Seismic Data Processing

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Streamline seismic data processing using high performance computing

Seismic data processing to interpret subsurface features is both computationally and data intensive.

Common procedures to streamline seismic data processing include:

  • Working with data files, such as SEGY, that are too large to fit in system memory
  • Automating the processing of shot record and travel-time field files
  • Developing algorithms to reconstruct the subsurface
  • Interpreting subsurface features using visualization and animation
  • Using multicore processors, GPUs, and clusters in parallel for faster processing of seismic data

For details on a platform for performing these tasks, see MATLAB® and Simulink®.

Examples and How To

Software Reference

See also: PID control, energy production, algorithm development, parallel computing, digital signal processing (DSP)