关键词: 水力压裂, 微地震事件点, 储层改造体积, 面元算法, 三维狄洛尼三角剖分算法, 最小体积覆盖椭球算法

Abstract: The microseismic event location-fitted computation of stimulated reservoir volume (SRV) was studied. The current methods available for computing microseismic event location-based SRV are not accurate because of the impact of noise. A three-dimensional hydraulic fracturing model was employed to simulate the development of principal fractures and the diffusion of fracturing fluids into the matrix. The existence of induced microseismic events was then determined by the existence of fractures and critical pressure in the pore space. Consequently, an SRV value was obtained by the hydraulic fracturing simulation. The SRV was then computed with different algorithms by fitting the point set of microseismic events, both with and without the abnormal points removed, and the resulting SRV values were compared with the SRV value obtained from the hydraulic fracturing simulation. The results showed that the removal of abnormal points reduced the impact of noise on the SRV values computed by all three microseismic event location-fitted algorithms. More specifically, the bin algorithm, although conservative, yielded an SRV value similar to that obtained by the hydraulic fracturing simulation and exhibited good stability and anti-noise characteristics. In contrast, both the three-dimensional Delaunay triangulation algorithm and minimum volume enclosing ellipsoid algorithm yielded SRV values quite different from the SRV value obtained by the hydraulic fracturing simulation; however, these algorithms were capable of clearly identifying the active zone of microseismic events mathematically and providing the geometric structure of SRV in a more detailed and quantifiable manner.

Key words: hydraulic fracturing, microseismic event location, stimulated reservoir volume (SRV), BIN algorithm, three-dimensional Delaunay triangulation algorithm, minimum volume enclosing ellipsoid algorithm