oil and gas reserve prediction method based on Monte Carlo Search + ARIMA algorithm: A case study of the Neuquén basin in South America

Oil and gas reserves are crucial resources for human survival, directly affecting the sustainable development and utilization of future energy. In order to protect the Earth we live on, it is crucial to enhance our understanding and judgment of the trends in oil and gas reserves and to use these resources wisely. To explore new methods for predicting oil and gas reserves, promote sustainable energy development, and provide a theoretical basis for oil and gas exploration and development, this study takes the Neuquén Basin in South America as an example. By combining oil and gas reserve growth data with various geological characteristics and other comprehensive information, a Monte Carlo search + ARIMA algorithm-based method for predicting oil and gas reserves is proposed and applied to the Neuquén Basin for predictive validation. This method analyzes the structural background and divides the basin into structural units to decompose the basin’s reserves into reserves within each structural unit. The reserve growth data from each unit are input into the model, and the parameters required by the model are obtained through Monte Carlo search to produce predictive results. This approach successfully captures the inherent trends of reserve changes and the dynamic features of reserve growth. The method shows significant effectiveness in predicting reserves in the Neuquén Basin, with the predictive model demonstrating high accuracy in fitting.