Massively-parallel electrical-conductivity imaging of hydrocarbonsusing the Blue Gene/L supercomputer

Large-scale controlled source electromagnetic (CSEM)three-dimensional (3D) geophysical imaging is now receiving considerableattention for electrical conductivity mapping of potential offshore oiland gas reservoirs. To cope with the typically large computationalrequirements of the 3D CSEM imaging problem, our strategies exploitcomputational parallelism and optimized finite-difference meshing. Wereport on an imaging experiment, utilizing 32,768 tasks/processors on theIBM Watson Research Blue Gene/L (BG/L) supercomputer. Over a 24-hourperiod, we were able to image a large scale marine CSEM field data setthat previously required over four months of computing time ondistributed clusters utilizing 1024 tasks on an Infiniband fabric. Thetotal initial data misfit could be decreased by 67 percent within 72completed inversion iterations, indicating an electrically resistiveregion in the southern survey area below a depth of 1500 m below theseafloor. The major part of the residual misfit stems from transmitterparallel receiver components that have an offset from the transmittersail line (broadside configuration). Modeling confirms that improvedbroadside data fits can be achieved by considering anisotropic electricalconductivities. While delivering a satisfactory gross scale image for thedepths of interest, the experiment provides important evidence for thenecessity of discriminating between horizontal and verticalconductivities for maximally consistent 3D CSEM inversions