DOI: 10.5194/hess-18-2943-2014
Scopus记录号: 2-s2.0-84923061029
论文题名: The effect of training image and secondary data integration with multiple-point geostatistics in groundwater modelling
作者: He X ; L ; , Sonnenborg T ; O ; , Jørgensen F ; , Jensen K ; H
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2014
卷: 18, 期: 8 起始页码: 2943
结束页码: 2954
语种: 英语
Scopus关键词: Groundwater
; Groundwater flow
; Hydrogeology
; Stochastic systems
; Airborne electromagnetic
; Geostatistical simulation
; Multiple-point geostatistics
; Multivariate distributions
; Probabilistic capture zones
; Stochastic hydrogeology
; Three-dimensional (3-D) simulation
; Unconditional simulations
; Data integration
; data set
; electromagnetic field
; geophysical method
; geostatistics
; groundwater
; groundwater flow
; hydrogeology
; hydrological modeling
; three-dimensional modeling
英文摘要: Multiple-point geostatistical simulation (MPS) has recently become popular in stochastic hydrogeology, primarily because of its capability to derive multivariate distributions from a training image (TI). However, its application in three-dimensional (3-D) simulations has been constrained by the difficulty of constructing a 3-D TI. The object-based unconditional simulation program TiGenerator may be a useful tool in this regard; yet the applicability of such parametric training images has not been documented in detail. Another issue in MPS is the integration of multiple geophysical data. The proper way to retrieve and incorporate information from high-resolution geophysical data is still under discussion. In this study, MPS simulation was applied to different scenarios regarding the TI and soft conditioning. By comparing their output from simulations of groundwater flow and probabilistic capture zone, TI from both sources (directly converted from high-resolution geophysical data and generated by TiGenerator) yields comparable results, even for the probabilistic capture zones, which are highly sensitive to the geological architecture. This study also suggests that soft conditioning in MPS is a convenient and efficient way of integrating secondary data such as 3-D airborne electromagnetic data (SkyTEM), but over-conditioning has to be avoided. © Author(s) 2014. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78173
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Geosciences and Natural Resource Management, Copenhagen University, Copenhagen, Denmark; Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Recommended Citation:
He X,L,, Sonnenborg T,et al. The effect of training image and secondary data integration with multiple-point geostatistics in groundwater modelling[J]. Hydrology and Earth System Sciences,2014-01-01,18(8)