Talal Al-Wahaibi

Deep oxidative desulfurization of liquid fuels

Abstract Increase in energy demand and consumption has been accompanied by a corresponding increase in sulfur emissions. These pollutants have both health and economic consequences. Furthermore, it significantly reduces the efficiency of advanced emission control systems of diesel engines, thereby indirectly causing more harm to the environment. This resulted in stringent sulfur emission limit down to about 15 ppm or less and in turn served as an incentive for research into alternative sulfur reduction technologies. Although feasible improvements to hydrodesulfurization are currently under investigation, adsorptive, extractive, oxidative and biodesulfurization have also been studied in recent years. Oxidative desulfurization appears to be one of the most promising desulfurization technologies due to its broadness and compatibility with other technologies such as extractive, adsorptive and biodesulfurization. The advent of ionic liquids as extraction solvents has made this even more so. This work, therefore, reviews the different approaches and investigations carried out on oxidative desulfurization while identifying research gaps and giving important recommendations.

Parameters of Drag Reducing Polymers and Drag Reduction Performance in Single-Phase Water Flow:

This study presents experimental investigation about the effect of polymer parameters on the performance of the drag reducing polymers in single-phase water flowing in a horizontal pipe of 30.6 mm ID. Master solutions (1000 ppm) of ten high-molecular weight polymers were injected at different flow rates to achieve polymer concentrations in the range of 2–40 ppm in the test section. The drag reduction increased with polymer concentration up to 10 ppm, above which it reached a plateau value. While the drag reduction at the plateau value increases with polymer molecular weight, the maximum drag reduction was not affected by the increase in polymer charge density up to 13%. For instance, the maximum drag reduction for anionic polymers with molecular weight 6–8 million Da. and charge density between 5 and 13% was around 60%, which decreased to around 38% for the polymer with charge density of 25%. Ionic polymers provided more drag reduction than nonionic ones. The overall conclusion is that drag reduction depends on polymer ability to form intermolecular associations and/or its flexibility, which can be enhanced by increasing molecular weight, decreasing charge density, and selecting smaller side groups in the main polymer backbone.

A Solid Organic Acid Catalyst for the Pretreatment of Low-Grade Crude Palm Oil and Biodiesel Production

Industrial low-grade crude palm oil (LGCPO) generated from industrial palm oil mills must be pretreated before utilizing it as a biodiesel raw material. The pretreatment of LGCPO was conducted using benzenesulfonic acid (BZSA) as solid organic acid catalyst. Batch pretreatment of LGCPO was carried out to study the influence of BZSA dosage (0.25--3.5% wt/wt), methanol molar ratio to LGCPO (4:1--20:1), temperature (40--80°C), and reaction time (3--150 min). The effects of those parameters on the free fatty acid content, and the yield of pretreated LGCPO were reported. This study illustrated the feasibility of using LGCPO from palm oil mills to produce biodiesel. The biodiesel produced from LGCPO meets the international standards (ASTM D6751 and EN 14214). Three times recycling of BZSA was achieved without appreciable degradation in its activity. This study introduces a possible batch esterification process using BZSA followed by an alkaline transesterification reaction for a possible future industrial application.

PREDICTION OF HORIZONTAL OIL-WATER FLOW PRESSURE GRADIENT USING ARTIFICIAL INTELLIGENCE TECHNIQUES

In oil-water flow, the two-fluid and the homogeneous models are commonly used to predict the pressure gradient. However, these models fail in many cases to predict the pressure gradient, especially in dual continuous flow. In this work, an artificial neural network (ANN) model with five inputs—oil and water superficial velocities, pipe diameter, pipe roughness, and oil viscosity—was developed to predict the pressure gradient of horizontal oil-water flow based on a databank of around 765 measurements collected from the open literature. Statistical analysis showed that the ANN model has an average error of 0.30%, average absolute error of 2.9%, and standard deviation of 7.6%. A comparison with the two-fluid model, the homogeneous model, and the Al-Wahaibi (2012) correlation showed that the ANN model better predicts the pressure gradient data over a wide range of superficial oil (U so = 0.05–3.0 m/s) and water velocities (U sw = 0.05–2.7 m/s), oil viscosity values (1–35 cp), pipe diameters (14–82.8 mm), and different pipe materials.

Characterization of pH-sensitive Polymer Microgel Transport in Porous Media for Improving Oil Recovery

Abstract We found that the sizes of poly(acrylic acid) microgels in solution were high enough to be retained by rock matrix. To overcome this problem, we varied the mixing period and mixing rate with and without heat, added NaOH followed by HCl, injected the polymer at the transient state, and added a chemical agent, but without any success. However, the microgel particles were not propagating through the cores and they plugged just the front face of the core. Thus, this kind of polymer can successfully improve oil recovery in fractured systems only, which we proved experimentally to be significant.

