Python for HPC geophysical electromagnetic applications: experiences and perspectives

Nowadays, the electromagnetic modelling are a fun-damental tool in geophysics due to their wide field of application: hydrocarbon and mineral exploration, reservoir monitoring, CO��� storage characterization, geothermal reservoir imaging and many others. In particular, the 3D CSEM forward modelling (FM) is an established tool in the oil & gas industry because of the hope that the application of such methods would eventually lead to the direct detection of hydrocarbons through their insulating properties. Although 3D CSEM FM is nowadays a well-known geophysical prospecting tool and his fundamental mathematical theory is well-established, the state-of-art shows a relative scarsity of robust, flexible, modular and open-source codes to simulate these problems on HPC platforms, which is crucial in the future goal of solving inverse problems. In this talk we describe our experience and perspectives in the development of an HPC python code for the 3D CSEM FM, namely, PETGEM. We focus on three points: 1) 3D CSEM FM theory from a practical point of view, 2) PETGEM features and Python potential for HPC applications, and 3) Modelling results of real-life 3D CSEM FM cases. These points depict that PETGEM could be an attractive and competitive HPC tool to simulate real-scale of 3D CSEM FM in geophysics.