Training schedule I-II quarters is available for download here.
Training schedule 2022 is available for download here.
Training schedule 2023 is available for download here.
«Smart field» is also known as “digital”, “cybernetic”, “integrated”, and “field of the future”… There is no one fixed term but tendency is clear – artificial intelligent systems optimize field management.
It is time for petroleum specialists to be acquainted with available permanent-type monitoring and field development management systems, as well as to acquire skills for estimation of informative value and need for appliance, calculation of additional recovery efficiency.
Leading through the course «Smart field: from tools to optimization” by experienced specialist you can learn to choose the most appropriate technologies for monitoring system organization based on development complexity, to diagnose emerging challenges, and to propose optimal solutions.
The course program and training methodology are unique due to the demonstration of “smart wells” permanent-type monitoring technology with real case study, including advantages/disadvantages presentation depending on complication type. The course covers not only analysis of optimization cases based on diagnostic indicators of permanent type monitoring, but also solution of efficiency improvement tasks with the use of up-to-date software.
Results of hydrodynamic monitoring, deconvolution algorithms application, and well interaction are analyzed with «Saphir» software. “Camerton” software is used for analysis of geophysical monitoring including the use of distribution fiber-optic indicators, results of chemical monitoring and automatic optimization decisions making.
Trainer of the course Danila Gulyaev, Ph.D. in Engineering, specialist of Polykod LLC (Sofoil) and Geophysical data system Department of Gubkin university (Russia). He has long-term experience in field development optimization, reservoir modeling, and applied analysis in Russia, South-East Asia, and Middle East with such companies as BashNIPIneft, Gazpromneft STC, Gazprom neft, Sibneft, etc.