Results 271 to 280 of about 1,087,662 (308)

Using the Snesim program for multiple-point statistical simulation

Computers & Geosciences, 2006
Traditionally, there are two mainstream avenues for geostatistical modeling: pixel-based two-point simulation and object-based simulation. Each is good at either data conditioning or reproducing geological shapes, but none is good at both. Multiple-point simulation combines the strengths of these two avenues.
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Hybrid geological modeling: Combining machine learning and multiple-point statistics

Computers & Geosciences, 2020
Abstract Accurately modeling and constructing a geologically realistic subsurface model remains an outstanding problem as the morphology controls the flow behaviors. Particularly, one of the pattern-based methods, namely cross-correlation based simulation, has been proved to be an effective way to reconstruct a realistic model, at both small and ...
Tao Bai, Pejman Tahmasebi
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Modeling complex reservoir geometries with multiple-point statistics

Mathematical Geology, 1996
Large-scale reservoir architecture constitutes first-order reservoir heterogeneity and dietates to a large extent reservoir flow behavior. It also manifests geometric characteristics beyond the capability of traditional geostatistical models conditioned only on single-point and two-point statistics.
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Multiple-point Statistics Simulations Accounting for Block Data

Proceedings, 2015
Multiple-point statistics methods allow to generate highly heterogeneous fields reproducing the spatial features within a given training image. Whereas punctual conditioning data can be handled straightforwardly, dealing with information defined at larger scales is challenging.
J. Straubhaar*, P. Renard, G. Mariethoz
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Handling Soft Probabilities in Multiple Point Statistics Simulation

2013
This paper is presenting a methodology to handle rigorously soft probabilities in Multiple Point Statistics (MPS) simulation for facies modeling. It is based on the second generation algorithm for MPS simulation using efficient Direct Sampling of the training image.
Pierre Biver, Gregoire Mariethoz, Julien Straubhaar, Tatiana Chugunova, Philippe Renard   +4 more
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CPU-MIC Acceleration of Multiple-point Statistical Simulation on Tianhe-2

2020 IEEE 22nd International Conference on High Performance Computing and Communications; IEEE 18th International Conference on Smart City; IEEE 6th International Conference on Data Science and Systems (HPCC/SmartCity/DSS), 2020
Multiple-point statistics (MPS) has shown promise in representing heterogeneous phenomena in earth science. However, since the MPS algorithms require scanning of the entire pattern library or the training image for each unknown location, this results in severe computational consumption.
Qiyu Chen 0001, Zhesi Cui, Gang Liu 0003, Jia Liu 0021, Xiaogang Ma 0001   +4 more
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GPU-accelerated Direct Sampling method for multiple-point statistical simulation

Computers & Geosciences, 2013
Abstract Geostatistical simulation techniques have become a widely used tool for the modeling of oil and gas reservoirs and the assessment of uncertainty. The Direct Sampling (DS) algorithm is a recent multiple-point statistical simulation technique.
Tao Huang 0011, Xue Li 0003, Ting Zhang 0004, Detang Lu   +3 more
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Accelerating simulation for the multiple-point statistics algorithm using vector quantization

Physical Review E, 2018
Multiple-point statistics (MPS) is a prominent algorithm to simulate categorical variables based on a sequential simulation procedure. Assuming training images (TIs) as prior conceptual models, MPS extracts patterns from TIs using a template and records their occurrences in a database.
Chen, Zuo, Zhibin, Pan, Hao, Liang
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Prediction of permeability for porous media reconstructed using multiple-point statistics

Physical Review E, 2004
To predict multiphase flow through geologically realistic porous media, it is necessary to have a three-dimensional (3D) representation of the pore space. We use multiple-point statistics based on two-dimensional (2D) thin sections as training images to generate geologically realistic 3D pore-space representations.
Hiroshi, Okabe, Martin J, Blunt
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Integrating Multiple-point Statistics into Sequential Simulation Algorithms

2005
Most conventional simulation techniques only account for two-point statistics via the modeling of the variogram of the regionalized variable or of its indicators. These techniques cannot control the reproduction of multiple-point statistics that may be critical for the performance of the models given the goal at hand (flow simulation in petroleum ...
Julian M. Ortiz, Xavier Emery
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