This study investigates the relationship between energy consumption and oil production in petroleum extraction using a Generalized Linear Model (GLM). By analyzing actual production data from a Daqing Oilfield production plant (2021–2024), key energy consumption features such as electricity usage, mechanical extraction, water injection, and transportation were selected to construct a GLM predictive model. Comparisons with Generalized Least Squares (GLS) and linear regression models demonstrated the superior performance of GLM, achieving a coefficient of determination (R2) of 0.884, with mean absolute error (MAE) and mean squared error (MSE) of 0.095 and 0.012, respectively. The study highlights the nonlinear impacts of energy consumption on oil production, offering theoretical insights for optimizing energy use and supporting low-carbon transitions in oilfield operations. Future research will explore interaction effects to enhance model generalizability.
Qian et al. (Tue,) studied this question.