Geostatistics, Using Software for Geospatial Analysis AZTech Training & Consultancy
Price: AED 18,181

    Course details

    This training course is an ideal presentation of using statistics methods in spatial data analysis. It presents the concepts used in geoscience with special emphasis on oil and gas exploration. The use of omnipresent Excel for the geospatial analysis for the initial applied research in geology and exploration. Advanced concepts of using free R software for geospatial analysis trough examples is also presented, with explaining of statistical methods used and the packages.  

    This AZTech training course is designed to help professionals in data analysis, geologists and oil and gas professionals to remove the limitations of using an off-the-shelf software, which is quite helpful but it limits the ability of the professional using it to apply its knowledge and extend the models used, as the readymade software applies pre-designed algorithms and ''forces'' the data into distributions applicable for the models. This training course will allow the professionals to understand how they can use free or low-cost software to extend the capabilities of commercial software and enable them to use their own ingenuity without ;
     
    This training course will feature:
    • Explanation of geoscience and its applications in oil and gas
    • Integrating information from various sources with varying degrees of uncertainty
    • Establishing relationships between measurements and reservoir properties
    • Using semi-variograms and kriging
    • Hands-on practice in using excel and R for spatial data analysis
    • Advanced concepts: Monte Carlo Simulation, k-means, numerical facies modeling, fuzzy logic
     
    What are the Goals?

    By the end of this training course, participants will be able to:
    • Learn the concepts and methods of geostatistics
    • Understand the capabilities of Excel and R programming language
    • Acquire the knowledge of available R packages for spatial data analysis
    • Import, analyze and interpret results from spatial data
    • Perform Monte Carlo simulation, clustering analysis and other advanced techniques
    Updated on 30 September, 2018

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