MATLAB-Based Seismic Data Processing with Code Implementation

MATLAB serves as a powerful scientific computing tool widely applied in seismic data processing. It efficiently performs preprocessing, analysis, and visualization of seismic data while also handling well-log data, providing crucial support for petroleum exploration and geological research. Key functions like readtable() or load() enable seamless data importing, and customized scripts can automate format conversions for diverse data types.

Seismic data processing primarily involves steps such as data importing, denoising, filtering, and time-frequency analysis. MATLAB offers extensive signal processing toolboxes (e.g., Signal Processing Toolbox) with functions like medfilt1() for median filtering or fft() for spectral analysis, simplifying implementation. Users can develop small programs to define custom workflows, adapting to specific data characteristics and requirements—for instance, using wavelet transforms (cwt()) for non-stationary signal analysis.

Data visualization is critical in seismic data processing. MATLAB's robust graphical capabilities support 2D and 3D visualizations, clearly displaying seismic waveform trends, spectral features, and more through functions like plot() and spectrogram(). For well-log data, curves or multi-dimensional charts (e.g., using subplot()) can present formation parameters at varying depths, facilitating geological interpretation.

In practical applications, MATLAB scripts can integrate multiple functionalities—data loading, preprocessing, analysis, and visualization—into a complete processing pipeline. This flexibility makes it a powerful tool for seismic and well-log data processing, particularly suitable for researchers and engineers to rapidly validate algorithms and models, such as testing custom noise-reduction filters or machine learning approaches for pattern recognition.