An applied machine learning approach to production forecast for basement formation - Bach Ho field

Oil production forecast is a major challenge in the oil and gas industry. Simulation model and prediction results play an important role in field operation and management. Currently, production forecast problems are resolved mainly by using pure traditional prediction methods. Generally, production forecast by dynamic simulations does not provide reliable results in case where a lot of uncertain parameters remain when the dynamic model is constructed.