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