Iraqi Journal of Chemical and Petroleum Engineering
The Iraqi Journal of Chemical and Petroleum Engineering is a quarterly peer-reviewed scientific journal that was established in 2000 by the College of Engineering / University of Baghdad. The Iraqi Journal of Chemical and Petroleum Engineering receives citations in the category of Chemical /Petroleum Engineering and relevant subjects.
University of Baghdad/ College of Engineering
Multi-output machine learning prediction of CO₂ enhanced oil recovery and geological storage performance
Carbon dioxide-enhanced oil recovery (CO₂-EOR) is one of the best commercial carbon capture, utilization, and storage (CCUS) technologies, enhancing oil recovery and achieving safe geological storage. However, data density and computational costs hinder conventional reservoir simulations. This research presents a multi-output machine learning model to simultaneously predict both incremental oil production and CO₂ storage volume. A selected global dataset of 173 projects was compiled, preprocessed, and optimized. Among the evaluated algorithms (random forest, gradient boosting, and random forest chain), gradient boosting achieved the best predictive performance, with a weighted coefficient of determination (R²) of 0.722. Model analysis showed that permeability, depth, and miscibility strongly influence oil recovery (R² for gradient boosting = 0.87), while the predictability of storage volume is low (R² for gradient e boosting = 0.5), which is significantly affected by reservoir depth and porosity. This study highlights the potential of machine learning as a rapid screening tool for evaluating carbon capture, utilization, and storage projects, identifying the performance of key factors, and emphasizing the need for standardized storage reporting to improve prediction accuracy.
CO2-EOR; CO2-Storage; CCUS; Subsurface Storage; Geological Field Data; Machine Learning
Copyright (c) 2026 The Author(s). Published by College of Engineering, University of Baghdad. https://creativecommons.org/licenses/by/4.0/
Optimization and adsorption modeling of lead ions (II) on carbonaceous materials: Comparative evaluation of raw and citric acid-modified commercial activated carbon and tea waste derived biochar
The article investigated the effectiveness of removal (R%) of a batch study in the removal of lead (II) ions from synthetic aqueous water. A number of experiments were performed to determine the optimal parameters for the maximum removal procedure by using commercial activated carbon. The primary process variables studied included initial lead (II) ions concentration (pb (II)), pH, adsorbent particle size, dosage of adsorbent, and adsorption time. The maximum removal occurred at an initial pb (II) ions concentration of 10 ppm, a pH of 5, an adsorbent dosage of 0.3 g with a particle size of 75 µm, and an adsorption time of 75 min. This research employed isotherm models to determine how the system reached a stable state. Langmuir model confirmed the largest accuracy, as evidenced by the results with a correlation coefficient (R²) of about 97.91%. The kinetic data was the most accurately described by pseudo-second-order model (PSO), suggesting that chemisorption is the limiting factor in the reaction rate, which was supported by a correlation coefficient of 99.5%. Four different adsorbent materials were investigated to evaluate their lead ions (II) removal %: commercial activated carbon (CAC), tea waste-derived biochar (TWDB), and CAC and TWDB modified with citric acid (CAC-CA and TWDB-CA). The study demonstrated that these four adsorbents were very effective and inexpensive agricultural waste may serve as an efficient method to remove pb (II) ions from contaminant water.
Lead Ions (II) Removal; Adsorption; Commercial Activated Carbon; Isotherms and kinetics; Tea Waste Derived Biochar; Citric Acid Modification
Adopting the addition of iron waste as a source for iron (II) ion in Electro-Fenton system for the removal of triple dyes
Use of electrodes that provide a high surface area for reaction, such as Nickel foam and Carbon Fiber Felt, has proven highly efficient in treating wastewater. In this study, a mixture of dyes (Eosin Y, Methylene Blue, and Methylene Violet) was treated using Ni foam as a cathode and carbon fiber felt as an anode in the Electro-Fenton process, relying on iron waste, such as iron filings, as the catalyst source. The analysis characterization of electrodes and iron filings was determined by Energy dispersive X-Ray (EDX) and Scanning electron microscopy (SEM) tests. The results showed high efficiency in decomposing the dye mixture. The highest Re % 96.4591 which attained after accomplishing the experiments based on Response Surface Method (RSM) was recorded at 75 mA of current, 0.25 g/L of iron filings concentration, and 0.015 M of electrolyte concentration. The highest specific energy expenditure for this process was 6.892939 kWh/kg of dyes. In addition to the process's energy efficiency, using iron scrap as a cheap alternative to expensive iron salts is a cost-effective and environmentally friendly approach.
