Reservoir Characterization
The objective of this course is to teach the basic science, technology
and related assumptions involved in carrying out an integrated reservoir
characterisation study. It will prepare students to understand and
interpret techniques that underlie commercial software (but will not
teach software usage itself). The emphasis is on providing students
with knowledge of a 'toolkit' for, but not a prescriptive approach to,
the ultimate goal of constructing 3D static models.
The course has three main components. 1) Data sources, quality and
analysis, including spatial analysis. 2) Generating 3D models of
reservoir properties - classical gridding and mapping, kriging as a
data-driven (variogram) form of classical mapping (estimation) and a
means of data integration. Simulation techniques are introduced as a
means of assessing uncertainty resulting from heterogeneity. 3) Scaling
of grids and property models for the purpose of reservoir simulation is
the final topic. The integration and application of all the major
ideas is illustrated by a case study.
Course Learning Outcomes
1 | Learn the main terminology, concepts, tools, and techniques used for generating 3D static reservoir models. |
2 | Understand some of key issues in reservoir characterisation & modelling, particularly uncertainty & heterogeneity |
3 | Practice using these tools – computer exercises |
4 | Develop a critical-thinking and problem-solving approach to modelling, rather than a prescriptive or “recipe” approach |
5 | Develop & practice skills in data analysis and using Excel (key tools for all engineers) |
6 | Illustrate how the main tools & techniques are used for real problems through case studies |
7 | If time, demonstrate some commercial software that is commonly used in the O&G industry (Petrel) |
8 | As an effective member of a team, research a paper/topic related to the course material and present a critical review of it |
9 | Read and understand a range of papers and articles related to reservoir characterization |