PhD
- Dr Gleb Shishaev, 2024: History Matching and Uncertainty Quantification of Reservoir Performance with Generative Deep Learning and Graph Convolutions
Supervisors: Prof Vasily Demyanov, Dr Dan Arnold
Examiners: Prof Denis Voskov (external, TU Delft), Prof Ahmed ElSheikh (internal) - Dr Athanasios (Athos) Nathanail, 2023: Capturing interpretational uncertainty of depositional environments with Artificial Intelligence, Appendix – Data tables.
Supervisors: Dr Dan Arnold, Prof Vasily Demyanov,
Examiners: Prof Mikhail Kanevski (external, University of Lausanne), Prof Dorrik Stow (internal) - Dr Chao Sun, 2023: Use of Generative Learning to Improve Realism in Fluvial Facies Modelling
Supervisors: Prof Vasily Demyanov, Dr Dan Arnold
Examiners: Prof Guillaume Rongier (external, TU Delft), Prof Ahmed H. Elsheikh (internal) - Dr Quentin Corlay, 2023: Detection of Geobodies in 3D Seismic using Unsupervised Machine Learning
Supervisors: Prof Vasily Demyanov, Dr Dave McCarthy (BGS), Dr Dan Arnold
Examiners: Prof Guillaume Caumon (external, University of Lorraine, RING), Prof Uisdean Nicholson (internal) - Dr Bastian Steffens, 2022: Integrating geological uncertainty and dynamic data into modelling procedures for fractured reservoirs,
Supervisors: Prof Vasily Demyanov, Dr Helen Lewis, Dr Dan Arnold
Examiners: Prof Insa Neuweiler (external), Dr Mark Bentley (internal) - Dr Behzad Nezhad Karim Nobakht, 2018: Modelling discrepancy in Bayesian calibration of reservoir models, Supervisors: Prof Mike Christie, Prof Vasily Demyanov.
- Dr Alexandra Kuznetsova, 2017: Hierarchical geological realism in history matching for reliable reservoir uncertainty predictions, 2nd place – SPE International student paper contest 2016, 1st place – SPE student paper contest, European region 2016
Supervisors: Prof Vasily Demyanov, Prof Mike Christie - Dr Junko Hutahaean, 2017, Multi-Objective Methods for History Matching, Uncertainty Prediction and Optimisation in Reservoir Modelling, 1st place – SPE student paper contest, European region 2013,
Supervisors: Prof Vasily Demyanov, Prof Mike Christie - Dr Doaa Mostafa Ali Elsakout, 2016: Application of multilevel concepts for uncertainty quantification in reservoir simulation
Supervisors: Prof Mike Christie, Prof Gabriel Lord - Dr Hamid Bazargan, 2014: An efficient polynomial chaos-based proxy model for history matching and uncertainty quantification of complex geological structures
Supervisors: Prof Mike Christie, - Dr Temistocles Rojas, 2014: Controlling Realism and Uncertainty in Reservoir Models using Intelligent Sedimentological Prior Information
Supervisors: Prof Vasily Demyanov, Prof Mike Christie - Dr Asaad Abdollahzadeh, 2014: Adaptive algorithms for history matching and uncertainty quantification
Supervisors: Prof Mike Christie, Prof Dave Corn - Dr Mohammad Ahmadi, 2012: Modelling and quantification of structural uncertainties in petroleum reservoirs assisted by a hybrid cartesian cut cell/enriched multipoint flux approximation approach
Supervisors: Prof Mike Christie - Dr Yasin Hajizadeh, 2011: Population-based algorithms for improved history matching and uncertainty quantification of Petroleum reservoirs, 2nd place – SPE international student paper contest 2010, 1st place – SPE student paper contest, European region 2009,
Supervisors: Prof Mike Christie, Prof Vasily Demyanov - Dr Linah Mohammed, 2011: Novel sampling techniques for reservoir history matching optimisation and uncertainty quantification in flow prediction
Supervisors: Prof Mike Christie, Prof Vasily Demyanov - Dr Monika Valjak, 2008: History matching and forecasting with uncertainty : challenges and proposed solutions for real field applications
Supervisors: Prof Mike Christie - Dr Dan Arnold, 2008: Geological parameterisation of petroleum reservoir models for improved uncertainty quantification
