The article addresses the reduction of carbon dioxide (CO₂) emissions by placing them in geological structures. The technical and economic aspects of monitoring the distribution of carbon dioxide in geological structures, including technical, economic and environmental issues related to long-term storage of CO₂ in geological formations, are studied. The need to ensure the reliability of carbon dioxide disposal and control their condition in the layers of the underground storage is considered. The main aspects of monitoring the distribution of carbon dioxide in the geological structure by gravimetric methods, including by the volume of the structural trap during its disposal, are studied. The article studies the features of the distribution of carbon dioxide in the reservoir with the initial saturation of the reservoir with low-density reservoir fluid and the possibility of activating gas-dynamic risks. The issue of the distribution and rate of distribution of carbon dioxide by the volume of the natural trap is considered. It is substantiated that gravity prospecting monitoring allows tracking the current state of the geological structure into which CO is injected and timely strengthening control over the tightness of old wells during the distribution of carbon dioxide in the area of their location. The possibility of using gravimetric monitoring of the distribution of carbon dioxide in the geological structure is substantiated and the possibility of constructing indicator maps and graphs characterizing the distribution of fluid in the trap is considered.

Keywords: technical and economic aspects; deposit; carbon dioxide (CO₂); gravity exploration; reservoir; structural trap; CO₂ placement; geological structure.

Date submitted: 09.09.2025     Date accepted: 23.02.2026

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The paper presents the results of a comprehensive experimental study aimed at the development and justification of the efficiency of formulations of thermally stable foam solutions for drilling and temporary well killing under conditions of abnormally low formation pressures (ALFP). The purpose of the study is the development, laboratory testing, and validation of the functional efficiency of multicomponent foaming fluids optimized to solve two key tasks: minimizing overbalance pressure on the formation during drilling and creating a long-term blocking barrier during well killing. Experimental results showed that the influence of the type and concentration of surfactants, polymer additives (CMC-HV, ChemPAC-LV), a structure-forming agent (bentonite), and stabilizers (liquid glass, NaCl) on key functional properties was investigated, including density (0.50–0.88 g/cm³), foam expansion ratio (3.0–4.0), thermal stability (up to 130 °C), and long-term structural stability (up to 7 days). The scientific novelty of the study lies in the identification of a synergistic effect resulting from the use of local components - monoethanolamine (MEA) derived from waste products of the Maryazot production association and the surfactant Guwlydere - in combination with bentonite, which made it possible to achieve a minimum density of 0.50 g/cm³ and maximum stability of up to 7 days. These parameters are critically important for application under ALFP conditions. The developed formulations were successfully implemented at the Yashyldepe, Yolguyi, and Garashsyzlygyn 10-yyllygy fields, demonstrating a reduction in lost circulation mitigation costs by 30–50 % and an increase in well production rates.

Keywords: foam solution; drilling, well killing; lost circulation; well completion.

Date submitted: 16.10.2025     Date accepted: 17.02.2026

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The service life of roller-cone drill bits is largely determined by the condition of their bearing units, which account for a significant share of drilling failures. Reducing friction and increasing load-carrying capacity in bearing assemblies are essential for improving rock-breaking efficiency and extending tool life. One promising approach is the use of a bionic surface texture, which stabilizes the lubricant film and redistributes pressure within the contact zone. In this work, a combined bionic surface texturing strategy is proposed for the thrust bearing of a roller-cone bit, integrating a phyllotactic-inspired distribution pattern with ellipsoidal micro-dimples in both symmetric and asymmetric configurations. A CFD model of the thrust bearing was developed using numerical simulations in ANSYS Fluent. Smooth and textured surfaces were compared. Analysis of pressure distribution and shear stress demonstrated that the combined texture increases the load-carrying capacity of the lubricant film by up to 9% and the phyllotactic pattern reduces the friction coefficient by more than two times compared to a smooth surface. Additionally, a comparison between the phyllotactic pattern and a linear arrangement of micro-dimples showed a 14% reduction in friction coefficient with a slight decrease in load-carrying capacity. The obtained results confirm the effectiveness of the bionic approach in the design of roller-cone bit bearings and can be applied to develop wear-resistant and energy-efficient structures that contribute to increasing the maintenance interval of drilling tools. 

