Multi-frequency seismic processing for fault-karst carbon storage site selection
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Solution Overview
Problem
The complexity in the distribution and geometric structures of carbon storage boxes near fault zones makes it difficult to accurately locate and identify spatial geometric structures for effective carbon dioxide storage, which is crucial for carbon capture, utilization, and storage (CCUS) technologies.
Innovation Solution
A method utilizing multi-frequency band seismic data to obtain and process seismic and well logging data, performing seismic wavelet spread spectrum simulation, multi-scale decomposition, and wave impedance inversion to characterize the geometric structure and wave impedance of fault-karst reservoirs, enabling the identification of suitable carbon storage sites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional seismic data processing methods are used, then the processing flow is simple, but the accuracy of fault-karst reservoir bed interpretation is insufficient
Solution Approach 1:
The patent segments the seismic data processing into multiple frequency bands (low, medium, high frequencies) and processes each band separately through specific filtering and enhancement operations. This segmentation allows targeted optimization of different frequency components to improve fault-karst interpretation accuracy while managing processing complexity through systematic division of the processing workflow.
Solution Approach 2:
The patent applies parameter changes by adjusting frequency domain characteristics of seismic data through Fourier transformation, applying different filtering parameters for different frequency bands, and modifying wavelet parameters during deconvolution. These parameter optimizations enable enhanced characterization of fault-karst structures by tailoring processing parameters to specific geological features.
2Measurement precision
If multi-frequency band seismic data processing is applied, then the characterization of underground geological bodies is improved, but the processing time increases
Solution Approach 1:
The patent performs preliminary frequency domain transformation and band separation early in the processing workflow, preparing the data structure for subsequent targeted processing. By pre-organizing the seismic data into frequency bands and applying preliminary filtering, the method reduces the computational burden of later processing steps, thereby optimizing the overall processing time while maintaining high characterization accuracy.
Solution Approach 2:
The patent extracts specific frequency components from the full seismic spectrum and processes them independently. By taking out and separately processing low, medium, and high frequency bands, the method focuses computational resources on the most geologically relevant frequency ranges, improving characterization efficiency and reducing unnecessary processing of less informative frequency components.
3Measurement precision
If complex seismic processing methods are used, then the identification of carbon storage boxes is more accurate, but the ease of operation decreases
Solution Approach 1:
The patent introduces intermediate processing products such as frequency-band separated seismic data, enhanced fault attributes, and karst feature maps that serve as mediators between raw seismic data and final carbon storage box identification. These intermediate results simplify the interpretation process by progressively highlighting relevant features, making the complex processing workflow more manageable and easier to operate while maintaining high identification accuracy.
Data Source
AI summary
The invention belongs to the field of environmental monitoring, and in particular relates to a method for optimally selecting a carbon storage site based on multi-frequency band seismic data. The method comprises the steps of: performing seismic wavelet spread spectrum simulation based on three-dimensional post-stack seismic data to obtain spread spectrum simulated wavelets; building an isochronous stratigraphic framework model of a target horizon, and calculating the geometric structure and spatial distribution of a fault-karst; then performing waveform-indicated inversion to obtain a wave impedance inversion data volume, and obtaining a stable stratum wave impedance data volume through a virtual well cross-well wave impedance interpolation; calculating the difference between the stable stratum wave impedance data volume and the wave impedance inversion data volume to obtain an abnormal wave impedance data volume, then obtaining a fault-karst reservoir bed interpretation model, and determining the position of a carbon storage box.