Triple Dyes; Electro-Fenton; Iron Filings; Response Surface Methodology; Ni-Foam; Carbon Fiber Felt
Carbone dioxide sequestration using downhole water sink (DWS) technology: Effects of well placement on trapping efficiency, leakage, and reservoir pressure
Geological CO₂ sequestration is a widely accepted technique that consists of safely and securely hiding carbon emissions from human activities by storing them underground. It is considered the main method of carbon dioxide capturing and sequestration because of its large-scale application. Use of Downhole Water Sink (DWS) systems and other advanced reservoir control technologies is driven by the necessity to manage effectively the reservoir pressure change, the CO₂ plume migration, and the leakage pathways. The effectiveness of the DWS technology in providing better CO₂ storage performance in a depleted reservoir surrounded by a saline aquifer has been the focus of this research. The study analyzed three operational scenarios to evaluate how the different distances between the DWS wells and the CO₂ injectors would affect the storage efficiency, the leakage behavior, and the management of the reservoir pressure. Scenario 1 had DWS wells located right under the CO₂ injectors which caused negative hydrodynamic interactions, decreased the total trapped CO₂ and increased the leakage indices. Scenario 2 had a tiny lateral offset which led to small improvements in trapping and tiny increases in leakage, implying partial but still insufficient mitigation of injector-sink interference. In Scenario 3, with a 10-grid offset between the injection and extraction wells, achieved the maximum CO₂ storage efficiency, where trapping gained 2.79% (431,235 tons) at a CO₂ injection rate of 20 MMSCF/day and a DWS flow rate of 12,500 bbl/day. Leakage did not change, maintaining a Leakage Index of +0.06898 which indicated only a slight increase that was barely noticeable when compared to the more varying responses in Scenarios 1 and 2. In addition, the operation of DWS in Scenario 3 led to a peak pressure of the reservoir that was lower than that of the case without DWS, as the pressure dropped from about 6150 psi to 5100–5794 psi, thus relieving some of the stress on the formation. Although no specific fracture pressures or geomechanical analyses were performed, the pressure drop is likely to create better injection conditions and also enhance the integrity of the storage area. The overall results show that the DWS wells, when placed and managed properly and strategically, can not only increase the CO₂ trapping efficiency but also stabilize the leakage behavior and provide pressure control, thus making the geological CO₂ sequestration more reliable.
CO₂ sequestration; depleted reservoirs; downhole water sink (DWS); leakage index; saline aquifers; trapping efficiency; Reservoir pressure management; well placement; CO₂ trapping mechanisms
Hybrid particle swarm neural network and regression models for dew-point pressure prediction
Accurate prediction of dew-point pressure (DPP) is essential for the development and production management of gas condensate reservoirs; however, existing empirical correlations and standalone machine learning models often suffer from limited generalization and sensitivity to data variability. This study addresses this gap by developing and comparing a nonlinear multiple regression (NLMR) correlation and a hybrid particle swarm optimized neural network (PSONN) model using a large and diverse dataset of 880 experimental samples collected from published literature and Middle East reservoirs. The PSONN model was selected due to its capability to overcome neural network limitations such as slow convergence by optimizing network weights through global swarm intelligence. The hybrid PSONN model achieved superior predictive accuracy with APRE of 2.45% and CC of 0.997, outperforming both the proposed NLMR correlation and previously published models. The results demonstrate that the developed hybrid framework can significantly improve dew-point pressure estimation, thereby supporting reliable reservoir characterization, surface facility design, and production planning in gas condensate fields.
