Iraqi Journal of Chemical and Petroleum Engineering

Oxidative desulfurization (ODS) has attracted interest in the academic and industrial fields to meet new, stringent environmental legislation and produce environmentally friendly fuel. In this work, catalytic oxidative desulfurization of dibenzothiophene (DBT) compounds in diesel fuel is studied using a co-magnetic active oxide over an activated carbon (Fe2O3 + MnO2/AC) catalyst. DBT oxidation reactions are conducted in new oscillatory and non-oscillatory baffled reactors (OBR and NOBR). New central baffles for handling catalyst particles as a fixed bed in the OBR are developed for the first time. ODS process is examined using hydrogen peroxide as oxidant under different operating parameters: temperatures: 30 - 90 °C, oxidation times: 3–12 min, frequency: 0.5 - 2 Hz, and amplitude: 3 -12 mm. The results observed that the highest desulfurization efficiency (98.1 %) is achieved under the best conditions (90 °C, 12 min, 2 Hz, and 12 mm) in OBR. The dramatic DBT oxidation in a short desulfurization time is mainly attributed to the synergistic effect of oscillatory flow and the high activity of the synthesized catalyst. The desulfurization kinetic model is examined under the best conditions. Kinetic results show that ODS reactions follow a first-order model. Also, a low activation energy (3.68 kJ/mol) is determined, which proves rapid DBT oxidation at a lower required energy.

This research paper uses pipesim software to reproduce and evaluate well performance, comparing vertical and horizontal wells using hydraulic fracturing. It examines the impact of key parameters, such as fracture length, width, permeability, and fracture number, on production improvement. In low-permeability reservoirs, simulation studies indicate that horizontal wells often achieve higher production rates than vertical wells, largely due to improved reservoir and fracture connectivity. Productivity in the vertical well increased to 300(stb/d), while in the horizontal well, it increased to over 9,000 (stb/d) after using hydraulic fracturing. The results indicate that fracture width has less of an impact on the performance of vertical wells than horizontal wells, although fracture length and fracture number significantly influence horizontal well productivity. This disparity underscores the need for strategic fracture design and well selection to optimize oil production under changing reservoir conditions. The research paper emphasizes the need to use advanced modeling tools such as PIPESIM to accurately predict well performance and guide decision-making in hydraulic fracturing operations. Tailor-made fracturing techniques based on reservoir properties can significantly enhance continuous production efficiency and extend well life.

The photocatalysis oxidation process is a promising technology within the series of advanced oxidation processes, which implements light-induced catalysts to generate strong oxidative species to eliminate organic pollutants from wastewater treatment. The Ag2O@CuO photocatalyst was successfully prepared by the co-precipitation method. The developed photocatalyst was characterized using X-ray diffraction, Fourier transform infrared spectroscopy, X-ray fluorescence spectrometer, field-emission scanning electron microscopy, Ultraviolet-Visible diffuse reflectance spectra, and photoluminescence spectra. The Ag2O@CuO efficiency was examined in the photocatalysis degradation of Rhodamine B (RhB) as a cationic dye under the illumination of ultraviolet light. The effect of various parameters, such as the type of light, photocatalyst dose, initial RhB concentration, and pH of the RhB solution, was studied. The results revealed that 90% degradation was achieved within 90 min at a pH of 6.8, 50 mg of a photocatalyst dose, and 10 mg/L of RhB dye under UV irradiation. However, 98% degradation of RhB dye was achieved at a pH of 10 under the same other conditions mentioned above. The kinetic study was performed based on the experimental data of the oxidative photocatalytic degradation of the RhB dye. The zero-order, pseudo-first order, and modified Freundlich kinetic models were applied to accomplish this study. The results showed that the photocatalytic oxidation of RhB dye by the Ag2O@CuO heterojunction photocatalyst followed a pseudo-first order kinetic model, with an apparent rate constant of 0.0429 min-1. Furthermore, the Langmuir-Hinshelwood model was used to investigate the RhB photocatalytic degradation kinetics of RhB at concentrations of 5-10 mg/L. The determined value of the intrinsic photocatalytic reaction rate constant was 0.7184 mg/L.min for the Ag2O@CuO heterojunction photocatalyst. Also, the equilibrium adsorption constant was 0.0767 L/mg for the Ag2O@CuO heterojunction photocatalyst.

