Abstract Machine Learning (ML) has demonstrated its immense contribution to reservoir
engineering, particularly reservoir simulation. The coupling of ML and metaheuristic …

Tackling emissions from hydrocarbon production is a necessity because hydrocarbon
production will last for a prolonged time. As a popular hydrocarbon production method …

This paper proposes a novel parametrization technique for deviated and horizontal wells
and investigates the potential of combining the Fast Marching Method (FMM) with Particle …

Well placement optimization refers to the identification of optimal locations for wells
(producers and injectors) to maximize net present value (NPV) and oil recovery. It is a …

A data-driven automatic well planner procedure is implemented to develop complex well
trajectories by efficiently adapting to near-well reservoir properties and geometry. The …

In this work we apply a recently developed machine learning routine for automatic well
planning to simplify well parameterization in reservoir simulation models. This reduced …

Operational decision-making during drilling for hydrocarbons or geothermal energy is
challenging due to the complex nature of the process. Many of the times, these decisions …