Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2021WR030608 |
Thermal experiments for fractured rock characterization: theoretical analysis and inverse modeling | |
Zitong Zhou; Delphine Roubinet; Daniel M. Tartakovsky | |
2021-11-24 | |
发表期刊 | Water Resources Research |
出版年 | 2021 |
英文摘要 | Field-scale properties of fractured rocks play crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion technique to infer two such parameters, fracture density and fractal dimension, from cross-borehole thermal experiments data. It is based on a particle-based heat-transfer model, whose evaluation is accelerated with a deep neural network (DNN) surrogate that is integrated into a grid search. The DNN is trained on a small number of heat-transfer model runs, and predicts the cumulative density function of the thermal field. The latter is used to compute fine posterior distributions of the (to-be-estimated) parameters. Our synthetic experiments reveal that fracture density is well constrained by data, while fractal dimension is harder to determine. Adding non-uniform prior information related to the DFN connectivity improves the inference of this parameter. This article is protected by copyright. All rights reserved. |
领域 | 资源环境 |
URL | 查看原文 |
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/342387 |
专题 | 资源环境科学 |
推荐引用方式 GB/T 7714 | Zitong Zhou,Delphine Roubinet,Daniel M. Tartakovsky. Thermal experiments for fractured rock characterization: theoretical analysis and inverse modeling[J]. Water Resources Research,2021. |
APA | Zitong Zhou,Delphine Roubinet,&Daniel M. Tartakovsky.(2021).Thermal experiments for fractured rock characterization: theoretical analysis and inverse modeling.Water Resources Research. |
MLA | Zitong Zhou,et al."Thermal experiments for fractured rock characterization: theoretical analysis and inverse modeling".Water Resources Research (2021). |
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