A Modification of Adaptive Greedy Algorithm for Solving Problems of Fractured Media Geophysics

Nowadays, the issue of direct modeling of seismic exploration problems is becoming increasingly important due to the development of a new field of application of such algorithms as generation of a training samples for subsequent solution of the appropriate inverse problem using neural networks. This challenges scientists to develop corresponding parallel algorithms and improve their efficiency. The current manuscript is devoted to the algorithm for decomposing a large number of individual computational grids of various sizes for a large number of MPI processes using the example of a 3D direct problem of seismic exploration of geological media treating the complex topology of the Earth’s surface, the complex shape of interfaces between geological layers and a large number of explicitly treated geological fractures, that are not aligned with the coordinate axes. Three modifications of the grid-characteristic numerical method on Chimera and curvilinear computational grids are compared with each other. The dependence on different numbers of fractures is studied. A large number (several hundreds or thousands) of fractures in the geological media significantly increases the amount of transmitted data, which imposes requirements on the developed modification of the greedy algorithm.