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Using Embedded Discrete Fracture Model (EDFM) and Microseismic Monitoring Data to Characterize the Complex Hydraulic Fracture Networks

机译:使用嵌入式离散裂缝模型(EDFM)和微震监测数据来表征复杂的液压骨折网络

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Microseismic monitoring is widely used in petroleum industry to image the created hydraulic fracture networks. In this technology, the recorded seismic information during hydraulic stimulation is analyzed to locate the rock deformation and to characterize the failure mechanism. Over the last few years, various approaches have been proposed to calibrate the corresponding discrete hydraulic fracture networks (DFN) with the measured microseismic pattern to study long-term reservoir production. However, due to complexity of the problem and the limitations of reservoir simulators, the direct application of such complex DFNs has been highly restricted. Instead, the spatial extent of microseismic cloud has been often used as a direct measure to assess the efficiency of the treatment. Such interpretation techniques without further modeling and simulations of hydrocarbon production and pressure drainage fail to represent an accurate view of connectivity and complexity of the fracture system. In this paper, we present a recently developed Embedded Discrete Fracture Model (EDFM) to capture the realistic geometry of fractures. In EDFM, each fracture plane is embedded inside the matrix gird and is discretized by the cell boundaries. Using EDFM, we study a series of reservoir simulation examples, in which the complex hydraulic fracture networks calibrated by microseismic monitoring are considered. We investigate different DFN realizations in both planar and complex fracture configurations. We explore the impact of network geometry and fractures properties on the overall performance of the reservoir. The simulation results indicate that the efficiency of well treatment is strongly controlled by fractures connectivity and the distribution of conductivity within the network. When the spatial extent of microseismic cloud is fixed, by changing the degree of connectivity, a wide range of production response is observed. For instance, when the interconnection between the fracture planes is weak, the observed drainage volume is much smaller compared to the one predicted by microseismic monitoring. On the other hand, taking into account the role of aseismic deformations (such as tensile openings) improves the cumulative production. Even in the case of bi-wing hydraulic fracture planes, it is displayed that neglecting the effect of small-scale fissure openings may lead to underestimation of stimulation efficiency. Although the microseismic monitoring depicts a preliminary view of the induced fracture network, more information can be obtained through numerical simulation of fluid transport inside the facture system. Modeling the complex DFNs shows that an accurate production forecast can be achieved using simulation models rather than direct application of total stimulated reservoir volume. Integrating the Embedded Discrete Fracture Model (EDFM) and the microseismic data provides a robust and efficient approach to investigate different DFN realizations.
机译:微震监测广泛应用于石油工业,以映像产生的液压骨折网络。在该技术中,分析了液压刺激期间的记录的地震信息以定位岩石变形并表征失效机制。在过去几年中,已经提出了各种方法来校准相应的离散液压骨折网络(DFN),以测量的微震模式来研究长期储层生产。然而,由于问题的复杂性和储层模拟器的局限性,这种复杂的DFN的直接应用已经受到高度限制。相反,微震云的空间程度通常被用作评估治疗效率的直接措施。这种不具有进一步建模和烃生产和压力排水的诠释的解释技术不能代表裂缝系统的连接性和复杂性的准确观点。在本文中,我们展示了最近开发的嵌入离散裂缝模型(EDFM)以捕获裂缝的逼真几何形状。在EDFM中,每个裂缝平面嵌入矩阵围绕内部,由细胞边界离散化。使用EDFM,我们研究了一系列储层仿真实例,其中考虑了通过微震监测校准的复杂液压断裂网络。我们调查平面和复杂骨折配置中的不同DFN实现。我们探讨了网络几何形状和裂缝性能对水库整体性能的影响。仿真结果表明,通过裂缝连通性和网络电导率分布强烈控制井处理的效率。当微震云的空间程度固定时,通过改变连接程度,观察到各种各样的生产响应。例如,当断裂架之间的互连较弱时,与通过微震监测预测的人相比,观察到的排水量要小得多。另一方面,考虑到抗震变形的作用(例如拉伸开口)改善了累积的生产。即使在双翼液压骨折平面的情况下,展示忽略小垢裂缝开口的效果也可能导致低估刺激效率。尽管微震监测描绘了诱导骨折网络的初步视图,但是可以通过物体系统内的流体输送的数值模拟来获得更多信息。建模复杂的DFN显示,可以使用模拟模型来实现准确的生产预测,而不是直接应用总刺激的储存量。整合嵌入的离散裂缝模型(EDFM)和微震数据提供了一种强大而有效的方法来调查不同的DFN实现。

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