Data Analysis and Machine Learning, cases and applications 

is devoted to works and researches that could be of applied value for the industry and for the analysis of geological, technological and geospatial data. In this section, the main focus is on the application of ML / AI technologies in the field of data analysis and processing, which have confirmed their initial hypothesis and can be applied or translated into exploration and production data domain. The ideal presentation for this section could be a demonstration of work, with a description of the "challenges" that the development team had to face and ways to solve these "challenges". The section does not provide any restrictions on the applicability of ML / AI technologies only in the domain of exploration or field development; all data scientists and applied researchers with similar problems and algorithms as in the tasks in the field of exploration and production of hydrocarbons are invited to present their reports

Intelligent data analysis in geology and geophysics 

The section will cover application of computational methods and machine analytics for processing, analyzing and detection of hidden features in geophysical, petrophysical and geological data. We welcome presentations that describe real practical cases where deep data analysis, machine learning and other digital technologies have been implemented for improvement of oil and gas reservoirs development.

Intelligent computing for planning and management of hydrocarbon development and production

The section is aimed at revealing the potential of intellectual analysis of reservoir production data to improve planning and management of hydrocarbon reservoir development.

We welcome presentations that describe real practical cases of application of contemporary mathematical methods and digital technologies for automated and deep analysis of large volumes of different types of reservoir monitoring data, which are used in green field green fields planning and mature fields development.

This also covers newly proposed approaches for integral modelling of subsurface and surface facilities to come up with optimal reservoir development and management solutions.

Data integration tools and case studies

This section is dedicated to discuss questions related to the use of software tools (platforms, environments and applications) for storage and integration of the data of oilfield asset lifecycle. Seismic, petrophysics, geophysics, geological, drilling, reservoir engineering, production and other kinds of data are considered. We welcome talks discovering case studies of implementation of data integration tools. Such technologies and applications should implement a transformational approach, change business models, and improve the decision-making process.

Tools for data analysis integration. Industry examples

The track is devoted to the experience in various machine learning and statistical data analysis tools integration. The tools can be represented by programming scripts, software extensions or standalone apps developed inside and/or outside an organization.

Presenters and proceedings are welcomed to describe the path of data analysis tools integration. The description can include data processing acceleration and tools usability estimation, challenges and solutions to the challenges which can happen during the integration process.