This course, 鈥淎I&ML Applications in Oil and Gas Industry鈥 takes into a comprehensive journey through the oil and gas industry, exploring both the fundamental overview and the cutting-edge applications of Artificial Intelligence and Machine Learning (AI&ML). It gives a holistic understanding of the industry's core principles, while uncovering the transformative potential of AI&ML technologies in revolutionizing operations and decision-making processes.

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AI & ML Applications in Oil and Gas Industry
Dieser Kurs ist Teil von Spezialisierung 蹿眉谤 Petroleum Engineering with AI Applications
Unterrichtet in Deutsch (KI-Synchronisation)

Dozent: Subject Matter Expert
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- Kategorie: Process Engineering
- Kategorie: Natural Resource Management
- Kategorie: Data Management
- Kategorie: Anomaly Detection
- Kategorie: Exploratory Data Analysis
- Kategorie: Production Process
- Kategorie: Data Processing
- Kategorie: Geostatistics
- Kategorie: 3D Modeling
- Kategorie: Energy and Utilities
- Kategorie: Artificial Intelligence and Machine Learning (AI/ML)
- Kategorie: Process Control
- Kategorie: Petroleum Industry
- Kategorie: Image Analysis
- Kategorie: Oil and Gas
- Kategorie: Physical Science
- Kategorie: Machine Learning
- Kategorie: Automation
- Kategorie: Big Data
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In diesem Kurs gibt es 2 Module
The module on "Overview of Oil and Gas Industry" provides students with a comprehensive understanding of the fundamentals and key components of the oil and gas industry. It begins with an exploration of the origin and formation of crude oil, enabling students to grasp the geological processes that lead to its existence. It further discusses elaborately the accumulation and types of reservoirs, gaining insights into the various geological formations that contain oil and gas. The module provides an overview of the life cycle of oil and gas fields, covering exploration methods used to identify potential reserves. It also explores the equipment used in upstream oil and gas production, including drilling rigs, gathering stations and surface production/separation facilities. Furthermore, it introduces crude oil treating systems and natural gas processing, understanding the processes involved in refining and purifying these resources. The module concludes with an exploration of onshore and offshore hydrocarbon storage facilities, highlighting their importance in the oil and gas industry.
Das ist alles enthalten
14 Videos1 Aufgabe
The module on "AI & ML Applications in the Oil and Gas Industry" explores the transformative role of artificial intelligence and machine learning in revolutionizing the operations and decision-making processes within the industry. The module begins with a comprehensive review of the impacts of ML in the oil and gas industry, highlighting the key advancements and benefits brought about by these technologies. It further delves into specific applications, starting with seismic data processing techniques, focusing on salt body delineation. It also explores the geomodelling process and its integration with AI and ML algorithms for accurate reservoir characterization. Reservoir engineering will be a key focus, with emphasis on ML techniques for reservoir rock classification and optimal production engineering. It gives insights into the application of AI in the upstream sector of the industry, exploring its use in exploration, drilling and production optimization. Advances in AI technology specific to the oil and gas industry is covered, including the integration of machine learning with sensor data, predictive maintenance and anomaly detection. It gives a fundamental understanding of data handling in the industry and the state-of-the-art approaches to handle big data in the oil and gas domain.
Das ist alles enthalten
15 Videos1 Aufgabe
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Bewertungen von Lernenden
44 Bewertungen
- 5 stars
88,63听%
- 4 stars
9,09听%
- 3 stars
2,27听%
- 2 stars
0听%
- 1 star
0听%
Zeigt 3 von 44 an
Gepr眉ft am 28. Dez. 2024
Provides overview of the AI & ML application with examples, simulated results. Changes traditional way of thinking to new AI dimension
Gepr眉ft am 3. Mai 2025
The course is very good. In my perspective they can add more practical sessions instead of theory
Gepr眉ft am 8. Sep. 2025
I enjoyed the course, but it would be better with more practical application.

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