Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2016WR019853 |
A distance transform for continuous parameterization of discrete geologic facies for subsurface flow model calibration | |
Hakim-Elahi, Siavash; Jafarpour, Behnam | |
2017-10-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:10 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Construction of predictive subsurface flow models involves subjective interpretation and interpolation of spatially limited data, often using imperfect modeling assumptions. Hence, the process can introduce significant uncertainty and bias in predicting the flow and transport behavior of these systems. In particular, the uncertainty in the facies distribution in complex geologic environments, such as alluvial/fluvial channels, can be consequential for forecasting the dynamic response of these systems to perturbations due to pumping and development activities. Conventional model calibration techniques that are designed to update continuous model parameters cannot be used to estimate discrete parameters from flow and pressure data. We present a distance transform approach for converting discrete facies models to continuous parameters that can be updated using continuous model calibration methods. Distance transforms are widely used in discrete image processing, where the discrete values in each pixel are replaced with their distance (i.e., a continuous variable) to the nearest boundary cell. After updating the continuous distance maps during model calibration, a back transformation is applied to retrieve the updated facies maps. To preserve large-scale facies connectivity, truncated singular value decomposition (SVD) parametrization may be used to represent the distance maps with low-rank parameters. A variant of the ensemble smoother, ES-MDA is used to update the continuous parameters of the inversion (either distance maps or their SVD coefficients if used). The distance transform method addresses an important problem in facies model calibration where model updating can result in losing facies connectivity and discreteness. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000418736000006 |
WOS关键词 | ENSEMBLE KALMAN FILTER ; CROSS-STRATIFIED SEDIMENT ; STEADY-STATE CONDITIONS ; DATA ASSIMILATION ; HYDRAULIC CONDUCTIVITY ; AQUIFER HETEROGENEITY ; GROUNDWATER-FLOW ; INVERSE METHODS ; SPATIAL CORRELATION ; IDENTIFICATION |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/21179 |
专题 | 资源环境科学 |
作者单位 | Univ Southern Calif, Dept Chem Engn & Mat Sci, Los Angeles, CA 90007 USA |
推荐引用方式 GB/T 7714 | Hakim-Elahi, Siavash,Jafarpour, Behnam. A distance transform for continuous parameterization of discrete geologic facies for subsurface flow model calibration[J]. WATER RESOURCES RESEARCH,2017,53(10). |
APA | Hakim-Elahi, Siavash,&Jafarpour, Behnam.(2017).A distance transform for continuous parameterization of discrete geologic facies for subsurface flow model calibration.WATER RESOURCES RESEARCH,53(10). |
MLA | Hakim-Elahi, Siavash,et al."A distance transform for continuous parameterization of discrete geologic facies for subsurface flow model calibration".WATER RESOURCES RESEARCH 53.10(2017). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论