Keywords: roller-cone bit; bearing; bionic surface texturing; phyllotactic; ellipsoidal dimples; CFD.

Date submitted: 24.11.2025     Date accepted: 09.02.2026

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42. Kurniawan, R., Kiswanto, G., Ko, T. J. (2017). Surface roughness of two-frequency elliptical vibration texturing (TFEVT) method for micro-dimple pattern process. International Journal of Machine Tools and Manufacture, 116, 77–95.

The study examines the effect of ZrO₂ micropowder additive (at 3 and 6 wt%) on the mechanical performance and wear behavior of 25C_diamond–(70.5WC–4.5Co) composites fabricated by spark plasma sintering (SPS), as well as the performance of impregnated drill bits based on these composites during exploration drilling in Kazakhstan. It was found that introducing 3 wt% ZrO₂ into the 25C_diamond–(70.5WC–4.5Co) composite reduces the wear rate by weight WR from 9.124±0.544 ⋅ 10^–5 to 4.116±0.382 ⋅ 10^–5 g/m, by volume WV from 9.237±0.645 ⋅ 10^–12 to 4.220±0.424 ⋅ 10^–12 m³/s, and the specific wear rate WS from 7.142±0.512 ⋅ 10^–13 to 4.022±0.254 ⋅ 10^–13 m³/(N ⋅ m). The twofold increase in wear resistance observed in the 25C_diamond–(67.68WC–4.32Co)–3ZrO₂ composite compared to the base 25C_diamond–(70.5WC–4.5Co) is attributed to grain refinement of WC, improved fracture toughness, and the transformation of the metastable tetragonal phase t-ZrO₂ into the thermodynamically stable monoclinic m-ZrO₂ phase. Even lower wear values were recorded for the 25C_diamond–(64.86WC–4.14Co)–6ZrO₂ composite: WR = 2.107±0.204 ⋅ 10^–5 g/m, WV = 2.102±0.162 ⋅ 10^–12 m³/s, and WS = 1.724±0.118 ⋅ 10^–13 m³/(N ⋅ m), which is approximately 4.3 times lower than those of the base sample. The superior wear resistance of the 6% ZrO₂ composite is linked to a higher content of the monoclinic m-ZrO₂ phase, resulting from a more complete transformation of t-ZrO₂. Field tests showed that the drilling footage achieved by the impregnated core bit based on the 25C_diamond–(64.86WC–4.14Co)–6ZrO₂ composite was four times greater than that of the standard core bit based on the 25C_diamond–(70.5WC–4.5Co) mixture during exploration drilling by «KazakhmysBarlau» LLP.

Keywords: diamond core drill bit; composite; tungsten carbide; cobalt; zirconium dioxide; wear resistance; spark plasma sintering.

Date submitted: 25.08.2025     Date accepted: 12.12.2025

References

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The article analyzes real-time detection of gas-oil (GOC) and oil-water (OWC) contacts during horizontal drilling in clastic reservoirs. Timely localization ensures high-quality geosteering, keeping the wellbore within the pay zone and preventing undesirable fluid intersections. Relying solely on conventional logging-while-drilling (LWD) is often insufficient. Limitations arise from electrical macroanisotropy distorting resistivity data, the clay electrical double layer masking responses, and tool «blind zones» causing delayed observations, which poses a critical risk in horizontal drilling. To address this, advanced mud gas logging is proposed. Instead of indirect electrophysical features, this method captures actual reservoir fluid dynamics. By using chromatographic analysis of C₁–C₅ fractions and calculating Wetness, Balance, and Pixler ratios, characteristic fluid signatures and transition zones are identified. Crucially, reliable interpretation requires mathematical normalization of gas data. Without it, operational artifacts from rate of penetration (ROP) and mud flow rate fluctuations create false anomalies or obscure actual boundaries. An Eastern Siberian field case study demonstrates that normalized mud gas logging achieved real-time GOC localization with sub-meter accuracy in a low-contrast reservoir. Validated by pulsed neutron logging (PNL),
this method proves to be an effective geosteering and risk management tool.

