The third “Federal IT Forum of the Russian Oil & Gas Industry” will be taking place in St Petersburg on 14 — 15 September 2017. The event will be supported by Gazprom Neft, as General Partner, for the third year running.
The aim of the Forum is to develop new approaches to and strategies for innovative development in information technologies throughout the vertically integrated oil companies of the Russian Federation.
As in previous years, leading participants at the Forum will include CIOs and senior managers of other key business functions at Russia’s most important oil and gas companies, as well as representatives from international oil and oil services organisations.
The key issues of the 2017 Forum will be the digital transformation of the oil and gas industry — from data management to “Real-Time Enterprise”* — and adapting approaches to “Industry 4.0”** in line with the specific needs of the domestic oil and gas sector.
Forum participants will discuss issues relating to the use of “Big Data” technologies in the energy sector and turning these into digital company assets; the development of import-substitution programmes and business continuity; improving efficiency at vertically integrated oil companies through the growing role of IT; innovation in the energy sector; the creation of cohesive network‑centricity from the “digital oilfield” to the “digital factory”; cloud computing solutions; and industrial automation and telecommunications in the oil and gas industry.
The Forum website is at www.it-vink.ru
* “Real-Time Enterprise” refers to businesses that operate immediately in processing information and responding to adaptive delays, allowing real-time responses to client and environmental demands cohesively through restructuring business processes and constantly modernising their structure.
** Industry 4.0 is a range of concepts and technologies involving the use of intellectual systems and their integration through the “Industrial Internet of Things” (IIoT), as well as the automated management of these through the use of feedback-coupling systems and analysis of large volumes of data.