Volume 35: CCUS Technologies for the Carbon Neutrality: Part III

Ridge Regression Method for Screening CO2 Flooding Reservoir in Daqing Oilfield Song Deng, Bihua Xian, Hongda Hao, Jirui Hou, Xiaopeng Yan, Jiangshuai Wang, Zheng Tang

Abstract

In recent years, the screening criteria for an ultra-low permeability reservoir in the periphery of Daqing Oilfield are not detailed, which leads to the problem of inapplicability of CO2 flooding. In this paper, a new screening criterion suitable for CO2 flooding in this ultra-low permeability reservoir is established by using the ridge regression method. Six factors including effective thickness, oil saturation, formation temperature, formation pressure, average permeability and gas injection rate were selected based on the results of CMG numerical simulation, and a total of 30 groups of sensitive factor analysis data were carried out. Then, a ridge regression method for CO2 flooding was established by using the t-value test for the CO2 flooding potential of an extra-low permeability reservoir in the periphery of Daqing Oilfield. Finally, CMG numerical simulation is used to evaluate the effect of increasing oil production of potential well groups. The ridge regression results show that the oil recovery is sensitive with effective thickness, oil saturation, formation temperature, formation pressure, average permeability and gas injection rate, and their index weights are 0.37, 0.21, 0.15, 0.12, 0.09 and 0.06, respectively. Then, the critical t-value are calculated as 0.5 according to the weights, which means that a well group is potential if its t-value is above 0.5. According to the above screening criteria, a total of 25 well group in the block are evaluated, and 18 groups are screened as the potential for CO2 flooding, which accounts for 72% of the block. The CMG simulation results show that the screened well groups contribute an average oil production of 0.36×104 t per year, and the annual oil change ratio is more than 0.4, which represents an excellent CO2 flooding efficiency for this block. The innovation of this study is to use the ridge regression method to evaluate the influence factors on oil recovery of CO2 flooding, and the calculate results are unique using the regression model. And a screening criterion for CO2 flooding are then established for this extra-low permeability reservoir.

Keywords ridge regression, CO2 flooding, numerical simulation, main control factors