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Uncertainty in reservoirs

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1 Uncertainty in reservoirs
Classification: Internal

2 Deepwater Horizon – Gulf of Mexico
The slightly more mundane situation I consider: We have a hydrocarbon reservoir We have a model for the reservoir which will be used for future decisions. The parameters in the model are uncertain. What do we do with the uncertainty? Operational uncertainties are unfortunately not a topic in this presentation. Classification: Internal

3 Uncertainty in the petroleum industry
Organisational issues: Strong financial inertia to ”stick with the truth”. Tradition for compartmentalized organisations where uncertainty information is not passed on. ”What happens happens” – limited tradition to reevaluate uncertainty estimates. Current topics: Choice of parameters – model selection. Different scales. Stochastic modelling. Classification: Internal

4 $€£ $€£ $€£ $€£ $€£ Maybe the reservoir is larger? Producing fields:
Or smaller? There is so much money, financial regulations e.t.c. in these questions that there is a strong organisational urge to just ignore the uncertainty. Classification: Internal

5 An organisational challenge
Geological model Structural model OK; I pass my best result on to Deborah! I am working hard to interpret the seismic and build a structural model. I am doing flow simulations, and management even wants uncertainty estimates these days I pass my best effort on to Phillip. I am creating a geological model. Well - I’ll try out different values for a couple of parameters and see what happens. Classification: Internal

6 ”What happens happens”
We do our best to model and quantify uncertainty. We make a decision to e.g. drill a well: Estimated oil volume: A +/- B – found nothing! Estimated gas volume: A +/ B – found both gas and oil. The new information is used to infer that we were just wrong. Uncertainty estimates are not really challenged. Classification: Internal

7 History matching – it is just plain stupid
Traditionally History Matching is percieved as an optimization problem – a very problematic approach: The problem is highly nonlinear, and severely underdetermined. The observations we are comparing with can be highly uncertain. The choice of parameterization is somewhat arbitrary – we will optimize in the wrong space anyway. Classification: Internal

8 Geological concept Channel system Deep marine
Shallow marine The choice of geological concept is an example of a choice which will have a profound effect on subsequent interpretations, and decisions. Classification: Internal

9 Model/parameter selection II
Good agreement between model simulation and observation! Two wrongs do not make a right – it is all to easy to get ”a match” for the wrong reasons: Maybe the ”real” reason was that the oil-water interface was shallower? Water rate Time Oil Simulations show to little water. Increase relative permeability of water Water Classification: Internal

10 Different scales Geo object 1 4 ~10 m 5 2 3 ~50 m ~0.25 m
Geological heterogeneities to model explicit using the REV concept Classification: Internal

11 Different scales II Pores Reservoir ~ 9 orders of magnitude
Classification: Internal

12 Different scales III: Upscaling
k1 k2 k3 Permeability: k1<< k2<<k3 Vertically: Horisontally: k1 k2 k3 ~k3 ~k1 Classification: Internal

13 Different porosity realisations
Geostatistics Different porosity realisations It is quite common to sample properties like permeability and porosity stochastically – with various constraints/trend parameters: Spatial gradient Point measurements Correlation length Classification: Internal

14 Modelling – the full loop
Sample geostatistical parameters Ideal approach: Make all alterations on geo parameters, and keep everything syncronized. Sample a geological realisation according to the parameters. Traditional approach: Cutting the link to geostatistical paramaters. Direct updates of the properties of the realisation Perform flow simulations and evaluate misfit. Classification: Internal

15 McMC and stochastic modelling – attempt 0
The geo modelling process is not a closed form PDF; it can only be observed from the created realizations. We have tried to update update geo parameters; initial attempts show some success! Uncertainty: Classification: Internal

16 Example – channel direction
Posterior: θ~0o Prior: θ~100O Conditioning the distribution P(θ|d) with McMC Classification: Internal

17 Thank you! Main challenges
Model selection – and how to handle the ”Uknown unknowns”. Conditioning of coarse parameters like geostatistical trends. Thank you! Classification: Internal

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