GSTDTAP  > 资源环境科学
DOI10.1002/2017WR022019
Tuning Fractures With Dynamic Data
Yao, Mengbi1; Chang, Haibin1; Li, Xiang1; Zhang, Dongxiao2,3,4
2018-02-01
发表期刊WATER RESOURCES RESEARCH
ISSN0043-1397
EISSN1944-7973
出版年2018
卷号54期号:2页码:680-707
文章类型Article
语种英语
国家Peoples R China
英文摘要

Flow in fractured porous media is crucial for production of oil/gas reservoirs and exploitation of geothermal energy. Flow behaviors in such media are mainly dictated by the distribution of fractures. Measuring and inferring the distribution of fractures is subject to large uncertainty, which, in turn, leads to great uncertainty in the prediction of flow behaviors. Inverse modeling with dynamic data may assist to constrain fracture distributions, thus reducing the uncertainty of flow prediction. However, inverse modeling for flow in fractured reservoirs is challenging, owing to the discrete and non-Gaussian distribution of fractures, as well as strong nonlinearity in the relationship between flow responses and model parameters. In this work, building upon a series of recent advances, an inverse modeling approach is proposed to efficiently update the flow model to match the dynamic data while retaining geological realism in the distribution of fractures. In the approach, the Hough-transform method is employed to parameterize non-Gaussian fracture fields with continuous parameter fields, thus rendering desirable properties required by many inverse modeling methods. In addition, a recently developed forward simulation method, the embedded discrete fracture method (EDFM), is utilized to model the fractures. The EDFM maintains computational efficiency while preserving the ability to capture the geometrical details of fractures because the matrix is discretized as structured grid, while the fractures being handled as planes are inserted into the matrix grids. The combination of Hough representation of fractures with the EDFM makes it possible to tune the fractures (through updating their existence, location, orientation, length, and other properties) without requiring either unstructured grids or regridding during updating. Such a treatment is amenable to numerous inverse modeling approaches, such as the iterative inverse modeling method employed in this study, which is capable of dealing with strongly nonlinear problems. A series of numerical case studies with increasing complexity are set up to examine the performance of the proposed approach.


领域资源环境
收录类别SCI-E
WOS记录号WOS:000428474500003
WOS关键词ENSEMBLE KALMAN FILTER ; POROUS-MEDIA ; DATA ASSIMILATION ; MODELING FLUID ; FLOW ; RESERVOIRS ; EFFICIENT ; PARAMETERIZATION ; FACIES
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/21211
专题资源环境科学
作者单位1.Peking Univ, Dept Energy & Resources Engn, Coll Engn, Beijing, Peoples R China;
2.Peking Univ, ERE, Beijing, Peoples R China;
3.Peking Univ, BIC ESAT, Beijing, Peoples R China;
4.Peking Univ, SKLTCS, Coll Engn, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Yao, Mengbi,Chang, Haibin,Li, Xiang,et al. Tuning Fractures With Dynamic Data[J]. WATER RESOURCES RESEARCH,2018,54(2):680-707.
APA Yao, Mengbi,Chang, Haibin,Li, Xiang,&Zhang, Dongxiao.(2018).Tuning Fractures With Dynamic Data.WATER RESOURCES RESEARCH,54(2),680-707.
MLA Yao, Mengbi,et al."Tuning Fractures With Dynamic Data".WATER RESOURCES RESEARCH 54.2(2018):680-707.
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