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Personal profile

Research interests

I have founded and lead GeoDataScience group at the Instute of GeoEnergyEngineering. My research interests lie broadly across spatial statistics, machine learning and uncertainty.

In particular my research is focused on:

  • uncertainty quantification in prediction modelling
  • inverse modelling for history matching
  • stochastic optimisation
  • Bayesian inference.
  • advance geostatistical techniques, such as multi-points statistics, and the problem of integration of relevant domain knowledge and data into statistical models.
  • machine learning and data mining approaches for reservoir modelling and uncertainty quantification. 

I lecture geostatistics to MSc students and also at IPE summer schools and EAGE educational days. I am a co-author of over 100 publications, including books: Challenges and Solutions in Stochastic Reservoir Modelling with D Arnold (EAGE 2018), Geostatistics: Theory and Practice  with E. Savelieva (Nauka, 2010, in Russian), Advanced Mapping of Environmental Data – Geostatistics, Machine Learning and Bayesian Maximum Entropy (Wiley, 2008).

Graduated PhD students supervised:

Collaboration:

  • University of Lausanne, Switzerland: Prof M. Kanevski, Prof. I. Lunati, L. Josset, Prof. M. Maignan
  • CERENA, Institute Superior Technico, Lisbon, Portugal: Prof. A. Soares, Dr L. Azevedo,Dr. S. Focaccia, M.-H. Caeiero.
  • Gubkin Oil and Gas University (Moscow, Russia)
  • Tomsk Polytechnic University, Russia.
  • Dr. E. Savelieva (Nuclear Safety Institute, Moscow, Russia)
  • Prof. J. Caers, Stanford University, USA
  • Prof. George Christakos
  • Marc Serre, University of Chapel Hill, USA

Biography

2003: I joined Heriot-Watt University and was later promoted to Research Fellow and then to a Lecturer.

2000-2002: Post-doc on population dynamics modelling, University of St Andrews, Mathematical Institute,.

1998: PhD degree in physics and mathematics from Russian Academy of Sciences (Nuclear Safety Institute)

Thesis on radioactive pollution modelling with geostatistics and artificial neural network.

1994: My first degree is in physics from Moscow State University. Thesis on atmospheric pollution transport modelling.

Editorial roles:
2011-2020: Computers and Geosciences, Associate Editor
2014-2015: Computers and Geosciences, Guest Editor for a special issue "Statistical learning in geoscience modelling: Novel algorithms and challenging case studies", Volume 85, Part B

2018-2019: Mathematical Geosciences, Guest editor for a special issue “Data Science for Geoscience”

2021: Energies MDPI Open Access Journal, Guest Editor for a SI "Data Science in Reservoir Modelling Workflows"

I am a member of the International Association for Mathematical Geosciences (IAMG) and European Association of Geoscientists and Engineers (EAGE).

I was a convener of the Machine learning session at Annual IAMG meetings in 2009 and 2013 and also a member of the scientific committees for a number of geostatistical and geosciences conferences.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 13 - Climate Action

Keywords

  • QC Physics
  • uncertainty
  • machine learning
  • statistics
  • geostatistics
  • optimisation
  • Bayesian
  • prediction modelling
  • petroleum
  • geoscience
  • environmental mapping
  • inverse modelling
  • predictions

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