Prediction of sand production onset in petroleum reservoirs using a reliable classification approach
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Amir H. Mohammadi | Amir H. Mohammadi | Farhad Gharagheizi | Amin Shokrollahi | Milad Arabloo | F. Gharagheizi | A. Shokrollahi | M. Arabloo | A. Mohammadi
[1] Amin Shokrollahi,et al. State-of-the-Art Least Square Support Vector Machine Application for Accurate Determination of Natural Gas Viscosity , 2014 .
[2] Alireza Nouri,et al. Review of Sand Production Prediction Models , 2013 .
[3] A Bazzani,et al. An SVM classifier to separate false signals from microcalcifications in digital mammograms , 2001, Physics in medicine and biology.
[4] Giovanni Luca Christian Masala,et al. A comparative study of K-Nearest Neighbour, Support Vector Machine and Multi-Layer Perceptron for Thalassemia screening , 2003 .
[5] Dirk Cattrysse,et al. Cost estimation for sheet metal parts using multiple regression and artificial neural networks: A case study , 2008 .
[6] Johan A. K. Suykens,et al. Least Squares Support Vector Machines , 2002 .
[7] Amin Shokrollahi,et al. Evolving an accurate model based on machine learning approach for prediction of dew-point pressure in gas condensate reservoirs , 2014 .
[8] Farhad Gharagheizi,et al. Gas Hydrate Phase Equilibrium in Porous Media: Mathematical Modeling and Correlation , 2012 .
[9] Amir H. Mohammadi,et al. Efficient estimation of natural gas compressibility factor using a rigorous method , 2014 .
[10] Ridha Gharbi,et al. Neural Network Model for Estimating The PVT Properties of Middle East Crude Oils , 1996 .
[11] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[12] M. Dusseault,et al. Sand-Production Simulation in Heavy-Oil Reservoirs , 2004 .
[13] Alireza Bahadori,et al. Prediction of natural gas flow through chokes using support vector machine algorithm , 2014 .
[14] Michel Minoux,et al. Mathematical Programming , 1986 .
[15] Christopher D. Brown,et al. Receiver operating characteristics curves and related decision measures: A tutorial , 2006 .
[16] Davut Hanbay,et al. Application of least square support vector machines in the prediction of aeration performance of plunging overfall jets from weirs , 2009, Expert Syst. Appl..
[17] W. Poquioma,et al. The Diagnosis, Well Damage Evaluation and Critical Drawdown Calculations of Sand Production Problems in the Ceuta Field, Lake Maracaibo, Venezuela , 1999 .
[18] Tung-Shou Chen,et al. A Novel Knowledge Protection Technique Base on Support Vector Machine Model for Anti-classification , 2011 .
[19] A. Bahadori,et al. Prediction of the aqueous solubility of BaSO4 using pitzer ion interaction model and LSSVM algorithm , 2014 .
[20] F. Tay,et al. Application of support vector machines in financial time series forecasting , 2001 .
[21] Millaray Curilem,et al. Neural Networks and Support Vector Machine Models Applied to Energy Consumption Optimization in Semiautogeneous Grinding , 2011 .
[22] Amir H. Mohammadi,et al. Predicting the Hydrate Stability Zones of Natural Gases Using Artificial Neural Networks , 2007 .
[23] B. Matthews. Comparison of the predicted and observed secondary structure of T4 phage lysozyme. , 1975, Biochimica et biophysica acta.
[24] Leo Breiman,et al. Classification and Regression Trees , 1984 .
[25] Kyung-shik Shin,et al. An application of support vector machines in bankruptcy prediction model , 2005, Expert Syst. Appl..
[26] F. J. Santarelli,et al. Basin scale rock mechanics: Field observations of sand production , 1994 .
[27] Farhad Gharagheizi,et al. Intelligent model for prediction of CO2 – Reservoir oil minimum miscibility pressure , 2013 .
[28] S. M. Willson,et al. New Model for Predicting the Rate of Sand Production , 2002 .
[29] Johan A. K. Suykens,et al. LS-SVMlab : a MATLAB / C toolbox for Least Squares Support Vector Machines , 2007 .
[30] Richard Wan,et al. An integrated modular approach to modeling sand production and cavity growth with emphasis on the multiphase and 3D effects , 2006 .
[31] Farhad Gharagheizi,et al. Toward a predictive model for estimating dew point pressure in gas condensate systems , 2013 .
[32] J. Hanley,et al. The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.
[33] Elif Derya íbeyli. Least squares support vector machine employing model-based methods coefficients for analysis of EEG signals , 2010 .
[34] Amir H. Mohammadi,et al. Application of constrained multi-variable search methods for prediction of PVT properties of crude oil systems , 2014 .
[35] R. Fletcher. Practical Methods of Optimization , 1988 .
[36] Johan A. K. Suykens,et al. Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.
[37] J. Hanley,et al. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. , 1983, Radiology.
[38] Ghasem Zargar,et al. A New Approach to Sand Production Onset Prediction Using Artificial Neural Networks , 2011 .
[39] Mazen Y. Kanj,et al. Realistic Sanding Predictions: A Neural Approach , 1999 .
[40] Reza Chamkalani,et al. SOFT COMPUTING METHOD FOR PREDICTION OF CO2 CORROSION IN FLOW LINES BASED ON NEURAL NETWORK APPROACH , 2013 .
[41] Nobuo Morita,et al. Parametric study of sand production prediction: analytical approach. , 1989 .
[42] Mahmood Amani,et al. Implementation of SVM framework to estimate PVT properties of reservoir oil , 2013 .
[43] Ali Naseri,et al. Reservoir oil viscosity determination using a rigorous approach , 2014 .
[44] Johan A. K. Suykens,et al. Coupled Simulated Annealing , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[45] A. Bahadori,et al. Prediction of phase equilibrium of CO2/cyclic compound binary mixtures using a rigorous modeling approach , 2014 .
[46] Nobuo Morita,et al. Typical Sand Production Problems Case Studies and Strategies for Sand Control , 1991 .
[47] P. M. Halleck,et al. Mechanisms of Arch Instability and Sand Production in Two-Phase Saturated Poorly Consolidated Sandstones , 2001 .
[48] F. J. Santarelli,et al. Economical Management of Sand Production by a Methodology Validated on an Extensive Database of Field Data , 1995 .
[49] Tom Fawcett,et al. An introduction to ROC analysis , 2006, Pattern Recognit. Lett..