سیویلیکا را در شبکه های اجتماعی دنبال نمایید.

Application of Intelligent Models for Prediction of Solution Gas Oil Ratio

Publish Year: 1394
Type: Conference paper
Language: English
View: 1,225

This Paper With 11 Page And PDF and WORD Format Ready To Download

این Paper در بخشهای موضوعی زیر دسته بندی شده است:

Export:

Link to this Paper:

Document National Code:

RESERVOIR05_005

Index date: 16 February 2016

Application of Intelligent Models for Prediction of Solution Gas Oil Ratio abstract

Accurate calculation of PVT properties is a basic requirement for petroleum engineering computations like reservoir simulation, material balance, and well-test. Experimental tests of PVT are time-consuming and costly. Therefore, prediction models for PVT properties such as bubble point pressure, dew point pressure and solution gas oil ratio have been developed using regression models. In this study, new intelligent models for solution gas oil ratio were developed using more than 1100 experimental data series. Two robust intelligent tools, namely adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network were used for development of the models. Precise comparison of the developed models with other published correlation showed that the developed models are superior to all other correlations. Comparison of the ANFIS model and ANN model showed that, ANFIS model is more accurate than ANN model and is the best model for calculation of solution gas oil ratio

Application of Intelligent Models for Prediction of Solution Gas Oil Ratio Keywords:

solution gas oil ratio , crude oil , adaptive neuro-fuzzy inference system , artificial neural network

Application of Intelligent Models for Prediction of Solution Gas Oil Ratio authors

Seyed Morteza Tohidi Hosseini

Master Student of Production Engineering, Amirkabir University of Technolgy

Sina Shahriari Moghaddam

Master Student of Petroleum Facilities, Amirkabir University of Technology

Babak Ahmadirad

Master Student of Reservoir Engineering, Oloom Tahqiaqat University

Mehran Hashemi Doulatabadi

Bsc of Petroleum Engineering, Amirkabir University of Techonology

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :
M. Vazquez, H.D. Beggs, Correlations for fluid physical property prediction, ...
M.A. Al-Marhoun, PVT correlations for Middle East crude oils, Journal ...
F. Frashad, J. LeBlanc, J. Garber, J. Osorio, Empirical PVT ...
J. Velarde, T. Blasingame, W. McCain Jr, Correlation of black ...
G. Petrosky Jr, F. Farshad, P re SSure-vo lume- temperature ...
B. Dindoruk, P.G. Christman, PVT properties and viscosity correlations for ...
M. Standing, A pre Ssure-vo _ ume -temperature correlation for ...
O.s.e. al., Optimization of Formation Volume Factor and Solution Gas-Oil ...
M. Al-Marhoun, E. Osman, Using artificial neural networks to develop ...
A. Moghadassi, F. Parvizian, S.M. Hosseini, A. Fazlali, A new ...
E.A. El-Sebakhy, Data mining in forecasting PVT correlations of crude ...
M.A. Mahmood, M.A. Al-Marhoun, Evaluation of empirically derived PVT properties ...
ME. Dokla, M.E. Osman, Correl, ation of PYT Properties for ...
J.N. Moghadam, K. Salahshoor, R. Kharrat, Introducing a new method ...
M. Omar, A. Todd, Development of new modified black oil ...
O. Bello, K. Reinicke, P. Patil, Comparison of the performance ...
R. Ostermann, C. Ehl ig-Economides, O. Owalabi, Correlations for the ...
D. Obomanu, G. Okpobiri, Correlating the PVT properties of Nigerian ...
G. De Ghetto, _ Villa, Reliability analysis _ PVT correlations, ...
G. Abdul-Majeed, N. Salman, B. Scarth, An empirical correlation for ...
W.S. McCulloch, W. Pitts, A logical calculus of the ideas ...
S. Shahab Mohaghegh, _ irtual- Intelligence Applications in Petroleum Engineering: ...
R.B. Gharbi, A.M. Elsharkawy, M. Karkoub, Universal neural -network-based model ...
_ Obanijesu, E. Omidiora, The artificial neural network's prediction of ...
L. Saini, M. Soni, Artificial neural network based peak load ...
J.-S. Jang, ANFIS: adap tive-network- based fuzzy inference system, Systems, ...
MathWork, Fuzzy logic toolbox. User's guide, Matlab R2010a version 7.8.0, ...
M. Arabloo, M.-A. Amooie, A. Hemmati- Sarapardeh, M.-H. Ghazanfari, A.H. ...
M. Hosseinzadeh, A. Hemmati- Sarapardeh, Toward a predictive model for ...
نمایش کامل مراجع