Seismic attribute selection method based on rock physical quantity models

The seismic attribute technology is experiencing rapid development, and the attributes are becoming rich in types. It is very necessary to improve the attribute selection methods accordingly. Currently, the seismic attribute selection technologies mainly include three categories: expert experience method, mathematical analysis method, and seismic forward modeling simulation method. They respectively have the shortcomings of strong subjectivity, heavy reliance on known sample points, lack of clear geological significance, and large computational volume. Moreover, attributes have barely used directly to analyze the characteristics of the changes in reservoirs’ physical properties. Especially in the case of tight sandstone oil and gas reservoirs, the maximum porosity is 8%, and it is difficult to distinguish the reservoir from the surrounding rocks. In addition, there are a few exploration wells in the area. Therefore, this paper proposed a method to establish a rock physics model that conforms to the characteristics of tight sandstone reservoirs for optimizing attributes. The method tested different porosity and water saturation parameters through the established rock physics model, performed forward modeling on the model, and obtained seismic attributes. These attributes were systematically clustered using Pearson correlation coefficients, and one or two attributes with the absolute value of the correlation coefficient in the reservoirs’ physical property parameters being the largest in each category were selected for optimization. This method effectively characterized the changes in the physical properties of the target layer in the study area. The method was applied to the H area, and a rock physics model of the tight reservoir in the H area was established, with high-porosity sand bodies identified. The results show that the seismic attributes selected by this method well reflect the changes in reservoir porosity.