Data-Driven Modeling Approach to Predict the Recovery Performance of Low-Salinity Waterfloods

This publication has 94 references indexed in Scilit:

• Artificial neural networks in medical diagnosis
  Journal of Applied Biomedicine, 2013
• ANFIS-based approach for predicting sediment transport in clean sewer
  Applied Soft Computing, 2012
• Neural network based unified particle swarm optimization for prediction of asphaltene precipitation
  Fluid Phase Equilibria, 2012
• Neural computing models for prediction of permeability coefficient of coarse-grained soils
  Neural Computing and Applications, 2011
• Performance Prediction of Waterflooding in Western Canadian Heavy Oil Reservoirs Using Artificial Neural Network
  Energy & Fuels, 2010
• Smart Water as Wettability Modifier in Carbonate and Sandstone: A Discussion of Similarities/Differences in the Chemical Mechanisms
  Energy & Fuels, 2009
• Development of a neural fuzzy system for advanced prediction of dew point pressure in gas condensate reservoirs
  Fuel Processing Technology, 2009
• Biotechnology in petroleum recovery: The microbial EOR
  Progress in Energy and Combustion Science, 2008
• A neuro‐fuzzy modeling tool to estimate fluvial nutrient loads in watersheds under time‐varying human impact
  Limnology and Oceanography: Methods, 2004
• Training feedforward networks with the Marquardt algorithm
  IEEE Transactions on Neural Networks, 1994