A Data-Driven Surrogate Framework for Economic Optimization of Thin Oil Rim Developments: A Comprehensive Methodological Review and Niger Delta Application

• Yetunde M. ALADEITAN

  Author

• Damilola V. ABRAHAM

  Author

Reservoirs with a thin oil rim where the hydrocarbon column is in danger of being breached by an active aquifer and gas cap is a long term optimization problem. Sour gas and water coning significantly impact recovery profits, and uncertainty underground makes development decisions challenging. The large number of scenarios and uncertainties involved in a robust field development plan cannot be sufficiently addressed through the traditional simulation-intensive processes. In this paper, a framework of the Surrogate Reservoir Model (SRM) is proposed and consists of three elements: the statistical design, the machine learning proxy modeling, and the economic analysis. The methodology includes the sequential experimental design for parameter screening, high-dimensional response surface and machine learning for proxy construction and Monte Carlo forecasting for probabilistic predictions. For a case study in the Niger delta, the key uncertainties identified are the permeability anisotropy, oil column height, and horizontal permeability. Seven development options have been investigated using a probabilistic analysis and it is found that the one with the greatest technical recovery is not economically best. The framework was able to enable economics-based decision making, such as simultaneous oil and gas production which show the best value of Net Present Value and Internal Rate of Return.

• FJET_21_92_92

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