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Research Associate in Machine Learning & 4D Seismic



School of Energy, Geoscience, Infrastructure and Society
Research Associate in Machine Learning and 4D seismic
£32,817 - £40,322

The Institute of Geoenergy Engineering (IGE) was founded in 1975 and is widely recognised as one of the internationally leading centres of excellence for learning, teaching, and research in petroleum engineering and petroleum geoscience.
IGE provides specialist training through its MSc programmes in Petroleum Engineering, Reservoir Evaluation and Management, Petroleum Geoscience, and Integrated Mature Field Management, which are offered on Heriot-Watt University’s campuses in Edinburgh, Dubai, and Malaysia, through Approved Learning Partnerships in Russia, Portugal, and Australia, or through distributed learning. IGE also partners with Schlumberger to deliver an MSc in the Management of the Oil & Gas Industry and with SOCAR to establish the Baku Higher Oil School, or with the Oil and Gas Innovation Centre. To-date, over 4000 students have graduated from IGE, many of them now holding leading positions in the energy industry or academia.
IGE’s industrially focused research involves over 60 academics and 100 PhD students and covers the full range of activities related to the upstream oil and gas industry, from exploring hydrocarbon provinces to characterising the reservoirs and providing robust uncertainty envelopes for future hydrocarbon production to developing new chemical and engineering solutions that ensure that production wells operate efficiently. More recently, IGE has extended its capabilities to develop and manage other subsurface forms of energy such as geothermal energy and CCUS through new collaborations with the Lyell Centre for Earth and Marine Science and Technology to support the transition to a low-carbon energy future. IGE leads several major UK-wide and interdisciplinary research centres, such as the NERC Centre for Doctoral Training in Oil and Gas, the International Centre for Carbonate Reservoirs, or the Centre for Energy Economics Research and Policy.
For further information visit http://hw.ac.uk/IGE

Essential

Qualifications

- A first degree in Mathematics, Physics, Geophysics, Computer Science, Data analytics or similar field
- A PhD in Mathematics, Geophysics, Computer Science, Data analytics

Experience

- Knowledge and experience in 4D seismic, rock physics
- Knowledge and experience in the use and development of machine learning
- High level competence in mathematics

Competencies, Skills and Knowledge

- Excellent IT skills
- Good team player with good interpersonal skills
- Good presentation skills and self-organised

Duties and responsibilities will include:
The applicant will be involved in an industry-sponsored research project whose goal is to develop novel rock physics driven machine learning /deep learning inversion methodologies for fluid and facies prediction using 3D and 4D data. The project will test the methods on synthetic datasets, before progressing to applications on one or several real field datasets. The applicant will undertake the necessary research and development of algorithms that aim to estimate dynamic and static changes in the subsurface using machine learning. They will also support and help to supervise a PhD student working on a similar theme. The tools developed will be developed in preparation for further mapping onto in-house company facilities. Over the course of the three years, the algorithms must be developed to a high TRL suitable for use within a company environment.

The post is available for 36 months.
For application details and further information please go to: www.hw.ac.uk/apply-jobs

Ref: IRC30968 Closing date 15 March 2021


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