Hybrid; Neural network; Particle swarm; Nonlinear regression; Dew-point pressure
Sustainable CO2-basd acidizing: A comprehensive review of chemical additives for enhanced carbonate reservoir stimulation
CO₂-based acidizing provides a corrosion-resistant alternative to potent mineral acids in carbonate reservoirs by producing carbonic acid in situ. This method synchronizes stimulation procedures with carbon-management objectives while minimizing the necessity for comprehensive corrosion-inhibitor systems. This review assesses six categories of chemical additives—amines, inorganic salts, inorganic bases, metal-oxide nanoparticles, biological macromolecules, and natural biopolymers—emphasizing their effects on CO₂ absorption, pH buffering, and wormhole morphology at reservoir-relevant temperatures and salinities. Experimental findings indicate that specific formulations can achieve CO₂ absorption levels reaching 2612 mg/L while maintaining pH levels between 4.5 and 5.2. Furthermore, computed CT imaging confirmed consistent wormhole development, indicating effective acid transfer and diminished corrosion risk. According to the reviewed literature, natural biopolymers and biological macromolecules provide the most advantageous equilibrium of reactivity and environmental compatibility; however, the heterogeneity of experimental data, diversity of reservoirs, and scalability are significant considerations. This review methodologically synthesizes peer-reviewed research and field reports published till October 2025, emphasizing mechanistic insights and identifying shortcomings in converting laboratory performance to field application. The proposed approach connects additive selection to carbonate reactivity, transport mechanisms, and operational limitations, thus informing the development of multifunctional fluids for sustainable stimulation and carbon-conscious reservoir management.
CO₂ acidizing; Carbonate reservoir stimulation; Chemical additives; In situ acid generation; Carbon sequestration; CO2 uptake
Silica sand-supported nZVI-Cu nanoparticles synthesized in a green method for antibiotics removal from aqueous solutions
It is challenging to remove antibiotics from water bodies, as they are among the most widespread contaminants in the environment, particularly with conventional wastewater treatment methods, due to their persistence and low biodegradability. The current study examined the use of nanoscale zero-valent iron to remove antibiotics. Conocarpus leaf extract, which is primarily composed of polyphenols like flavonoids and tannins, was employed as a green source to prepare Fe/Cu nanoparticles, which can act as an eco-friendly reducing agent. The nanoparticles were immobilized onto silica sand (SS), forming SS-Fe/Cu nanocomposite to remove tetracycline (TC) and ciprofloxacin (CIP) from aqueous solutions. The structural characteristics of the produced nanocomposite were examined using a number of analytical techniques, including XRD, FTIR, FE-SEM, EDS, TEM, BET, TGA, and DSC. The structural and morphological analyses confirmed the successful synthesis of the SS–Fe/Cu nanocomposite, with well-dispersed nanoparticles (FE-SEM/TEM), characteristic functional groups (FTIR), crystalline structure (XRD), surface area enhancement (BET), elemental composition (EDS), and good thermal stability (TGA/DSC). Studies were conducted through batch experiments, and the influence of various variables (contact time, pH, agitation speed, nanocomposite dosage, and initial pollutant concentration (Co)) was investigated. The maximum removal efficiencies of 93% and 85% were achieved for TC and CIP, respectively, under ideal conditions: time = 90 min, pH of 11 for TC and 7 for CIP, agitation speed = 200 rpm, Co = 10 mg/L, and nanocomposite dosage of 1 g/50 mL. Isotherm, kinetic, and thermodynamic studies showed that adsorption of both TC and CIP followed the Freundlich model and pseudo-second-order kinetics, indicating chemisorption as the main mechanism. Thermodynamic results revealed that TC adsorption was endothermic and non-spontaneous (positive ΔS°), while CIP adsorption was exothermic and spontaneous (negative ΔS°), confirming the efficiency of the SS–Fe/Cu nanocomposite. The results revealed that the green-fabricated SS-Fe/Cu nanocomposite could be used as an efficient agent for extracting TC and CIP from aqueous solutions.
Conocarpus leaf extract; nZVI; SS-Fe/Cu nanocomposite; Tetracycline; Ciprofloxacin; Adsorption
Glutaraldehyde-crosslinked chitosan reinforced with nanoparticles for wastewater treatment: Chemical structure modification
Lead (II) pollution from the various industries is a serious environmental problem that requires urgent attention due to its stability and non-biodegradability. Current research addresses the development of a natural polymer's chemical structure to produce an absorbent nanocomposite for lead removal. This development relied on the available functional groups (amino-NH2 and hydroxyl-OH groups) in biopolymers to create adsorbent material through two steps. The first step was chemical bonding of chitosan with glutaraldehyde as a crosslinking agent (CT-GLA) using emulsion cross linking technique, followed by another bonding with a heterogeneous organic compound to provide additional functional groups (CT-GLA-PD). The second step involved supporting the compound with copper oxide nanoparticles (CT-GLA-PD-Cu) to improve characterizations of the adsorbent. The chemical structure of the materials prepared by paraffin dispersion followed by nanoparticle support was carried out in the current study to explain the functional groups that disappeared and formed during the preparation stages. The surface characterization and chemical composition of the adsorbent resulting from the two stages were performed using advanced descriptive techniques such as Fourier Transform Infrared spectroscopy, X-ray Diffraction, Field Emission Scanning Electron Microscope and Energy Dispersive X-ray. According to the experimental data, the chemical modification showed a significant enhancement in morphology properties and composition elements, which positively impacted removal efficiency. This structure development has been reflected in the lead removal efficiency compared to the raw adsorbent. The results showed that the adsorbent produced in the first stage achieved acceptable lead removal efficiency. This performance was further doubled after the use of nanoparticles as supporting material in the second stage.
