Python for Geophysical Data Processing and Visualization

The Python language excels as a tool for processing and visualizing scientific data. The array processing tools in NumPy handle multi-dimensional arrays and provide convenient representations for common geophysical data types such as well logs (1D), horizons (2D) and seismic volumes (3D). SciPy provides a wealth of efficient algorithms (interpolation, statistics, signal processing, etc.) common in processing such data, and matplotlib, chaco, and Mayavi provide plotting and 3D visualization capabilities. For those interested in harnessing the powers of the GPU, libraries such as CLyther, PyOpenCL, and PyCUDA offer a convenient bridge to these technologies. This presentation will provide an overview of these Python tools and demonstrate how to apply them to geophysical problems. We will provide examples of how these open source tools can be used for academic research as well as incorporated into commercial applications.