Oil and Gas

Participants will learn to:

1. Form a fluid-sensitive conceptual model for a heterogeneous reservoir, built from a selection of elements and placed in a realistic architectural framework: the “sketch”.
2. Intuitively-guide the use of geostatistical tools, balancing deterministic and probabilistic components with awareness of the limits of the tools.
3. Select appropriate methods for modelling of matrix properties, including the handling of net (cut-off’s vs total property modelling).
4. Evaluate fracture properties, covering both faults and fault seal and also flow through open fracture systems; understand how to model these practically.
5. Understand issues surrounding permeability modelling and why this differs from the handling of other properties.
6. Learn a rule of thumb (‘Flora’) to help assess what level of static model detail matters to flow modelling and forecasting.
7. Review how to use well test analysis to constrain models.
8. Review options for model based uncertainty handling (base case led, multi-deterministic, multi-stochastic ‘ensembles’), how to post-process the results and how to select an appropriate workflow which minimises impact of behavioural bias.

The central theme of the event is Reservoir Model Design, on the premise that it is design rather than software knowledge that typically distinguishes ‘good models’ from ‘bad models’. This is organised around the following five themes, issues within which are often the cause of a poor model outcome:

1. Model purpose

2. Elements and architecture

How much detail should be incorporated in the models? From the rich spectrum of potential lithofacies, electrofacies, biostratigraphic and analogue data inputs, how do we select the ‘right’ number of components (elements) to take forward into the modelling process? Once selected, how do these elements combine into a realistic description of length scales and reservoir architecture? How to capture this in an interpretative sketch that can be used as a cross-discipline communication tool.

3. Probability and determinism

Is the balance of probabilistic and deterministic components appropriate given the model purpose? Should heterogeneities be handled implicitly or explicitly in the static and dynamic models and if implicitly, then how should we average properties? What are our expectations of geostatistics and how do we control the algorithms intuitively to replicate a sketched reservoir concept?  This applies both to modelling of the matrix and also fractures, and we explore how we can use well test data to place deterministic constraints on our models.

4. Multi-scale modelling

What scale should we be modelling and simulating at given the fluid type and model purpose? Can everything be modelled at one scale, or are static/dynamic multi-scale models required? We address the full spectrum of heterogeneity using the concept of Representative Elementary Volumes and conclude that traditional static-dynamic upscaling is only part of the story, and not always the main part.  Illustrations of fine-scale 'Ultimate Truth' models will be used to illustrate where we sometimes go wrong with over-simplifying a design.

5. Model-based uncertainty-handling

What are the tools we can use to identify natural bias in the modelling process and select workflows which capture useful ranges in a practical way, minimising bias in the process? We summarise the current range of stochastically- and deterministically-led options, including the current trend to 'ensemble' modelling, and discuss which techniques are appropriate to use, and when, and how to post-process the results and communicate them usefully to colleagues.

Geoscientists with some knowledge of reservoir modelling; Petrophysicists who provide input to static reservoir models; Reservoir engineers involved in simulation work who deal with the static-dynamic interface and upscaling on a regular basis. Multidisciplinary asset teams would benefit from attendance as a group. The course is also of benefit to team leaders who wish to have a deeper understanding of the principles behind modelling, and any subsurface staff involved in the QC of models made by others.