Keywords: mud gas logging; horizontal wells; gas-oil contact (GOC); oil-water contact (OWC); geosteering; mud logging; gas chromatography; gas data normalization.

Date submitted: 18.05.2026     Date accepted: 11.06.2026

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One of the promising EOR technologies is a relatively recent technique of injecting low-salinity water into carbonate reservoirs. There are some Russian and foreign papers studying the effect of changing the injected water properties on the rate of production and reservoir recovery. Most of the studies analyze the effect of water composition on terrigenous reservoirs, while there are few studies concerning carbonate reservoirs. Therefore, development of carbonate reservoirs and their waterflooding, in particular, is of great interest. The paper discusses production target III of an oil and gas condensate field, composed of the Bobrikovian carbonate rocks. This heterogeneous, tight, fractured reservoir is currently developed under depletion drive. Reservoir stimulation is not provided by design, which indicates deficiency of field development strategy, preventing exploitation of full potential of this reservoir. To obtain an objective, a problematic zones in production target III has been analyzed. This analysis considered cumulative production against a thickness map between OWC and the upper carbonate reservoir. An extensive analysis of water sources was carried out for future use of this water as a reservoir-repressuring agent, as well as compatibility of the injected water, reservoir rock, and underlying groundwater was analyzed with regard to predicted chemical reactions. Laboratory testing of core samples was performed using a gas permeameter-porosimeter. For estimating efficient parameters of a reservoir pressure maintenance system is well interference study. Understanding well interference in carbonate reservoirs is complicated by natural fracturing, so, Express Pressure Tool data has been interpreted to analyze well interference. 

Keywords: water flooding; injected water; salt content; reservoir rock; underlying groundwater compatibility.

Date submitted: 01.04.2025     Date accepted: 21.01.2026

References

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3. Aghdam, S. Kh., Kazemi, A., Ahmadi, M. (2023). Studying the effect of various surfactants on the possibility and intensity of fine migration during low-salinity water flooding in clay-rich sandstones. Results in Engineering, 18, 101149.
4. Keller, Yu. A., Uskov, A. A., Krivoguz, A. N. (2020). Application of SVKTT technology to assess the efficiency of flooding with low-mineralized water of the carbonate formation of the Kharyaginskoye field. Oil Industry, 7, 109-113.
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   «Current issues in the study of oil and gas reservoir systems» (SPRS-2020). Moscow: LLC «Research Institute of Natural Gases and Gas Technologies - Gazprom VNIIGAZ».
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This article aims to provide literature for the development of new technologies in enhanced oil recovery (EOR), with a focus on reservoir modelling using machine learning (ML). The inaccuracy and inefficiency of traditional physics-based numerical simulations necessitate the development of faster and more intelligent tools. This review serves as a comprehensive resource on applied ML approaches for reservoir modelling. This research classifies the previous artificial intelligence (AI) research in EOR into three methods: water flooding (WF), chemical enhanced oil recovery (CEOR), and thermal flooding. The comprehensive classification is based on the algorithm used, dataset, purpose, inputs, results, and evaluation for each method in each paper. A novel method for simulating dynamic fluid distributions in WF, the Conditional Deep Convolutional Generative Adversarial Network (CDC-GAN) significantly lowers computational costs while handling complex nonlinear relationships. Particle Swarm Optimization (PSO) combined with Bayesian Random Forest (BRF) provides reliable proxy modelling and optimization, also the Echo State Network (ESN) improves prediction accuracy, however it requires high-quality historical data. While Adaptive Neuro-Fuzzy Inference Systems (ANFIS) efficiently handle uncertainties, Least Square Support Vector Machines (LSSVM) and Artificial Neural Networks (ANNs) demonstrate predictive capabilities for nonlinear relationships in the CEOR. This review emphasizes the role of Reinforcement Learning (RL) in thermal, along with the incorporation of Principal Component Analysis (PCA) and clustering techniques for improved data interpretation. Consequently, this study presents a comprehensive analysis of AI techniques in Enhanced Oil Recovery (EOR) from 2009 to 2024, offering researchers and technical experts insights for future investigations.

Keywords: Bayesian random forest; particle swarm optimisation; least square support vector machine; ANNs; reinforcement learning.

