globalchange  > 气候变化与战略
DOI: 10.5194/hess-22-6547-2018
论文题名:
Locality-based 3-D multiple-point statistics reconstruction using 2-D geological cross sections
作者: Chen Q.; Mariethoz G.; Liu G.; Comunian A.; Ma X.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2018
卷: 22, 期:12
起始页码: 6547
结束页码: 6566
语种: 英语
Scopus关键词: Computational efficiency ; Geology ; Probability density function ; Sensitivity analysis ; Three dimensional computer graphics ; 3-d geological models ; Application examples ; Geological features ; Multiple-point statistics ; Probability density functions (PDFs) ; Search strategies ; Subsurface structures ; Threedimensional (3-d) ; Image reconstruction ; anisotropy ; density ; geology ; image ; model ; sensitivity analysis ; simulation ; statistical analysis
英文摘要: Multiple-point statistics (MPS) has shown promise in representing complicated subsurface structures. For a practical three-dimensional (3-D) application, however, one of the critical issues is the difficulty in obtaining a credible 3-D training image. However, bidimensional (2-D) training images are often available because established workflows exist to derive 2-D sections from scattered boreholes and/or other samples. In this work, we propose a locality-based MPS approach to reconstruct 3-D geological models on the basis of such 2-D cross sections (3DRCS), making 3-D training images unnecessary. Only several local training subsections closer to the central uninformed node are used in the MPS simulation. The main advantages of this partitioned search strategy are the high computational efficiency and a relaxation of the stationarity assumption. We embed this strategy into a standard MPS framework. Two probability aggregation formulas and their combinations are used to assemble the probability density functions (PDFs) from different subsections. Moreover, a novel strategy is adopted to capture more stable PDFs, where the distances between patterns and flexible neighborhoods are integrated on multiple grids. A series of sensitivity analyses demonstrate the stability of the proposed approach. Several hydrogeological 3-D application examples illustrate the applicability of the 3DRCS approach in reproducing complex geological features. The results, in comparison with previous MPS methods, show better performance in portraying anisotropy characteristics and in CPU cost. © Author(s) 2018.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/163102
Appears in Collections:气候变化与战略

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作者单位: Chen, Q., School of Computer Science, China University of Geosciences, Wuhan, 430074, China, Institute of Earth Surface Dynamics, University of Lausanne, Lausanne, 1015, Switzerland, Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, 430074, China; Mariethoz, G., Institute of Earth Surface Dynamics, University of Lausanne, Lausanne, 1015, Switzerland; Liu, G., School of Computer Science, China University of Geosciences, Wuhan, 430074, China, Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, 430074, China; Comunian, A., Dipartimento di Scienze della Terra 'A. Desio', Università degli Studi di Milano, Milan, Italy; Ma, X., Department of Computer Science, University of Idaho, 875 Perimeter Drive MS 1010, Moscow, ID 83844-1010, United States

Recommended Citation:
Chen Q.,Mariethoz G.,Liu G.,et al. Locality-based 3-D multiple-point statistics reconstruction using 2-D geological cross sections[J]. Hydrology and Earth System Sciences,2018-01-01,22(12)
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