DBT oxidation; Adsorption; Chitosan; Copper oxide; Composite; Emulsion; Glutaraldehyde
Adsorption of methyl violet dye using MgO nanoparticles: Synthesis and kinetics
A scalable method of oxalate co-precipitation was used to prepare magnesium oxide (MgO) nanoparticles. The precipitant used was oxalic acid and the source of soluble magnesium was magnesium sulfate. Highly crystalline MgO nanoparticles prepared by calcining at 700 were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and Atomic Force Microcopy Analysis (AFM). The (MgO) nanoparticles were employed to investigate the adsorption performance of Methyl Violet (MV) dye from aqueous solutions under different conditions, i.e., contact time, pH, dye concentration and temperature. Maximum adsorption (96%) was obtained at time (60 min.), pH 6, at (20 ) and adsorbent dosage (0.05 g/L). It was found that the effect of temperature is inversely proportional to the percentage of dye removal in the studied range (20-50 ). Pseudo-second-order (R2=0.9968) and Langmuir models (R2=0.9931) described excellent fits in kinetic and isotherm experiments, respectively, indicating monolayer coverage and chemisorption. The greater adsorption capability of MgO was verified in comparison to equivalent adsorbents (qmax=83.1 mg/g).
Magnesium Oxide Nanoparticles; Methyl Violet Dye; Adsorption Isotherm; Adsorption kinetics
Photocatalytic degradation of a cationic dye using Ag2O@CuO nanoellipsoidal photocatalyst under ultraviolet irradiation
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.
Bimetallic oxide; Co-precipitation; Copper oxide; Photocatalysis; Rhodamine B dye; Silver oxide
Copyright (c) 2025 The Author(s). Published by College of Engineering, University of Baghdad. https://creativecommons.org/licenses/by/4.0/
Petroleum refinery wastewater degradation by heterogeneous-electro-fenton process using activated carbon loaded with Iron and Cerium: A kinetic study
This work aims to study the kinetics of heterogeneous electro-Fenton (HEF) process used to treat petroleum refinery wastewater by a catalyst made of an activated carbon loaded with iron and cerium. Effects of HEF operating variables such as current density, dose of catalyst, and pH on the removal of COD and reaction rate constant (kapp) were examined. Results showed that decline of COD with time at different operating conditions obeys a pseudo-first-order kinetics with a regression fitting (R2) not less than 0.97. Furthermore, increasing the current density was found to give higher rate of COD removal and kapp to a limit beyond which no longer enhancement can be achieved. Similar behaviour regarding to the dose of catalyst while increasing pH has an adverse effect. The best operating conditions that give high rate of COD removal and kapp were a current density of 10 mA/cm2, a dose of catalyst equal to 1.0 g/L, and a pH of 3, in which 86.97% of COD was removed with kapp value equal to 0.0188538 min-1 which required only13.06 KWh/kg COD as an electrical energy consumption. The present system approved to have high reaction rate and could be applied to treat various types of wastewaters.
petroleum refinery wastewater; pseudo first order kinetics; heterogeneous electro-Fenton; Advanced oxidation process
Experimental study of gas-brine capillarity measurement at high temperature and pressure
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.
Capillary Pressure; Coreflooding; HPHT; Gas Reservoir
Prediction of cadmium removal efficiency by emulsion liquid membrane using an artificial neural network
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.
emulsification; surfactant; cadmium removal; emulsion; artificial neural network
Design and evaluation of advanced nanocomposite drilling fluid systems through marl-based lithologies: A study based on outcrop samples from Kurdistan
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.
Nanotechnology; Drilling Engineering; Marl-Rich Formation; Swelling, Rheological and Filtration
Kinetic modeling of Dodonaea viscosa decomposition under microwave-assisted pyrolysis: A combined model-fitting and iso conversional approach
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.
