Data-driven modeling for determination of asphaltene stability condition in oil system

Asphaltene precipitation is accounted as one of the most serious problems during oil production so that it can decrease the production of crude oil and cause the blockage of reservoir rock pores, etc. An accurate prediction of phase behaviour of asphaltene is therefore important in oil production industry. Accurate prediction of phase behaviour of asphaltene precipitation i.e. stability state of asphaltene precipitation in oilfields is greatly desirable. To this end, the applicability domains of the most important variables for the determination of the stability state of asphaltene precipitation viz. aromatic + resin and asphaltene + saturates have been specified by using decision tree (DT) algorithm. Next, adaptive neuro-fuzzy inference system (ANFIS) approach was implemented in order to determine the stability state of asphaltene precipitation using the efficient variables of aromatic + resin and asphaltene + saturates. The results obtained in the current study demonstrate that the models proposed in this study provide desirable results in estmating the stability state of asphaltene precipitation in oilfields.     

Synthesis and characterization of insulin/zirconium phosphate@TiO2 hybrid composites for enhanced oral insulin delivery applications

Abstract

In this work, a series of composites of insulin (Ins)/zirconium phosphate (ZrP) were synthesized by intercalation method, then, these composites were coated with TiO₂ by sol-gel method to prepare Ins/ZrP@TiO₂ hybrid composites and the drug release of the composites was investigated by using UV-Vis spectroscopy. Ins/ZrP (10, 30, 60?wt%) composites were prepared by intercalation of insulin into the ZrP layers in water. Then Ins/ZrP composites were coated with different amounts of TiO₂ (30, 50, 100?wt %) by using titanium tetra n-butoxide, as precursor. Formation of intercalated Ins/ZrP and Ins/ZrP@TiO₂ hybrid composites was characterized by FT-IR, FE-SEM, BET and XRD analysis. Zeta potential of the optimized Ins/ZrP@TiO₂ hybrid composite was determined ?27.2?mV. Cytotoxic effects of the optimized Ins/ZrP@TiO₂ hybrid composite against HeLa and Hek293T cell lines were evaluated using MTT assay and the results showed that designed drug delivery system was not toxic in biological environment. Compared to the Ins/ZrP composites, incorporation of TiO₂ coating enhanced the drug entrapment considerably, and reduced the drug release. The Ins/ZrP composites without TiO₂ coating released the whole drug after 30?min in pH 7.4 (phosphate buffer solution) while the TiO₂-coated composites released the entrapped drug after 20?h. In addition to increasing the shelf life of hormone, this nanoencapsulation and nanocoating method can convert the insulin utilization from injection to oral and present a painless and more comfortable treatment for diabetics.     

Synthesis,characterisation and potential application of deoxycholic acid carboxymethyl chitosan as a carrier agent for rotenone

In the present study, deoxycholic acid carboxymethyl chitosan (DACMC) was synthesised via a two-step reaction, namely carboxymethylation and alkylation. Fourier Transform Infrared (FTIR) Spectrometer, Proton Nuclear Magnetic Resonance (¹H NMR) Spectrometer, Transmission Electron Microscope (TEM) and Thermogravimetric Analyser (TGA) were used to characterise DACMC. Spherical self-aggregates of DACMC micelles with the size ranging from 91.3 to 140.0 nm was observed. DACMC was soluble in pH range studied (1–13), except pH 4. DACMC micelles were formed at critical concentration (CMC) value of 0.468 mg/mL. The ability of DACMC to encapsulate and load rotenone was determined at different weight ratios. The highest value of encapsulation efficiency (EE%) (more than 98%) was obtained for weight ratio of 100:1 (DACMC:Rotenone). The in vitro release data of rotenone-loaded DACMC followed Ritger and Peppas Case II transport mechanism. Results from this study highlight the potential of DACMC to reduce organic solvent application in water-insoluble pesticide production.     

The effects of ice storage on inosine monophosphate, inosine, hypoxanthine, and biogenic amine formation in European catfish (Silurus glanis) fillets

European catfish fillets in ice were evaluated by measuring nucleotide components and biogenic amine contents and these then compared with sensory and microbiological assessment during the 21 days of iced storage. Analyses were carried out using two different rapid HPLC methods for nucleotid degradation products and biogenic amine contents in European catfish fillets. Sensory evaluation showed that storage life of European catfish found to be 14–18 days. Initial inosine monophosphate (IMP) level was 12.6 μmol g^­1 and then decreased during the rest of storage period. Inosine (INO) level increased rapidly until 7 days of storage. Hypoxanthine (Hx) level increased almost linearly with storage time. The most accumulated biogenic amines were putrescine, cadaverine, spermidine, spermine, and serotonin in all the European catfish fillets during the storage, although the formation of biogenic amines levels was fluctuated. Histamine was only detectable at 4 and 7 days of storage as low as 1 mg 100 g^­1 fish. Total viable count in European catfish increased rapidly with storage time and reached ≤10⁹ cfu g^­1 when the fillets were not acceptable for consumption.     

