Seismic Data Processing

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), Smart Emergency Response System