Locating and producing hydrocarbons in an economically viable and sustainable way has become more challenging than ever in a volatile oil price climate and challenging exploration and development environments. The project aims to improve the understanding uncertainty modelling involved in high-stake decisions that are crucial in making exploration and development choices. The proposed research will enhance quantitative Earth imaging investigation for realistic estimation of reservoir rock properties with a novel way to fuse together the richness of geological interpretation, geophysical observations and statistical rigor in data conditioning with respect to the underlying physics. The combination of the data-driven and model-driven approaches will enable to characterize the associated uncertainty more consistently with respect to the non-uniqueness in interpretation and data conditioning. The research outcome will have high business impact potential in reserves estimation accuracy, reducing the risk in frontier exploration, appraisal and maximising the value of the existing production by guiding the well placement.
The methodology we propose is compatible with the state-of-the-art geostatistical, geophysical and geological modelling components of the reservoir characterization workflow. Models become increasingly important in a sparse data environment like petroleum exploration where strategic decisions are costly. Quantitative description of geology is non-trivial because it is based on incomplete, contradictory and subjective information. Implementation of recent advanced geostatistical methods in real 3D cases with large datasets remains difficult. To overcome this issue, the elementary training image (ETI, Mariethoz, Kelly, 2011) concept will be adapted. ETI’s are considered as puzzle pieces to be assembled in a certain way to represent a meaningful geological architecture and honour the available geophysical measurements.
The project will develop a method to build geologically realistic combinations of such puzzle pieces to establish the balance between the modelled subsurface patterns and the observed data. This balance is non-unique and is subject to interpretational uncertainty associated with possible geological concepts and the data acquisition and processing. The assemblage rules will be derived by combing the geometrical relationships between the rock layers (stratigraphy) and the physical relations between their properties derived from seismic. The proposed method is a relatively simple way to parameterise complex geological structures with the quantitative stratigraphic characteristics extracted from the seismic data and embedded in the statistical property modelling to accommodate the realistic geological trend with ETI geometrical transformations.
The suggested methodology will be extendable to a wider range of subsurface modelling applications, such as water and mineral resource exploration and environmental pollution issues, where integration of geological knowledge and geophysics data is needed for uncertainty prediction.
The project will be developed in collaboration with Prof. Gregoire Mariethoz of University of Lausanne (UNIL), who is an internationally renowned expert on multiple-point geostatisticasl modelling. The prospective PhD candidate will have the opportunity to visit UNIL during the course of the PhD. Heriot-Watt University has a good track record of student exchanges with University of Lausanne with two successful PhD projects co-supervised by HWU academics and resulted in several publications.
Informal enquiries should be directed to the primary supervisor, Professor Vasily Demyanov.
Applicants should have a first-class honours degree in a relevant subject or a 2.1 honours degree plus Masters (or equivalent). Scholarships will be awarded by competitive merit, taking into account the academic ability of the applicant.
Please complete our online application form and select PhD programme Petroleum Engineering, Petroleum Geoscience or Applied Geoscience within the application and include the project reference, title and supervisor names on your application. Applicants who do not include these details on their application may not be considered.
Please also provide a written proposal, at least one side of A4, outlining how you would approach the research project. You will also be required to upload a CV, a copy of your degree certificate and relevant transcripts and one academic reference. You must also provide proof of your ability in the English language (if English is not your mother tongue or if you have not already studied for a degree that was taught in English). We require an IELTS certificate showing an overall score of at least 6.5 with no component scoring less than 6.0 or a TOEFL certificate with a minimum score of 90 points.
Applicants MUST be available to start the course of study in October 2019.
Scholarships will cover tuition fees and provide an annual stipend of approximately £14,999 for the 36 month duration of the project.