only the essential components needed for discrimination rather than processing the entire trace data, thereby reducing computational time while maintaining precision
Solution Approach 2:
The patent applies feature matching to a selected subset of key trace features rather than exhaustive comparison of all trace parameters, achieving sufficient discrimination precision with reduced computational effort by focusing on the most diagnostic features
Data Source
AI summary
Implementations of various technologies for a method for processing seismic data. In one implementation, the method includes (a) selecting a first trace from a first seismic data set and a second trace from a second seismic data set; (b) extracting one or more features of the same types from the first trace and the second trace; (c) matching the extracted features from the first trace with the extracted features from the second trace; and (d) calculating for a displacement field using one or more of the matching features of the first trace and the second trace.