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| GEOL0097-2 | Geostatistics
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| Duration : | 30h Th, 30h Labo. |
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| Number of credits : |
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| Lecturer : | Eric Pirard |
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Language(s) of instruction :
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| English language |
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Organisation and examination :
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| Teaching in the first semester, review in January |
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Course contents :
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| 1. Computers and Geosciences
2. Statistical terminology and data typology
3. Principles of geological monitoring and spatial sampling
4. Exploratory Data Analysis
Univariate Visualisation (histograms, box plot)
Univariate analysis (percentiles, mean, variance,...)
Identification of outliers
Principles of data levelling
Bivariate Visualisation (scatterplots)
Bivariate Analysis (covariance, correlation,...)
5. Spatial Exploratory Data Analysis
Post plot
Spatial Correlation Analysis
The experimental variogram
6. General principles of spatial modeling
1.1. Probabilistic vs. Deterministic Modelling
1.2. Standard techniques of deterministing modelling (recap.)
7. Introduction to regionalized variables
2.1. Random variable and random function.
2.2. Random function and regionalized variable
2.3. Characterization of the spatial law
2.4. The covariance function
2.5. The theoretical variogram
2.6. Ergodic and stationarity hypotheses
8. Modelling the variogram
3.1. The theoretical and the experimental variogram
3.2. Variogram models
3.3. Omnidirectional variogram modelling
3.4. Modelling the anisotropy
9. Spatial multivariate analysis
4.1. Bivariate statistics (correlation)
4.2. Multivariate statistics (correlation matrix)
4.3. Cross-Variogram and co-regionalisation
10. Local grade estimation
5.1. Conditions for optimization of a non-biased linear estimator
5.2. Simple Kriging
5.3. Ordinary Kriging
5.4. Kriging in presence of a spatial drift
5.5. Influence of the geometry of the neighbourhood and variogram shape on the estimation
5.6. Cross-validation
11. Kriging and secondary information
6.1. Stratified Kriging
6.2. Co-kriging
12. Local uncertainty and local distribution estimation
7.1. Kriging and estimation error
7.2. MultiGaussian approach
7.3. Indicator kriging
13. Spatial uncertainty and geostatistical simulations
14. Mining applications
9.1. Kriging and change of support (bloc kriging)
9.2. Classification of ore resources.
9.3. Tonage/grade curves
9.4. Open Pit Optimization |
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Learning outcomes of the course :
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| 1) To present the main geostatistical inference tools (advantages and drawbacks)
2) To acquire a good mastership of the most utilised concepts
3) To provide the basis for understanding themost advanced papers on spatial inference
4) To learn about the most common professional geostatistical applications |
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Prerequisites and co-requisites/ Recommended optional programme components :
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| Probability and Statistics (basic course) |
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Planned learning activities and teaching methods :
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| All partical sessions will be organized using programming in PYTHON and SGEMS. |
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Mode of delivery (face-to-face ; distance-learning) :
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| 2h theory followed by 2h of supervised practice |
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Recommended or required readings :
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| Copy of all PPT used for teaching.
Main reference :
Goovaerts P., 1997, Geostatistics for natural resources estimation, Oxford Univ. Press
Recommended Lectures :
Isaaks E. & Srivastava M., 1989, Introduction to applied geostatistics, Oxford Univ. Press
Cressie N., 1993, Statistics for Spatial Data, Wiley |
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Assessment methods and criteria :
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| Evaluation will bear on a personal project performed by the student and an oral examination.
Each student will receive a set of data and will habe to characterize and spatial model the data set with the tools seen during the course.
The written work will be submitted before the oral examination and will be subject to additional questions/oral presentation during the exam.
The oral examination will bear on the theoretical principles.
The final notation will be a weighted average : 75% (oral examination) + 25% (personal work). None of these two notes being inferior to 8/20.
If the oral examination is < 10/20 only this last note will be taken into account. |
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Work placement(s) :
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Organizational remarks :
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Contacts :
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| Mlle Nadia ELGARA
Secrétariat GeMMe
Bât B52
Tél. : 366.37.99
nelgara@ulg.ac.be |
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