THE 22ND GEOFRIDAY ACADEMIC DAY
The meeting was presided over by Professor Li Jijun
The 22nd GeoFriday Academic Day was held on June 6th, combining online and offline modes successfully. Professor Li Jijun invited Associate Professor Wang Guochang from St. Francis University to give a speech on "Shale Reservoir Geological Modeling Using Data in Both Vertical and Horizontal Wells ."
In recent years, the theory and technology of shale oil and gas exploration and development have become increasingly perfect and gradually become an important field for oil and gas production, and horizontal well development is considered to be the optimal solution for shale oil and gas development and has also received extensive attention from researchers.
In the report, Associate Professor Wang Guochang elaborated on some fundamental theories and key technologies in the process of establishing Formation structure models and attribute models using vertical well and horizontal well data according to the latest research results of the team, taking the Longman Formation in Sichuan Basin as an example, and specifically introduced how to establish a structural model by adding virtual vertical wells and the whole process of establishing attribute models through grid processing. After the lecture, Associate Professor Wang Guochang actively discussed and exchanged with the participating teachers and students to answer everyone's questions.
Associate Professor Wang Guochang is currently working at St. Francis University and serves as the director of the Intelligent Reservoir Research and Service Center of St. Francis University, a member of the Nanogeology Committee of the Geological Society of China, and an editorial board member of the Journal of Coal Science and Engineering (China). His research interests include shale oil and gas reservoir characteristics and resource estimation, CO2 geological storage in aquifers and depleted oil and gas reservoirs, fluid flow simulation in fractured rocks, and the application of artificial intelligence and machine learning in earth science. At present, he has published 90 papers in various journals, and his results have extensive influence in the field of shale oil and gas reservoirs.
