Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018WR023262 |
Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics With Level-Set Transformation | |
Song, Xuehang1,2; Chen, Xingyuan1; Ye, Ming2; Dai, Zhenxue3; Hammond, Glenn4; Zachara, John M.1 | |
2019-04-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
卷号 | 55期号:4页码:2652-2671 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Peoples R China |
英文摘要 | The facies-based approach has been widely adopted to delineate an aquifer into distinct geological units with unique distributions of hydraulic, physical, and/or chemical properties. The recent development in ensemble-based data assimilation methods allows both the direct and indirect data to be used to improve facies delineation. A major difficulty in those applications is to honor the spatial continuity and avoid overfitting after data assimilation. We introduce a new facies delineation framework to integrate ensemble data assimilation with traditional transition probability-based geostatistics. A level-set concept is used to parametrize discrete facies indicators and for updating facies shape. During the iterative data assimilation process, we impose spatial continuity by conditioning facies field generation on points selected adaptively based on their sensitivity to observation data. This reconditioning step is a key step to maintain spatial continuity and overcome overfitting problems in inversion. We selected two examples to evaluate the performance of the new framework in estimating facies-based permeability field. The first example is a two-dimensional synthetic system with transient head data induced by pumping tests used for delineating two facies. The second example is a three-dimensional case with three facies, conceptualized from a field tracer experiment within the Columbia River corridor in Washington State, USA. Both examples demonstrate that the new method can adequately capture the spatial pattern of hydrofacies with reconditioning, which leads to the improved prediction of system behaviors. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000468597900006 |
WOS关键词 | KALMAN FILTER ; GEOLOGIC FACIES ; AQUIFER CHARACTERIZATION ; CHANNELIZED RESERVOIRS ; FRACTURED RESERVOIRS ; FLOW ; ENKF ; PARAMETERIZATION |
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/182211 |
专题 | 资源环境科学 |
作者单位 | 1.Pacific Northwest Natl Lab, Richland, WA 99352 USA; 2.Florida State Univ, Dept Earth Ocean & Atmospher Sci, Tallahassee, FL 32306 USA; 3.Jilin Univ, Coll Construct Engn, Changchun, Jilin, Peoples R China; 4.Sandia Natl Labs, Appl Syst Anal & Res, POB 5800, Albuquerque, NM 87185 USA |
推荐引用方式 GB/T 7714 | Song, Xuehang,Chen, Xingyuan,Ye, Ming,et al. Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics With Level-Set Transformation[J]. WATER RESOURCES RESEARCH,2019,55(4):2652-2671. |
APA | Song, Xuehang,Chen, Xingyuan,Ye, Ming,Dai, Zhenxue,Hammond, Glenn,&Zachara, John M..(2019).Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics With Level-Set Transformation.WATER RESOURCES RESEARCH,55(4),2652-2671. |
MLA | Song, Xuehang,et al."Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics With Level-Set Transformation".WATER RESOURCES RESEARCH 55.4(2019):2652-2671. |
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