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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 Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 5 Similar Profiles
history Earth & Environmental Sciences
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Sampling Engineering & Materials Science

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

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

Reservoir development optimization under uncertainty for infill well placement in brownfield redevelopment

Hutahaean, J., Demyanov, V. & Christie, M., Apr 2019, In : Journal of Petroleum Science and Engineering. 175, p. 444-464 21 p.

Research output: Contribution to journalArticle

redevelopment
infill
Recovery
history
cost

Uncertainty Quantification in Reservoir Prediction: Part 1—Model Realism in History Matching Using Geological Prior Definitions

Arnold, D., Demyanov, V., Rojas, T. & Christie, M., Feb 2019, In : Mathematical Geosciences. 51, 2, p. 209-240 32 p.

Research output: Contribution to journalArticle

Open Access
File
history
prediction
parameter
depositional environment
modeling

Uncertainty Quantification in Reservoir Prediction: Part 2—Handling Uncertainty in the Geological Scenario

Demyanov, V., Arnold, D., Rojas, T. & Christie, M., Feb 2019, In : Mathematical Geosciences. 51, 2, p. 241–264 24 p.

Research output: Contribution to journalArticle

Open Access
File
prediction
inverse problem
sampling
history
geology

Press / Media