GEO 122
Reservoir Modeling Using Geostatistics
Reservoir Modeling Using Geostatistics
COURSE SCHEDULE
| Code | Date | Location | price (€)* |
|---|---|---|---|
| GEO 122 | 9 - 13 Oct 2023 | Online | 1790 |
| GEO 122 | 11 - 15 Dec 2023 | Online | 1790 |
| GEO 122 | 2 – 6 Sep 2024 | Online | 1990 |
| GEO 122 | 7 – 11 Oct 2024 | Online | 1990 |
| GEO 122 | 5 – 9 Aug 2024 | Stavanger | 3990 |
| GEO 122 | 9 – 13 Dec 2024 | Abu Dhabi | 3990 |
* 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
The goal of this course is to introduce and teach participants some of the important current techniques of geostatistics used for reservoir modeling. The mathematical theory will be briefly summarized, to provide an intuitive understanding. Strong emphasis will be on conceptual understanding and practical use of the algorithms, such that their capabilities and limitations are understood. Hands-on exercises will be demonstrated, using the open-source SGeMS (Stanford Geostatistical Modeling Software) platform, allowing the attendees to experience first-hand how each algorithm works, and the importance and sensitivity of the key input parameters. This is a hands-on workshop, and the format will alternate between lectures and computer exercises, about half the time being devoted to the hands-on exercises.
COURSE OUTLINE
5 days
Day 1
o Geostatistics and reservoir modeling
o Review of statistics and probability
o Introduction to SGeMS
Day 2
o Modeling geological continuity: variograms
o Building training images
Day 3
o Building high resolution geo-cellular model: facies
o Building high resolution geo-cellular model: petrophysical properties
o Sequential simulations
Day 4
o Using seismic data to constrain models: facies
o Using seismic data to constrain models: petrophysical properties
o Co-simulations
Day 5
o Multipoint geostatistics
o History matching
o Modeling uncertainty
INSTRUCTOR
Professor Tapan Mukerji
Professoe Tapan Mukerji is a Professor (Research) at Stanford University where he got his Ph.D. (1995) in Geophysics. Tapan co-directs the Stanford Center for Earth Resources Forecasting (SCERF), the Stanford Rock Physics and Borehole Geophysics (SRB) and Basin and Petroleum System Modeling (BPSM) projects at Stanford University. His research interests include rock physics, geostatistics, wave propagation, and stochastic methods for quantitative reservoir characterization and time-lapse reservoir monitoring. Tapan combines experience in conducting leading edge research, teaching, and directing graduate student research. He was awarded the Karcher Award in 2000 by the Society of Exploration Geophysicists, and received the ENI award in 2014. He has been an associate editor for Geophysics, journal of the Society of Exploration Geophysicists, and Computers and Geosciences. In addition to numerous journal publications, Tapan has co-authored The Rock Physics Handbook, Quantitative Seismic Interpretation, and The Value of Information in the Earth Sciences, all published by Cambridge University Press. He has been an invited keynote speaker and instructor for numerous short courses on rock physics and geostatistics, in North and South America, Europe, Africa, Australia and Asia.
FAQ
DESIGNED FOR
Quantitative geologists, geomodelers, reservoir geophysicists and engineers concerned with building stochastic reservoir models for reservoir forecasting and uncertainty quantification.
COURSE LEVEL
o Intermediate to Advance
LEARNING OBJECTIVES
After completing this course, participants will be familiar with the following:
o Use spatial data science to analyze reservoir data
o Understand pros and cons of two-point and multiple point spatial statistics
o Apply spatial simulation to build reservoir models
o Integrate well and seismic data to build stochastic subsurface models
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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