A fracture identification method for low-permeability sandstone based on R/S analysis and the finite difference method: A case study from the Chang 6 reservoir in Huaqing oilfield, Ordos Basin

Abstract

Low-permeability reservoirs are characterized by poor physical properties, strong heterogeneity and natural fractures. Accurate identification of the fracture distribution is of great significance for the exploration and development of low-permeability reservoirs. Field outcrop, core and imaging log analyses show that stratabound vertical and high-angle structural fractures are the main types of fractures in the Chang 6 formation in the Huaqing oilfield. The fracture orientations include NE-SW, NNE-SSW, NW-SE, and NNW-SSE. The NE-SE-oriented fractures formed in the Himalayan stage, while the NW-SE fractures formed in the Yanshan period, and the other fractures derived from the fracturing in the Yanshan period during the Himalayan tectonic activity. The traditional rescaled range (R/S) analysis method is upgraded by introducing the finite difference (FD) method in this research, and the newly proposed method is called the R/S-FD method. Core data show that the R/S-FD method can accurately recognize vertical fractures and high-angle fractures. By comparing the fracture development section on the imaging log, it is found that fractures discrimination parameter F has a good linear relationship with both the fracture linear density and the fracture surface density. This method is verified by dynamic data (water injection profiles) and static data (image logging), and the results show that the recognition error is eliminated when the lower limit of F is 0.5, resulting in a crack identification accuracy of 76.9%. Combining the R/S and finite difference methods reduces the artificial recognition error of the traditional R/S method, and the recognition process is automated and intelligent. The R/S-FD method can be used in combination with multiple logging curves. A high fracture recognition accuracy could be accomplished by using this proposed method with only conventional logging curves, of great practical significance to some low-permeability oilfields that lack image logging data.