Desulfurization of liquid fuel via extraction with imidazole-containing deep eutectic solvent

Abstract The desulfurization of liquid fuels with deep eutectic solvent (DES) newly synthesized from inexpensive constituents of imidazole and tetrabutylammonium bromide salt was conducted via liquid-liquid extraction. The aim of the work is to lower the sulfur content of liquid fuels to below the environmental regulation using DES in a process with low energy requirement. A simulated fuel containing dibenzothiophene (DBT) and thiophene as representative refractory sulfur compounds and a commercial-grade diesel fuel were used for this work. Quantitative monitoring of sulfur compounds in the raffinate phase of the fuels was performed using high-performance liquid chromatography and energy-dispersive X-ray fluorescence techniques. The results of sulfur extraction showed that DBT and thiophene extraction efficiencies of 70% and 47%, respectively, could be achieved from the simulated fuel in a single run extraction. Similarly, 47% total sulfur removal from the commercial-grade diesel fuel was achieved with the solvent. The deep desulfurizations of the fuels were successfully achieved in four and five successive stages with the simulated fuel and the diesel fuel, respectively. The solvent was effectively regenerated after the extraction process with both fuels, thus allowing for its repetitive usage.

Efficient non-catalytic oxidative and extractive desulfurization of liquid fuels using ionic liquids

Oxidative desulfurization (ODS) is one of the promising alternative and heavily researched desulfurization technologies. This is partly due to its ability to preferentially oxidize and ease the removal of refractory sulfur compounds with the aid of a suitable solvent. Despite its long list of advantages, challenges in different research areas within ODS technology still exist. In this work, an effort was made to bridge the gap that exists in terms of the selection of suitable oxidant and strategy. A preliminary kinetic modeling of the experimental data showed that the non-catalytic conversion of dibenzothiophene (DBT) and benzothiophene (BT) to their corresponding sulfones using the electrophilic meta-chloroperoxybenzoic acid (mCPBA) can be considered a bimolecular and a trimolecular reaction respectively. Using an ionic liquid (IL) as an extraction solvent in a simultaneous oxidation and extraction setup (EODS), >78% BT was removed at optimum experimental conditions. Using the post-oxidation extractive desulfurization setup (OEDS), 99% removal of BT was achieved at milder optimum experimental conditions. Also using the OEDS strategy, >99% of DBT removal was achieved after only 15 min at 60 °C, with a mass fraction of ≥0.5 and O/S of 3/1 for all the ILs tested. Finally, the sulfur content of a commercial diesel fuel was reduced to 15.6 ppm using the OEDS strategy with tetrabutylphosphonium methanesulfonate as a suitable extraction solvent, which can be readily regenerated.

Viscosity correlations for light Omani crude using artificial neural networks

Predicting the crude oil viscosity is very crucial to the oil industry. Accurate prediction of the viscosity will lead to a better design of an energy efficient transportation system and helps in determining the enhanced oil recovery method. There has been intensive work in generating viscosity empirical correlations for under-saturated, saturated and deal oil. Due to the rapid growth in computational capabilities, artificial neural networks (ANNs) are found to be a useful tool for the development of crude oil viscosity correlations. In this work, artificial neural networks (ANNs) model is developed to predict the viscosity of dead, saturated and under-saturated Omani crude oil. Detailed comparison was also made with 38 oil viscosity correlations using Omani crude oil viscosity database. Twelve of these correlations are for dead oil viscosity, 14 are for saturated oil viscosity and 12 for under-saturated oil viscosity. The oil viscosity data were collected from PVT reports. Statistical analysis and cross-plots showed that the ANN model outperformed the considered viscosity correlations.

Effect of Water-Soluble Drag-Reducing Polymer on Flow Patterns and Pressure Gradients of Oil/Water Flow in Horizontal and Upward-Inclined Pipes

Experimental investigations of flow patterns and pressure gradients of oil/water flow with and without drag-reducing polymer (DRP) were carried out in horizontal and upward-inclined acrylic pipe of ...

Experimental Study of the Effects of IFT and Hysteresis on Resistivity and Capillary Pressure of Carbonate Rocks

Characterizing the electrical resistance of the formation rock is of great importance in, for example, interpreting the well log data, calculating the porosity, and water saturation for the formation rocks. The relation between the resistivity factor and porosity and also between the resistivity index and water saturation (Archie equation) in the formation rock uses the parameters, such as the cementation factor and saturation exponent. However, the direct application of Archie equation to carbonate rocks that are very heterogeneous and mostly oil-wet needs further investigation. In this experimental work, the effects of overburden pressure, temperature, and interfacial tension on the capillary pressure and resistivity characteristics during the imbibition and drainage processes are studied. The results showed a decrease of the saturation exponent when the rock changes from the oil-wet to the water-wet, during the primary drainage (e.g., from 5.6 to 2.29), imbibition (e.g., from 3.98 to 1.93), and the secondary drainage (e.g., from 4 to 2.04). As a result, this study improves understanding of the reservoir rock behavior especially when the enhanced oil recovery processes are studied.