USI provides a new forecasting application that incorporates a production analysis system using neural network models learning from pre-run simulation results for the evaluation of petroleum reservoir performance. Our Science-Based Forecaster (SBF) software implements a physics-based methodology for type well matching, optimization in well spacing and timing, as well as maximizing efficiency and operational performance.
USI provides a new forecasting application that incorporates a production analysis system using neural network models learning from pre-run simulation results for the evaluation of petroleum reservoir performance. Our Science-Based Forecaster (SBF) software implements a physics-based methodology for type well matching, optimization in well spacing and timing, as well as maximizing efficiency and operational performance.