Stimulated reservoir volume (SRV) is the most critical index to represent the hydraulically fractured volume after stimulation. The existing models using microseismic events usually lack a sufficient unified basis on the geometric definition, leading to significant differences in SRV calculation and interpretation.

This paper has generally conducted the classification and the evaluation for the existing models and the newly proposed model. According to three typical grid structures, we firstly divided SRV models into three categories: boundary-based, voxel-based, and density-based. Three typical SRV calculation methods are also proposed based on the alpha shape method, the voxel discretization, and the octree decomposition. Then, we have developed an integrated workflow based on synthetic events to evaluate their performance quantitatively under different fracture configurations and noise ratios. Through a large number of simulated calculations, it is indicated that the density-based method outperforms the other two methods in accuracy, adaptability, and anti-noise ability for complex fracture networks with different configurations. Besides, the engineering application has also its practicability and superiority in generating more refined grid structures. This paper attempts to summarize and evaluate the existing methods and proposes new methods based on the classification. It would provide helpful guidance for developing more superior SRV calculation methods.

增产储层体积（SRV）是代表增产后水力压裂体积的最关键指标。现有的利用微震事件的模型在几何定义上往往缺乏足够统一的依据，导致SRV计算和解释存在显着差异。

本文一般对现有模型和新提出的模型进行了分类和评估。根据三种典型的网格结构，我们首先将 SRV 模型分为三类：基于边界的、基于体素的和基于密度的。基于α形状法、体素离散化和八叉树分解，还提出了三种典型的SRV计算方法。然后，我们开发了一个基于合成事件的集成工作流程，以定量评估它们在不同裂缝配置和噪声比下的性能。通过大量的模拟计算表明，基于密度的方法对不同构型的复杂裂缝网络的精度、适应性和抗噪声能力均优于其他两种方法。除了，工程应用在生成更精细的网格结构方面也具有实用性和优越性。本文试图对现有方法进行总结和评价，并提出基于分类的新方法。它将为开发更优越的 SRV 计算方法提供有益的指导。