Characterization and Modelling of Multiscale Natural Fractures in Shale Reservoirs: A Case Study from a Block in the Southern Sichuan Basin. (7th October 2022) - Gai, Shaohua; Jia, Ailin; Wei, Yunsheng; Liu, Ruohan
Abstract : Natural fractures are vital to the efficiencies of drilling and completion operation. The purpose of this paper is to characterize and model multiscale natural fractures in shale reservoirs. Based on the seismic and log responses, as well as outcrop and core observations, we divide natural fractures into Macro, Meso, and Micro three scales. Macroscale fractures are the faults picked directly in seismic profiles. Also, Mesoscale fractures are the natural fracture corridors analyzed by ant tracking technique in 3D seismic data. Furthermore, Microscale fractures are the fractures observed in imaging logs and cores. The fracture intensity is obtained by the correlation between ant tracking attributes and fracture density in borehole. The fracture aperture, dip, and azimuth are three main parameters, which are recognized by the loggings and cores. Stochastic modelling is applied to factures. We find that faults identified by the ant tracking result are excellent in line with Macroscale faults interpreted directly from seismic data. In addition, Mesoscale fractures are indicated from the ant tracking result, which are in accord with breakpoint in the well and in keeping with tectonic history of the area. Such high consistency indicates the ant tracking result is reliable. Moreover, image logs and cores reveal that it mainly develops high angle natural fractures and the fracture aperture is about 1 mm. The fracture strike includes three sets (NNW-SSE, NE-SW, and NNE-SSW). The distribution of the natural fractures in discrete fracture network (DFN) system is distributed controlled by the ant tracking result. Comparing the histograms of DFN results and fracture characterized by seismic and logging responses, as well as outcrop and core observation, it suggests that the major part of the observed natural fractures is retained into our DFN model.