Microwave-assisted pyrolysis; Dodonaea viscosa; Thermogravimetric analysis (TGA); Kinetic modeling; Isoconversional methods; Activation energy
Sustainable air gap membrane distillation using recycled acrylic (RA) membranes: Application to Shatt Al-Arab water desalination
One of the research motivations in the MD field is to develop high-performance membranes by preparing hydrophobic membranes due to their high throughput and rejection. The current work focuses on the fabrication and performance evaluation of electrospun nanofiber membranes using recycled acrylic (Polymethyl Methacrylate) (RA) via air gap membrane distillation (AGMD). Recycling this material not only reduces plastic waste and pollution, but it also offers a low-cost alternative to virgin polymers, which aids in membrane fabrication. Scanning Electron Microscopy (SEM) confirmed a uniform, highly porous nanofibrous structure with interconnected pores in the prepared nanofiber membranes. Atomic Force Microscopy (AFM) revealed a rough surface morphology, while water contact angle measurements exceeding 121° indicated excellent hydrophobicity, critical for effective liquid-vapor separation. Fourier-transform infrared spectroscopy (FTIR) verified the preservation of key ester functional groups, confirming the chemical integrity of the RA. The assessments revealed that the electrospun nanofibers demonstrated considerable flexibility while preserving their structural and surface characteristics as evaluated through mechanical strength testing. The resulting membranes were utilized in a water desalination process employing an AGMD setup, tested under varying feed temperatures (45, 55, and 65°C) and flow rates (0.2, 0.3, and 0.4 L/min) to evaluate their impact on desalination efficiency. It was observed that increasing the feed temperature significantly boosted water flux; moreover, the feed flow rate notably improved permeate flux within AGMD systems, thereby enhancing mass and heat transfer capabilities. The highest permeate flux recorded was approximately 19 kg/m²·hr, achieved at a temperature of 65°C with a flow rate of 0.3 L/min and a salt rejection rate of 99.999%. Consequently, this study's results indicate that RA-based nanofiber membranes hold potential for sustainable and effective water desalination. Furthermore, AGMD proved to be highly efficient in salt removal from the Shatt al-Arab river and may serve as a viable solution for providing clean drinking water in southern Iraq.
Desalination; Air gap membrane distillation (AGMD); Electrospinning system; Hydrophobic polymer; Nonwoven Nanofibers; Shatt al-Arab River
Implementation of chemical injection with WJSTP in the Gullfaks field attributed to reservoir permeability
The Gullfaks field is a complex field and it’s divided into several formations, which have reservoirs in several stratigraphic layers and fragments of numerous faults. With current technological advancement techniques used in the Gullfaks field, the WJSTP is one of the solution-testing platforms that focuses on treating produced water for re-injection back into the reservoir to increase oil production. The implementation of chemical injection with WJSTP in the Gullfaks field, attributed to reservoir permeability to increase oil production, is the aim of this paper. To attest to the set aimed, a three-dimensional static model of the reservoir is constructed using data provided by NGB Geosciences Consulting LTD. With credit to the Petrel software simulation tool, an in-place volume estimate of 2,748,727,672.95 Bbls of oil and 970,264,150,943.39 SCF of gas was reviewed. Subsequently, a dynamic model is constructed on the foundation of the static model and the specified water injection parameters, and simulated with the use of the Eclipse software. The reduction in permeability of the reservoir's high-permeability zones through chemical injection of WJSTP resulted in 70% oil recovery, representing a 44.99% increase, and 74% gas recovery, representing a 37.9% increase. The sensitivity analysis conducted on oil price, oil production, and investment demonstrates that the viability of the project is highly contingent on the oil price. The findings of this study indicate that chemical injection of WJSTP represents a technically feasible and economically profitable method of enhancing oil production in the Gullfaks field.
