Training Images-Based Stochastic Simulation on Many-Core Architectures

In the past decades, multiple-point geostatistical methods (MPS) are increasing in popularity in various fields. Compared with the traditional techniques, MPS techni‐ ques have the ability to characterize geological reality that commonly has complex structures such as curvilinear and long-range channels by using high-order statistics for pattern reconstruction. As a result, the computational burden is heavy, and some‐ times, the current algorithms are unable to be applied to large-scale simulations. With the continuous development of hardware architectures, the parallelism implementa‐ tion of MPS methods is an alternative to improve the performance. In this chapter, we overview the basic elements for MPS methods and provide several parallel strategies on many-core architectures. The GPU-based parallel implementation of two efficient MPS methods known as SNESIM and Direct Sampling is detailed as examples.

[1]  Jef Caers,et al.  Abstract: Geostatistical quantification of geological information for a fluvial-type North Sea reservoir , 2000 .

[2]  Andre G. Journel,et al.  Geostatistics: Roadblocks and Challenges , 1993 .

[3]  L. Y. Hu,et al.  Multiple‐point geostatistics for modeling subsurface heterogeneity: A comprehensive review , 2008 .

[4]  Pejman Tahmasebi,et al.  Multiple-point geostatistical modeling based on the cross-correlation functions , 2012, Computational Geosciences.

[5]  Roussos G. Dimitrakopoulos,et al.  HOSIM: A high-order stochastic simulation algorithm for generating three-dimensional complex geological patterns , 2011, Comput. Geosci..

[6]  Pejman Tahmasebi,et al.  MS-CCSIM: Accelerating pattern-based geostatistical simulation of categorical variables using a multi-scale search in Fourier space , 2014, Comput. Geosci..

[7]  M. Blunt,et al.  Pore space reconstruction of vuggy carbonates using microtomography and multiple‐point statistics , 2007 .

[8]  A. Journel,et al.  Hierarchical simulation of multiple-facies reservoirs using multiple-point geostatistics , 2005 .

[9]  Rúben Nunes,et al.  Parallelization of sequential Gaussian, indicator and direct simulation algorithms , 2010, Comput. Geosci..

[10]  Colin Daly,et al.  Higher Order Models using Entropy, Markov Random Fields and Sequential Simulation , 2005 .

[11]  Gregoire Mariethoz,et al.  The Direct Sampling method to perform multiple‐point geostatistical simulations , 2010 .

[12]  G. Mariéthoz,et al.  Demonstration of a geostatistical approach to physically consistent downscaling of climate modeling simulations , 2013 .

[13]  G. Mariéthoz,et al.  An Improved Parallel Multiple-point Algorithm Using a List Approach , 2011 .

[14]  Tao Huang,et al.  GPU-based SNESIM implementation for multiple-point statistical simulation , 2013, Comput. Geosci..

[15]  Sebastien Strebelle,et al.  Conditional Simulation of Complex Geological Structures Using Multiple-Point Statistics , 2002 .

[16]  G. Mariéthoz,et al.  Multiple-point Geostatistics: Stochastic Modeling with Training Images , 2014 .

[17]  Alexandre Boucher,et al.  Applied Geostatistics with SGeMS: A User's Guide , 2009 .

[18]  R. Mohan Srivastava,et al.  An Overview of Stochastic Methods for Reservoir Characterization , 1994 .

[19]  Pejman Tahmasebi,et al.  Accelerating geostatistical simulations using graphics processing units (GPU) , 2012, Comput. Geosci..

[20]  Clayton V. Deutsch,et al.  Integrating Large-Scale Soft Data by Simulated Annealing and Probability Constraints , 2000 .

[21]  Grégoire Mariethoz,et al.  A general parallelization strategy for random path based geostatistical simulation methods , 2010, Comput. Geosci..

[22]  G. Mariéthoz,et al.  Simulation of Earth textures by conditional image quilting , 2014 .

[23]  Paul Switzer,et al.  Filter-Based Classification of Training Image Patterns for Spatial Simulation , 2006 .

[24]  Julián M. Ortiz,et al.  Parallel implementation of simulated annealing to reproduce multiple-point statistics , 2011, Comput. Geosci..

[25]  Tao Huang,et al.  GPU-accelerated Direct Sampling method for multiple-point statistical simulation , 2013, Comput. Geosci..

[26]  M. Sahimi,et al.  Cross-correlation function for accurate reconstruction of heterogeneous media. , 2013, Physical Review Letters.

[27]  Jef Caers,et al.  Sequential simulation with patterns , 2005 .

[28]  Andrew Richard Gardiner,et al.  Best practice stochastic facies modeling from a channel-fill turbidite sandstone analog (the Quarry outcrop, Eocene Ainsa basin, northeast Spain) , 2006 .

[29]  Andre G. Journel,et al.  Spatial Connectivity: From Variograms to Multiple-Point Measures , 2003 .

[30]  Andre G. Journel.  Beyond Covariance: The Advent of Multiple-Point Geostatistics , 2005 .

[31]  P. Goovaerts.  Geostatistical tools for characterizing the spatial variability of microbiological and physico-chemical soil properties , 1998, Biology and Fertility of Soils.

[32]  M. Blunt,et al.  Pore space reconstruction using multiple-point statistics , 2005 .

[33]  3D Porosity Modeling of a Carbonate Reservoir Using Continuous Multiple-Point Statistics Simulation , 2006 .