The application of machine learning (ML) tools and data-driven modeling became a standard approach for solving many problems in exploration geology and contributed to the discovery of new reservoirs. This study explores an application of machine learning ensemble methods – random forest (RF) and extreme gradient boosting (XGBoost) to derive porosity and saturation type (gas/water) in multihorizon...
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.