Nikos Varotsis

发表

Machine Learning Methods to Speed up Compositional Reservoir Simulation

Vassilis Gaganis, Nikos Varotsis, V. Gaganis, 2012 .

An integrated approach for rapid phase behavior calculations in compositional modeling

Vassilis Gaganis, Nikos Varotsis, V. Gaganis, 2014 .

Application of Artificial Neural Networks to Downhole Fluid Analysis

Vassilis Gaganis, Chengli Dong, Peter S. Hegeman, 2007 .

Quality Assurance Tool for PVT Simulator Predictions

Vassilis Gaganis, Nikos Varotsis, J. Nighswander, 2001 .

An accurate method to generate composite PVT data for black oil simulation

Vassilis Gaganis, Nikos Varotsis, Elias Kourlianski, 2017 .

Identification of the Compositional Path Followed During Reservoir Simulation Improves the Accuracy and Accelerates the Phase Behavior Calculations

Vassilis Gaganis, Nikos Varotsis, Steve Todman, 2016 .

A general framework of model functions for rapid and robust solution of Rachford–Rice type of equations

Vassilis Gaganis, Nikos Varotsis, V. Gaganis, 2012 .

An improved BIP matrix decomposition method for reduced flash calculations

Vassilis Gaganis, Nikos Varotsis, V. Gaganis, 2013 .

Solubility measurements of (methane + ethane + propane) mixtures in the aqueous phase with gas hydrates under vapour unsaturated conditions

Nikos Varotsis, N. Varotsis, D. Marinakis, 2013 .

Modelling gas hydrate thermodynamic behaviour: theoretical basis and computational methods

Nikos Varotsis, N. Varotsis, D. Avlonitis, 1996 .

Application of Artificial Neural Networks to Downhole Fluid Analysis

Vassilis Gaganis, Chengli Dong, Peter S. Hegeman, 2009 .