Simulation on the Channeling Flow in Porous Media with Open-type Crack under Low Frequency Vibration
- DOI
- 10.2991/msbda-19.2019.18How to use a DOI?
- Keywords
- Low frequency wave, Dual porous media, Open-type crack, Seepage, Channeling rate
- Abstract
The application of wave stimulation technology in low permeability reservoirs with natural cracks was involved with the coupling of wave-induced flow, initial flow and solid deformation during the wave propagation process. Researchers had much work on the mechanism of seepage variation in dual porous media with constant permeability crack. However, the natural crack might be open-type some time, of which the width could increase with fluid pressure. The seepage in dual porous media under wave impact became more complicated. Thereby, a mathematic model about the seepage in porous media with open-type crack under low frequency vibration excitation was established. A comparison on the variation of channeling flow between matrix and crack was made before and after low frequency wave stimulation. The influence of a coefficient in the above empirical relationship on channeling flow rate was analyzed. It was found that the channeling rate (4 – 6 times with the simulation parameters) and permeability of open-type crack in dual porous media had both increased after the impact of low frequency vibration. The stimulation effect decreased gradually with the attenuation of wave. The easier the crack was to open, the stronger the variation of crack permeability was.
- Copyright
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Liming Zheng AU - Jie Fan AU - Lianjin Wang AU - Qingzhong Chu AU - Xinjun Yang PY - 2019/08 DA - 2019/08 TI - Simulation on the Channeling Flow in Porous Media with Open-type Crack under Low Frequency Vibration BT - Proceedings of the 2019 International Conference on Modeling, Simulation and Big Data Analysis (MSBDA 2019) PB - Atlantis Press SP - 112 EP - 118 SN - 2352-538X UR - https://doi.org/10.2991/msbda-19.2019.18 DO - 10.2991/msbda-19.2019.18 ID - Zheng2019/08 ER -