Training Geostatistics and Reservoirs Modeling - BBM TRAINING AND CONSULTING

Training Terbaru

Jadwal Training 2020

Start Date

Duration

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06 January 2020

1/2/3/5 Days

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06 January 2020

1/2/3/5 Days

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03 February 2020

1/2/3/5 Days

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02 March 2020

1/2/3/5 Days

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27 April 2020

1/2/3/5 Days

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18 May 2020

1/2/3/5 Days

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22 June 2020

1/2/3/5 Days

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20 July 2020

1/2/3/5 Days

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17 August 2020

1/2/3/5 Days

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14 September 2020

1/2/3/5 Days

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12 October 2020

1/2/3/5 Days

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09 November 2020

1/2/3/5 Days

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01 December 2020

1/2/3/5 Days

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Training Geostatistics and Reservoirs Modeling

Training Geostatistics and Reservoirs Modeling
INTRODUCTION
This course designed to understanding the fundamental theory and practice of reservoir description and modeling for reservoir management. Participants will learn the fundamental concepts of reservoir description and modeling using geostatistical techniques. This course emphasizes the principles and practice of integrated studies and uncertainty analysis
PROGRAMME OBJECTIVES
  • Learning how to apply reservoir description and modeling to support reservoir management
  • Recognizing the limitations and opportunities of reservoir modeling.
  • Learning the Kriging techniques
  • Understanding the  statistics and probability 
WHO SHOULD ATTEND?
  • Petroleum/ Geophysicists/ Geologists/Reservoir engineers
  • Technical/ reservoir engineers
  • Processing engineers
  • Commercial analysts
  • Decision makers/ investors in oil and gas sector
PROGRAM OUTLINE


    • Course Objectives
    • Fundamentals of Reservoir Modeling 
    • Basic Statistical Principles 
    • Probability Principles 

    • Data Analysis
    • Quality Control 
    • Preparation 
    • Variogram Modeling 

    • Kriging Techniques 
    • Stochastic Simulation 
    • Modeling Case Studies 
    • Overview of Uncertainty Analysis 

    • Overview of Integrated Studies
    • Spatial Modeling
    • Structural Modeling
    • Estimation of Properties at Well Locations

    • Conditional Simulation
    • Facies/Rock Type Modeling
    • Petrophysical Properties Simulation
    • Ranking of Realizations
    • Construction of Simulator Input Model
    • Future Predictions and Quantification of Uncertainty

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