This book presents unique features of the adaptive modeling
approach based on new machine learning algorithms for petroleum
exploration, development, and production. The adaptive approach
helps simulation engineers and geoscientists to create adequate
geological and hydrodynamic models. This approach is proven to be a
real alternative to traditional techniques, such as deterministic
modeling. Currently, machine-learning algorithms grow in popularity
because they provide consistency, predictiveness, and convenience.
The primary purpose of this book is to describe the theoretical
state of the adaptive approach and show some examples of its
implementation in simulation and forecasting different reservoir
processes.
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