A machine learning approach to reservoir characterization
Abstract
Nowadays, one of the most critical engineering problems in optimized reservoir development is Petroleum Reservoir description and characterization. There have been many reports on successful applications of Fuzzy Inference System (FIS) and Ensemble learning method in reservoir characterization. In this study, we propose an ensemble of multi-model regression framework based on FIS architecture to tackle the challenge of permeability prediction using logs data properties. During the research, the capability of the ensemble model when being tested in well log properties, which is practical data of Oligocene geological types from Cuu Long basin, is also demonstrated and these will finally be shown in section IV-RESULTS as graphs. Furthermore, empirical results also indicate that our proposed algorithm framework is efficient and has the significant improvement compared to each existing standard single model.