Greenfield development planning is a challenging problem due to the complex objective function and the large number of variables. While stochastic algorithms and data-driven offline surrogate models have been used to locate and control wells, these methods often require a large number of runs or fail to reach an accurate optimal solution. For this reason, the current study aimed to develop a dynamic surrogate model updated after each evaluation, referred to as an active learning model. In this study, deepEnsemble and gaussian process (GP) algorithms were applied as an active alternative model. This approach was compared with optimization algorithms directly coupled with real simulations, where algorithms such as genetic algorithms (GA), particle swarm optimization (PSO), complex matrix adaptation evolution strategy (CMA-ES), and differential evolution (DE) were used for comparison. The deepEnsemble active model outperformed the other approaches, achieving a net present value (NPV) of more than 1 E+10 and 17% recovery factor (RF) for a field in southern Iraq for a production scenario. The algorithm suggested shutting in two existing wells and drilling 23 new wells. The algorithm was also tested using a water injection scenario; a stable pressure, NPV of approximately 1.28 E+10, and 25% RF was achieved by suggesting drilling 39 new wells, 17 of which were injection wells. The approach has proven effective in dealing with complex field development problems with a minimum number of runs.

The induced electrochemical-Fenton (I-EF) process is one of the electrochemical advanced oxidation processes (EAOPs) that has been recently applied to treat various types of wastewaters. In this work, the I-EF process, comprising a graphite/SnO2-Sb2O3 anode, an iron-screen-induced electrode, and an air-diffusion cathode, was used to treat petroleum refinery wastewater. The effects of current density (2-10 mA/cm²), pH (3-7), and the number of screens on the induced electrode (1 and 4) on chemical oxygen demand (COD) removal were investigated. Results showed that increasing pH improved COD removal, whereas increasing current density beyond 3 mA/cm2 reduced it. Increasing the screen number also enhanced the COD removal. The preferred conditions were a current density of 3 mA/cm², pH of 7, and four screens, resulting in a COD removal of 88% within 120 min, which claimed an electrical energy consumption of 0.8575 kWh/m³, confirming the successful application of I-EF in petroleum refinery wastewater treatment under natural pH with minimum sludge generation.

Swelling is recurring challenges, which can lead to formation damage and compromising the wellbore integrity. Synergizing nanomaterials with their distinctive properties, alongside cost-effective materials, can provide a significant approach in enhancing the treatment of wellbore stability. This study employs a green, simple, and economical approach for the biosynthesis of SiO₂/KCl/Xanthan nanocomposites (NCs), aimed at reducing swelling and improving the rheological and filtration properties of Water-Based Drilling Fluids (WBDFs). The impact of SiO₂/KCl/Xanthan nanocomposite on swelling was assessed, followed by a comprehensive investigation into fluid’s filtration and rheological properties, including apparent viscosity, plastic viscosity, yield point, gel strength, and filter cake thickness. The results confirmed that the green-synthesized NCs effectively reduced clay swelling by approximately 22.2%. Furthermore, they significantly improved the mud’s rheological characteristics, decreasing filter cake thickness and fluid loss by approximately 91.29% and 91.7%, respectively, under HPHT conditions. The findings strongly suggest that SiO₂/KCl/Xanthan NC is an effective additive for mitigating clay swelling, enhancing rheology, and reducing filtration challenges in marl rich formation.

This study investigated the textural properties of 13X zeolite, FeX zeolite, TiO2/FeX zeolite, ZnO/FeX zeolite, and TiO2+ZnO/FeX zeolite using nitrogen adsorption-desorption data at consistent low temperatures. The adsorption-desorption isotherm indicated that the studied materials have a type IV mesoporous structure, as defined by the International Union of Pure and Applied Chemistry. The results of nitrogen adsorption data analysis using the Langmuir, Freundlich, and Brunauer-Emmett-Teller models indicated that the data were best described by the Brunauer-Emmett-Teller model. The Barrett, Joyner, and Halenda model was used to analyze the pore size distribution, pore diameter, and average pore volume of the adsorbents. After the ion exchange and loading process, there was a notable decrease in surface area and pore size distribution values, while the reduction in pore volume was minimal. Zeolite 13X showed a larger pore diameter, suggesting that some structural damage or the formation of wider pores within the mesoporous range occurred during the ion exchange steps or modification by the addition of semiconductor oxides. In contrast, the FeX zeolite exhibited a smaller pore size, indicative of a more compact microporous structure. While the modified zeolites—TiO2, ZnO, and TiO2+ZnO—demonstrated a consistent pore structure, suggesting stable mesoporosity with a smaller pore size, this implies that some of the zeolite's pores were blocked or filled with TiO2 and ZnO particles.

