MATLAB Implementation for Seismic Data Processing

In seismic exploration, data processing constitutes a critical step. The wiggle transform serves as a widely employed method in time-frequency analysis, typically implemented in MATLAB using visualization functions like wigb() or custom scripts that plot seismic traces with amplitude variations along the time axis. However, alternative transformation methods exist including Fourier transform (implementable via fft() for frequency domain analysis) and wavelet transform (achievable through Wavelet Toolbox functions like cwt()). Each method presents distinct advantages: Fourier transform excels in stationary signal analysis while wavelet transform provides multi-resolution capabilities for non-stationary signals. During seismic data processing, essential preprocessing steps involve noise removal using filtering techniques (filter() or medfilt1()) and data normalization. Additionally, quality control procedures including spike detection (findpeaks()) and amplitude correction (detrend()) are necessary to ensure data accuracy and reliability throughout the processing workflow.