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Integrated Reservoir Management From Seismic Field Development Planning PET585

Students will learn, get familiar, and apply the following concepts:

  • Closed Loop Reservoir Management
  • Big Loop Model conditioning
  • Multidisciplinary way of thinking
  • Integrated workflows

The course will introduce an integrated reservoir management workflow that starts with seismic and ends with the field development planning.


Course description for study year 2021-2022

Facts
Course code

PET585

Version

1

Credits (ECTS)

10

Semester tution start

Spring

Number of semesters

1

Exam semester

Spring

Language of instruction

English

Offered by

Faculty of Science and Technology, Department of Energy Resources

Learning outcome

Knowledge

  • Understand the essential parts/building blocks of the whole integrated reservoir management workflow
  • Understand the links and the communication between these blocks
  • Understand the importance of uncertainty quantification in each block.

Skills

  • Be able to follow up the whole closed loop workflow
  • Use the uncertainties concept
  • Qualitative and quantitative uncertainty analysis

Competence

Students should be able to:

  • Understand fundamentals of deterministic and stochastic inversion methodologies
  • Implement these technologies in computer code
  • Apply these concepts, get results and analyze them
  • Write a report on their findings.
Content

The combination of models and measurements, in order to optimally estimate different parameters of interest and to improve the prediction capability of models, is named data assimilation. Different data-assimilation methods have been used for many years in geosciences and they are used operationally in fields like weather prediction, oceanography, air quality, and hydrology. In the area of reservoir engineering this approach is known as assisted history matching, since one searches for parameter values that allow the model simulations to match a history of observed data. The process of updating, or rather conditioning, the values of different uncertain parameters of the subsurface, using all available data, in order to obtain a match with the historical data, can be seen as a model calibration problem. The holy grail of the history-matching process is not only to obtain models that fit the data, but also models with improved predictability, to be able to generate accurate simulations of the future production. Thus, the logical approach is to use the updated models obtained from the history matching as input to a production-optimization process, in the larger framework of a field development or redevelopment plan. The combination of model-based optimization and assisted history matching is called closed-loop reservoir management and was introduced by Jansenet al, 2008. Students will learn about, get familiar with and will apply the following concepts:

  • Closed Loop Reservoir Management
  • Big Loop Model conditioning
  • Multidisciplinary way of thinking
  • Integrated workflows

The course will introduce an integrated workflow that starts with seismic and ends with the field development planning.

Main topics

  • Statistics fundamentals - Bayes theory
  • Optimization fundamentals
  • The integrated workflow: Seismic to geomodel and geomodel to robust optimization
  • Synthetic case study (OPM + case study + Assisted History matching+ Optimization)
  • Geophysics role in the integrated workflow
  • Geology role in the integrated workflow
  • Reservoir engineering role in the integrated workflow
Required prerequisite knowledge
None
Exam

Portfolio evaluation and oral exam

Form of assessment Weight Duration Marks Aid
Portfolio evaluation 3/10 A - F
Oral exam 7/10 A - F

Continuous assessment consisting of a portfolio and an oral exam. 
• Portfolio consist of 2 written course assignments counting 30% of the total grade.
• Oral exam counts 70% of the total grade.

The sum of these two items gives the final grade. If a student fails or want to improve the grade, she/he have to take the whole course again the following year.

Course teacher(s)
Course coordinator: Remus Gabriel Hanea
Course coordinator: Aojie Hong
Head of Department: Alejandro Escalona Varela
Method of work
The assignments will consist in working with a synthetic reservoir case using Matlab based reservoir simulator.
Open for
Admission to Single Courses at the Faculty of Science and Technology Computational Engineering, Master's Degree Programme Petroleum Geosciences Engineering - Master of Science Degree Programme Petroleum Engineering - Master of Science Degree Programme Petroleum Engineering - Master`s Degree programme in Petroleum Engineering, 5 years
Course assessment
Standard UiS protocol.
Literature
Search for literature in Leganto