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Thursday 7th December 2017

Schlumberger Gould Research Centre

United Kingdom


Schlumberger (SLB) is the largest supplier of technical services to the oil and gas industry, helping its customers find and produce hydrocarbons more efficiently. SLB services range from seismic data acquisition and interpretation to drilling and constructing wells, not only for hydrocarbon and geothermal energy production but also for CO2 sequestration. SLB understands the challenges and requirements to innovate that give rise to short- and long-term vision.

The Schlumberger Gould Research Center houses multidisciplinary research teams focusing on drilling, chemistry, fluid mechanics, and geophysics, through a combination of theory, experiment, and computational simulation. Because variational methods play a crucial role at all stages of SLB’s research and operation,  SLB partnered with the Variational Methods and Effective Algorithms for Imaging and Vision Programme  at the Isaac Newton Institute (INI) to bring academics and industrial researchers together under a series of workshops to explore the potentials of emerging methods in large-scale optimisation, optimal transport and machine learning for oil and gas industry.

The workshops titles and dates were as follows:

Speakers for this event were: Sergey Safonov (Schlumberger), Ben Veitch (Schlumberger), Ivan Graham (University of Bath), Martin Benning (University of Cambridge), Olga Veksler (University of Western Ontario), Thomas Pock (Graz University of Technology), Mila Nikolova (Ecole Normale Superieure Cachan), Hossam Isack & Yuri Boykov (University of Western Ontario) & Antonin Chambolle (Ecole Polytechnique). 

Speakers were: Chris Budd (University of Bath), Christoph Brune (University of Twente), Lukas Lang (University of Cambridge), Winston Lewis (SLB), Ozan Öktem (KTH Royal Institute of Technology in Stockholm), Clarice Poon (University of Cambridge) & Matthew Thorpe (Carnegie Mellon University). 

  • Machine Learning for Acquisition Systems on 7 December 2017

Speakers at this event were: Victor Aarre (SLB), Simon Arridge (University College London), Richard Dearden (SLB), Winston Lewis (SLB),  Francois Malgouryes (Institut de Mathématiques de Toulouse), Ozan Öktem (KTH Royal Institute of Technology in Stockholm), Marco Palombo (University College London), Ivan Yakimchuk (SLB) & Ganchi Zhang (Goldman Sachs).

This knowledge exchange event was delivered by the TGM as part of the Isaac Newton Institute Research Programme on Variational Methods and Effective Algorithms for Imaging and Vision. 

Aims and Objectives

SLB invited participants of the Isaac Newton Institute programme on Variational Methods and Effective Algorithms for Imaging and Vision Programme to attend this day of talks and discussions on topics relevant to large scale optimisation and their industrial applications. The talks were from INI and SLB participants with broad ranging discussions sought between academic and industrial researchers.


Registration was by invitation only and interested participants were asked to contact Evren Yarman or Carola Schönlieb. The event took place at Schlumberger Gould Research Center, Schlumberger, High Cross, Madingley Road, Cambridge CB3 0EL.