.png){kind=icon}
返回
Fracture network characterization with deep generative model based stochastic inversion
.png){kind=icon}
OA
AI
DOI：10.1016/j.energy.2023.127302.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The characterization of fracture networks is challenging for enhanced geothermal systems, yet is crucial for the understanding of the thermal distributions, and the behaviors of flow field and solute transport. A novel inverse modeling framework is proposed for the estimation of the fracture networks. The hierarchical parameterization method is adopted in this work. For a small number of large fractures, each fracture is characterized by fracture length, azimuth and coordination of the fracture center. For dense small fractures, fracture density and fractal dimension are utilized to characterize the fracture networks. Moreover, we adopt variational auto-encoder and generative adversarial network (VAE-GAN) and fuse the GAN objective with prior constraint information to capture the distribution of the parameters of complex fracture networks and to satisfy the prior knowledge of fracture fields, thereby mapping the high-dimensional complex parameter distribution into low-dimensional continuous parameter field. Afterwards, relying on the Bayesian framework, ensemble smoother is adopted based on the collected data from hydraulic tomography to reduce the uncertainty of the fracture distribution. Two numerical cases with different complexity are used to test the performance of the proposed framework. The results show that the proposed algorithm can estimate effectively the distribution of the fracture fields.
Keyword:
Fracture inversion
Deep learning
Generative adversarial network
Variational auto -encoder
Data assimilation
Enhanced geothermal system
期刊
IF:
9.4
论文数:
4.3W
被引数:
20.2W
机构
引用论文
Energy transfer through laterally confined Bragg mirrors and its impact on pillar microcavities
PREAI
分享收藏Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications水文建模中的全球敏感性分析: 概念，方法，理论框架和应用综述.png)
JOURNAL OF HYDROLOGY
OAAI
JOURNAL OF HYDROLOGYIF6.3
OAAI分享收藏Numerical simulation of heat extraction performance in enhanced geothermal system with multilateral wells多分支井强化地热系统排热性能数值模拟APPLIED ENERGY
APPLIED ENERGYIF11
PREAI
分享收藏
查看更多内容