Deconvolution MATLAB Data Processing Package for Seismic Data

This deconvolution MATLAB data processing package is highly valuable for seismologists. It implements multiple deconvolution methods including predictive deconvolution, spike deconvolution, and sparse deconvolution, each serving crucial roles in seismic data processing. The predictive deconvolution algorithm utilizes Wiener filtering techniques to predict seismic-related physical parameters by removing predictable components from seismic traces. Spike deconvolution employs inverse filtering methods to detect sharp impulses within seismic signals, effectively enhancing temporal resolution. Sparse deconvolution leverages L1-norm optimization algorithms to handle large-scale seismic datasets efficiently, significantly reducing computational time and storage requirements through sparse representation techniques. Additionally, the package includes various visualization tools implemented through MATLAB's graphics functions, enabling seismologists to better interpret and analyze seismic data through waveform displays, spectrum analysis plots, and deconvolution result comparisons. The code architecture features modular design with separate functions for each deconvolution type, allowing easy customization and integration with existing seismic processing workflows. In summary, this deconvolution MATLAB data processing package is an essential tool for seismologists, providing indispensable capabilities for seismic data processing and analysis with robust algorithmic implementations and user-friendly visualization interfaces.