Applied Mining Geostatistics
Jayakarta Hotel, Bandung | May 3-6, 2010 | Rp. 7.250.000,-
INTRODUCTION
Since geo-statistics developed by Prof George Matheron in 1960, it has been applied greatly in mining industry for mineral resources evaluation and reserves modeling. Geo-statistical method considers the spatial structure which is represented by variogram model in estimation methods such as polygonal, triangular grouping, inverse distance square, nearest point, etc. Moreover, parameters of variogram model can be drawn on to optimize the drilling pattern or the influence area of sampling points.
Kriging is the most famous geo-statistical method used for reserves estimation, and it has been known as BLUE (Best Linear Unbiased Estimator). Krigging variance can be applied to assess the uncertainly (error) of estimation result.
Beside kriging, there are any other geo-statistical methods employed for spatial characterization and modeling of natural resource such as conditional simulation. Geo-statistics can also be utilizing to evaluate mineral reserves classification.
COURSE OBJECTIVES
- To give knowledge about the concept of regionalized variable that is the principle of geo-statistics method, analysis and interpretation of variogram.
- To give understanding about the principle of kriging method and its application for resources modeling and reserves estimation.
- To give introduction about the principle of geo-statistical simulation, uncertainly analysis, and their application in natural resources evaluation.
COURSE OUTLINE
- Review of statistics,
- Concept of regionalized variable,
- Concept of experimental variogram,
- Analysis of variogaram model and its interpretation
- Conventional reserves estimation methods
- Variance of dispersion and variance of estimation
- Principle of kriging method and its application
- Introduction about deterministic method
- Geo-statistical simulation
- Uncertainty analysis
- Reserves classification based on geo-statistical method
SCHEDULE
Day 1
- Review of statistics
- Conventional reserves estimation methods
- Concept of regionalized variable and calculation of experimental variogram
Day 2
- Analysis and interpretation of variogram
- Exercise and practice of variogram calculation and fitting model
- Concept of variance dispersion
- Concept of variance of estimation.
Day 3
- Principle of kriging method and its application for reserve estimation
- Exercise and practice of kriging method
- Introduction and deterministic method for mineral deposit evaluation
Day 4
- Uncertainty analysis based on kriging variance and conditional simulation
- Optimization of drilling pattern and reserves classification based on geo-statistical method
WHO SHOULD ATTEND
- Miners (Engineer, Business Development Manager)
- Geo-scientist (Geologist, Geophysicist, Exploration)
- New Venture & Field Business Development
- Hydrologist
- Everybody or professional who want better understanding and to broaden the knowledge from the course subject
Instructor
Mohamad Nur Heriawan, ST, MT, Ph.D graduated from Bachelor of Engineering (ST.), Division of Mining Exploration, Department of Mining Engineering, ITB, Master of Engineering (MT.), Master Program of Applied Geophysics, Postgraduate Program, ITB and Postgraduate Diploma, Option of Mine Geostatistics, Geostatistics Groups, Center of Geosciences, Ecole des Mines de Paris, France. Doctor of Philosophy (Ph.D), Department of Environmental Science, Graduate School of Science and Technology, Kumamoto University, Japan. Now, he is a Lecturer/ Assistant Professor at the Research Group of Earth Resources Exploration, Faculty of Mining and Petroleum Engineering (FTTM), ITB. He is a member of International Association for Mathematical Geology (IAMG). He has experiences for teaching geo-statistics course in PT. INCO Tbk, Unit Geomin PT. ANTAM Tbk, Divison of Geo & Technical Services PT. Freeport Indonesia, PT. Arutmin Indonesia, and some public course.
Schedule
May 3-6, 2010
4 days
Venue
Jayakarta Hotel, Bandung
Tuition Fee
Rp. 7.250.000,- per participant, excluding accommodation & tax.
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