Assisted History Matching Using Tempest ENABLE

Hydrocarbon production from maturing basins is constantly declining and new frontiers are not only harder to find but also have complex geology. Operators are continuously looking for opportunities to maximize recovery from existing fields. Subsurface models are instrumental to optimize the recovery from existing fields. Calibrating the models to production data can help characterize the model resulting in more realistic production forecasts. This calibration process is known as history matching whereby uncertain parameters in the numerical reservoir models are iteratively adjusted to create a collection of models which capture the uncertainty. In this webinar, our reservoir engineering expert Usman Aslam presents Emerson’s state-of-the-art machine learning tool Tempest ENABLE that can help ease this time-consuming process and identify multiple calibrated models critical for reliable production forecast.