Upscaling and Artificial Intelligence Based Proxies for Uncertainty Assessment of Reservoir Production

Course Description

The aim of the course is to recap main techniques required to build an integrated reservoir model and to explain different potential workflows for field development and/or history matching processes. This course will include explanations of upscaling techniques and the use of proxies for uncertainty assessment of production forecasts.

All these methods will be illustrated and applied to the Brugge case.

Course Objectives

Upon completion of the course, participants will be able to:

  • Understand the fundamentals of Geostatistics and Spatial Modeling
  • Calculate a variogram
  • Know what are the principal of Kriging
  • Know the main methods of Geostatistical Simulations for modeling heterogeneous and fractured reservoirs
  • Be familiar with the main Upscaling techniques used in reservoir simulators
  • Know how to use proxy models for assessing Uncertainty in Production Forecasts
  • Application to the Brugge field will be given to illustrate the methodology.

Course Outline

Integrated Geological Modeling and Reservoir Simulation

  • Geostatistics and Spatial Modeling
  • Variogram
  • Kriging
  • History Matching Principles

Geostatistical Simulations

  • Limitations of Kriging
  • Geostatistical Simulation
  • What do we want from a simulation?
  • Principles of stochastic modeling
  • Pixel based model
  • Object based model
  • Sequential Gaussian Simulation (SGS)
  • Random Character
  • Properties of SGS
  • Scale
  • Cell Sizes & Ranges
  • Indicator Formalism
  • Sequential Indicator Simulation


  • Why Upscaling is Needed?
  • Orders of magnitudes for the Geological Model and the Reservoir Simulators
  • Is it necessary to take into account all heterogeneities?
  • Impact on CPU cost
  • Can we replace heterogeneities by homogeneity?
  • Is it right to call “equivalent” the upscaled permeabilities?
  • The upscaling problems considered here
  • Upscaled Values Depends on Flow
  • Upscaling of Geo-cellular Models
  • Upscaling in Integrated Studies
  • Upscaling of porosity
  • Upscaling of absolute permeability
  • Differences between additive and non additive variables
  • Single phase
  • Darcy’s law
  • Single Phase Flow around Wells
  • What happens in 1 D?
  • Arithmetic Average
  • Harmonic Average
  • Geometric Average
  • Weighted Arithmetic Average
  • Weighted Harmonic Average
  • What happens for a layer cake model?
  • Upscaling generates anisotropy
  • How to handle barriers & faults?
  • How to handle fractures?

Uncertainty Assessment in Production Forecast

  • Intuitive Workflow
  • Recommended Workflow
  • Artificial Neural Network as Proxy
  • Applications on case studies
  • Application to Brugge field

Participants’ Profile

The course is primarily addressed to reservoir geologists and reservoir engineers involved in building reservoir models but could also be of interest to production engineers who have to deal with the consequences of uncertainty in reservoir performance.


Darcy’s law, basic probability and statistics.

Recommended Reading

  • Corvi P., Heffer K., King P., Tyson S., Verly G., Ehlig-Economides C., Le Nir I., Ronen S., Schultz P., Corbett P., Lewis J., Pickup G., Ringrose P., Guérillot D., Montadert L., Ravenne C., Haldorsen H., Hewett T. 1992. Reservoir characterization using expert knowledge, data and statistics. Oilfield Review 4(1):25-31.
  • Guérillot, D. and Bruyelle, J. 2014. A fast and accurate upscaling of transmissivities for field scale reservoir simulation. In ECMOR XIV- 14th European Conference on the Mathematics of Oil Recovery.
  • Bruyelle, J., & Guérillot, D. (2019, October 21). Proxy Model Based on Artificial Intelligence Technique for History Matching - Application to Brugge Field. Society of Petroleum Engineers. doi:10.2118/198635-MS
  • Bruyelle, J., & Guérillot, D. (2019, September 17). Optimization of Waterflooding Strategy Using Artificial Neural Networks. Society of Petroleum Engineers. doi:10.2118/196643-MS
  • Bruyelle, J., & Guérillot, D. (2019, October 21). Well Placement Optimization with an Artificial Intelligence Method Applied to Brugge Field. Society of Petroleum Engineers. doi:10.2118/198656-MS

About the Instructor

Former member of the Executive Committee of IFP and Program Director for the Upstream R&D of Saudi Aramco, he is focusing in Oil and Gas Exploration and Production including Unconventional, CO2 EOR and Carbon storage. After a PhD in Applied Mathematics, he joined IFP in 1982 in the Reservoir Engineering Dpt. He started his career in the Exploration and Production sector developing Expert system for selecting EOR methods and Advanced Compositional Reservoir Simulators for EOR (CO2 and thermal methods).

In 1985, he began cooperating with geologists and he invented with the Paris School of Mines the first software package integrating reservoir characterization and flow simulations in porous media proposing innovative methods for upscaling absolute permeabilities.

After being the Director of the Geology and Geochemistry (95-01, in 2001, he became member of the Executive Committee of IFP and Managing Director of Exploration and Reservoir Engineering Centre with a total budget of 30 Millions of Euros. Consequently, IFP nominated him as board member of several Exploration and Production subsidiaries of IFP: Beicip-Franlab and RSI in France, IFP MEC in Bahrain, etc. He developed new strategic orientations for the business unit he was in charge modifying its business model to generate revenues based on royalties through the development of several strategic marketed software for IFP.

In 2009, he created a Young Innovative Company (YIC), Terra 3E, in Energy and Environment: developing innovative plug-ins in Petrel software among which the first tool for accurate calculations of fluids in place for gas and oil shales and upscaling transmissivities.

From 2010 to 2013, he was senior expert for Petrobras, Brazil.

In 2012, he served the European Commission for selecting R&D projects on CO2 Storage.

In 2013, Qatar Petroleum called Dominique Guérillot for developing their R&D Centre at the Qatar Sciences and Technology park in Doha, Qatar. He is currently full professor at Texas A&M University in their campus of Qatar.

He published more than 50 full and refereed papers, holds 5 patents, is member of the IJOGCT editorial team, the SPE and EAGE associations, is referee of the Oil & Gas Science and Technology (OGST), and member of the editorial board of the Petroleum Geoscience journal of the Geological Society.