Combining Deterministic and Probabilistic Approaches in an Improved Volumetric Model With the Aim to Reduce Geological Uncertainties for Accurate Hydrocarbon Reserve Estimation: Case Study in the Rio Del Rey Basin, Cameroon

Abstract

The aim of this study is to improve hydrocarbon reservoir estimation by combining the deterministic and probabilistic approaches in an improved volumetric model with the objective of reducing geological uncertainties and achieving better reserve estimations. The case study was made in the Rio Del Rey basin of Cameroon. To achieve this goal, a mathematical model was built using the volumetric expression of the stock tank original oil in place (STOIIP), the Raymer–Hunt expression of porosity and transit time, and the Simandoux model modified by the Schlumberger expression of water saturation. The application and validation of the proposed model were made through Interactive Petrophysics, Petrel software, and Monte Carlo simulation on Minitab Workspace. The results obtained by a deterministic approach on the investigated area of 2000 m 2 give a total estimated quantity of oil in place of 11897.67 MMbbl, a total estimated quantity of gas in place of 27.79 Bcf, a total estimated quantity of recoverable oil of 3606.28 MMbbl, and a total estimated quantity of recoverable gas of 19.52 Bcf. The probabilistic approach permitted to obtain an estimated quantity of oil in place of 150194141.45 MMbbl. In this study, it appears that the net value added is $288,898,222. This therefore confirms the accuracy of the model and the profitability of the project.