Understanding capillary pressure profiles during gas-brine coreflooding is essential for analyzing fluid behavior in porous media, particularly in gas reservoirs. Direct measurement of capillary pressure in dynamic displacement experiments relies on evaluating the balance between capillary forces and pressure gradients within the porous structure. In this experimental study three rock samples were taken from a natural gas reservoir located on Australia's Northwest Shelf. Experiments were conducted under simulated reservoir conditions (~ 41.37 MPa and 368.15 K) to investigate the effects of pore size, porosity, and water saturation on the capillary pressure profile. The capillary pressure curves (Samples C1–C3) reveal distinct dynamic behaviors. Samples C1 and C2, which have higher permeability and porosity, exhibit an initial decrease followed by a monotonic rise in capillary pressure until breakthrough. In contrast, Sample C3, characterized by lower permeability and porosity, shows lower brine saturation. However, higher brine saturation would typically be expected in low-porosity samples due to increased grain surface area and smaller pore throats that trap the wetting phase. This unexpected result is attributed to the experiments being conducted under high-pressure and high-temperature conditions. These findings underscore the critical role of pore geometry in governing displacement efficiency and capillary trapping. They also provide valuable quantitative insights for reservoir modeling, particularly in predicting gas recovery under HPHT conditions where capillary forces are significant.

Carbon capture and storage technologies are crucial in mitigating greenhouse gas emissions. This study investigates the enhancement of CO2 absorption through refining amine blends, specifically diethylenetriamine (DETA) with monoethanolamine (MEA) and tetraethylenepentamine (TEPA) with MEA at different concentrations and employing chemical promoters to boost the performance of the gas treatment system. The behaviour of these amines was evaluated by the impact of mixing DETA and MEA across different concentrations. The results showed that the removal efficiency increased with increasing DETA concentration. Similarly, the TEPA-MEA blend was investigated, demonstrating an increase in removal efficiency with increasing TEPA concentration. Removing efficiency improved from 75% with 30% MEA to about 96% with a 15% MEA and 15% TEPA mixture while maintaining the absorption rate due to the sufficient column height. Also, the study explores the effect of utilizing chemical promoters, specifically piperazine (PZ), potassium carbonate (K₂CO₃), and benzylamine (BZ), when combined with 15 % MEA and 10% DETA to boost the absorption rate and improve the CO2 loading capacity. The findings indicate that adding 5% BZ to the MEA-DETA solution increases removal efficiency by 10%. Moreover, adding 5% PZ to the same mixture increased efficiency by about 18%. Meanwhile, the volumetric mass transfer coefficient, KGav, more than doubled. Finally, the study examined the effect of using the same promoters with 15% MEA and 10% TEPA on CO2 capacity and mass transfer rates. The outcomes demonstrate that both removal effectiveness and KGav were dropped when using BZ and K₂CO₃ in the MEA-TEPA blend. The removal efficiency increased somewhat with PZ, but KGav was not significantly affected. In conclusion, the mass transfer rate and CO2 removal efficiency from flue gases will be enhanced by the use of bi-amines such as MEA-DETA and MEA-TEPA in chemical absorption. However, because they enhance the amine group in the absorbent, promoters such as PZ and BA can raise the carbon dioxide removal efficiency to an economically valuable level.

Gas lift is one of the most important artificial lift methods for increasing oil production, as wells often require this method after the reservoir's energy has decreased. In this research, an optimal gas lift system is designed for five horizontal wells in the Ahdab oil field, which suffers from low production. At the same time, water cut in some of these wells reaches 66%, while the productivity index is low in others, which makes the challenges clear, and a deep analysis is needed to find an optimal system. The Pipesim program is used to design the optimal gas lift system, which contains features that facilitate the implementation of the appropriate design and provide the ability to analyze and determine the optimal design values, as well as to detect future production problems. A single system is designed for wells located in the same formation, where an injection pressure of 1750 psi, an injection rate of 1 mmscf/d, and a wellhead pressure of 300 psi are chosen for wells in the Mishrif formation, noting that three valves will be installed in the system. For the wells in the Rumaila formation, an injection pressure of 1950 psi, an injection rate of 1.25 mmscf/d, a wellhead pressure of 475 psi, and four valves were selected for the unloading process. The results proved the design efficiency and that the selected values were optimal, as the increase in production for the five wells was 238%, 146%, 56.6%, 55.9%, and 37.4%.

