EAGE Short Course on Uncertainty in Reservoir Management

12 - 12 November
Perth, Australia
Call for papers

Uncertainty in Reservoir Management



Prof. Peter King (Imperial College, London UK)


 12 Nov 2019 (1 day)


Engineering – Reservoir Management




  5 CPD points


Course description

Uncertainty arising from lack of precise knowledge about the subsurface is present in all reservoir developments. It can impact significantly on the development plan even making the field uneconomic to develop. Failure to account for it can lead to sub-optimal development with a potential for a large loss in investment or failure to be able to achieve a potential upside. The aim of this course is to give an introduction into how the uncertainty can be quantified and accounted for in production optimisation. To achieve this the course is broken into three main sections. First an introduction to the sources of uncertainty and the basic statistical tools used to quantify it are given. Specific reference will be made to reservoir heterogeneity and the sources of data required to model this. Then a short overview of the geostatistical tools used to incorporate uncertainty into reservoir modelling is made. This will cover the different tools required to model different geological environments. Finally a review of some formal optimisation tools used for making production decisions is made. Specifically these include algorithms such as simulated annealing, genetic algorithms and so on. A key issue is how reservoir uncertainty can be accounted for by these methods. This leads to the use of a variety of techniques such as real options and portfolio optimisation. These methods will be exemplified by by real field examples. the material covered ranges from established practice to current research activities.
Whilst many of the methods described are potentially highly mathematical detailed derivations will not be gone through. Rather the aim of the course is to provide the background required and to achieve an understanding of why these formal methods are needed as well as the potential benefits of using them. Key to this is an introduction to formal decision making techniques, as developed in other industry sectors. At the end of the course participants should have an understanding of the basic vocabulary of the techniques that can be used, or are being developed, to improve production optimisation decisions in the presence of uncertainty. Additionally the limitations of existing methods and need for future research will be discussed. Delivery will be through presentation of the basics and examples of use but it is expected that participants will involve in active discussion. The course is primarily aimed at reservoir engineers but should be accessible to geotechnical specialists in the upstream oil and gas sector.


Course objectives

  • 1) Have an understanding of uncertainty in reservoir modelling, where it comes from and its impact.
    2) Have knowledge of the basic statistical tools used to describe uncertainty and the tools used for stochastic reservoir modelling
    3) Have basic knowledge of some tools used for optimising reservoir production, especially in the presence of uncertainty


Participants' profile

Upstream geotechnical experts (Geoscientists, Reservoir Engineers), Production planning, Asset managers.



Familiarity with the concepts of reservoir modelling. Some knowledge of statistics and probability is useful but not essential.


About the instructor

After completing a PhD in theoretical statistical physics from Cambridge University in 1982 Professor Peter King spent 17 years with BP at their technology centre in Sunbury-on-Thames where he worked on a wide variety of subjects applying methods of mathematical physics to reservoir characterisation and modelling. In particular he developed a real space renormalisation approach to both single and two phase upscaling. He has used percolation theory to estimate connectivity of sands as well as uncertainties in production from low to intermediate net-to-gross systems. With a former student (Prof Mohsen Masihi) he published a book on "Percolation Theory in Reservoir Engineering" in 2018. He had also developed network models of pore scale flow and viscous fingering, object based methods for characterising reservoir heterogeneities. In conjunction with Boston University he worked on segregation in avalanches in granular materials as an explanation for the formation of crossbeds in Aeolian systems. Recently he has worked on applying stochastic search algorithms (simulated annealing and genetic algorithms) to optimising business decisions with particular interest to decision making in the presence of uncertainty. He joined the Department of Earth Science & Engineering at Imperial College in 2000.

Professor King is a Fellow of both the Institute of Physics (Chairman of the Theoretical Condensed Matter Physics sub-group from 1999) and the Institute of Mathematics and its Applications (having served on its Governing Council from 1991-1994). He was a Royal Academy of Engineering Visiting Professor in the Department of Engineering at Cambridge University and a Visiting Scholar in the Department of Physics at Boston University.