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316篇 您的检索式:作者名="Fath"
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1Implementation of multilayer perceptron(MLP)and radial basis function(RBF)neural networks to predict solution gas-oil ratio of crude oil systems显示文摘Exact determination of pressure-volume-temperature(PVT)properties of the reservoir oils is necessary for reservoir calculations,reservoir performance prediction,and the design of optimal production conditions.The objective of this study is to develop intelligent and reliable models based on multilayer perceptron(MLP)and radial basis function(RBF)neural networks for estimating the solution gas–oil ratio as a function of bubble point pressure,reservoir temperature,oil gravity(API),and gas specific gravity.These models were developed and tested using a total of 710 experimental data sets representing the samples of crude oil from various geographical locations around the world.Performance of the developed MLP and RBF models were evaluated and investigated against a number of well-known empirical correlations using statistical and graphical error analyses.The results indicated that the proposed models outperform the considered empirical correlations,providing a strong agreement between predicted and experimental values,However,the developed RBF exhibited higher accuracy and efficiency compared to the proposed MLP model.Aref Hashemi Fath Farshid Madanifar Masood Abbasia 2020Petroleum2020,6,1:3
2Development of an artificial neural network model for prediction of bubble point pressure of crude oils显示文摘Bubble point pressure is one of the most important pressureevolumeetemperature properties of crude oil,and it plays an important role in reservoir and production engineering calculations.It can be precisely determined experimentally.Although,experimental methods present valid and reliable results,they are expensive,time-consuming,and require much care when taking test samples.Some equations of state and empirical correlations can be used as alternative methods to estimate reservoir fluid properties(e.g.,bubble point pressure);however,these methods have a number of limitations.In the present study,a novel numerical model based on artificial neural network(ANN)is proposed for the prediction of bubble point pressure as a function of solution gaseoil ratio,reservoir temperature,oil gravity(API),and gas specific gravity in petroleum systems.The model was developed and evaluated using 760 experimental data sets gathered from oil fields around the world.An optimization process was performed on networks with different structures.Based on the obtained results,a network with one hidden layer and six neurons was observed to be associated with the highest efficiency for predicting bubble point pressure.The obtained ANN model was found to be reliable for the prediction of bubble point pressure of crude oils with solution gaseoil ratios in the range of 8.61e3298.66 SCF/STB,temperatures between 74 and 341.6F,oil gravity values of 6e56.8 API and gas gravity values between 0.521 and 3.444.The performance of the developed model was compared against those of several well-known predictive empirical correlations using statistical and graphical error analyses.The results showed that the proposed ANN model outperforms all of the studied empirical correlations significantly and provides predictions in acceptable agreement with experimental data.Aref Hashemi Fath Abdolrasoul Pouranfard Pouyan Foroughizadeh 2018Petroleum2018,4,3:3
3Analysis of a new design of a multi-stage flash-mechanical vapor compression desalination process显示文摘A A Mabrouk A S Nafey H E S Fath 2007Desalination2007,,:1
4On fuzzy non-continuous mappings显示文摘MASHOUR A S GHANIM M H FATH ALLA M A 1986Bull Calcutta Math Soc1986,,78:1
5Direct Electrochemical Reduction of Titanium Dioxide to Titanium in Molten Calcium显示文摘CHEN G Z FRAY D J FATHING T W 2000Nature2000,407,9:1
6Micro-climatic environmental conditions inside a greenhouse with a built-in solar distillation system显示文摘E S Fath H Abdelrahman K 2004Desalination2004,171,:1
7Neuronal localization of the TNF alpha converting enzyme (TACE) in brain tissue and its correlation to amyloid plaques显示文摘Skovronsky DM Fath S Lee VM 0,,:1
8Evolutionary games on graphs显示文摘Szabo G Fath G 2007Phys Rep2007,446,456:1
9Modulated temperature differential scanning calorimetry for examination of tristearin polymorphisms:isothermal crystallization of metastable forms显示文摘Satish KSingh Ali Fathe Jalali Maggie Alden 1999JAOCS1999,76,4:1
10Cervical spine fractures in patients 65 years or older:a 3-year expefience at a level I trauma center显示文摘Damadi Saxe AW Fath JJ 2008J Trauma2008,64,3:1
11Mitochondrial electron transport chain blockers enhance 2-deoxy-D-glucose induced oxidative stress and cell killing in human colon carcinoma cells显示文摘Fath MA Diers AR Aykin-Burns N 2009Cancer Biol Ther2009,8,:1
12Influence of an ammonia activation prior to the PECVD SiN deposition on the solar cell performance显示文摘Alexander Hauser Markus Spiegel Peter Fath Ernst Bucher 0,,:1
13Ecological network analysis of an urban energy metabolic system: Model development, and a case study of four Chinese cities显示文摘ZHANG Yan YANG Zhifeng FATH B D 2010Ecological Modelling2010,221,16:1
14Investigation of Cavitation in Real Size Diesel Injection Nozzles 显示文摘Badock C Wirth R Fath A 1999International Journal of Heat and Fluid Flow1999,20,5:1
15PV and thermally driven small-scale, stand-alone solar desalination systems with very low maintenance needs显示文摘Fath H E S Elsherbiny S M Hassan A A 2008Desalination2008,225,13:1
16ABC transporters : bacterial exporters 显示文摘FATH M J KOLTER R 1993Microbiot1993,57,:1
17Abnormar expression and function of E-cadherin-catenin complex in gastric carcinoma cell lines显示文摘 Noda M Fathing MJ 1999Br J Cancer1999,80,34:1
18A Matlab function for network environ analysis 显示文摘FATH B D BORRETT S R 2006Environmental Modelling and Software2006,21,:1
19Optical Wireless Transmitter Employing Discrete Power Level Stepping显示文摘FATH T HELLER C HAAS H 2013IEEE Lightwave Technology2013,31,11:1
20Nitric oxide acts as an an- tioxidant and delays prograrmned cell death in barley aleurone layers 显示文摘Beligni M V Fath A Bethke P C 2002Plant Physiology2002,129,4:1
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