This study presented Intelligent Network's proposed methodology for forecasting the effectiveness of cadmium removal from wastewater using emulsion liquid membrane (ELM). The research examined the removal of cadmium from an aqueous solution in the internal phase of water-in-oil emulsions. ELM was composed of kerosene as the membrane phase, Span 80 as the surfactant, di-2-ethylhexyl phosphoric acid (D2EHPA) as the extracting agent, and hydrochloric acid (HCl) as the stripping solution. Experiments were conducted to investigate the effects of five parameters: surfactant concentration, feed-phase agitation speed, internal-to-membrane phase volume ratio, emulsion-to-feed volume ratio, and stripping-phase concentration in the internal phase. More than 97.4% of cadmium can be extracted in less than 15 minutes. This study evaluates the effectiveness of various learning algorithms, including gradient descent (GD), resilient back propagation (RB), gradient descent with momentum (GDM), gradient descent with learning momentum and adaptive rate (GDX), polak-ribiére conjugate gradient (CG), and levenberg marquardt (LM), in predicting the efficiency of cadmium elimination from wastewater using liquid emulsion membrane technology. The researchers developed a neural network model with 8 input neurons, 10 hidden neurons, and 1 output neuron. This feed-forward artificial neural network (ANN) incorporated various back-propagation training algorithms to simulate the cadmium removal process using ELM. The neural network model's predictions closely aligned with results from batch experiments, as demonstrated by a correlation coefficient (R2) of 0.9723 and a Mean Squared Error (MSE) of 0.0041, calculated in MATLAB. In conclusion, the ANN models demonstrated high accuracy and reliability in predicting cadmium removal efficiency, confirming their potential as practical tools for process optimization.

The green synthesis of nanoparticles and activated carbon has attracted researchers' interest due to its rapid, cost-effective, sustainable, and environmentally friendly nature. In this paper, the synthesis of activated carbon (AC) and nickel oxide nanoparticles (NiO-NPs) from Ficus carica leaf and their extracts for the removal of malachite green from aqueous solutions. activated carbon (AC) was synthesized from Ficus carica leaves using a pyro-carbonic acid microwave method. In contrast, nickel oxide nanoparticles were produced using leaf extracts as a reducing and stabilizing agent. The manufactured activated carbon and NiO nanoparticles were characterized by Brunauer-Emmett-Teller analysis, scanning electron microscopy with energy-dispersive X-ray spectroscopy, X-ray diffraction, and Fourier transform infrared spectroscopy. The influence of various factors, including malachite green concentration, pH, contact time, and dosages of NiO, AC, and NiO/AC, was examined using Response Surface Methodology (RSM) in Design-Expert (13 Stat-Ease). the optimal parameters for achieving maximum removal efficiency of malachite green dye were determined to be an initial concentration of 150 mg/L, pH of 4, a contact period of 120 minutes, and an adsorbent dosage of 0.25 g/L, resulting in removal efficiencies of 97.9202%, 98.8932%, and 99.9776%, respectively. The equilibrium adsorption data were analyzed using the Langmuir, Freundlich, and pseudo-first- and second-order kinetic models. the results indicated that the Freundlich isotherm and pseudo-second-order kinetic models were the most effective in representing the equilibrium adsorption data.

Concentration polarization is a critical problem for nanofiltration membranes, as it reduces permeate flux and increases operating costs. This study aims to assess the efficacy of air spraying technology as an innovative approach to enhance nanofiltration membrane performance, specifically in water treatment. The methodology focused on conducting comprehensive trials using simulated water and on implementing air-spraying technology at flow rates ranging from 1.5 to 4.5 liters per minute. The membrane's performance was tested under a range of conditions, including varied input concentrations (2,000 to 15,000 ppm), pressures (4 to 6 bar), water flow rates, and temperatures (20 and 32°C). The results showed that adding air efficiently reduces concentration polarization, thereby significantly increasing permeate flux and the effectiveness of sodium chloride rejection. At 2,000 ppm and 6 bar, the most significant flow was 168 liters/h, with a rejection ratio of 90.8%. The highest achievable flux was likewise reached at 32°C, with an excellent rejection ratio of 91.75%. The study, on the other hand, indicated that increasing the feed concentration worsened the permeability flux. This study demonstrates that air-spraying technology is an effective means of improving nanofiltration membrane performance.