Date submitted: 16.07.2025     Date accepted: 05.02.2026

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The process of developing a rectangular gas reservoir in the gas regime is considered. A one-dimensional model of is proposed to describe this process. The pressure distribution in the reservoir at the initial moment of time, the pressure and volume flow rate of gas in the production gallery of wells are considered to be set. However, data on the pressure and flow of gas at the outer boundary of the reservoir are assumed to be unknown. Within the framework of the proposed model, the task is to determine the pressure distribution in the reservoir only based on the information specified in the operational gallery. This problem belongs to the class of boundary inverse problems. First, a discrete analogue of the problem is constructed using the method of difference approximation. To numerically solve the resulting system of difference equations, a special computational algorithm is proposed based on the use of representation for solving a system of linear algebraic equations with a tridiagonal matrix. As a result, an explicit formula was obtained for determining the pressure value at the outlet boundary of the reservoir and a recurrent formula for determining the pressure distribution in the reservoir at each time layer. To ensure the stability of the solution of the inverse problem, the method of natural regularization is used. Numerical experiments for a model gas reservoir were carried out based on the proposed computational algorithm.

Keywords: gas regime of reservoir development; rectilinearly parallel gas flow; boundary inverse problem; self-regularization method; difference approximation method.

Date submitted: 10.12.2025     Date accepted: 02.04.2026

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In oil fields operated under depletion drive, improving oil recovery remains a critical challenge, requiring methods that can modify the physicochemical properties of the reservoir system, improve displacement efficiency, and provide additional pressure support. This study evaluates water-gas mixture (WGM) injection, supported by digital reservoir monitoring and numerical modeling, as an integrated approach for increasing the recovery of remaining oil reserves from heterogeneous reservoirs. A series of laboratory experiments was conducted using a linear reservoir model to compare the displacement efficiency of conventional waterflooding, WGM injection, and polyacrylamide (PAM) injection. The experiments show that WGM injection, particularly when applied from the early stage of development and compared with PAM-based mobility-control displacement, enables the target recovery factor to be achieved considerably faster. This improves the time-dependent oil recovery factor, shortens the overall development period, and reduces the required volume of the displacement agent. To validate the experimental conclusions under field-scale conditions, a hydrodynamic reservoir simulation study was performed for a selected block of the Gum Deniz oil field in Azerbaijan, which is characterized by complex geology, layered heterogeneity, and variable displacement behavior. The simulation workflow was implemented using the Landmark Nexus (Nexus-Black-Oil) software package and calibrated against historical production and pressure trends. The combined laboratory and numerical modeling results confirm that WGM injection can provide stronger pressure maintenance, improved sweep efficiency, and higher recovery potential than conventional waterflooding and PAM injection, making it a promising enhanced oil recovery strategy for mature depletion-drive reservoirs.

Keywords: enhanced oil recovery; water–gas mixture injection; sweep efficiency; oil displacement; heterogeneous reservoirs; history matching; polyacrylamide; PAM; EOR.

Date submitted: 14.02.2026     Date accepted: 30.04.2026

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Multistage hydraulic fracturing (MHF) is the primary method for developing extremely tight oil reservoirs (TORs) with nanopores. Currently, this technology is considered the only economically viable way to develop these resources. However, MHF suffers from geomechanical limitations, including formation heterogeneity and limited pumping capacity at surface facilities. This paper reviews the current state of MHF in tight oil reservoirs, connecting geomechanical concepts to field applications and highlighting key challenges and future trends, including sustainability and digital transformation. The industry has evolved from simple planar fracturing operations to complex stimulated reservoir systems (SRS). Modern design is based on geological characteristics; in-situ stresses and natural fractures guide engineering decisions, such as the use of hydraulic fracturing fluids. However, this sector faces ongoing challenges, including overlap of parent and child wells, low recovery factors (less than 10%), and loss of conductivity, caused by gaps in the scaling of complex physical processes across time and space. Addressing these challenges is facilitated by digitalization. By harnessing data analytics, ML and real-time DAS/DTS, operators transition from a «design and pump» paradigm to a «sense and respond» approach. This empowers them to optimize real-time hydrocarbon sweep and bridge key sustainability gaps. In conclusion, this review illustrates how optimized water management, efficient operational scaling and sustainable design in MHF directly contributes to SDGs 6, 8, 9 and 12, promoting responsible global resource stewardship.

