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GEO 119

Introduction to Principles of Geomodelling Practice

PetroTeach offers 5 days course on practical aspects of geomodelling combined with data analysis. The course contains of many exercises which are designed to reinforce the theory and lecture through hands-on learning. 

COURSE SCHEDULE

Code Date Location price (€)*
GEO 119 15 – 17 Apr 2024 Online 1390
GEO 119 1 – 3 Aug 2024 Online 1390
GEO 119 27 – 29 Mar 2024 London 2990
GEO 119 11 – 13 Sep 2024 Stavanger 2990

* Prices are subject to VAT and local terms. Ph.D. students, groups (≥ 3 persons) and early bird registrants (8 weeks in advance) are entitled to a DISCOUNT!

COURSE OVERVIEW

Geostatistics is the mathematical engine of spatial data analysis and geomodeling. Solid grounding in geostatistics is an essential qualification of a proficient Geomodeler, data scientist and problem solver within subsurface teams. PetroTeach offers 3 days course on practical aspects of geomodelling combined with data analysis. The course contains of many exercises which are designed to reinforce the theory and lecture through hands-on learning. 

The multi-disciplinary sub-surface team uses the geomodel to render the geologic interpretation into a digital format suitable for input to reservoir simulation software to better understanding the physical hydrocarbon extraction processes, for resource evaluations, for well and field planning, as part of reservoir uncertainty management, and in a variety of decision making processes. Challenges exist to adapt workflows and build efficiencies for subsurface modeling needs. Improved technical sophistication and open communication across disciplines can improve the ability of teams to reframe subsurface practices, mitigate bottlenecks and improve subsurface cycle time. The advanced exercises are scripted to allow flexibility to experience the impact of key parameter choices on model outcomes without getting bogged down in the software during a short course. The Isatis Geostatistics toolkit is used for exercises since it is a flexible software where basic techniques are transferable to common geomodeling software packages.

COURSE OUTLINE

3 days
Day 1

o Regionalized Variables: Data Types, definitions
o Univariate Statistics: Measures of position, spread, and shape; , stationarity, proportional effect
o Box plots, Q-Q plots
o Bivariate Statistics: Covariance and correlation
o Multi-variate: Principal Components analysis
o Quantifying Variability/Spatial continuity: Variograms- experimental, anisotropy; hand calculations; variogram maps; Behaviour, impact of outliers and calculation tips
o Variogram Models: illustrations; nested, issues, fitting tips and tricks, impact of choices
o Geostatistical Estimation
o General estimation techniques
o Kriging: simple and ordinary; Kriging by hand with a variogram model; Kriging weights, Cross validation, stationarity
o Trends in data: handling non-stationarity
o Case examples with mapping

Day 2

o Stochastic Methods summary
o Stratigraphic coordinate systems
o Deterministic facies trend modeling as a model constraint
o Object methods-summary
o Pixel methods: Illustrated description of algorithms for Truncated Gaussian (TGS), Truncated Pluri-Gaussian (PGS), Sequential Indicator (SIS), Multiple Point (MPS)
o Facies method characteristics and choices

Day 3

o Case Histories
o Compiling and checking the input databases, data types, model planning
o Defining the structure and stratigraphic framework; faults, grids and model sizing
o Facies inputs for models: Diverse Sources; Visual versus Electrofacies classification (machine learning); Issues, scale, rules for preparing for modeling; improving Rock Types
o Facies trend modeling: proper techniques and choices for building 1D, 2D and 3D proportions; integration of seismic attributes
o Topics on Petrophysical modeling of porous media and fluids: Porosity, water saturation methods, permeability, mechanical; scale, physics and specific rules, oil in place methods
o Re-scaling for the simulator techniques, specific parameter choices, practices and issues
o Post-processing: net pay, connectivity, summarizing and using uncertainty, parameter distributions, ranking and choosing
o Linking static to dynamic behavior through direct forecasting (proxies and type curves) in resource plays, statistical plays, delineation, and developments

INSTRUCTOR

David Garner

FAQ

DESIGNED FOR

The course is intended for technical people and decision makers working on subsurface hydrocarbon reservoirs in multi-disciplinary teams to raise their level of skills for using or considering using geomodeling. This includes geomodelers, reservoir engineers, geologists, geophysicists, petrophysicists, technologists and technical managers.

COURSE LEVEL
  •  Beginner to Intermediate

LEARNING OBJECTIVES

The learning objectives of the top-most level content of the course are grounding in:
o Geostatistical theory with data analysis
o Geomodeling thought process
o Best practices and Trade Craft

REGISTER

Registration is now OPEN!

* Prices are subject to VAT and local terms. Ph.D. students, groups (≥ 3 persons) and early bird registrants (8 weeks in advance) are entitled to a DISCOUNT!

For more details and registration please send email to: register@petro-teach.com

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