Journal ArticleDOI
Multiple-point geostatistical simulation based on conditional conduction probability
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In this paper, the authors proposed a new MPS simulation method based on conditional conduction probability, namely the CCPSIM algorithm, to mitigate the uncertainty of MPS realizations.Abstract:
Multiple-point geostatistical (MPS) simulation can enhance extraction and synthesis of various information in earth and environmental sciences. In particular, it is able to characterize the complex spatial structures of heterogeneous phenomena more accurately. In this paper, we propose a new MPS simulation method based on conditional conduction probability, namely the CCPSIM algorithm, to mitigate the uncertainty of MPS realizations. In CCPSIM, the simulated nodes will be treated differently from the original samples. The probability distributions of the simulated nodes will be used as prior conditions to calculate the probability distributions of the following nodes, and the prior conditions will be conducted during the whole simulation process. 2D and 3D synthetic tests are used to verify the applicability and advantages of CCPSIM. The results confirm that CCPSIM is able to reproduce spatial patterns of heterogeneous structures presented in categorical training images, and it reduces the uncertainty of the MPS realizations caused by the undistinguished using of the original known samples and the simulated uncertain values.read more
Citations
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Journal ArticleDOI
Hybrid parallel framework for multiple-point geostatistics on Tianhe-2: A robust solution for large-scale simulation
TL;DR: In this article, a new hybrid parallel framework is proposed for the case of multiple point geostatistical (MPS) simulation on large areas with an enormous amount of grid cells, which can efficiently achieve the high-resolution reproduction and characterization of complex structures and phenomena in earth sciences.
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Automatic reconstruction method of 3D geological models based on deep convolutional generative adversarial networks
TL;DR: Experimental results show that the proposed 3D automatic reconstruction method based on DCGAN can capture the features, trends and spatial patterns of geological structures well and is able to reconstruct more accurately and quickly by using the proposed method.
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Deep convolutional generative adversarial networks for modeling complex hydrological structures in Monte-Carlo simulation
TL;DR: In this article , the authors proposed a method to reconstruct complex hydrological structures by using deep convolutional generative adversarial networks (DCGAN) in the Monte-Carlo simulation process, named MC-GAN.
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A parametric 3D geological modeling method considering stratigraphic interface topology optimization and coding expert knowledge
TL;DR: The NURBS Surface Dynamic Topology (NURBS-SDT) method is proposed to regularize the complex topological structure of the geological interfaces, thereby expressing them parametrically and subjective expert knowledge input is translated into objective modeling rules through the proposed BLSOGI method, which means different geological bodies can be automatically modeled.
References
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Journal ArticleDOI
Conditional Simulation of Complex Geological Structures Using Multiple-Point Statistics
TL;DR: The approach proposed in this paper consists of borrowing the required multiple-point statistics from training images depicting the expected patterns of geological heterogeneities from the geostatistical numerical model where they are anchored to the actual data in a sequential simulation mode.
Book ChapterDOI
Multivariate Geostatistics: Beyond Bivariate Moments
TL;DR: In this paper, higher order sample statistics such as three, four, multi-point covariances, as obtained, for example, from a training image, would improve considerably stochastic images if they could be reproduced.
Journal ArticleDOI
The Direct Sampling method to perform multiple‐point geostatistical simulations
TL;DR: This work proposes to sample directly the training image for a given data event, making the database unnecessary, and shows its applicability in the presence of complex features, nonlinear relationships between variables, and with various cases of nonstationarity.
Journal ArticleDOI
Connectivity metrics for subsurface flow and transport
Philippe Renard,Denis Allard +1 more
TL;DR: This paper provides a review of the various metrics that were proposed so far, and they are classified in four main groups which depend only on the connectivity structure of the parameter fields (hydraulic conductivity or geological facies).
Journal ArticleDOI
Conditional Simulation with Patterns
G. Burc Arpat,Jef Caers +1 more
TL;DR: An entirely new approach to stochastic simulation is proposed through the direct simulation of patterns, which borrows heavily from the pattern recognition literature and simulates by pasting at each visited location along a random path a pattern that is compatible with the available local data and any previously simulated patterns.