Supervisors: Prof Mike Christie - Dr Hashem Monfared, 2007: An investigation into the links between upscaling and history-matching
Supervisors: Prof Mike Christie - Dr Demet Erbas, 2007: Sampling strategies for uncertainty quantification in oil recovery prediction
Supervisors: Prof Mike Christie - Dr Pinngang Zhang, 2007: Upscaling in highly heterogeneous reservoir models
Supervisors: Dr Gillian Pickup, Prof Mike Christie, - Dr Hirofumi Okano, 2006: Quantification of uncertainty in coarse-scale relative permeability for reservoir production forecast
Supervisors: Prof Mike Christie, Dr Gillian Pickup - Dr Alannah O’Sullivan, 2004: Modelling simulation error for improved reservoir prediction
Supervisors: Prof Mike Christie
MSc (selected)
2020
- Arnaud Colat-Parros, Evaluation of seismic well tie for turbidite fan identification with machine learning
- Adilet Kydyrgazy, Top-bottom modelling of hydrocarbon reservoirs based on data-driven proxy models
2019
- Nikita Yasenkov, Uncertainty quantification of reservoir prediction with Bayesian Evidential Learning based on the Watt benchmark
- Julia Katie Alexandra Neill, Waterflood Optimisation in a Mature Field using Flow Diagnostics
- Stephanie Herrington, Reservoir Characterization of the UDDGP reservoir using Rapid Reservoir Modelling Tool (RRM)
- Rose Elisabeth Harriet Leadbitter, Using Process Modelling and Flow Diagnostics to assess geomorphological parameter influence on the static and dynamic response of fluvial reservoirs
- Nathan Amaral, GAN Applications to Imaging of Seismic Obscured Areas (MACS)
2018
- Lindsay Herbert, Field Development Planning Utilizing Value of Information and Value of Flexibility Techniques to Reduce Uncertainty and Capitalize on Potential Opportunity
- Alex Asiedu Nimo, Value of Information in History Matching and Reservoir Prediction
2017
- Julie Halotel, Facies classification using machine learning
- Martial Morelle, Data driven based modelling of fluvial reservoir properties based on geologically realistic manifolds.
2016
- Ludmila Belyakova, Characterisation of uncertainty in naturally fractured reservoirs (NFR) flow response through static properties: connectivity and heterogeneity
- Looi Lee Teng, Modelling Uncertainty of Non-Stationary Fractured Reservoirs
- Tom Buckle, Investigating Fluvial Reservoir Uncertainty Using Process Models, and Their Application as Training Images in Multiple-Point Statistical Simulation
- Rhona Hutton, Using high resolution braided process models for multi-scale MPS modelling of the Wytch Farm field, English Channel
- Victoria Elizabeth Spooner, Uncertainty Quantification for Foam Flooding in Fractured Carbonate Reservoirs
2015
- Alexander Bakay, Uncertainty quantification in fractured reservoirs based on outcrop modelling from northeast Brazil
- Alexander Aitchison, Statistical Analysis and Modelling of Neoproterozoic Stromatolites Irece Basin, Brazil
2014
- Ross McGavin, Top-Down Reservoir Modelling of a Compartmentalised Reservoir
- María Méndez Ramírez, Relative performance of History Matching algorithms applied to a real North Sea case
- Fahad A. Bajammal, Assisted History Matching and Optimisation of CO2 Injection into the Naturally Fractured Reservoir of Tensleep Formation, Teapot Dome Field
- Elena Muñoz Saiz, Geological history matching of Brugge reservoir section
- Diana Carolina Tocancipa, Optimisation of Watt Field development plan for different top side facilities/ cost/constrains with economic uncertainties.
- Daniel Orlando Higuera Roa, Optimisation of well placement in Brugge reservoir
2013
- Andrew Fernie, The differences between Buckley Leveret and simulation for different reservoir architectures
- Junko Hutahaean, Optimisation of well placement to minimise the risk of scale deposition
- Konstantin Gopa, Exploring uncertainty of discrete fracture network models
2012
- Jhonnatan Jose Nodar Royero, Use of Produced Water Chemistry in Automatic History Matching of a Reservoir Model