Gullfaks field; static and dynamic model; permeability; WJSTP; Petrel; Eclipse; profitability
Ciprofloxacin adsorption via compressed wood activated carbon with ZnCl2 activating agent from simulated wastewater: Mechanism studying
The current study objective is to synthesize activated carbon (AC) from compressed wood using the ZnCl2 activating agent and to assess the ciprofloxacin (CIP) elimination efficiency in simulated wastewater. The produced AC was characterized using multiple techniques, including SEM, BET, FTIR, AFM, and XRD. The adsorbent demonstrates high adsorption performance, achieving 91% removal of CIP within 5 hours at an initial pollutant concentration of 100 mg/L with an AC dose of 2 g/L. Experimental data correspond to the Freundlich isotherm model (R² = 0.995) as well as the Langmuir competitive fitting (R² = 0.99), while the root mean square error (RMSE) equation best fits the Langmuir model. Moreover, the pseudo-second-order model (R² = 0.999) was used to describe the kinetic data. The adsorption thermodynamics indicate spontaneous adsorption with exothermic behavior (ΔG◦<0, ΔH◦<0, ΔS◦<0). A combination of mechanisms contributed to the CIP adsorption process (π-π interaction, hydrophobic interaction, bulk diffusion, hydrogen bonds, in addition to physical and chemical adsorption mechanisms). Pyrolysis recoverability shows a good result after three cycles (qe = 101.08 mg/g, compared to 170.13 mg/g in the first cycle). In conclusion, compressed wood AC offers a sustainable, low-cost adsorbent for treating wastewater and presents a prospect for addressing ecosystem contamination challenges.
Compressed wood; activated carbon; ZnCl2 activating agent; intraparticle diffusion; Temkin model; ciprofloxacin; adsorption mechanism; exothermic adsorption
Field development planning using an active surrogate model and optimization algorithms for a Southern Iraqi oil field
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.
DeepEnsemble; Optimization; Proxy Model; Well Placement; Field Development
Characterization and kinetic studies of oxidation desulfurization of model diesel fuel in an oscillatory baffled reactor using co-magnetic active oxides over activated carbon catalyst
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.
DBT oxidation; Co-active catalyst; Activated carbon; Oscillatory baffled reactor; Kinetic parameters
Enhanced transportation of crude oil from the East Baghdad field using kerosene mixed with silica nanoparticles and the presence of surfactant
This study investigates the enhancement of heavy crude oil transportability from the East Baghdad Oil field through viscosity and density reduction. The proposed approach combined the use of silica (SiO₂) nanoparticles, kerosene, and the anionic surfactant SDBS. Prior to application, the silica nanoparticles were thoroughly characterized using thermogravimetric analysis (TGA), X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (SEM-EDX). These techniques confirmed the particles’ thermal stability, crystalline structure, nanoscale morphology, and elemental composition, validating their suitability for crude oil modification. A nanofluid was formulated with 18 vol% kerosene, 2 wt% SiO₂ nanoparticles, and 10wt% surfactant relative to nanoparticle mass. The mixture was dispersed ultrasonically under controlled thermal and temporal conditions. Optimal performance was achieved at 75 °C and 60 minutes of mixing, reducing viscosity from 58.15 cP to 16.53 cP and increasing API gravity from 19.67 to 28.84. Further enhancement was achieved with increased additive concentrations of 30% vol. kerosene, 3,000 ppm SiO₂, and 300 ppm surfactant, yielding a viscosity of 5.5 cP and an API gravity of 32.67. These results correspond to improvements of 90.5% and 66%, respectively. Control experiments using kerosene alone highlighted the superior efficiency of the ternary system. Given its affordability and availability, kerosene contributes to the practicality of this technique, offering a scalable and economically viable strategy for upgrading heavy crude oil in real-field applications.
Heavy crude oil; East Baghdad field; Reducing viscosity; Density; Nanoparticles; Silica; Kerosene; Surfactant
Comparative evaluation of hydraulic fracturing performance in vertical and horizontal wells using pipesim software
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.
Halfaya oil field; hydraulic fracturing; horizontal wells; vertical wells
Enhancing nanofiltration desalination performance using air sparging technique
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.
Air sparging; Nanofiltration membrane; Permeate flux; Concentration polarization; pressure; Feed concentration; Temperature
Characterization of fluid properties and pseudo-fraction analysis for oils with low gas oil ratios
The Sadi reservoir is one of the largest and most important unconventional tight oil reservoirs in southern Iraq. However, it suffers from low production rates, necessitating many development strategies that require a correct and reliable characterization of reservoir fluid properties. Whilst these properties are originally obtained from laboratory experiments, measurement errors often occur despite rigorous workflows, which negatively affect the calculation of reservoir fluid properties. This study utilizes the fluid thermodynamics characterization program (PVTp) to generate a reliable model for determining the oil properties of Sadi reservoir. A methodology was developed to simulate fluid thermodynamic tests, including Differential Liberation (DL) and Constant Composition Expansion (CCE) tests. This was achieved through adjusting the Peng-Robinson Equation of State (PR-EOS) by splitting and lumping the C7+ plus fractions and calibrating the Ω parameters to match model results with experimental data using regression. Using the absolute average error (AAE) as a model performance benchmark, the model achieved an AAE of 1% for estimating the relative volume, 0% for estimating oil density, 0.41% for estimating oil formation volume factor, 4% for oil viscosity, and 5% for the gas oil ratio. These values represent the highest AAE recorded for this dataset and show good agreements within the acceptable limits. The PR-EOS model proves to be an accurate fluid characterization alternative that can be applied to similar field data, providing a valuable tool for reservoir management, improving performance, and reducing costs in the future.
