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Neural network based unified particle swarm optimization for prediction of asphaltene precipitation
Abstract The precipitation and deposition of crude oil polar fractions such as asphaltenes in petroleum reservoirs reduce considerably the rock permeability and the oil recovery. In the presentExpand
Adsorption of Novel Nonionic Surfactant and Particles Mixture in Carbonates: Enhanced Oil Recovery Implication
Over 40% of the current world conventional oil production comes from carbonate reservoirs, dominantly mature and declining giant oilfields. After primary and secondary oil production stages usingExpand
Nonionic Surfactant for Enhanced Oil Recovery from Carbonates: Adsorption Kinetics and Equilibrium
Around 40% of the current world conventional oil production comes from carbonate reservoirs, dominantly mature and declining giant oilfields. Tertiary oil production methods as part of an EnhancedExpand
Prediction of Condensate-to-Gas Ratio for Retrograde Gas Condensate Reservoirs Using Artificial Neural Network with Particle Swarm Optimization
Condensate-to-gas ratio (CGR) plays an important role in sales potential assessment of both gas and liquid, design of required surface processing facilities, reservoir characterization, and modelingExpand
Connectionist model predicts the porosity and permeability of petroleum reservoirs by means of petro-physical logs: Application of artificial intelligence
Abstract In this paper, a new approach based on artificial intelligence concept is evolved to monitor the permeability and porosity of petroleum reservoirs by means of petro-physical logs at variousExpand
New approach for prediction of asphaltene precipitation due to natural depletion by using evolutionary algorithm concept
Abstract Asphaltene precipitation affects enhanced oil recovery processes through the mechanism of wettability alteration and blockage. Asphaltene precipitation is very sensitive to the reservoirExpand
Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir
TLDR
Based on a real case of MPFM, a new method for oil rate prediction of wells base on Fuzzy logic, Artificial Neural Networks (ANN) and Imperialist Competitive Algorithm is presented, proving the effectiveness, robustness and compatibility of the ICA-ANN model. Expand
A LSSVM approach for determining well placement and conning phenomena in horizontal wells
Abstract Understanding the time of water/gas breakthrough has a prominent role in cost effective oil production, improve oil recovery and extension the reservoir production time. The importance liesExpand
Connectionist technique estimates H2S solubility in ionic liquids through a low parameter approach
Abstract Adequate knowledge of solubility of acid gases in ionic liquids (ILs) at different thermodynamic conditions is of great importance in the context of gas processing and carbon sequestration.Expand
Experimental investigation of adsorption of a new nonionic surfactant on carbonate minerals
Abstract The adsorption of surfactants on reservoir rock has been known from early studies on surfactant flooding for this purpose, Adsorption mechanism of new nonionic surfactant on carbonate rockExpand
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