Geostatistical Simulation & MPS Boot Camp

Geostatistical Simulation & Multiple Point Statistics

What you'll learn
- Understand core concepts of Geostatistics – including variograms, spatial continuity, and uncertainty in subsurface modeling.
- Run Your Own Scripts with R & Python.
- In this course, students will gain both theoretical knowledge and hands-on skills in geostatistical simulation and Multiple-Point Statistics (MPS).
- Learn key MPS algorithms such as SNESIM, FILTERSIM, and Direct Sampling, and how they are applied in real-world case studies.
- Develop practical skills in simulation workflows, from preparing training images and geological data to generating realizations.
- Apply geostatistical and MPS methods in practice using free tools, coding, and visualization techniques to model groundwater, petroleum reservoirs.

Requirements
- A computer (Windows, Mac, or Linux) with stable internet access. R and Python installed , Interest and curiosity to explore geostatistical modeling and simulation.
- No programming experience required.

Description
Geostatistical Simulation

Geostatistical simulation is a stochastic (probabilistic) method used to generate multiple equally probable realizations of spatial variables (e.g., soil properties, groundwater levels, ore grades).

Unlikedeterministic interpolation(like kriging, which gives a single “best estimate”), simulation captures theuncertainty and variabilityof spatial data.

This is crucial in hydrogeology, mining, petroleum, and environmental sciences, where decision-making requires understandingboth the mean trend and possible fluctuations.

Applications:

Risk assessment (e.g., contamination spread, groundwater depletion).

Resource estimation in mining/oil.

Modeling heterogeneity in reservoirs and aquifers.

Multiple-Point Statistics (MPS)

MPS is anadvanced form of geostatistical simulation.

Instead of relying only ontwo-point correlations(variograms) like traditional geostatistics, MPS usespatterns from training images(conceptual models or real data) to reproduce complex geological structures (channels, fractures, lineaments, etc.).

MPS can capturenon-linear, non-Gaussian featuresthat variogram-based methods cannot.

For example, in groundwater modeling, MPS can represent connected sand channels or fracture networks more realistically than variogram-based kriging/simulation.

Why They Are Very Important

Uncertainty Quantification– Instead of one map/model, we get a range of possible outcomes, essential for risk-based decisions.

Better Representation of Geology– Especially when geology is complex (channels, faults, karst systems) and cannot be captured by standard variograms.

Decision-Making Support– Helps in optimizing well placement, mine planning, reservoir management, and contamination remediation.

Who this course is for:
- This course is for anyone who wants to boost their career with practical geostatistical and MPS skills. If you are a student, researcher, or professional in geology, hydrogeology, petroleum engineering, mining, reservoir modeling, geophysics, or environmental sciences — this course is built for you. If you’re working in the oil and gas sector, mining industry, or reservoir modeling field, geostatistical simulation and MPS are among the most demanded skills for jobs and research opportunities. This course will help you learn how to apply these methods step by step using R and Python, making you confident to handle real-world data and projects. By the end, you won’t just know the theory — you’ll have hands-on, job-oriented skills that can make your profile stand out in consulting firms, research institutes, energy companies, and environmental agencies.
More Info