Recent technological innovation in drilling and completion allowed for achieving complex multilateral wells with significantly higher recovery rates at marginal additional costs. These advanced installations resulted in improved reservoir contact, ultimate recovery, zonal isolation and pressure drawdown control, and management of water/gas breakthrough. Equipped with state-of-the-art instrumentation and control systems, smart wells provide continuous flowrate and pressure data streams in space and time. One major component of these completions is the inflow control valve (ICV) which regulates the flow of reservoir fluids from different branches.
Numerical reservoir simulations represent the standard approach to analyzing oil and gas fields and deciding on the optimal ICV settings. However, using a solver, e.g. genetic algorithm (GA), to optimize over numerical simulators involves many computationally expensive function evaluations. Hence, surrogate-based optimization (SBO) is commonly used to efficiently find the optimal decision variables.
Explore the docs »
Report Bug
·
Request Feature
Distributed under the MIT License. See LICENSE for more information.
Name: @MJAljubran - m.j.aljubran@gmail.com
Project Link: https://github.com/aljubrmj/ENERGY291-Final-Project