Journal of Petroleum Research and Studies

Separator Control of Tuba Degassing Using Model Predictive Control (MPC)

Seaar Al-Dabooni, Zainab A. Ashour — Mon, 21 Sep 2026 00:00:00 +0300

The Proportional-Integral-Derivative (PID) controller is widely used in the Basrah Oil Company (BOC) to control oil equipment, such as the inlet and outlet valves of separators in degassing sites. PID controllers are simple and do not require a full model of the equipment to be controlled. However, they can be difficult to tune, and the trial-and-error method used by BOC engineers can be risky and inefficient. Additionally, PID controllers are single-input and single-output, which limits their flexibility. Otherwise, Model Predictive Control (MPC) is a multi-input and multi-output (MIMO) controller that can be used to control complex systems with multiple interacting variables. MPC also requires a model of the system, but this model can be uncertain. In this paper, we use MPC to control the valves of a three-phase separator in the Tuba degassing station of the Tuba oil field in Basrah city. We use a Matlab program to derive a model of the separators’ valves from collected data stored in the Distributed Control System (DCS) network control system. We compare the responses of the PID and MPC and show that the MPC performs better. We also estimate that using an MPC instead of PID controllers could improve annual gas production by 58.5% and oil production by 87.2% (equivalent to 31,800 barrels of oil). This would not only increase oil and gas production but also reduce gas flaring and oil-water mixing. Therefore, MPC is a promising alternative to PID controllers for controlling oil equipment to improve performance, reduce risks, and increase efficiency.

Aphron-Microbubbles: A Friendly Innovation in Enhancing Water-Based Mud Performance for Future Drilling Operations in Iraqi Depleted

Waleed K. Mutter, Faleh H. Mohammed, Maryam M. Ahmed — Mon, 21 Sep 2026 00:00:00 +0300

Microbubble-based Aphron drilling fluids (ADFs) are becoming a viable option of the mud system in the oil and gas sector nowadays and for good reason, they can pass through reservoir rocks without being left inside the tiny pores. Surfactants are the source for developing microbubbles inside the conventional drilling and completion fluids that improve the main characteristics of the drilling mud including density, rheology, filtration and wellbore stability. Most of the oilfields in northern Iraq are in the state of depletion and can’t be drilled using the conventional drilling fluids due to the lost circulation and instability problems.

This study investigates the role of Aphron -a microbubble drilling fluid that excels in decreasing the potential of circulation loss inside the borehole by minimizing the differential pressure. Hence, several ADFs with low density were developed using environmentally friendly surfactants, such as CTAB and SDBS at different concentrations. All the necessary measurements of density, pH, viscosity, gel strength and filtration properties were performed according to the American Petroleum Institute (API) standards.

The obtained results show that Aphron-microbubbles have a major impact on the density where it was lowered by 32%. In addition, the fluid loss rate was lowered by 46% with 0.15% w/v of the SDBS surfactant.

Lithology and Reservoir Characteristics of the Euphrates Formation in the Y Oil Field of Northern Iraq

Peshwar K. M. AL-barzanji, Ahmed I. S. AL-Naemi, Saad A. M. Al-Hamdani — Mon, 21 Sep 2026 00:00:00 +0300

This research studies the lithology and reservoir characteristics of the Euphrates Formation in the Y Oilfield, which is located in the low fold’s zone 80 km southeast of Kirkuk City and 10 km north of Salah Al-Din City. The research focuses on the Euphrates Formation, which belongs to the sedimentary cycle of early Miocene.

The objective of this research is to analyze the lithological section of the Euphrates Formation, which has been divided into three reservoir units (Euph.1, Euph.2, and Euph.3), using well logs and cross-plot techniques. The study focuses on three selected wells (Well-A, Well-B, Well-C), employing Gamma Ray, Neutron, Density, Sonic, and Resistivity log data, which were processed using Techlog software. The aim is to calculate essential petrophysical properties such as effective porosity, permeability, and water saturation. These properties are then used to evaluate the reservoir characteristics and identify the most suitable reservoir units for hydrocarbon exploitation.

