IEEE Transactions on Computational Imaging

A novel approach is presented for fast generation of synthetic seismograms due to microseismic events, using heterogeneous marine velocity models. The partial differential equations (PDEs) for the 3D elastic wave equation have been numerically solved using the Fourier domain pseudo-spectral method which is parallelizable on the graphics processing unit (GPU) cards, thus making it faster compared to traditional CPU based computing platforms. Due to computationally expensive forward simulation of large geological models, several combinations of individual synthetic seismic traces are used for specified microseismic event locations, in order to simulate the effect of realistic microseismic activity patterns in the subsurface. We here explore the patterns generated by few hundreds of microseismic events with different source mechanisms using various combinations, both in event amplitudes and origin times, using the simulated pressure and three component particle velocity fields via 1D, 2D and 3D seismic visualizations.

[1]  Bradley E. Treeby,et al.  Modelling elastic wave propagation using the k-Wave MATLAB Toolbox , 2014, 2014 IEEE International Ultrasonics Symposium.

[2]  David A. Yuen,et al.  Seismic Wave Propagation Simulation Using Accelerated Support Operator Rupture Dynamics on Multi-GPU , 2011, 2011 14th IEEE International Conference on Computational Science and Engineering.

[3]  Haixia Zhao,et al.  Modeling the propagation of diffusive-viscous waves using Flux Corrected Transport-Finite Difference Method , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[4]  Michael Prange,et al.  A unified Bayesian framework for relative microseismic location , 2013 .

[5]  Po Chen,et al.  Accelerating the discontinuous Galerkin method for seismic wave propagation simulations using the graphic processing unit (GPU) - single-GPU implementation , 2013, Comput. Geosci..

[6]  Mirko van der Baan,et al.  Scaling relations and spectral characteristics of tensile microseisms: evidence for opening/closing cracks during hydraulic fracturing , 2014 .

[7]  P. Szymczyk,et al.  Matlab and Parallel Computing , 2012 .

[8]  Stefan Mertl,et al.  Hazard Estimation of Deep Seated Mass Movements by Microseismic Monitoring , 2008 .

[9]  Mirko van der Baan,et al.  Body Wave Separation in the Time-Frequency Domain , 2015, IEEE Geoscience and Remote Sensing Letters.

[10]  Muhammad Sahimi,et al.  Numerical Simulation of Wave Propagation, Part I: Sequential Computing , 2008, Computing in Science & Engineering.

[11]  S. Bojinski,et al.  An approach to upscaling for seismic waves in statistically isotropic heterogeneous elastic media , 2000 .

[12]  William J. Dally,et al.  The GPU Computing Era , 2010, IEEE Micro.

[13]  Moshe Reshef,et al.  Three-dimensional elastic modeling by the Fourier method , 1988 .

[14]  Laurent Baillet,et al.  Analysis of seismic signals recorded on a prone-to-fall rock column (Vercors massif, French Alps) , 2011 .

[15]  Siyuan Cao,et al.  Microseismic forward modeling based on different focal mechanisms used by the seismic moment tensor and elastic wave equation , 2015 .

[16]  Michael Prange,et al.  Joint location of microseismic events in the presence of velocity uncertainty , 2014 .

[17]  Albert Farrés,et al.  Finite-difference staggered grids in GPUs for anisotropic elastic wave propagation simulation , 2014, Comput. Geosci..

[18]  Augusto Beléndez,et al.  Performance analysis of SSE and AVX instructions in multi-core CPUs and GPU computing on FDTD scheme for solid and fluid vibration problems , 2014, The Journal of Supercomputing.

[19]  Gordon Erlebacher,et al.  Porting a high-order finite-element earthquake modeling application to NVIDIA graphics cards using CUDA , 2009, J. Parallel Distributed Comput..

[20]  Deborah K. Fagan,et al.  Clustering revisited: A spectral analysis of microseismic events , 2013 .

[21]  M. Stein Large sample properties of simulations using latin hypercube sampling , 1987 .

[22]  Youngmin Kim,et al.  Accelerating MATLAB with GPU Computing: A Primer with Examples , 2013 .

[23]  Moshe Reshef,et al.  Elastic wave calculations by the Fourier method , 1984 .