A clean environment and human health depend on removing heavy metal ions from wastewater. Ecosystems and public health are seriously threatened by heavy metal ions, such as nickel (Ni), lead (Pb), cadmium (Cd), vanadium (V), chromium (Cr), and copper (Cu). For example, because of its toxic effects, cadmium is only permitted at 0.005 mg/L in drinking water, while lead has a maximum permissible concentration of 0.015 mg/L. Heavy metal ions have been extracted from various wastewater types using methods such as adsorption, membrane filtration, chemical addition, electrochemical treatment, and photocatalysis. Nevertheless, conventional techniques frequently encounter obstacles like exorbitant operating expenses and restricted effectiveness, with removal rates occasionally falling below 70%. These techniques can also result in hazardous byproducts, which makes wastewater treatment procedures more difficult. Because photocatalysis is so versatile in environmental remediation, it can be used to remove heavy metals. The ability of semiconductor nanostructures based on metal oxides to effectively remove heavy metals from contaminated water has garnered attention recently. For instance, when exposed to particular light wavelengths, zinc oxide (ZnO) and titanium dioxide (TiO2) can remove some heavy metals with up to 95% removal efficiencies. Zeolites have been used increasingly in wastewater treatment over the past 20 years; applications have shown removal capacities of up to 100 mg/g for cadmium and 150 mg/g for lead. This article examines recent developments in using zeolites to extract heavy metals from contaminated solutions. Both traditional and modern wastewater treatment methods are compiled and discussed in this comprehensive analysis, including the application of ZSM-5 zeolites in photocatalytic technology, which can lower operating costs by up to 30% and improve removal efficiencies. Combining zeolites with photocatalytic systems is a viable strategy to raise the efficacy of heavy metal remediation in wastewater treatment.

Over the past decade, sustainable bimetallic nanoparticles (NPs) have attracted significant scientific attention. However, challenges related to synthesis efficiency and environmental impact remain major concerns. In this study, we present the green synthesis of bimetallic selenium nanoparticles (SeNPs) using pomegranate peel extract (PPE) as a natural, eco-friendly reducing and stabilizing agent. The synthesized nanoparticles were thoroughly characterized using Fourier-transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), ultraviolet-visible (UV–Vis) spectroscopy, transmission electron microscopy (TEM), and energy-dispersive X-ray (EDX) analysis, confirming their successful formation, uniform morphology, and homogeneous distribution. The biosynthesized SeNPs demonstrated potent in vitro anticancer activity against the human breast cancer cell line (MCF-7), exhibiting a half-maximal inhibitory concentration (IC₅₀) of 11 μg/mL, while remaining non-toxic and biocompatible at lower concentrations. These findings highlight the significant biomedical potential of PPE-mediated bimetallic SeNPs as safe and effective anticancer agents. Overall, this green biosynthetic approach provides a sustainable and efficient alternative to conventional chemical synthesis methods for producing functional metal oxide nanoparticles.

This work examines the kinetic behavior of Dodonaea viscosa during microwave-assisted pyrolysis as a means of addressing the limited insight regarding how biomass degradation pathways are affected by non-conventional heating. Thermogravimetric data were analyzed using both model-fitting (Coats–Redfern) and model-free (Friedman and Kissinger–Akahira–Sunose) methods to provide a thorough analysis. Results indicated that a third-order kinetic model appropriately described the general trend of decomposition; in contrast, iso-conversional analyses verified a multi-stage sequence with the activation energy declining during volatile yields and increasing at elevated conversion levels as a result of carbonaceous residue decomposition. These complementary understandings demonstrate that microwave-assisted heating ensures the development of characteristic reaction dynamics rather than those derived from traditional pyrolysis and thus supply mechanistic support for increased energy efficiency. The results not only unify methodology gaps between model-fitting and iso-conversional methodology but also provide useful direction for the optimization of microwave pyrolysis parameters, thus enhancing the sustainable production of lignocellulosic biomass-derived bioenergy.