Modeling viscosity of methane,nitrogen,and hydrocarbon gas mixtures at ultra-high pressures and temperatures using group method of data handling and gene expression programming techniques

Accurate gas viscosity determination is an important issue in the oil and gas industries.Experimental approaches for gas viscosity measurement are timeconsuming,expensive and hardly possible at high pressures and high temperatures(HPHT).In this study,a number of correlations were developed to estimate gas viscosity by the use of group method of data handling(GMDH)type neural network and gene expression programming(GEP)techniques using a large data set containing more than 3000 experimental data points for methane,nitrogen,and hydrocarbon gas mixtures.It is worth mentioning that unlike many of viscosity correlations,the proposed ones in this study could compute gas viscosity at pressures ranging between 34 and 172 MPa and temperatures between 310 and 1300 K.Also,a comparison was performed between the results of these established models and the results of ten wellknown models reported in the literature.Average absolute relative errors of GMDH models were obtained 4.23%,0.64%,and 0.61%for hydrocarbon gas mixtures,methane,and nitrogen,respectively.In addition,graphical analyses indicate that the GMDH can predict gas viscosity with higher accuracy than GEP at HPHT conditions.Also,using leverage technique,valid,suspected and outlier data points were determined.Finally,trends of gas viscosity models at different conditions were evaluated.

Characterization and physicochemical aspects of novel cellulose-based layered double hydroxide nanocomposite for removal of antimony and fluoride from aqueous solution

A series of novel adsorbents composed of cellulose(CL)with Ca/Al layered double hydroxide(CC_(x)A;where x represent the Ca/Al molar ratio)were prepared for the adsorption of antimony(Sb(V))and fluoride(F^(-))ions from aqueous solutions.The CC_(x)A was characterized by Fourier-transform infrared spectroscopy(FTIR),Brunauer–Emmett–Teller(BET),elemental analysis(CHNS/O),thermogravimetric analysis(TGA-DTA),zeta potential,X-ray photoelectron spectroscopy(XPS)and scanning electron microscopy with energy dispersive Xray spectroscopy(SEM-EDX)analysis.The effects of varying parameters such as dose,pH,contact time,temperature and initial concentration on the adsorption process were investigated.According to the obtained results,the adsorption processes were described by a pseudo-second-order kinetic model.Langmuir adsorption isotherm model provided the best fit for the experimental data and was used to describe isotherm constants.The maximum adsorption capacity was found to be 77.2 and 63.1 mg/g for Sb(V)and F^(-),respectively by CC_(3)A(experimental conditions:pH 5.5,time 60 min,dose 15 mg/10 mL,temperature 298 K).The CC_(3)A nanocomposite was able to reduce the Sb(V)and F^(-)ions concentration in synthetic solution to lower than 6μg/L and 1.5 mg/L,respectively,which are maximum contaminant levels of these elements in drinking water according to WHO guidelines.