The results of the research showed a two type of lithological facies in the Euphrates Formation, consisting mainly of limestone and dolomite. The analyses show that the Well-C shows the best reservoir characteristics, with a range effective porosity of 11-26%, oil saturation between 81-89%, and permeability of 55 mD, making it more suitable for hydrocarbon exploitation. while the Well-B showed less efficient reservoir properties due to the presence of anhydrite bed, which reduce the permeability of formation. In addition, the Well-C has a net pay thickness of 74.92 m, which enhances production capabilities.

This research emphasizes the importance of using well logs to analyze reservoir characteristics, which contributes to improving resource exploitation plans and directing exploration efforts towards the most productive areas, and highlights the role of facies analysis, porosity and permeability in determining the reservoir characteristics of geological formations.

Machine Learning and Flow Zone Indicator for Permeability Estimation in Uncored Intervals of a Southern Iraqi Oil Field

Mohammed Rajaa, Ayad A. Al-haleem — Mon, 21 Sep 2026 00:00:00 +0300

The precise estimation of permeability is a difficult task due to the nature of heterogeneous reservoirs. Attributable to the high costs of core sampling and the poor accuracy of the linear regression method, the Flow Zone Indicator (FZI) method is regarded as one of the most commonly used techniques in Iraqi fields in recent years to predict permeability. However, this method requires statistical or machine learning to predict FZI in uncored intervals. This study aims to identify the most suitable machine learning model for FZI prediction in uncored intervals using conventional well logs as input. Following this, the reservoir is divided into hydraulic flow units (HFUs) using unsupervised learning. Specifically, AutoGluon is used as an automated machine learning framework to find the best algorithm and optimal hyperparameters for FZI estimation. The k-means algorithm was employed to classify the reservoir into HFUs. This integrated approach was applied to a field case study in southern Iraq. The study utilized both core and log data from three wells. The results demonstrated that the neural network (NN) outperformed the other algorithms within the framework, achieving more than an R² of 90% and a root mean squared error (RMSE) of 1.69 on the test data, and more than an R² of 96% and an RMSE of 0.493 on the training data. By applying the derived correlations for each HFU, the permeability prediction achieved an R² of 85% and an RMSE of approximately 0.37. This demonstrates the effectiveness of the automated machine learning framework in improving FZI estimation and, consequently, permeability predictions.

Predictive Maintenance in the Oil and Gas Industry: A Literature-Based Analysis of Techniques and Their Impact on Equipment Reliability

Abaas Abdulmaged — Mon, 21 Sep 2026 00:00:00 +0300

The global supply of energy depends heavily on the oil and gas industry nevertheless unexpected equipment failures cause substantial financial consequences alongside operational interruptions. Predictive Maintenance )PdM( has gained popularity because it increases reliability while reducing costs through IoT sensors and real-time data applications of machine learning. Existent scholarly research demonstrates restricted effectiveness of these methods in industrial domains because of extreme operational parameters and complicated data acquisition methods and substantial implementation expenses. The analysis employs systematized reviews of PdM techniques used in the oil and gas industry to assess their utility while identifying functional implementation challenges. The fundamental achievement of this study produced an extensive evaluation of PdM approaches which measured their measurement accuracy and cost-saving potential while demonstrating reliability improvement gains. The research team used PRISMA guidelines for conducting a systematic review which included 1,842 peer-reviewed scholarly works from 2015 to 2023 and obtained 1,325 studies after eliminating duplicates. The application of predictive maintenance by Aramco, Shell and ExxonMobil reveals that companies can achieve $2.8M annual cost savings as well as a 28% improvement in mean time between failures (MTBF). The studies demonstrate that Random Forest exhibits 85.7% accuracy while LSTM detects faults twenty-two percent earlier than traditional systems do. The results from statistical tests (including ANOVA alongside ROC curves) validate that AI-powered PdM gives better outcomes than established approaches do. The Weibull distribution demonstrates that reliability has improved because the objects show a 63.2% chance of failing after 2,000 hours

Developing novel systems for processing high-value refinery products

Haider M. H. Alkhafaji — Mon, 21 Sep 2026 00:00:00 +0300

This study presents new systems to help refineries make valuable products. The goal is to produce more, work better, and be kinder to the environment. The research uses new chemical methods and separation techniques to find better catalysts for hydrocracking and hydrotreating. Machine learning is used to improve these catalysts and forecast how well they work under different conditions. Tests in a continuous flow reactor showed a 30% increase in the amount of valuable products compared to old methods. This is because the catalysts used are stable and selective, which helps reduce unwanted byproducts. Better separation technologies made things more efficient, and using machine learning shows how it can help improve processes. In summary, these improvements help make the refining industry better for the environment. They support the need for new technologies that can meet increased demand while reducing harm to the environment. This leads to cleaner energy and helps the industry last longer

