Application of R/S analysis in fracture identification of shale reservoir of the Lower Cambrian Niutitang Formation in northern Guizhou Province, South China

Abstract

Natural fractures not only improve the physical properties of shale reservoirs but also promote the formation of hydraulic fracturing networks. The accurate identification of natural fractures in shale reservoirs is of a great significance to the exploration and development of shale gas. In this paper, the Lower Cambrian Niutitang Formation in Cen'gong block of northern Guizhou Province is taken as the research horizon. A variety of conventional logging parameters are selected to identify the natural fractures in the Niutitang Formation of three shale gas wells in the study area by combining R/S analysis method. Fracture locations can be accurately determined by calculating the second derivatives of lg(R/S) function. Considering the sensitivity of logging parameters to natural fractures, the analytic hierarchy process (AHP) is used to assign the corresponding weight to each logging parameter. A new parameter, fracture development coefficient, is introduced to quantitatively characterize the development degree of natural fractures. The results of R/S analysis are compared with those of core fracture observation and statistics. The results show that R/S analysis has a good effect on shale fracture identification, and the effect of fracture identification of three wells presents the following order: TM‐1 > TX‐1 > CY‐1. There is a positive correlation between fracture development coefficient and fracture linear density, indicating that the larger the fracture development coefficient is, the more developed the shale fractures are. Therefore, the fracture development coefficient can be used to characterize the degree of fracture development. In addition, we also analyze the errors of the identification results of R/S analysis and compare this method with conventional logging method. R/S analysis based on conventional logging is an accurate and efficient fracture identification method, which provides a new idea for the study and quantitative characterization of the natural fractures in shale reservoirs.