[24]  Heiner Igel,et al.  Anisotropic wave propagation through finite-difference grids , 1995 .

[25]  Andrew W. Hill,et al.  Beyond the Dots in the Box – Microseismicity-constrained Fracture Models for Reservoir Simulation , 2010 .

[26]  Giada Adelfio,et al.  Simultaneous seismic wave clustering and registration , 2012, Comput. Geosci..

[27]  Po Chen,et al.  Accelerating the discontinuous Galerkin method for seismic wave propagation simulations using multiple GPUs with CUDA and MPI , 2013 .

[28]  George A. McMechan,et al.  Comparison of two viscoacoustic propagators for Q-compensated reverse time migration , 2016 .

[29]  Gordon Erlebacher,et al.  Modeling the propagation of elastic waves using spectral elements on a cluster of 192 GPUs , 2010, Computer Science - Research and Development.

[30]  Michael Fehler,et al.  Bayesian inversion of pressure diffusivity from microseismicity , 2015 .

[31]  Jun Zhou,et al.  Hands-on Performance Tuning of 3D Finite Difference Earthquake Simulation on GPU Fermi Chipset , 2012, ICCS.

[32]  W. A. Mulder,et al.  Experiments with Higdon's absorbing boundary conditions for a number of wave equations , 1997 .

[33]  Tomasz Danek Seismic Wave Field Modeling with Graphics Processing Units , 2009, ICCS.

[34]  Dimitri Komatitsch,et al.  Fluid–solid coupling on a cluster of GPU graphics cards for seismic wave propagation , 2011 .

[35]  Vijay Gadepally,et al.  MATLAB for Signal Processing on Multiprocessors and Multicores , 2010, IEEE Signal Processing Magazine.

[36]  T. Okamoto,et al.  Accelerating large-scale simulation of seismic wave propagation by multi-GPUs and three-dimensional domain decomposition , 2010 .

[37]  Simon Rogers,et al.  A First Course in Machine Learning , 2011, Chapman and Hall / CRC machine learning and pattern recognition series.

[38]  Arun Chauhan,et al.  Automating GPU computing in MATLAB , 2011, ICS '11.

[39]  Dheeraj Bhardwaj,et al.  An explicit predictor-corrector solver with application to seismic wave modelling , 2000 .

[40]  Peter Huthwaite,et al.  Accelerated finite element elastodynamic simulations using the GPU , 2014, J. Comput. Phys..

[41]  Gary Martin,et al.  Marmousi2 An elastic upgrade for Marmousi , 2006 .

[42]  B T Cox,et al.  k-Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields. , 2010, Journal of biomedical optics.

[43]  Shuai Xu,et al.  Accelerating MatLab code using GPU: A review of tools and strategies , 2011, 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC).

[44]  Scott B. Baden,et al.  Accelerating a 3D Finite-Difference Earthquake Simulation with a C-to-CUDA Translator , 2012, Computing in Science & Engineering.

[45]  J. Del Rio,et al.  A Low Power Datalogger based on Compactflash memory for Ocean Bottom Seismometers (OBS) , 2005, 2005 IEEE Instrumentationand Measurement Technology Conference Proceedings.

[46]  Hans-Peter Harjes,et al.  Spatio-temporal microseismicity clustering in the Cretan region , 2006 .

[47]  V. Vavryčuk Moment tensor decompositions revisited , 2014, Journal of Seismology.

[48]  Peter Bailey,et al.  Accelerating geoscience and engineering system simulations on graphics hardware , 2009, Comput. Geosci..

[49]  Peter Messmer,et al.  Forward and adjoint simulations of seismic wave propagation on emerging large-scale GPU architectures , 2012, 2012 International Conference for High Performance Computing, Networking, Storage and Analysis.

[50]  Dimitri Komatitsch,et al.  Accelerating a three-dimensional finite-difference wave propagation code using GPU graphics cards , 2010 .

[51]  Yair M. Altman Accelerating MATLAB Performance: 1001 tips to speed up MATLAB programs , 2014 .

[52]  Robin M. Weiss,et al.  Solving 3D anisotropic elastic wave equations on parallel GPU devices , 2013 .