Preparation and Characterization of MoO3/TiO2 Catalysts for Hydroisomerization of n-Hexane

Sara A. Al-Naib , Sattar J. Hussein, Haider A. Al-Jendeel — Mon, 21 Sep 2026 00:00:00 +0300

This research investigated the isomerization of n-hexane using molybdenum trioxide supported on titanium dioxide as a catalyst. The study explored the effect of liquid hourly space velocity (LHSV) and reaction temperature on n-hexane isomerization. The synthesized catalyst contained 20.46 wt.% molybdenum trioxide, with LHSV values ranging from 0.5 to 2 hr-1 and temperatures between 200oC and 275oC. The research aimed to identify the best reaction conditions, specifically temperature and LHSV, for maximizing the conversion of n-hexane to isomers. The results indicated that the highest conversion, 53.21%, occurred at an LHSV of 0.5 hr⁻¹ and a temperature of 275°C. The reaction followed first-order kinetics with an activation energy of 25.753 kJ/mol.

A Review on Desulfurization of Kerosene: Current Practices and Future Innovation

Haider J. Ismaeel, Safaa M. R. Ahmed — Mon, 21 Sep 2026 00:00:00 +0300

Kerosene desulfurization is one of the most pressing tasks for the petroleum sector because the amount of slfur emissions that affect air quality is more strictly controlled by legislation. This review addresses the growing scope and challenge of kerosene desulfurization technology by providing an integrative perspective on current practices and development trends. The perspectives presented in this paper aim to help improve the development of efficient and environmentally friendly solutions to meet changing social and industrial requirements. In this review, advanced desulfurization technologies are available for use in kerosene including hydrodesulfurization (HDS), oxidative desulfurization (ODS) and adsorption desulfurization methods to meet the permissible compliance level of the Global Fuel Standard (October 2023). HDS is very efficient and widely applied but there are a number of limitations to HDS such as high energy consumption and high maintenance cost as the refractory sulfur compound cannot be removed. This is because recent developments in utang technologies are of great interest as they may improve the degree of desulfurization at low environmental and economic costs. These include advanced catalyst designs, ionic liquids and bio-desulfurization techniques. The paper presents key aspects of new possibilities such as green chemistry application and hybrid setup of processes that utilize the advantages of several technologies to achieve better performance.

Correlation of TSB and Urea with Pb, Na and Mg in Workers of Fuel Station

Basim A. Twaij — Mon, 21 Sep 2026 00:00:00 +0300

Petrol, manufactured from crude oil, is a primary pathway of exposure to polycyclic aromatic hydrocarbons (PAHs). Among hazardous substances related to fuel-associated occupational exposure, benzene, being a natural component of crude oil and a byproduct from petrol refining, is classified as having one of the highest risks. The aim of this study was to compare serum levels of total serum bilirubin (TSB), urea, sodium (Na), magnesium (Mg), and lead (Pb) between fuel station workers and a control group of non-exposed individuals.

In this study, a total of 60 male fuel station workers and 30 male controls were recruited from Al-Najaf City, Iraq. Serum levels of urea, TSB, Na, and Mg were measured using spectrophotometric methods with commercially available diagnostic kits. Serum lead (Pb) concentrations were measured with flame atomic absorption spectrophotometry.

The results show that serum TSB and Pb levels were significantly higher among fuel station workers than in controls (p < 0.001, each). Conversely, serum levels of urea (p < 0.001) and sodium (p = 0.021) were significantly lower in the workers' group. No statistically significant difference was observed in serum magnesium levels between the two groups.

Correlation analysis in the workers' group showed a statistically significant negative correlation between urea and TSB (r = −0.446) and a statistically significant positive correlation between urea and Pb (r = 0.578). In addition, TSB correlated significantly and positively with Pb (r = 0.538, p < 0.01) and negatively with Na (r = −0.264, p < 0.05). Pb levels were negatively correlated with Na levels (r = −0.360, p < 0.01).

