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Personal profile

Research interests

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 50 publications, including books: Geostatistics: Theory and Practice (Nauka, 2010, in Russian), Advanced Mapping of Environmental Data – Geostatistics, Machine Learning and Bayesian Maximum Entropy (Wiley, 2008).

Graduated Studen

International Research ts:

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: IPhD 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.

As an Associate Editor of Computers and Geosciences journal I acquire contributions bridging geoscience problems and advances in soft computing.

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.

Keywords

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

Fingerprint Dive into the research topics where Vasily Demyanov is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 3 Similar Profiles
history Earth & Environmental Sciences
modeling Earth & Environmental Sciences
prediction Earth & Environmental Sciences
simulation Earth & Environmental Sciences
History Matching Mathematics
learning Earth & Environmental Sciences
methodology Earth & Environmental Sciences
Uncertainty Mathematics

Co Author Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 1995 2019

A consistent stochastic framework to quantify large-scale geological uncertainty in stochastic seismic inversion

Azevedo, L., Demyanov, V., Lopes, D., Soares, A. & Guerreiro, L., 2019.

Research output: Contribution to conferencePaper

Acoustic impedance
acoustics
variogram
Particle swarm optimization (PSO)
histogram

Ensemble history matching enhanced with data analytics - A brown field study

Tolstukhin, E., Barrela, E., Khrulenko, A., Halotel, J. & Demyanov, V., 2019, 4th EAGE Conference on Petroleum Geostatistics. EAGE Publishing BV, ThPG04

Research output: Chapter in Book/Report/Conference proceedingConference contribution

History Matching
Field Study
Ensemble
History
histories

Flow through fractured reservoirs under geological and geomechancial uncertainty

Steffens, B., Demyanov, V., Couples, G., Arnold, D. & Lewis, H., 3 Jun 2019, 81st EAGE Conference and Exhibition 2019. EAGE Publishing BV

Research output: Chapter in Book/Report/Conference proceedingConference contribution

fracture network
modeling
Electric power distribution
carbonate rock
decision making

Improving local history match using machine learning generated regions from production response and geological parameter correlations

Buckle, T., Hutton, R., Demyanov, V., Arnold, D., Antropov, A., Kharyba, E., Pilipenko, M. & Stulov, L., 2019, 4th EAGE Conference on Petroleum Geostatistics. EAGE Publishing BV, ThPG06

Research output: Chapter in Book/Report/Conference proceedingConference contribution

machine learning
Learning systems
Machine Learning
histories
Neural networks

Multiscale uncertainty assessment in geostatistical seismic inversion

Azevedo, L. & Demyanov, V., May 2019, In : Geophysics. 84, 3, p. R355-R369 15 p.

Research output: Contribution to journalArticle

Open Access
File
Acoustic impedance
Spatial distribution
simulation
inversion
Uncertainty

Press / Media