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Advanced fractal modelling of heterogeneous and anisotropic geological hydrocarbon reservoirs

Dr. Piroska Lorinczi (SEE), Prof Paul W.J. Glover (SEE)

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  • Opportunity to fully implement and test an exciting new approach to reservoir modelling, taking it to the edge of commercialisation.
  • The project is a blend of geophysics, mathematics and advanced coding, which is a stepping stone to both IT and Geoscience-based industries.
  • Join a diverse research group covering all aspects of rock physics with an international reputation and links to industry.
  • The project is supported by successful pilot studies with the potential to generate early publications and consequent option of PhD assessment by publications alone.


The modern oil and gas industry is refocussing its efforts. Most of the large and simple conventional reservoirs have now been found and exploited. New reservoirs are discovered regularly, but these are small, complex and difficult to produce. Reservoir modelling, a key tool in reservoir management, struggles to be relevant in the new complex heterogeneous and anisotropic reservoirs. Fractal-based methods allow the complexity of the reservoir to be accounted for in the reservoir model over a large range of scales. Research at the University of Leeds has already made significant progress in creating these state-of-the-art models (Al-Zainaldin et al., 2017; Glover et al., 2018). Initial coding exists that allows us to make generic Advanced Fractal Reservoir Models (AFRMs), and some research has examined how hydrocarbon production depends on the spatial and directional distribution of critical reservoir properties such as porosity and permeability.

Aims and Objectives.

The aim of the research is to develop the AFRM technique to the edge of commercialisation. Its objectives include:

  • To convert existing AFRM code into a consistent set of procedures, including the development of QA and statistical tools.
  • To develop methods for extracting reservoir fractal dimensions and anisotropy factors from 3D seismic data cubes.
  • To carry out a full study of how the heterogeneity and anisotropy of reservoirs affects reservoir production.
  • To further develop methods for carrying out fractal interpolation for conditioning AFRMs to real reservoirs.
  • To carry out full AFRM and conventional modelling on a limited number of type reservoirs.
  • To develop, test and validate a pre-commercial beta version of the AFRM code including a UX-rich UI.


The PhD will progress in 5 consecutive, but overlapping strands.

  • The first strand will involve modification to the existing code for creating generic AFRMs, followed by its use to examine how changing reservoir heterogeneity, anisotropy and well placement affects hydrocarbon production over time.
  • The second strand concerns the analysis of 3-D seismic data cubes. In this strand the candidate will develop methodologies for extracting fractal dimension and anisotropy data from raw seismic and seismic attribute data.
  • The third strand involves the further development and testing of the fractal interpolation method that will be used to condition AFRMs to represent real reservoirs. This is a critical step that we know from pilot studies to be possible.
  • The fourth strand is dedicated to a full comparative testing of the conditioned AFRMs and conventional reservoir models on a limited number of well-characterised reservoirs.
  • The fifth and final strand to the PhD involves the implementation of existing coded procedures within a clear and easy to use UI.


This PhD proposal is unusual in that it combines (i) geophysics, (ii) the elaboration of a new analytical approach, (iii) software development, and (iv) pre-commercialisation in one piece of work, making it ideal for an industry-focussed student with the right qualities. The software development is prefigured by a number of successful pilot studies which have already led to scientific papers (Al-Zainaldin, 2017; Glover et al., 2018), and which need to be expanded upon in order to provide early publications. All AFRM development and 4 reservoir modelling will be carried out using the extensive computer facilities and state-of-the-art software of the School of Earth and Environment. The supervisory team is extremely experienced in reservoir modelling, and has an excellent track record in PhD supervision.


Applicants should have a BSc or BEng degree (or equivalent) in mathematics, computer science, physics, geology, earth sciences, geophysics, petroleum engineering or a similar discipline. An relevant Master?s level qualification would be an advantage. The applicant must be competent in handling discrete mathematical equations and be able to code in common languages effectively. Some experience of UX/UI design is desirable.

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Related undergraduate subjects:

  • Computer science
  • Computing
  • Earth science
  • Engineering
  • Geophysical science
  • Geophysics
  • Geoscience
  • Mathematics
  • Natural sciences
  • Physical science
  • Physics