基于一个增强的三维离散断裂网络模型的基础上,通过断裂岩石质量进行流体流动的实验和数值研究
Na Huang1, Xiaoying Wang1, Yujing Jiang2
1College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China.
Journal of contaminant hydrology
|April 24, 2025
概括
一个增强的离散断裂网络 (DFN) 模型准确地模拟了断裂中的流体流动,性能优于传统模型. 这种改进的DFN方法最大限度地减少了透率估计的错误,这对于理解破碎岩石中的流体运输至关重要.
科学领域:
- 地质科学 地质科学
- 水文地质学 水文地质学
- 计算力学 计算力学 计算力学
背景情况:
- 岩石断裂中的液体流对于地下资源管理和环境评估至关重要.
- 传统的离散断裂网络 (DFN) 模型经常简化复杂的断裂几何形状,导致流量预测的不准确性.
- 了解表面粗度和孔径异质性对流体流动的影响对于现实的建模至关重要.
研究的目的:
- 开发和验证一个增强的DFN模型,准确地表示粗壁断裂中的3D空隙几何.
- 为了比较增强的DFN模型与传统的DFN模型和实验流量测试的准确性.
- 调查非线性流动的出现,并提出一个对等透率估计的模型.
主要方法:
- 在不同的液压梯度下,在3D打印的DFN样本上进行了实验性流体流量测试.
- 使用增强的DFN模型 (解决纳维埃-斯托克斯方程) 和传统的DFN模型 (解决雷诺兹方程) 进行了数值模拟.
- 通过将模拟结果与实验数据进行比较,证实了模型的有效性,随后进行了数值调查,以改进透性计算.
主要成果:
- 增强的DFN模型准确地捕捉了受表面粗度和光圈异质性影响的非线性流动行为.
- 传统的DFN模型高估了透率高达82%,而增强的DFN模型显示的误差明显低于5.3%.
- 非线性流动开始的临界液压梯度随着断裂数量和表面粗度的增加而减少.
结论:
- 增强的DFN模型提供了更现实的断裂表示,并产生了更准确的流体流量和透率估计.
- 该研究强调了传统的DFN模型在预测通过复杂的断裂网络流量的局限性.
- 一个拟议的模型可以通过纳维埃-斯托克斯方程和雷诺兹方程计算的等效透率进行直接比较,帮助在破裂介质中进行实际评估.
更多相关视频
10:06Microfluidic Fabrication Techniques for High-Pressure Testing of Microscale Supercritical CO2 Foam Transport in Fractured Unconventional Reservoirs
Published on: July 2, 2020
6.6K
10:27A Uniaxial Compression Experiment with CO2-Bearing Coal Using a Visualized and Constant-Volume Gas-Solid Coupling Test System
Published on: June 12, 2019
8.6K
相关概念视频
01:30Typical Model Studies
155
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
155
01:21Design Example: Creating a Hydraulic Model of a Dam Spillway
79
Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
79
01:24Rapidly Varying Flow
32
Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
32