Petrel Property Modeling - RILS (Remote Instructor Led Series)

Session 1 : Modules 1, 2 & 3

(4.5 Hours)

• Introduction to property modeling in Petrel
• Data preparation
• Scale up well logs

This session first introduces the Petrel reservoir modeling workflow - in particular, the Petrel Property modeling workflow - and presents the differences between Deterministic and Stochastic methods and the difference between Kriging and simulation. Then, the participants will learn how to prepare inputs for Property modeling through the different methodologies for generating lighological/sedimentological facies and petrophysical logs and through the Scale-up well logs process.   

Session 2 : Modules 4, 5, 6 & 7

(5 Hours)

• Univariate and bivariate geostatistical analysis
• Variogram analysis
• Facies data analysis
• Variogram modeling in the horizontal direction

This second session covers geostatistical analysis fundamentals forming the basis of the property modeling tools and methods in Petrel. In addition to variogram analysis, the session will also provide an overview of the facies modeling process in Petrel: how to build a realistic facies model, perform a statistical discrete data analysis for preparing inputs, and quality control the results.

Session 3 : Modules 8, 9, 10 & 11

(4.5 Hours)

• Facies modeling overview and workflow
• Sequential indicator simulation
• Facies object modeling
• Truncated Gaussian Simulation

During this session, the participants will first learn about all the facies modeling techniques available in Petrel. Then, they will discover the basic concepts specific to each technique and apply the Sequential Indicator Simulation, Facies Object Modeling and Truncated Gaussian Simulation methods.

Session 4 : Modules 12, 13, 14 & 15

(4.5 Hours)

• Facies modeling using secondary data
• Petrophysical modeling data analysis
• Petrophysical modeling overview and workflow
• Kriging in petrophysical modeling

In addition to presenting the different ways of creating and applying trends in Facies Modeling algorithms, this session will focus on petropohysical modeling: the preparation of the input data needed, the overview of deterministic and stochastic approaches, the key features, strengths and issues with the Kriging algorithm.

Session 5 : Modules 16 & 17

(5.5 Hours)

• Gaussian simulation in petrophysical modeling
• Petrophysical modeling using secondary data

In this final session, the participants will learn about the stochastic petrophysical modeling algorithms (Sequential Gaussian Simulation & Gaussian Random Function Simulation). They will also learn how to use various methods to identify the spatial variation of each petrophysical parameter and its correlations and how to use secondary information by applying Collocated Co-kriging, Bivariate distribution, and Local varying mean in the Petrophysical modeling process.