Artificial Intelligence for Optimal Chemical Dosing in Water Treatment Plants: A Comparative Study Using Random Forest and XGBoost Algorithms

Ali S. Abdulhussein — Mon, 21 Sep 2026 00:00:00 +0300

This research relies on artificial intelligence (AI) instead of laboratory testing (jar test) to determine the optimal dosage of chemicals (polymer, alum and micro sand) used to treat water at the Qarmat Ali site in Basra Governorate, which is used for reservoir injection in the Rumaila oil field. The research utilized the XGBoost and Random Forest algorithms. The results demonstrated high consistency with experimental results collected over three years. When comparing these two algorithms, the Random Forest algorithm consistently outperformed XGBoost in accuracy across all variable river water specifications. The results support the use of AI to determine the optimal dosage at any given moment and in all seasons, thereby improving export capacity and produced water specifications.

Ceramic Fiber and Refractory Castable Linings in a Refinery Furnace: A Case Report from Haditha Refinery

Mon, 21 Sep 2026 00:00:00 +0300

Most refinery furnaces have a metal shell around the entire assembly with a backup layer in the linings to protect the working lining from extreme conditions. Conventional thermal insulation approaches in small refinery furnace units have used refractory castable, while ceramic fibers offer different thermal properties, but this installation does not allow direct material comparison. This paper presents a case report of a 2023 crude oil heating furnace installed at Haditha Refinery, where ceramic fibers were used in the radiation zone (≈ 800 ^oC, 103 m²) and refractory castable in the convection zones (≈ 450 ^oC, 250 m²). Because the two zones differ in temperature, heat transfer mechanism, and mechanical stress, this study does not provide a direct material comparison. Steady‑state thermal modeling gave an estimated heat flux of ≈ 1850 W/m² for ceramic fiber under its actual operating conditions, and ≈ 3120 W/m² for refractory castable under its own conditions. Theoretical heat flux estimates are reported, but no direct material comparison is possible due to different operating conditions. No operational fuel consumption or external temperature measurements were collected. All heat loss and fuel consumption estimates presented in this paper are theoretical, based on steady‑state conduction modeling using manufacturer‑supplied thermal conductivity values. No validated fuel savings percentage is reported.

Investigating the Crisis Management Approaches in Liquid Petroleum Gas Storage Projects

Kadhim J. Obayes — Mon, 21 Sep 2026 00:00:00 +0300

This research aimed to investigate the crisis management approaches in liquid petroleum gas storage projects in Iraq, using a descriptive survey-type method with an applied goal in 2024. 75 people participated in the study using the census method of senior and middle managers of 15 oil and gas companies in Iraq. In this study, research questionnaire under 3 criteria (before the crisis, during the crisis, after the crisis) and 30 sub-criteria were designed based on the research literature, interviews with 15 CEOs of Iraqi oil and gas companies and 2 Delphi phases with an agreement coefficient of 0.741. The validity was confirmed by using Lawshe content validity and construct validity and reliability by use of Cronbach’s alpha coefficient in SmartPLS software. Data was analyzed by the help of SPSS software. The results of the t-test indicated that crisis management in liquid petroleum gas storage projects in Iraq is above-average. On the other hand, it was determined in the ranking of the factors by the Friedman test that the approach of before the crisis with a mean rank of (2.15) was ranked 1st, after the crisis with a mean rank of (1.99) was ranked 2nd and during the crisis with a mean rank of (1.87) was ranked 3rd. Also, the sub-criterion of “Design and strengthening of pressure and heat infrastructures, automatic fire extinguishing systems and emergency evacuation equipment for liquid petroleum gas storage against crisis” with a mean rank of (18.08) was ranked 1st and the sub-criterion of “repair and reconstruction of damaged equipment including replacing pipes, repairing tanks and upgrading safety systems” with a mean rank of (13.74) was achieved the last rank in the general ranking of the sub-criteria.

Iraq Crude Oil Exports – July, August, September/ 2025

Oil Marketing Company SOMO — Mon, 21 Sep 2026 00:00:00 +0300

Table 1. Iraq Crude Oil Exports – July 2025

Table 2. Iraq Crude Oil Exports – August 2025

Table 3. Iraq Crude Oil Exports – September 2025