Environmental Research, Год журнала: 2025, Номер unknown, С. 121006 - 121006
Опубликована: Янв. 1, 2025
Язык: Английский
International Journal of Applied Research in Social Sciences, Год журнала: 2024, Номер 6(6), С. 1227 - 1243
Опубликована: Июнь 13, 2024
Carbon capture and storage (CCS) has emerged as a critical technology in the fight against climate change, offering viable pathway to mitigate CO2 emissions from industrial processes power generation. This review explores best practices innovations CCS for effective storage, highlighting key strategies advancements that optimize capacity, enhance security, minimize environmental risks. The begins by delineating importance of reducing greenhouse gas meeting global targets. It underscores urgency deploying technologies at scale address dual challenge decarbonizing energy systems ensuring security. Drawing upon recent research industry developments, elucidates capture, transport, emphasizing integrated holistic approaches. discusses technologies, including post-combustion pre-combustion oxy-fuel combustion, efficiency improvements cost reduction strategies. Furthermore, delves into techniques, such geological ocean mineralization, evaluating their respective advantages, challenges, scalability. site selection, characterization, monitoring, need robust risk assessment frameworks regulatory oversight ensure safety integrity sites. Moreover, examines emerging trends CCS, enhanced oil recovery (EOR) using CO2, direct air (DAC) carbon utilization (CCUS) initiatives. potential synergies between renewable solutions leverage enable decarbonization hard-to-abate sectors heavy aviation. pivotal role achieving deep transitioning low-carbon economy. calls continued research, investment, collaboration unlock full accelerate deployment scale. By embracing fostering innovation, stakeholders can pave way contribute efforts combat change. Keywords: Best Practices, Innovation, Carbon, Capture, Storage, CO2.
Язык: Английский
Процитировано
11
Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(6), С. 1469 - 1487
Опубликована: Июнь 25, 2024
In the rapidly evolving landscape of digital transformation, cloud computing has emerged as a pivotal technology enabling businesses to achieve unparalleled scalability and operational flexibility. This review explores transformative impact advanced technologies on business operations, highlighting key innovations their implications for organizational growth efficiency. Cloud offers dynamic scalable environment where resources can be provisioned managed on-demand, allowing respond swiftly changing market conditions customer demands. By leveraging infrastructure, companies scale operations seamlessly without need significant upfront investments in physical hardware. flexibility not only reduces capital expenditure but also enhances ability innovate adapt competitive marketplace. Advanced technologies, such multi-cloud hybrid solutions, further augment by organizations optimize IT environments. Multi-cloud strategies allow distribute workloads across multiple providers, mitigating risks associated with vendor lock-in ensuring high availability redundancy. Hybrid which integrate on-premises infrastructure public private clouds, provide balanced approach managing sensitive data while benefiting from cloud. Moreover, cloud-native like containerization serverless have revolutionized application development deployment. Containers encapsulate applications dependencies, consistency different environments facilitating rapid Serverless reviews underlying developers focus solely code, thus accelerating cycle reducing overhead. The integration analytics artificial intelligence (AI) capabilities. platforms offer robust tools AI services that process vast amounts real-time, providing actionable insights predictive decision-making. empowers improve experiences, drive strategic initiatives data-driven precision. conclusion, are instrumental transforming harnessing power cloud, greater agility, cost efficiency, innovation, positioning themselves sustained advantage age. As continue evolve, potential redefine economic value will expand, making adoption critical imperative modern enterprises. Keywords: Operational Flexibility, Transforming, Business Scalability, Advanced, Computing Technologies.
Язык: Английский
Процитировано
11
Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(7), С. 1680 - 1694
Опубликована: Июль 25, 2024
In the era of data-driven decision-making, ensuring data quality is paramount for organizations seeking to leverage their assets effectively. This paper explores comprehensive strategies enhancing through robust governance, methodologies, tools, and continuous improvement techniques. It highlights critical dimensions quality, including accuracy, completeness, consistency, timeliness, validity, uniqueness. discusses various assessment techniques, such as profiling, auditing, metrics. The also examines role cleansing, enrichment, integration, interoperability in maintaining high quality. Additionally, it provides an overview leading management evaluation criteria, best practices implementation. Finally, underscores importance monitoring, feedback loops, root cause analysis, fostering organization's culture. By adopting these strategies, can ensure reliability integrity data, improved business outcomes. Keywords: Data Quality, Governance, Profiling, Cleansing, Continuous Improvement.
Язык: Английский
Процитировано
11
Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(7), С. 1648 - 1665
Опубликована: Июль 25, 2024
Advances in machine learning (ML) have revolutionized pore pressure prediction complex geological settings, addressing critical challenges oil and gas exploration production. Traditionally, predicting accurately heterogeneous anisotropic formations has been fraught with uncertainties due to the limitations of conventional geophysical petrophysical methods. Recent developments ML techniques offer enhanced precision reliability estimation, leveraging vast datasets sophisticated algorithms analyze interpret complexities. ML-driven approaches utilize a variety data sources, including well logs, seismic data, drilling parameters, train predictive models that can handle non-linear multi-dimensional nature subsurface conditions. Techniques such as neural networks, support vector machines, ensemble methods shown significant promise capturing intricate relationships between variables pressure. These adaptively learn from new improving their capabilities over time. A notable advantage is its ability integrate disparate types scales, providing holistic understanding regimes. This integration enhances accuracy forecasts, which crucial for wellbore stability, safety, hydrocarbon recovery. For instance, real-time operations be fed into dynamically update estimates, allowing immediate adjustments plans reducing risk blowouts or other hazards. Moreover, facilitate identification subtle patterns trends might overlooked by traditional capability particularly valuable deep-water environments, tectonically active regions, unconventional reservoirs, where often fall short. Despite promising advances, remain widespread adoption prediction. include need extensive training datasets, interpretability models, workflows existing geoscientific practices. Addressing these requires interdisciplinary collaboration geoscientists, scientists, engineers develop robust, user-friendly solutions. In summary, represents advancement managing complexities geology. By enhancing reliability, technologies are poised improve efficiency, productivity industry, challenging settings. Keywords: Advance, ML, Pore Pressure, Prediction, Geological Settings.
Язык: Английский
Процитировано
8
Environmental Research, Год журнала: 2025, Номер unknown, С. 121006 - 121006
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
1