Keywords: tight oil reservoirs; hydraulic fracturing; stimulated reservoir system; fracturing fluids; energy efficiency; sustainable energy; clean energy technology.

Date submitted: 13.08.2025     Date accepted: 28.04.2026

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This study presents an observation-driven approach for integrated geological and hydrodynamic reservoir modelling using multi-source data. Reservoir systems are complex due to heterogeneous structures, nonlinear flow behaviour, and limited direct access to subsurface information. These factors make accurate modelling a challenging task in reservoir engineering. Conventional modelling approaches usually follow a sequential workflow from geological interpretation to numerical simulation. This often increases computational cost and introduces uncertainty in model construction. To address these limitations, the study explores the use of artificial intelligence methods together with physics-informed and hybrid modelling concepts. In the proposed framework, geological, petrophysical, and production data are combined in a unified processing scheme. A simple encoder–decoder structure is used to extract latent features that describe reservoir behaviour. A bridge mechanism is introduced to connect these features with physically meaningful reservoir properties such as connectivity, flow capacity, and pressure response. The method does not replace traditional reservoir simulation but aims to support it by improving data integration and reducing computational effort. A synthetic validation study shows that the proposed approach can reproduce main reservoir behaviour trends with reasonable accuracy. Overall, the results suggest that data-driven methods, when guided by physical understanding, can be a useful complement to classical reservoir modelling workflows.

Keywords: reservoir modelling; artificial intelligence; data integration; physics-informed methods; hybrid modelling; surrogate models.

Date submitted: 12.03.2026     Date accepted: 09.06.2026

References

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Rod pumping systems represent a fundamental component of artificial lift technologies, particularly in the development and exploitation of mature oil fields. Despite their widespread use, the quantitative evaluation of their operational efficiency remains a challenging task, largely due to the nonlinear dynamics of well behavior and the inherent limitations of conventional diagnostic methods. This study presents a comprehensive and structured methodology for evaluating the efficiency of sucker-rod pumping wells by integrating field measurements with advanced computer-based simulation techniques. The proposed framework is based on directly measurable operational parameters in order to formulate a practically applicable concept for evaluating the efficiency of pump operation. Within this framework, efficiency is conceptualized as a function of reservoir productivity, pump fillage factor, production rate, stroke speed, the geometric characteristics of the pump, and other indicators that collectively characterize the well–reservoir system. The proposed methodology is demonstrated under various geo-technological conditions using a computer simulator of the pump–well–reservoir system developed on the basis of the authors’ Discrete-Imitation Modeling Concept. It provides a robust analytical basis for evaluating the efficiency of production using sucker-rod pumps and supports the development of informed strategies for production enhancement. The notions of the Pump Productivity Index and the Technological Efficiency Coefficient are introduced, and analytical expressions for efficiency evaluation are presented. Using the simulator, a methodology for the investigation and optimization of the sucker-rod pump
well–reservoir system is demonstrated.Validation using data from a real field well confirms the methodological soundness and practical relevance of the approach, demonstrating its potential as an effective decision-support tool for petroleum engineers engaged in the optimization of sucker-rod pump systems.

Keywords: sucker-rod pump; efficiency conception; technological efficiency; pump performance indicator; production data analysis; optimization. 

