Advances and Application in Intelligent Oil and Gas Field Development Technology

Dear Colleagues,

Intelligent oil and gas field development refers to the application of advanced technologies (such as Artificial Intelligence, Machine Learning, Big Data Analysis, Digital Twin, Large Model Technology, etc.) to optimize the exploration, production and maintenance of oil and gas fields. These technologies will enable the real-time monitoring and management of actual operations. They will facilitate reservoir characterization, increase production rates, and reduce operational costs. Intelligent oil and gas field development involves the integration of multiple disciplines (such as geology, carbon utilization and sequestration, critical minerals, petroleum engineering, data science, etc.) to form a comprehensive approach to oil and gas resources management.

This Topic aims to highlight the latest advances in intelligent oil and gas development and production, including cutting-edge technologies for real-time monitoring, production optimization, and predictive maintenance. The research topics covered in this Topic include, but are not limited to:

1. Artificial Intelligence and Machine Learning applications in the conventional and unconventional reservoirs.

2. Big Data Analysis techniques for decision-making in oil and gas resource development and production.

3. Digital Twin techniques for real-time monitoring and control during oil and gas well production.

4. Intelligent safety monitoring in oil and gas resources development.

5. Case studies and field trials of intelligent oil and gas field development.

6. Intelligent technology deployment and application of CO2 utilization and sequestration in the formation.

7. The application of large model technology about knowledge base construction and the use of a knowledge question-answering model-trained intelligent computing agent in the petroleum industry.

8. Any other Topics related to intelligent techniques during oil and gas resource development and production.

Prof. Dr. Liming Zhang
Dr. Yin Zhang
Topic Editors