Reservoir Modelling and simulation (GEO506)

In this course we consider static and dynamic reservoir simulation based on theory and practical work with industry standard commercial software (Schlumberger package including Eclipse and Petrel) and modelling approaches. Students are trained to create and apply such models, solve technical reservoir problems, assess fluid-in-place volumes, and test different engineering solutions such as well placement, injection / production schemes. The interplay of rock and fluid properties, geology, well pattern and drive mechanisms are considered for their impact on production and economics. The course offers relevant expertise for modelling petroleum production and carbon/energy storage in porous media. It is based on consistent mathematical description and implementation in commercial software. 3D grid construction and geostatistical property modelling will be explored to determine in-place volume, account for uncertainty and give input to simulation models. The Black Oil Model and Compositional Model will be applied, and the role of important transport and storage mechanisms will be explored on simple model cases and a realistic field model case from the Norwegian Continental Shelf.

Course description for study year 2024-2025. Please note that changes may occur.


Course code




Credits (ECTS)


Semester tution start


Number of semesters


Exam semester


Language of instruction



3D grid-building and different alternatives will be explored, including the important consideration relating to fault modelling and the principle of combined horizon/fault modelling. For geostatistical property modelling, various facies modelling techniques, including object and indicator simulation, will be considered, along with stochastic petrophysical modelling techniques, Sw calculations, and uncertainty analysis. An introduction to the benefits of the workflow manager will be given, including how this tool can be used for constructing multiple realisations/scenarios for the purpose on uncertainty analysis.

The differential equations for mass conservation in the context of subsurface multiphase flow are derived for Black Oil and compositional models. Important input parameters and functions are described, as well as grid parameters, boundary conditions and transport and storage mechanisms. We briefly outline the numerical solution procedure for the differential equations, including discretization by finite differences, linearization and the Newton-Raphson method. Continuous use of commercial simulator is considered to gain practical experience with solving reservoir technical problems. Practice and reports on simple cases is considered before working on the field case.

Learning outcome


After completing the course, the student should know:

  • Principles of geomodelling
  • How to construct a geomodel
  • The main components of a 3D grid
  • Stochastic facies/property modelling techniques
  • In-place volume calculations
  • Handling uncertainties within 3D models
  • Important considerations and limitations of geomodels
  • Differential equations for mass conservation.
  • Black Oil and compositional models.
  • Assess fluids-in-place.
  • Evaluate impact of uncertainty in key parameters.
  • Key transport mechanisms for fluid transport and production.
  • How to use a simulator for solving reservoir technical problems.
  • Main steps of numerical solution of reservoir problems (discretization with finite differences, Newton-Raphson, IMPES and fully implicit, solving linear equations).


After completing the course, the student should be able to:

  • Construct a geomodel using typical field input data and calculate volumes.
  • Prepare the model input ready for simulation.
  • Handle uncertainties in geomodels.
  • Perform sensitivity analyses and interpret simulation results.
  • Describe specific porous medium flow problems consistently using mass balance equations, constraints, fluid and rock properties, boundary conditions and source terms.
  • Implement and solve reservoir engineering problems with simulation software.
  • Understand key features of a model and modify it for prediction, implementation of new engineering solutions or improved representation of the geology or field development.

General competence:

After completing the course, the student should be able to communicate:

  • Techniques required for 3D grid building
  • Different methods for facies and property modelling
  • Modelling approaches in reservoir simulation.
  • The role of mechanisms such as advective, gravity and capillary forces and fluid properties for fluid distribution and flow.
  • Solutions for modelling specific porous media flow systems.

Required prerequisite knowledge



Reports and oral exam

Form of assessment Weight Duration Marks Aid
Report 1 2/10 3 Weeks Letter grades All
Report 2 5/10 2 Months Letter grades All
Oral exam 3/10 30 Minutes Letter grades All

This course has a continuous assessment containing two reports and one oral exam.There is no continuation opportunity in this course. Students who fail or wish to improve their grade must re-take one or both of the assessment parts the next time the course has regular instruction.

Coursework requirements

A mandatory project plan must be made and approved to take the graded activities. A revised plan can be submitted if the quality is insufficient.

Course teacher(s)

Course teacher:

Christopher Townsend

Course coordinator:

Pål Østebø Andersen

Study Program Director:

Lisa Jean Watson

Study Adviser:

Karina Sanni

Head of Department:

Alejandro Escalona Varela

Method of work

Lectures, group projects, simulation exercises, theoretical exercises

The course includes an introduction to an industrial software being taught at the beginning of the semester or the end of the foregoing semester. Participation of this is not mandatory but highly recommended to better be able to successfully complete the assessments.

Overlapping courses

Course Reduction (SP)
3D Geomodelling (GEO540_1) 5
Reservoir Simulation (PET660_1) 5

Open for

Admission to Single Courses at the Faculty of Science and Technology
Data Science - Master of Science Degree Programme Computational Engineering - Master of Science Degree Programme Computer Science - Master of Science Degree Programme Energy, Reservoir and Earth Sciences - Master of Science Degree Programme Mathematics and Physics - Master of Science Degree Programme Industrial Asset Management - Master of Science Degree Programme Marine and Offshore Technology - Master of Science Degree Programme Petroleum Engineering - Master of Science Degree Programme Risk Analysis - Master of Science Degree Programme
Exchange programme at Faculty of Science and Technology

Course assessment

There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital subject evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.


Search for literature in Leganto