Geo–Statistical Resource: Modeling and Estimation

in Bandung,Chemical, Oil and Gas,Mining


Multivariate geo-statistics involves more than one variable. It can improve the estimation of a variable from other variables sampled either at same points (isotopic case) or not always at the same points (heterotypic case). In many cases when drilling a layering deposit, not all drill holes obtained both top and bottom of the deposit. In this case, estimates on top or bottom elevation can be solved by multivariate or vicariate geo-statistics. Simple co-kriging or ordinary co-kriging is very often used to estimate top or bottom elevation of a layering deposit, when they are unknown in a drill hole. Simple cokriging is used if the variables are stationary and their mean are known well, otherwise we should use ordinary cokriging. Top elevation can be estimated using variable of bottom elevation or on the contrary. In case the cross-variogram of top and bottom elevation is identical or proportional with their simple variogram in isotopic case, the cross variogram is a model of intrinsic correlation, so their cokriging coincides with their own kriging. In other word, top and bottom elevation are self-krigeable. In general, the using of cokriging can improve the consistency between estimation of different variables.


1. Statistical analysis of sampling and data QA/QC

  • Principles of sampling, sampling error and its components
  • Statistics of sample (measure, shape, character of population, etc.)
  • Distribution models (normal, lognormal)
  • The variance of the mean and detecting sampling bias
  • Data QA/QC, verification and analysis

2. Geological models and domains

  • Volume variance concept
  • Statistical testing of domains
  • Influence of domains on resource estimates

3. Geo-statistics

  • Measure of heterogeneity or spatial continuity
  • Stochastic random fields, correlation function and semivariogram
  • Variography (variograms and geology)
  • Transformation of data prior to variogram calculation
  • Tricks and tips facing multiple variograms (Gaussian, spherical, exponential, zonal anisotropy, geometric anisotropy, etc.)

4. Kriging (linear and non-linear)

  • Kriging process
  • Kriging sensitivity

5. Geo-statistics applications and other methods

  • Inverse distance, nearest neighbor, polygon
  • Resource modeling and estimation
  • Understand place of geo-statistics in mining
  • Understand issues that affect accurate estimation

6. Resource reserve classification

7. Case studies and practical exercises


  • 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


Mohamad Nur Heriawan, ST, MT, Ph.D

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.


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