Date submitted: 18.05.2026     Date accepted: 16.06.2026

References

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In the present study, the protective efficacy of conservation fluids formulated from bisimidazoline derivatives synthesized via the reaction of oleic acid with polyethylenepolyamine and triethylenetetramine in a 2:1 molar ratio was systematically investigated under various corrosive conditions, including hydrochamber exposure, seawater immersion, and in a 0.001% sulfuric acid solution. The resulting formulations were prepared at 5 and 10 % concentrations in a T-30 oil distillate matrix and applied for temporary corrosion protection of metallic surfaces. Experimental results showed that the T-30 oil distillate alone, in the absence of any corrosion inhibitor, exhibited minimal protective capability, providing surface protection for only 9–34 days. In contrast, formulations incorporating bisimidazoline derivatives particularly those containing 10% concentrations of polyethylenepolyamine- and triethylenetetramine-based compounds achieved continuous protective performance exceeding 300–400 days across all tested environments. The relative extension of the protection period was estimated to be approximately 10- to 23-fold. Furthermore, imidazolines synthesized using polyethylenepolyamine exhibited superior corrosion inhibition performance compared to those derived from triethylenetetramine, which can be attributed to their higher density of functional groups and enhanced coordination capability with metal surfaces. Consequently, these imidazoline-based formulations represent effective and practical candidates for temporary corrosion protection in atmospheric and aqueous environments. 

Keywords: atmospheric corrosion; conservation fluids; bisimidazoline; polyethylenepolyamine; triethylenetetramine; conservation time; inhibitor effectiveness.

Date submitted: 15.07.2025     Date accepted: 22.12.2025

References

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The article investigates the causes of failures of downhole pumping equipment (DPE) used in mechanized oil production, as well as methods for analyzing and forecasting its reliability. Despite continuous improvements in pump design and materials, a significant proportion of failures is associated with the effects of abrasive particles, corrosion, and cavitation. An analysis of domestic and foreign studies aimed at identifying patterns of failure mechanisms and increasing the mean time between repairs (MTBR) of pumps has been carried out. It has been determined that the key factor affecting the reduction in efficiency and durability of the equipment is the presence of mechanical impurities, as well as their concentration, shape, and grain-size distribution. Based on data from oil fields in Kazakhstan, Russia, and Azerbaijan, fuzzy clustering of operating conditions was performed, which allowed the identification of four groups of objects with different combinations of factors. Threedimensional dependencies were constructed, and the results of the analysis formed the basis for fuzzy logic rules «if..., then...». The application of fuzzy cluster analysis confirmed the effectiveness of this method in solving diagnostic and optimization problems in oilfield equipment operation. Based on the results of the analysis, a new-generation filter element was developed, demonstrating significantly higher efficiency compared to leading global analogues and successfully implemented at one of the fields in Serbia. The results obtained can be used to improve the reliability of downhole pumps, reduce failure frequency, and form a knowledge base for managerial decision-making in oil production.

Keywords: oil production; downhole pumping equipment; failure; mean time between repairs; mechanical impurities; uncertainty; fuzzy cluster analysis; reliability; filter element.

Date submitted: 21.01.2026     Date accepted: 18.03.2026

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The research work is devoted to a comprehensive analysis of thermal stresses and deformations arising on the working surface of prestressed components operating under critical temperature regimes. During service, these components are subjected to a combination of high temperatures, mechanical pressure, and frictional effects, which lead to complex thermo-mechanical interactions and non-uniform heat distribution across the contact surface. Such conditions significantly influence the stress–strain state, potentially causing structural instability, loss of functionality, or premature failure. To investigate these phenomena, mathematical models based on Fourier series expansions and governing differential equations of heat conduction and elasticity were developed. These models enable the determination of temperature fields, as well as the calculation of thermal stresses and displacements within both zero-order and first-order approximations. The analytical approach provides insight into the distribution patterns of stresses and allows the identification of critical zones where maximum thermal loading occurs. The practical significance of the study lies in the application of the obtained analytical results to engineering design. Based on the developed models, constructive and technological solutions are proposed to minimize the risk of critical stresses and excessive deformations on the working surface of prestressed parts. In addition, optimization of normal and contact stresses is carried out by defining permissible parameter ranges, taking into account the thermophysical and mechanical properties of the material, as well as surface quality indicators such as roughness and hardness. These findings contribute to improving the reliability, durability, and operational efficiency of prestressed components under severe thermal conditions.

Keywords: surface; deformation; precession part; critical heating; mathematical model.

