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

Numerical simulation of oil reservoirs is one of the most commonly used methods for
reservoir production prediction, but its accuracy is based on accurate geological modeling …

Production prediction in petroleum industry plays a significant role in designing the strategy
of the exploration and development. However, due to the complex and uncertain …

Traditional decline curve methods have been one of the most widely used methods for
forecasting production in both conventional and unconventional reservoirs. In recent years …

As real production data of a well have an irregular pattern, accurate prediction of oil rate
demands a powerful model to capture the non-linear behavior of data. In addition to the …

Oil production from tight oil reservoirs has become economically feasible because of the
combination of horizontal drilling and multistage hydraulic fracturing. Optimal fracture design …

Monitoring of production rates is essential for reservoir management, history matching, and
production optimization. Traditionally, such information is provided by multiphase flowmeters …

To improve the accuracy of short-term multiphase production forecasts with one-step-ahead
predictions, a Contextual Bi-directional Long Short-Term Memory (C–Bi-LSTM) was …

Reliable hydrocarbon production forecasting is necessary for optimizing field development
and management and for assisting asset teams in making sound business decisions. In …

Prediction of well production from unconventional reservoirs is a complex problem even with
considerable amounts of data especially due to uncertainties and incomplete understanding …