Smart Well Drilling Completion: Horizontal Wells and Integrity
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COURSE DATES AND LOCATIONS
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INTRODUCTION
This course presents the basics of drilling and completion operations, plus post-completion enhancement. Participants will learn to visualize what is happening downhole, discover what can be accomplished, and learn how drilling and completion can alter reservoir performance. Learn to communicate with drilling and production personnel.
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COURSE OBJECTIVES
At the end of this course you will be able to:
- The advantages and disadvantages of early and modern types of drilling styles
- Rig type classification and selection for onshore and offshore drilling
- Types of platforms and techniques used for offshore rigs
- The purpose and function of non-vertical drilling, including directional and horizontal drilling
- The components of a drilling system
- The components of a drilling rig
- The drilling systems of a rig
- The purpose and function of the rotating system
- Drilling fluid properties and function
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COURSE AUDIENCE
This course is made for
- Process design
- Unit Operator
- Process safety engineer
- Gasoline blender engineer
- Lab supervisor
- Supply chain engineer
- Distillates analyst
- Models engineer
- Chemical Operator
- Chemical Plant Operator
- Chemical Process Technician
- Control Room Supervisor
- Gas Plant Process Operator
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COURSE OUTLINE
Day One
Statistical Analysis and Probability Theory
- Describing Data with Numbers
- Probability and Displaying Data with Graphs
- Random Variables, Probability Density Function (pdf)
- Expectation and Variance
- Bivariate Data Analysis
- Sample case: preparing a well log plot and identifying the correlation
Day Two
Descriptive Geostatistics
- Geologic constraints
- Univariate distribution and Multi-variate distribution
- Gaussian random variables
- Random processes in function spaces
- Geostatistical Mapping Concepts
- Structural Modeling
- Cell-Based Facies Modeling
- Sample case: Analytical interpretation of centrifuge data to determine the relative permeability curve
Day Three
Modeling Uncertainty
- Sources of Uncertainty
- Deterministic Modeling
- Models of Uncertainty
- Model and Data Relationship
- Model Verification and Model Complexity
- Sample case: Reservoir Modeling
- Creating Data Sets Using Models
- Parameterization of Subgrid Variability
Day Four
Quantifying Uncertainty
- Introduction to Monte Carlo methods
- Sampling-based on experimental design
- Gaussian simulation
- General sampling algorithms
- Simulation methods based on minimization
- Sample case: Monte Carlo method for determining oil and gas reserves
- Sample case: Multiwell systems calculation using Darcy’s law
Day Five
Visualizing Uncertainty
- Distance Methods for Modeling Response Uncertainty
- K-means clustering
- Estimation using simple kriging
- Petrophysical Property Simulation
- Sample case: Oil reservoir uncertainty visualization
- Value of Information and the cost of data gathering
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