Geostatistical Quantification of Facies Relationships in Reservoir Models
PHD STUDENTSHIP WITH IMPERIAL COLLEGE LONDON
Supervisor: Prof. Olivier Dubrule
Geostatistical simulation is now the routine approach used in petroleum geosciences to model
reservoir heterogeneities. The generation of 3D facies distributions is usually based on one of
the four following approaches: indicator simulation, pluri-gaussian models, object-based
models or multi-point statistics approaches. The chosen method should be the one which is
best capable of representing the quantified geological information associated with the
reservoir’s depositional environment: indicator variograms, rock-type rules, genetic units
geometry or training images are the quantification tools respectively associated with each of
the four modelling approaches.
It is fair to say that the above quantification tools are not necessarily familiar and easy to
approach by geologists, who often prefer to discuss geological architecture in terms of
cyclicity, coarsening/fining-upward sequences, or probability of transitions between facies
(for instance). As a result the geostatistical reservoir models are not always as realistic as the
geologists would like.
This PhD will first consist of comparing the various quantitative assumptions made by the
different geostatistical methods and express those in relations with the quantitative rules used
by geologists. For instance, what are the implicit and explicit architectural controls imposed by
a training image vs pluri-gaussian assumption.?
An important subject to address will be that of the modelling of vertical vs lateral variations
and geostatistical uses that can be made of geological principles such as Walther’s Law and
sequence stratigraphy considerations.
The above methods will be tested using commercial software available at Imperial College
London. It is likely that some computer developments will be required through earth modelling
plug-ins or Matlab-like developments.
Tests will be performed using field data, both from carbonate and clastic environments.
The outcome of the work is expected to be new geostatistical simulation techniques better
suited to geological quantification, or new ways of parametrizing existing methods.
The successful candidate will join, and be supported by a vibrant and dynamic research group
with world-class expertise in sedimentology and industry leading expertise in petroleum
geostatistics. He/she will be trained in state-of-the-art geostatistical methods for modelling
reservoirs. The candidate will have the opportunity to develop his/her career and profile by
presenting at international conferences and publishing in high impact journals.
Entry requirements: Candidate for this PhD position should have a Geoscience MSc degree,
a good mathematical background and a strong interest in computer modelling.
Application: if interested please contact Prof. Olivier Dubrule (o.dubrule@imperial.ac.uk),
Those looking to apply for an ESE departmental PhD scholarship to support their studies
should be aware that the deadline for formal applications is 31st January 2015.