Modeling porous rock fracturing induced by fluid injection

Modeling porous rock fracturing induced by fluid injection
复制标题

DOI:
10.1016/j.ijrmms.2015.04.003
复制
发表时间:
2015-07
影响因子:
7.2
通讯作者:
T. Heinze;B. Galvan;S. A. Miller
T. Heinze;B. Galvan;S. A. Miller
中科院分区:
工程技术1区
文献类型:
--
作者:
T. Heinze;B. Galvan;S. A. Miller

文献摘要

被引文献

相似文献

在本文中,我们描述并实现了一个理论模型,捕获的物理过程中发生的水力压裂的饱和和不饱和,多孔岩石。该模型基于具有Mohr-Coulomb屈服函数和非关联流动法则的多孔弹塑性流变学,并包括摩擦硬化、凝聚力弱化、损伤和动员的非线性效应。此外,流体注入使用理查德近似描述。我们在交错网格上使用有限差分格式数值实现了该模型,并将模型结果与Stanchits等人(2011)[16]中发表的实验室实验进行了比较。根据Stanchits等人进行的各种实验,我们使用三种不同的实验室配置来比较我们的模型结果和观察结果:(a)排水岩石样品的三轴压缩,(B)低压流体注入排水的临界应力岩石,和(c)高压流体注入饱和岩石样品。我们发现所有情况下,模型和观测之间的良好协议,表明一个适当的制定和实施的主导物理机制的作用。该模型再现了宏观断裂,流体前沿定位,和应力-应变响应曲线的实验观察。从实验室规模的实验匹配观察建立了一个基准和校准模型进行数值模拟实验在更大的,现场规模。
In this paper, we describe and implement a theoretical model that captures the physical processes occurring during hydraulic fracturing of saturated and unsaturated, porous rock. The model is based on a poro-elastic–plastic rheology with a Mohr–Coulomb yield function and unassociated flow rule, and includes frictional hardening, cohesion weakening, damage and mobilized dilatancy effects. In addition, fluid injection is described using the Richard׳s approximation. We numerically implement the model using a finite difference scheme on a staggered grid, and compare the model results with laboratory experiments published in Stanchits et al. (2011) [16]. From various experiments performed by Stanchits et al., we use three different laboratory configurations for comparing our model results and observations: (a) triaxial compression of a drained rock sample, (b) low pressure fluid injection into a drained, critically stressed rock, and (c) high pressure fluid injection into a saturated rock sample. We find good agreement between model and observations for all cases, indicating a proper formulation and implementation of the dominant physical mechanisms acting. The model reproduces experimental observations of macroscopic fracture, fluid front localization, and the stress–strain response curves. Matching observations from laboratory scale experiments establishes a benchmark and a calibrated model for numerically simulating experiments performed at the larger, field scale.