China Petroleum Exploration ›› 2024, Vol. 29 ›› Issue (5): 148-155.DOI: 10.3969/j.issn.1672-7703.2024.05.012

Previous Articles     Next Articles

A new method for the prediction of oil and gas reserve growth based on time series of drilling effectiveness

Wu Xinsong1,Guo Yuling2,Li Meng2   

  1. 1 College of Geosciences, China University of Petroleum-Beijing; 2 Research Institute of Petroleum Exploration and Development, SinoPec
  • Online:2024-09-14 Published:2024-09-14

Abstract: The scientific prediction of growth potential of oil and gas reserves is an important prerequisite and foundation for conducting exploration planning and deployment of oil companies. However, all of the commonly used methods have certain deficiencies in predicting oil and gas reserve growth. For example, the prediction methods based on reserve upgrading often have inadequate conditions for application in areas with low level of exploration; The prediction methods based on extrapolation of exploration results lack the concept of time series, so they are difficult to reveal the change rules of oil and gas reserves with time duration. The prediction methods based on life cycles have no connection with exploration workload, so they are difficult to play an effective guiding role in exploration planning and deployment. By properly integrating the petroleum exploration results and time series in this study, a new reserve growth prediction method based on time series of drilling effectiveness has been proposed, and a highly operational modeling and prediction process have been established. In addition, selection strategies for the targeted models in various reserve increase stages have been put forward. The practical application shows that this prediction method is of great significance in revealing oil and gas reserves discovery rules, evaluating the potential of reserve growth, and guiding the exploration planning and deployment in the exploration block.

Key words: oil and gas reserve growth, prediction method, petroleum exploration planning

CLC Number: