CO2 storage in geological formations represents today one of the main new technological solutions for CO2 emission mitigation. Carbon capture and storage technology (CCS) includes capture of anthropogenic CO2 from various emitters, its transportation and injection in different types of geological formations such as: depleted oil and gas reservoirs, saline formations, unmined coal beds, partially depleted oil reservoirs for enhanced oil recovery (EOR-CO2 method) and others. The analysis of numerous criteria that are determining the success of process implementation from a technical, safety, ecological and economic point of view is necessary for considering the optimal CO2 geological storage option. In this paper, an overview of CO2 geological storage types is presented, with an emphasis on criteria for selection of most adequate CO2 storage option. They include geological, physical, thermodynamic, hydrodynamic, techno economic, social criteria, as well as the regulatory issues that are key factors for CCS technology development and further deployment.

Artificial lift methods have applications in oil wells where oil production is no longer possible due to natural reservoir energy, so this necessary energy is added by introducing lift methods. In order to achieve optimum production, the selection of an artificial lift method is very important. This paper uses fuzzy logic as a mathematical and conceptual model for selection of the optimal artificial lift method. The outcome or IF-THEN rules, as the central part of the model, is based on empirical data from the selected oil fields. Results are presented in two ways: according to the surfaces of irregular geometric bodies, and their gravity with the scattering of results, i.e., on smaller and greater possibilities of interpreting results when there are small differences in outputs. Finally, a sensitivity analysis of the model is presented.

This study delves into the heightened efficiency and accuracy of 11 deep learning models classifying 11 dynamograph classes in the oil production sector. Introducing a novel framework with the Grad–CAM method, we address the “black box” issue, providing transparency in the models’ decision-making processes. Our analysis includes a comparative study with human experts, revealing a comprehensive understanding of both machine and human interpretive strategies. Results highlight the notable speed and precision of machine learning models, marking a significant advancement in rapid, reliable dynamograph classification for oil production decision-making. Additionally, nuanced findings in the model’s diagnostic accuracy reveal limitations in situations featuring the simultaneous occurrence of multiple pump issues. This underscores the need for additional features and domain-specific logic to enhance discernment and diagnostic precision in complex scenarios. The exploration of qualitative aspects distinguishes interpretive approaches, highlighting strengths and limitations. Machines, driven by algorithmic patterns and data processing, excel in rapid identification, albeit with occasional misclassifications. In contrast, human experts leverage experience and domain-specific knowledge for nuanced interpretation, providing a comprehensive understanding of both quantitative metrics and qualitative nuances. In conclusion, this study not only demonstrates the accelerated and enhanced accuracy of dynamograph classification by machine learning models compared to junior and medior domain experts, but also provides valuable insights into specific features and patterns guiding the decision-making process. This understanding allows continuous refinement, combining machine speed with human understanding for improved results in oil production. The potential for further studies and improvements in this domain is substantial.

Tertiary methods in oil production process called 'Enhanced Oil recovery methods' (EOR) are mostly applied in mature oil fields with declining production trend after primary and secondary recovery methods or immediately after primary production phase. These 'Enhanced Oil Recovery' methods implies injection of gases or fluids to mobilize residual oil captured in reservoir rock due to presence of strong viscous and capillary forces and high value of interfacial tension between fluid and rock. Depending on the type of injected fluid, production mechanism, as well as an approach to implementation, EOR methods are divided into thermal methods, chemical methods, miscible/immiscible gas injection methods and other methods that so far have an experimental application. The paper analyzes the key factors influencing the successful implementation of EOR projects: phases of EOR project implementation, the price of crude oil at the world market as a criterion for the beginning and the justification for EOR process application and development of new technologies for more efficient process realization.

The integration of wastewater heat pumps (using purified water) in district heating systems is analyzed in this paper. The simulation procedure is proposed to analyze the impacts of stochasticity of purified water temperature and flow to heat pump integration and operation. The analysis includes calculation of the daily and seasonal coefficient of performance, as well as fossil fuel savings and CO2 emission reduction due to wastewater heat pump use. The proposed procedure is implemented for the case study in the city of Šabac (Serbia) and obtained results are discussed and evaluated. The historical data for two heating seasons was used for simulation. It was shown that the wastewater heat pump could provide 27-28% savings in fuel consumption, and 3.6-4.1% GHG emissions reduction, while the seasonal COP could be 4.2 - 4.3. Simulation based approach shows approximately 40% less savings of fuel consumption, compared to the approach based on the average values of heat pump input parameters.

The water produced at the Amal oil field in Libya is directly stored for evaporation in in-ground-pits. As there are a large number of oil production wells, there is a risk of environmental pollution because of the waste water’s eventual penetration into subsoil and surface waterways. From a technical point of view, the existing system of reservoir water disposal into storage pits will not be adequate to meet the increasing water production. Besides, the discharge of produced water without previous treatment is ecologically unacceptable. In this paper, a modern concept of produced water preparation is proposed, and the method of its disposal defined, applying an integrated approach to solving this problem, including technological, economic and environmental aspects. Produced water preparation in an oil field in Libya was chosen for the proposed implementation of an option with the lowest operating costs (storage tanks and liquid hydrophobic filter tank).