كود البرنامج : EU-14820

---

INTRODUCTION:

Geostatistics is a class of statistics used to analyze and predict the values associated with spatial data. It incorporates the coordinates of the data within the analyses. Geostatistical tools were originally developed as a practical means to describe spatial patterns and interpolate values for locations where samples were not taken. The mining industry for example uses geostatistics for several aspects of a project: initially to quantify mineral resources and evaluate the project's economic feasibility, then on a daily basis in order to decide which material is routed to the plant and which is waste, using updated information as it becomes available.

you will understand the basic terminologies about this science and how they work, a step-by-step variogram modelling is also covered in this course

 

Who this course is for:

Geologists

Mining engineers

Petroleum engineers

GIS engineers

 

Program content:

 

Day 1

Establish why stochastic methods are useful in reservoir modelling. Use this to plan which statistical ideas and methods we need to study.

Goals - At the end of the module you should:

• appreciate why this course is important
• be able place the remainder of the course in a context of what is useful in geology.

The data

• preparation
• exploratory analysis

Statistical basics

• use of basic tools for summarizing and understanding data
• use of basic tools for preparing data for further statistical analysis or for geological analysis

Goals - At the end of the module you should:

• be able to choose suitable techniques for analysis of data
• use every day tools such as Microsoft Excel® to check data quality and undertake the basic statistical analysis
• prepare data, using such common tools, for input to Petrel

 

Day 2

Why do we need statistics?

The data requirements of a simulator

• collecting data together from different disciplines, on different support, for modelling.

Goals - At the end of the module you should:

• understand what to do when inferring from incomplete data: e.g. known values at wells, what happens between?
• know what to do when we cannot measure a parameter directly but have to predict from one we can measure

Sources of error

• confidence
• variance
• reliability

Goals - At the end of the module you should:

• be able to quantify the confidence in a prediction.
• know limitations of Petrel, when to transform and when to re-analyses.

 

Day 3

How does a spatial dependence in the data affect statistics?

How to analyses data for spatial dependence.

Goals - At the end of these modules you should:

• be able to choose suitable techniques for analysis of data
• use everyday tools such as Microsoft Excel® to undertake the basic statistical analysis
• Take a spatial data set and plot it using Excel®

Geostatistical basics

• use of basic tools

Goals - At the end of the module you should:

• be able to establish trends
• use tools such as directional semi variograms as tools in their own right

 

Day 4

Support and upscaling

• averaging and simulation techniques
• static and dynamic data

Goals - At the end of this module you should:

• be able to correctly choose techniques for upscaling different data types
• be able to distinguish correctly upscaled data from badly upscaled data

Estimation, including Kriging:

• understand the basics
• simple exercises to illustrate how kriging incorporates spatial variation and allows estimation of variance
• Using co-located co-kriging for better prediction of important parameters between

 

Day 5

More advanced techniques

• Making use of new data:
• History matching
• Bayesian statistics

• Objects:

   

• Sequential / Indicator simulation
• Object modelling in Petrel:
• defining objects
• incorporating objects in models
• Multi-point statistics:
• limitations of semi variograms
• combining with object modelling

Goals - At the end of this module you should:

• be able to correctly and appropriately use techniques presented in Petrel.

Recap and reinforcement:

• cover any techniques shown by the exercises to be shaky

Goals - At the end of this module you should:

• leave the course with a firm understanding of the basics and the ability to use all of the techniques covered in the course, in everyday work
• know how to re-familiarize (get back up to speed) after not using the techniques for any length of time