Application of machine learning to leakage detection of fluid pipelines in recent years: A review and prospect

Measurement, Год журнала: 2025, Номер unknown, С. 116857 - 116857

Опубликована: Янв. 1, 2025

Язык: Английский

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Artificial intelligence in geoenergy: bridging petroleum engineering and future-oriented applications

Journal of Petroleum Exploration and Production Technology, Год журнала: 2025, Номер 15(2)

Опубликована: Фев. 1, 2025

Язык: Английский

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Waste-to-energy poly-generation scheme for hydrogen/freshwater/power/oxygen/heating capacity production; optimized by regression machine learning algorithms

Process Safety and Environmental Protection, Год журнала: 2024, Номер 187, С. 876 - 891

Опубликована: Май 3, 2024

Язык: Английский

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Experimental Investigation of Early Leak Detection in Offshore Multiphase Flow Pipelines Using Non-Invasive Electrical Resistance Tomography

Опубликована: Апрель 22, 2024

Abstract Prompt and reliable detection of pipeline leaks is vital for human safety, the economy, environment, corporate reputation. The objective current analysis to investigate effectiveness non-invasive Electric Resistance Tomography (ERT) in detecting locating offshore oil gas pipelines under various multiphase flow scenarios compare it with real-time visualization data. A loop apparatus a diameter 0.0508 m length 6.9 used conducting experiments. Water employed as representative Newtonian fluid, while air utilized simulate phase different scenarios. experiments were conducted on rates liquid (150-383.50 kg/min) (10-50 g/min). three distinct leak sizes (3, 2,5 1.8 mm) are introduced together replicate this study. For same input scenario (10 g/min), increasing mass rate from 150 383.50 kg/min reduces system's composition ERT 4.16% 1.44% which about 65.3% less, highlighting influence rate. Furthermore, measurement revealed that when quantities 50 g/min) constant conditions (173.5 244.8 kg/min), more pockets identified observations, resulting higher compositions. Moreover, case conditions, provides relatively fewer voids compared no cases, indicating applicability correlation between indicates potential optimizing operations by adjusting minimize presence. leaks, especially scenarios, promising water (Newtonian fluid), however, further experimentation needed assess its performance non-Newtonian fluids, multiple locations often encountered real-world pipelines.

Язык: Английский

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The role of carbon dioxide in enhancing geothermal energy: A review of current developments and future potential

Renewable and Sustainable Energy Reviews, Год журнала: 2025, Номер 214, С. 115525 - 115525

Опубликована: Фев. 21, 2025

Язык: Английский

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Leakage Risk Assessment in Geologic Carbon Sequestration Using a Physics-Aware Convlstm Surrogate Model

Опубликована: Янв. 1, 2025

Язык: Английский

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Study on Risk Assessment Methods for Geological Storage of Carbon Dioxide

International Journal of Natural Resources and Environmental Studies, Год журнала: 2025, Номер 5(1), С. 51 - 55

Опубликована: Фев. 25, 2025

Carbon dioxide capture and storage (CCS) represents an effective approach for mitigating CO₂ emissions. However, the potential leakage of stored poses significant risks to both surrounding environment human health, necessitating comprehensive risk assessment management CCS systems. This paper reviews fundamental principles applications commonly employed methods geological provides insights into future development trends.

Язык: Английский

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Storage Efficiency Prediction for Feasibility Assessment of Underground CO2 Storage: Novel Machine Learning Approaches

Energy, Год журнала: 2025, Номер unknown, С. 136040 - 136040

Опубликована: Апрель 1, 2025

Язык: Английский

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Numerical and experimental study of CO2 jet impingement on curved surfaces with different phases

Process Safety and Environmental Protection, Год журнала: 2025, Номер unknown, С. 107157 - 107157

Опубликована: Апрель 1, 2025

Язык: Английский

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APPLICATION OF MACHINE LEARNING IN THE DETERMINATION OF ROCK BRITTLENESS FOR CO2 GEOSEQUESTRATION

Machine Learning with Applications, Год журнала: 2025, Номер unknown, С. 100656 - 100656

Опубликована: Апрель 1, 2025

Язык: Английский

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