Date submitted: 17.04.2026     Date accepted: 04.05.2026

References

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Performance evaluation of oil exploitation centers is crucial in both economic and environmental aspects. Data Envelopment Analysis (DEA), as a powerful mathematical optimization model, is commonly used to measure the efficiency of multi-input/output decision making units (DMUs). However, computational limitations in solving large-scale evaluation problems have motivated this research to combine DEA models with artificial intelligence (AI) techniques for estimating the efficiency scores of oil refineries. Machine learning (ML) and deep learning (DL) methods can be employed to address the challenges associated with large-scale mathematical optimization models. Additionally, metaheuristic methods can be utilized to improve hyperparameters of ML and DL algorithms. In this study, metaheuristic-assisted DL and ML approaches were integrated with mathematical linear programming to estimate the performance of oil refineries. First, the efficiency scores of oil refineries calculated by DEA model were used as training and testing datasets for the DL and ML models - Long Short-Term Memory (LSTM) and Multi-Layer Perceptron (MLP)-. Then, the metaheuristic algorithms - Grid Search and Particle Swarm Optimization (PSO) - were used to optimize the hyperparameters of the LSTM and MLP models. The results indicated that tuning the hyperparameters of the MLP and LSTM algorithms significantly reduced prediction errors. Additionally, LSTM-based algorithms had higher prediction accuracy compared to MLP-based algorithms. Furthermore, the LSTM-PSO approach predicted the efficiency scores with the highest accuracy value of 96%.

Keywords: oil refinery; performance evaluation; Data Envelopment Analysis (DEA); Machine Learning (ML); Deep learning (DL); Metaheuristics.

Date submitted: 28.08.2025     Date accepted: 26.01.2026

References

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The author presents a study dedicated to a quantitative assessment of the influence of key macroeconomic factors on the dynamics of commodity export volumes in the Republic of Kazakhstan and the Republic of Azerbaijan. The article examines the problem of the high dependence of export earnings on commodity prices and external macroeconomic conditions, a topical issue for the national economy. The study aims to identify long-term and short-term relationships between commodity exports, total international reserves, the base rate, residents' income from foreign sources, and Brent crude oil prices. The article consistently presents methodological approaches to time series analysis, including stationarity testing, cointegration testing, evaluation of error correction models, and the construction of autoregressive moving average models of various orders. To analyze short-term reactions, an impulse response function is used to identify the nature of the reaction of commodity exports to macroeconomic shocks. The author finds that Brent crude oil prices are the most significant factor exerting a persistent influence on commodity exports in the long and short term for both countries. Total international reserves and the base rate exhibit a moderate impact, while the impact of residents' income from foreign sources is characterized by a short-term and statistically weak effect. The article concludes that commodity exports are highly sensitive to external shocks and confirms the feasibility of considering macroeconomic factors when formulating trade and currency policies. The results can be used to forecast export performance and assess the economy's resilience to fluctuations in the external environment.

Keywords: oil price; exports; total international reserves; income from foreign sources; interest rate; autoregressive integrated moving average; vector autoregression model; autoregressive distributed lag model.

Date submitted: 30.11.2025     Date accepted: 01.04.2026

References

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In this study, the corrosion inhibition effect of Dioscorea dumentorum leaf extract on mild steel was evaluated in a 1 M H₂SO₄ solution at various concentrations, using weight loss measurements and Tafel polarization techniques. This study represents an effort to curb metallic corrosion in the transportation and storage sectors of the oil industry. The highest inhibition efficiency recorded was 90.8% in 3 g of inhibitor concentration with a corrosion rate of 0.0140 mpy and weight loss of 0.2567 g, respectively. Also, the inhibition efficiency increased with higher concentrations of the Dioscorea dumentorum leaf extract. The presence of phytochemical constituents such as saponins, phenols, steroids, and flavonoids in the extract was found to be responsible for the effective inhibition, as these compounds adsorbed onto the metal surface. The adsorption of the inhibitor on the mild steel surface followed both Langmuir and Temkin adsorption isotherms, as plots for both isotherms showed good regression that were all near unity (≅1), respectively, for samples with 0.5 to 3 g/0.25 L extract concentrations, while the computed Gibbs free energy of the adsorption process (ΔG⁰_ads) for both isotherm models showed values less than -20 kJ mol⁻¹. This suggests that adsorption of the extract onto the metal surfaces was by physisorption. The results confirm that the leaf extract acts as a corrosion inhibitor by enhancing surface protection on the metal.

