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Modelling and Managing Uncertainty in the Subsurface (RES38)

  • To be announced for 2020


Uncertainty quantification is a synthesis course that brings together various disciplines such as geology, geophysics, reservoir engineering, data science and decision analysis. Uncertainty quantification is not seen as some posterior analysis, or skill, but as key to successful decision making in real field situations. Participants will learn how a proper management of uncertainty reduces costs and unwanted surprises.

In this short course we cover a modern approach to managing and modelling uncertainty in subsurface formations within a decision making framework. We outline an uncertainty quantification workflow that focuses on several elements:
  • Decision-driven sensitivity analysis to determine key reservoir variables
  • Geological scenario development to avoid reducing uncertainty artificially and during history matching
  • Use of seismic and production data for model rejection
  • Issues of computational challenges through model validation and screening

For in-house presentations this course can also be arranged as 5-day "Workshop" with practical exercises.

Course Level: Skill
Instructor: Jef Caers

Designed for you, if you are...

  • A reservoir geologist, geophysicist or engineer who is involved in a multi-disciplinary asset team building uncertainty models for reservoir appraisal and production planning

How we build your confidence

  • The course uses practical field studies to guide you through the modelling workflow from geological interpretation to history matching and forecasting
  • In addition to the course manual you will also receive the textbook 'Modeling Uncertainty in the Earth Sciences' by Jef Caers

The benefits from attending

By the end of the course, you will feel confident in your understanding and use of practical workflows for modelling uncertainty and the integration of geological, geophysical and production data for forecasting and decision making.


  • What is uncertainty?
  • Managing uncertainty in the oil & gas industry
  • Decision making under uncertainty
  • Representing uncertainty in metric space
  • Decision-focused sensitivity analysis for reservoir models
  • Validating uncertainty models with reservoir log, seismic and production data
  • Model selection and model complexity: addressing the computational challenge
  • Uncertainty quantification with seismic and production data
  • Calculating value of information

Customer Feedback

"The topic is difficult, but Jef was phantastic in bringing things down to the simplest examples." - Sr. Reservoir Engineer at OMV

"The topic is widely useable, not only to surface modelling. Jef very intelligently brings all facets together. Important for the RE & Modelling crowd to follow this approach. I believe we need a Part II of this course." - Production Engineer at OMV

"It opens a new area in the industry and changes your view on it" - Reservoir Engineer at MND

"Very thought provoking, excellent tools and strategies for problem solving." - Reservoir Engineer at BG Group




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