A Reliable Model for Estimating the Wax Deposition Rate During Crude Oil Production and Processing

Deposition of wax in surface and subsurface pipes and even perforations can lead to serious problems including pore spaces blockage, plugging of pipelines, and minimum profitability. Therefore, understanding wax deposition and wax related-properties improves the oil recovery and processing operations in petroleum industry. In this research work, the rate of wax deposition is correlated to a number of main parameters such as the dynamic viscosity of crude oil, shear stress, gradient of wax molecular concentration and temperature difference in pipeline system through implementation of a newly developed model, known as least squares support vector machine (LSSVM) along with the coupled simulated annealing (CSA) optimization strategy. The possible outliers are detected through employing the Leverage technique which involves residual errors plots, Williams' plot, and Hat matrix. The results imply that whole collected real data are in applicability domain of the proposed model. Using a comprehensive statistical investigation, a very good agreement between the predicted LSSVM-CSA outputs and real wax deposition rate is found such that the average relative error percentage and determination coefficient (R2) are 0.048% and 0.999, respectively. Such a study can assist to provide better designs (technically and economically) for underground and surface facilities while dealing with wax deposition cases.     

New correlation for estimation of cementation factor in Asmari carbonate rock reservoirs

The cement factor is one of the most important Archie parameters which is a major source of uncertainty in the calculation of water saturation for a given reservoir condition. In carbonate rocks, due to the sensitivity of this parameter to pore type, water saturation estimation has associated with high inaccuracy. Laboratorial measurements also are available just for few cases. Despite of great importance of these factors in reservoir studies, there is no general and precise relationship for Iran reservoirs and saturation calculations are carried out by equations which usually with great error. Hence, developing a reliable correlation according to the local geology to determine this property accurately is of crucial importance.In this study, in order to establish a new correlation relationship between the mentioned parameter and porosity, 68 core samples from of one the biggest Middle East’s carbonate reservoirs (Asmari Formation) were evaluated and this new correlation compared with Borai, Shell and Sethi correlations. In the next part, according to flow zone indicator (FZI) and quality index (RQI) methods, all core samples were classified into seven discrete rock types (DRT). Finally, based on microscopic studies, the samples were categorized into 6 petrofacieses in terms of rock and pore types. Plots of the porosity versus formation resistivity measurements are shown for every petrofacieses.This study shows that using the new correlations is associated with lower error in calculations of cementation factor (based on core data set) comparing with Borai, Shell and Sethi correlations. Also, FZI-DRT and petrofacieses methods in compare with the new correlation don’t express satisfying relationships between cementation factor and porosity.     

Modeling of the Properties of Gasoline and Petroleum Fractions Using a Robust Scheme

Gasoline is one of the most recognized products of the petroleum industry due to its use as a liquid fuel worldwide. As a result, it is of great importance to accurately determine the properties of gasoline, so as to evaluate its quality. In this article, an effective mathematical and predictive strategy, namely least squares support vector machines (LSSVM) is applied to predict some gasoline properties, viz. specific gravity (SG), motor octane number (MON), research octane number (RON), and Reid vapor pressure (RVP). A comprehensive error analysis is also undertaken to compare the values predicted from the model with actual data which enables one to evaluate the performance of the model developed in this study. The results indicate that the model developed has reasonable accuracy and prediction capability. The correlation indices, R², are 0.990, 0.933, 0.955, and 0.920 for SG, MON, RON, and RVP, respectively.     

Evaluation of wax disappearance temperatures in hydrocarbon fluids using soft computing approaches

In this study, modeling wax disappearance temperatures (WDTs) in hydrocarbon fluids is presented using three different soft computing approaches, namely feed forward artificial neural network; multilayer perceptron (MLP), least squares support vector machines (LSSVM), and decision tree (DT). Results indicate that the models presented in this study provide acceptable results. Furthermore, a comparative study demonstrates the superiority of decision tree model in terms of accuracy compared to the other models investigated in this study.     

Effect of Calcination Temperature on the Structural and Optical Properties of (ZnO)0.8 (ZrO2)0.2 Nanoparticles

Calcination temperature has influenced the structural and optical features of nanocrystalline (ZnO)_0.8 (ZrO₂)_0.2 series. Indeed, at present, general research in the approach to synthesis of (ZnO)_0.8 (ZrO₂)_0.2 nanoparticles by combustion using zinc nitrate hexahydrate (Zn (NO₃)₂·6H₂O) and zirconium (11) nitrate pentahydrate (Zr (NO₃)₂·5H₂O) is still in its infancy. A Thermogravimetric (TG) assessment was performed to determine the precursor of the conduction. Characterizations such as energy dispersive X-ray analysis (EDX), X-ray diffraction (XRD), transmission electron microscopy (TEM), UV–Visible, Fourier transform infrared spectroscopy (FTIR), and photoluminescence (PL) spectroscopy were carried out. The crystallite size of the binary oxides (ZnO)_0.8 (ZrO₂)_0.2 on the maximum expansion of ZnO–ZrO₂ nanoparticle was studied using Scherrer’s equation. Due to calcination, significant modifications were observed in terms of the size of the particles, the absorption spectra, and the intensity of the photoluminescence. In the XRD result, an increment in crystallinity was observed from 10.20 nm to 28.00 nm while the FTIR findings showed the removal of the polymer as well as the presence of nanoparticles metals. The optical band gap results indicated a decline in energy band gap between (3.27 and 3.12) eV for (ZnO)_0.8 and (4.89–4.51) eV for (ZrO₂) _0.2 nanoparticles. A photoluminescence result showed two individual peaks at 655 nm (1.89 eV) and 715 nm (1.73 eV) respectively. The study also showed the application which can be a suitable choice to be used in solar cell applications.