Introduction:

Reservoir characterization technology has changed dramatically over the last decade. Reservoir modeling software now has a wide range of powerful statistical and geostatistical functionality and has spread rapidly through the industry as PCs have become faster and user interfaces have simplified the application of complex methods. However, the understanding required to make optimum use of this functionality has not kept pace, and users continue to struggle with understanding many fundamental principles. Hence, a number of misunderstandings and poor workflows have become common place. This course addresses these misunderstandings and poor workflows in order to improve your effectiveness in reservoir modeling. Classroom exercises utilize Decision Space software, but the learnings are also applicable to other software platforms. This course delivers expertise in the applied geostatistical methods that are an essential underpinning of effective modern reservoir characterization and modeling. Variograms, kriging and stochastic simulation are thoroughly explained from their basics upwards and illustrated in their application to modeling problems.

Course Objectives:

By the end of this course, delegates will be able to:

• Assess modern reservoir characterization and modeling techniques
• Design data quality control and analysis strategies for classical univariate and multivariate statistical methods
• Appraise the similarities and differences between traditional statistical methods and geostatistical methods
• Construct Variograms and formulate their use in spatial analysis and “mapping” of geosciences data
• Formulate strategies to provide more spatially rigorous reservoir models  using geostatistical interpolation and stochastic simulation methods
• Illustrate the use of Kriging and collocated Co-Kriging to provide the most-likely reservoir model
• Characterize commonly used stochastic simulation methods, illustrate their use and highlight their pros and cons for capturing heterogeneity and assessing uncertainty
• Assemble the essential elements of a static 3D reservoir model from structural framework through to petrophysical integration, ready for use in dynamic simulation
• Assess the differences between uncertainty assessment, sensitivity analysis and risk analysis in reservoir characterization
• Evaluate reservoir heterogeneity and provide upscaling criteria to capture the scale of critical resolution that addresses stated objectives
• Formulate reservoir modeling ranking criteria and evaluate their importance within an overall development plan

Who Should Attend?

Geologists, Geophysicists, Reservoir Engineers, Production Engineers, Petrophysicists, Petroleum Engineers, Drilling Engineers, Field Development Engineers, Managers, Asset Managers, Oil & Gas Engineers, Reservoir Operators, Surveillance Engineers, Technicians, Engineering Trainees, Technical Managers, Technical Assistants, Technicians, Chemists, Physicists, Technical Supervisors, Service Company Personnel responsible for improving the performance of petroleum reservoirs

Course Outline:

• Introduction
• What is reservoir characterization?
• What is geostatistics?
• Reservoir characterization today
• The basic workflow
• Overview of classic statistical principles
• Exploratory data analytics and project design
• Statistical measures
• Spatial analysis and modeling
• Variography, variograms and modeling
• Geostatistical estimation
• Principles of Kriging and Co-Kriging
• Kriging workflows
• Principles of conditional simulation and cosimulation
• Estimation versus simulation
• Stochastic simulation
• Pixel versus object methods
• Common facies simulation algorithms
• Common continuous property algorithms
• Multivariate conditional simulation
• Uncertainty analysis and risk
• The space of uncertainty
• Orders of uncertainty
• Visualizing uncertainty
• Building the 3D Model
• General workflow
• Size and resolution of the model
• Conceptual geological modeling: structural and stratigraphic framework
• Overview of ranking and upscaling
• Cells; regular, irregular, unstructured
• Common upscaling methods
• Common upscaling problems

COURSE LOCATIONS