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Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review
Mathematical modeling and simulation methods are important tools in studying various
processes in science and engineering. In the current review, we focus on the applications of …
processes in science and engineering. In the current review, we focus on the applications of …
Application of artificial intelligence techniques in the petroleum industry: a review
In recent years, artificial intelligence (AI) has been widely applied to optimization problems
in the petroleum exploration and production industry. This survey offers a detailed literature …
in the petroleum exploration and production industry. This survey offers a detailed literature …
Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir
Multiphase flow meters (MPFMs) are utilized to provide quick and accurate well test data in
numerous numbers of oil production applications like those in remote or unmanned …
numerous numbers of oil production applications like those in remote or unmanned …
Performance forecasting for polymer flooding in heavy oil reservoirs
As a supply for future fuel and energy demand, 95% of the bitumen deposits in North
America are expected to become a major source. The Steam Assisted Gravity Drainage …
America are expected to become a major source. The Steam Assisted Gravity Drainage …
Prediction carbon dioxide solubility in presence of various ionic liquids using computational intelligence approaches
A Baghban, MA Ahmadi, BH Shahraki - The Journal of supercritical fluids, 2015 - Elsevier
Ionic liquids (ILs) are highly promising for industrial applications such as design and
development of gas sweetening processes. For a safe and economical design, prediction of …
development of gas sweetening processes. For a safe and economical design, prediction of …
Hybrid machine learning algorithms to predict condensate viscosity in the near wellbore regions of gas condensate reservoirs
ARB Abad, S Mousavi, N Mohamadian… - Journal of Natural Gas …, 2021 - Elsevier
Gas condensate reservoirs display unique phase behavior and are highly sensitive to
reservoir pressure changes. This makes it difficult to determine their PVT characteristics …
reservoir pressure changes. This makes it difficult to determine their PVT characteristics …
Neural network-based fuel consumption estimation for container ships in Korea
Due to the outstanding strength of advanced machine-learning techniques, they have
become increasingly common in predictive studies in recent years, particularly in predicting …
become increasingly common in predictive studies in recent years, particularly in predicting …
[HTML][HTML] Determination of oil well production performance using artificial neural network (ANN) linked to the particle swarm optimization (PSO) tool
Greater complexity is involved in the transient pressure analysis of horizontal oil wells in
contrast to vertical wells, as the horizontal wells are considered entirely horizontal and …
contrast to vertical wells, as the horizontal wells are considered entirely horizontal and …
Optimization of type-2 fuzzy weights in backpropagation learning for neural networks using GAs and PSO
In this paper the optimization of type-2 fuzzy inference systems using genetic algorithms
(GAs) and particle swarm optimization (PSO) is presented. The optimized type-2 fuzzy …
(GAs) and particle swarm optimization (PSO) is presented. The optimized type-2 fuzzy …
Prediction breakthrough time of water coning in the fractured reservoirs by implementing low parameter support vector machine approach
Owing to water coning, water flows into the production wellbore from below the perforated
channels and normally causes several technical issues in wellbore and surface production …
channels and normally causes several technical issues in wellbore and surface production …