Using the Multiple Linear Regression Method for CO2 Flooding Evaluation in the Daqing Oilfield - Wang, Zhenhua; Hou, Jirui; Hao, Hongda; Wang, Cheng; Wang, Likun (Frontiers in Energy Research, 2022)
In order to better improve the CO2 flooding and burial efficiency, a reference standard for screening CO2 flooding reservoirs suitable for Daqing Oilfield should be established, and the influencing indexes of CO2 flooding can be divided into three categories : geological factors, fluid properties and development indexes. Ranking according to the importance of multiple factors, the evaluation index system is established and the hierarchical structure is constructed. In the process of establishing the evaluation index system, the human subjective analysis error is relatively large, especially in the fitting curves drawn by different analysts are likely to be different. In this paper, combined with the geological characteristics of block Bei14 in Daqing Oilfield, a typical CMG model is established. 15 factors in the 72 models are used as independent variables, and recovery factor is used as dependent variable for multiple linear regression calculation, furthermore sensitivity tests are performed based on the magnitude of the absolute value of the significance indicator t in the calculated results. When analyzing the calculation results of the multiple linear regression model, as long as the model and data used are the same, a unique result can be calculated by standard statistical methods. On the basis of mathematical understanding of multi-factors on CO2 flooding effect, the screening standard evaluation system score results are corresponding to the practical production history of the oilfield. The oil saturation around the high score well group decreases significantly, and the cumulative production is generally higher than that of the low score well group. The calculation results of block Bei 14 show that the evaluation value of 76% well groups is above 0.50, and the annual oil exchange ratio of 72% well groups is about 40%, more than 70% well groups are suitable for CO2 flooding to improve oil recovery. Therefore, CO2 flooding has a good application prospect in Daqing Oilfield, and multiple linear regression evaluation method can provide effective guidance suggestions in the development process of Daqing Oilfield.