Keywords: polarization curves; mild steel coupons; sulfuric solution; physisorption; Dioscorea dumentorum; corrosion inhibition.

Date submitted: 30.08.2025     Date accepted: 30.04.2026

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This study presents the first comprehensive, basin-wide assessment of offshore wind energy potential in the Caspian Sea based on a unified and reproducible analytical framework. We process 85 years (1940–2024) of hourly ERA5 reanalysis at 0.25° resolution for 653 grid points, assigning each to the EEZ of Azerbaijan, Iran, Kazakhstan, Russia, or Turkmenistan. A two-stage 90th-percentile filter selects the windiest decile per EEZ; two-parameter Weibull distributions provide hub-height (100 m) wind-power density (WPD) statistics. High-potential zones cover ≈36,10 km² – 10 % of the sea yet about 70–85 % of its usable wind. Median 100 m wind speeds peak in Turkmenistan (7.52 m s⁻¹), however, the highest wind power density is found in Azerbaijan (613.48 W m⁻²), followed by Russia (560.62 W m⁻²), Kazakhstan (555.90 W m⁻²), and Turkmenistan (477.62 W m⁻²), while dropping significantly in Iran (168.50 W m⁻²). Shallow depths, existing oil-and-gas logistics and proximity to load centers make ≥1 GW pilot projects viable in the northern shelf before 2030. A 15 GW build-out by 2040 could displace ≈40 TWh of gas-fired generation and avoid ≈25 Mt CO₂ annually. The reproducible Python pipeline forms an updatable evidence base that can be refined with LiDAR campaigns and mesoscale down-scaling to underpin bankable offshore-wind development.

Keywords: Caspian Sea; offshore wind resource; ERA5 reanalysis; Weibull distribution; wind-power density; renewable energy; data-driven analysis.

Date submitted: 12.08.2025     Date accepted: 03.11.2025

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Two new mononuclear Cu(II) complexes, [Cu(H₃pzpz)(NO₃)]∙NO₃∙H₂O (1) and [Cu(H₃tpz)Cl]₂ ∙2(Cl)∙5H₂O (2), with pyrazine-modulated oligo- α-pyridylamine ligands N²-(pyrazin-2-yl)-N⁶-(6-(pyrazin-2-ylaminopyridin-2-yl)pyridin-2,6-diamine (H₃pzpz) and N²-(pyrazin-2-yl)-N⁶-(6-(pyridin-2-ylaminopyridin-2-yl)pyridin-2,6-diamine (H₃tpz), have been synthesized, structurally characterized, and their antimicrobial efficacy has been studied. Single-crystal X-ray diffraction revealed that the central Cu(II) atom in complexes 1 and 2 was located in a distorted trigonal bipyramidal geometry. In both complexes, H₃pzpz or H₃tpz acts as a tetradentate ligand; it coordinates the copper(II) ion in an all-anti conformation, and the Cu(II) atom is five-coordinated in a distorted trigonal bipyramidal geometry. The distorted trigonal bipyramidal structures of the compounds are consistent with both the «inverted type» EPR spectra, in which g‖ is smaller than g┴, and two spin-allowed transitions in the visible region of their electronic spectra. The complexes are built into a three-dimensional network by extensive hydrogen bonding and intermolecular π-π interactions, which stabilize the crystal packing. The antimicrobial efficacy of 1 and 2 was evaluated against P. aeruginosa, M. phlei, A. niger, and P. chrysogenum. Both complexes demonstrated significant potency, with complex 2 showing superior activity, particularly against P. aeruginosa with an inhibition zone of 26 mm compared to 20 mm for complex 1 (at 100 μg/mL). The sulfur-binding affinity and redox activity of these metal complexes also present potential for neutralizing hydrogen sulfide (H₂S) in petroleum reservoirs and preventing the oxidative degradation of crude oil. Specifically, the catalytic properties of Cu(II) complexes may be utilized as inhibitors or catalysts in hydrocarbon oxidation reactions during petroleum refining processes.

Keywords: modulated oligo-α-aminopyridine ligand; copper complex; hydrogen bonds; supramolecular networks; antimicrobial activity.

Date submitted: 12.03.2026     Date accepted: 15.05.2026

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