Sadi Reservoir; PVT modeling; Equation of state; Splitting and Lumping; Regression
Tetracycline removal from aqueous solution through photo-anodic oxidation process using rotating graphite cylinder anode
In the present work, tetracycline (TC) was removed from a simulated wastewater through a new photo-anodic oxidation process with a rotating graphite cylinder anode. The effects of current density, pH, rotation speed, and NaCl addition were evaluated. The results confirmed that increasing the current density results in improving the removal of TC. However, increasing the current density beyond 5 mA/cm2 had little effect on TC removal. Results revealed that TC removal using photoanodic oxidation can be achieved at high performance with an initial pH of 5. Increasing or decreasing pH beyond this value has a negative effect on TC removal. Increasing rotation speed gave better performance for TC removal due to the increase in mass transfer. The addition of NaCl improved the removal efficiency of TC due to the participation of indirect anodic oxidation within the oxidation process. The best conditions were: current density of 5mA/cm2, pH=5, 250 rpm, and the addition of 1 g/L NaCl, in which TC removal of 84% was achieved that claims (103 kWh/m3) as a total electrical energy consumption. In comparison with the anodic oxidation process alone, photo-anodic improved TC removal by an increment of (13.73%), confirming the photo-anodic process can be adopted successfully for treating wastewaters.
Tetracycline; anodic oxidation; photo-oxidation; rotating anode; graphite; wastewaters
Efficient treatment of petroleum refinery wastewater by an induced electro-Fenton process
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.
Induced Electro-Fenton; Petroleum refinery wastewater; Fenton reaction; COD removal
Green synthesis of NiO nanoparticles with activated carbon from Ficus carica leaf and extract for malachite green removal
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.
Ficus carica leaf; green synthesis nanoparticles; activated carbon; malachite green
Optimum design and performance analysis of a gas lift system in the carbonate reservoir of Ahdab oil field
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%.
Ahdab oilfield; Artificial lift; Gas lift, Pipesim; Oil production
Improving the elimination of methyl orange dye by combining electrocoagulation system with the adsorption process by oven-dried alum sludge: adopting different combined systems
Due to their recalcitrant characteristics, Azo dyes such as methyl orange (MO) are extremely poisonous substances, making their removal from textile industry wastewater a major problem. By employing various EC-Adsorption combined system configurations and reusing alum sludge as an adsorbent, the current study seeks to investigate the efficiency of these various systems in removing MO dye. To estimate their benefits and limitations, experiments were carried out utilizing nickel foam (NiF) and aluminum plate (Al plate) as anodes, and stainless-steel mesh (SS mesh) as cathode in the presence of alum sludge as an adsorbent in all systems. The EC-Adsorption combined system with NiF as anode and two SS meshes as cathodes with 10 g/L of alum sludge in the solution, which is referenced as S3, offered 98.968% of MO dye removal efficiency within 30 minutes without the need for prolonged treatment and with very low concentration of leached Ni ions. The BET surface area, pore size, surface morphology, and composition of alum sludge were examined. The utilization of alum sludge in the combined system enhanced the removal of excess Ni ions and reduced its impact in the treated solutions, and moderately enhanced the MO dye removal efficiency. To attain a detailed explanation of the adsorption mechanism, various kinetics and isotherm models were applied. The adsorption of MO dye in the S3 EC-Adsorption system follows the intra-particle diffusion model, and the best-fit isotherm was the Freundlich isotherm.
combined systems; alum sludge; electrocoagulation; Adsorption; kinetic model
Removal of Ni and Cd cations from wastewater using photocatalytic reactions: Review paper
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.
Cadmium; Heavy metal ions; Nickel; Photocatalyst; Wastewater