Automatic Global Multiscale Seismic Inversion

Michael Afanasiev, Christian Boehm, Alexey Gokhberg, Andreas Fichtner
2016 Proceedings of the Platform for Advanced Scientific Computing Conference on - PASC '16  
Modern global seismic waveform tomography is formulated as a PDE-constrained nonlinear optimization problem, where the optimization variables are Earth's visco-elastic parameters. This particular problem has several defining characteristics. First, the solution to the forward problem, which involves the numerical solution of the elastic wave equation over continental to global scales, is computationally expensive. Second, the determinedness of the inverse problem varies dramatically as a
more » ... n of data coverage. This is chiefly due to the uneven distribution of earthquake sources and seismometers, which in turn results in an uneven sampling of the parameter space. Third, the seismic wavefield depends nonlinearly on the Earth's structure. Sections of a seismogram which are close in time may be sensitive to structure greatly separated in space. In addition to these theoretical difficulties, the seismic imaging community faces additional issues which are common across HPC applications. These include the storage of massive checkpoint files, the recovery from generic system failures, and the management of complex workflows, among others. While the community has access to solvers which can harness modern heterogeneous computing architectures, the computational bottleneck has fallen to these memory-and manpower-bounded issues. We present a two-tiered solution to the above problems. To deal with the problems relating to computational expense, data coverage, and the increasing nonlinearity of waveform tomography with scale, we present the Collaborative Seismic Earth Model (CSEM). This model, and its associated framework, takes an open-source approach to globalscale seismic inversion. Instead of attempting to monolithically invert all available seismic data, the CSEM approach focuses on the inversion of specific geographic subregions, and then consistently integrates these subregions via a common computational framework. To deal with the workflow and storage issues, we present a suite of workflow management software, along with a custom designed optimization and data compression library. It is the goal of this paper to synthesize these above concepts, originally developed in isolation, into components of an automatic global-scale seismic inversion.
doi:10.1145/2929908.2929910 fatcat:7edoe2kafbgdbb4ubv4mymn4me