The course aims at providing the fundamentals needed to investigate, characterize, model and develop a hydrocarbon reservoir. The course integrates the knowledge gained during the previous courses (especially Geophysical Prospecting, Reservoir Geology, Petroleum Geomechanics and Fluid Mechanics in Porous Media) with the analytical and numerical approaches typical of reservoir engineering so as to obtain a consistent understanding of the reservoir dynamic behavior and to define field development strategies. The course on Well logging and Well Testing is to be considered complementary to gain a complete knowledge on reservoir characterization. Furthermore, strict connections with the Well Drilling and Completion course, with the design of surface facilities (course on Petroleum Chemistry and Technology) and with economic considerations (course on Resources and Environmental Economics) are necessary when forecasting the future field performance and evaluating the effectiveness of the potential production strategies. For these reasons the reservoir engineering course is very central and has a key role in the petroleum engineering program, just like reservoir engineering would have in the industrial practice.
Specific goals of the course are to provide the ability of quality assessing and interpreting ' when needed - all the input data necessary to understand the reservoir behavior and to build a reservoir dynamic model, to understand the cause-effect relationships when history matching the reservoir past performance, and to optimize the field development and production strategy. The skills gained in the Reservoir Engineering course will allow the students to cooperate at, or to be in charge of, integrated reservoir studies. Students will acquire the competences needed to efficiently communicate with experts from other disciplines who can provide scientific and technical insights or design constraints for an effective reservoir understanding and exploitation. Attitude to team working, accurate and meticulous approach to data analysis and management, and an open mindset are essential traits of this course.
The course provides the fundamentals to investigate, characterize, model, develop and manage hydrocarbon reservoirs. The course integrates the knowledge gained during the first year with the analytical and numerical approaches typical of reservoir engineering so as to obtain a sound understanding of the reservoir dynamic behavior and define the field development strategies. Furthermore, strict connections with well drilling and completion plan, design and safe management of surface facilities and economic considerations are necessary when forecasting the field performance and evaluating the effectiveness of the potential production strategies.
The course also provides the ability to quality assess and interpret - when needed - all the data necessary to characterize underground systems, build a reservoir dynamic model, understand the cause-effect relations when history-matching the reservoir past performance, and optimize the field production strategy.
The skills gained in the Reservoir Engineering course will allow the students to cooperate at, or to be in charge of, integrated reservoir studies. Students will acquire the competencies needed to efficiently communicate with experts from other disciplines who can provide scientific and technical insights or design constraints for an effective reservoir understanding and exploitation. Attitude to teamwork, an accurate and meticulous approach to data analysis and management, and an open mindset are essential traits of this course.
The course on Well logging and Well Testing is complementary to gaining complete knowledge of reservoir characterization.
Students will acquire:
- Deep knowledge of the technologies and methodologies applied for the characterization of hydrocarbon-bearing formations through reservoir geology and geophysics, laboratory data, productivity tests as well as through the analysis of historical production data.
- Profound understanding of the production drives and their implications on the reservoir productivity and hydrocarbon recovery.
- Good knowledge of the improved and enhanced oil recovery methods.
- Ability to identify the key elements of a technical problem in reservoir engineering. Ability to understand, describe and analyze the physical phenomena occurring in a reservoir during production through the governing equations and through the use of analytical models.
- Ability to handle the methods and software adopted worldwide in the oil industry for static and dynamic reservoir numerical simulation based on a good understanding the principles and assumptions of which they rely.
- Ability to define the most adequate production strategies based on technical, economic and environmental indicators, also with the aid of scientific software, graphs, and other convenient tools or representations.
- Ability to capture the essential messages, the methodologies and their implications from technical papers and manuals.
Students will acquire:
- Deep knowledge of the technologies and methodologies applied for the characterization of hydrocarbon-bearing formations through reservoir geology and geophysics, laboratory data, production tests as well as through the analysis of historical production data.
- Profound understanding of the production drives and their implications on reservoir productivity and hydrocarbon recovery.
- Knowledge of enhanced oil recovery methods.
- Ability to identify the key elements of a technical problem in reservoir engineering. Ability to understand, describe and analyze the physical phenomena occurring in a reservoir during production through the governing equations and application of analytical models.
- Ability to handle the methods and software adopted worldwide in the oil industry for static and dynamic reservoir numerical simulation based on a good understanding of the principles and assumptions on which they rely.
- Ability to define the most adequate production strategies based on technical, economic and environmental indicators
- Ability to capture the essential messages, the methodologies and their implications from technical papers and manuals.
Students should have a good knowledge of geophysics, geology and geomechanics to be able to truly understand the reservoir earth model, which is the basis for describing the reservoir dynamic behavior and for subsequent simulations of the production performance. It is essential that students master the concepts and the basics of rock and fluid properties and their mutual interactions, the flow equations, and the pressure analysis and interpretation techniques. Familiarity with the orders of magnitude of the most relevant quantities (fluid properties, petrophysical characteristics, fluid-rock interaction properties, hydrocarbon recovery factors) is required.
Students should have a good knowledge of geophysics, geology and geomechanics to truly understand the reservoir earth model, which is the basis for describing the reservoir fluid-flow behavior and subsequent simulations of the production performance. Students must master the concepts and the basics of rock and fluid properties and their mutual interactions, flow equations, pressure analysis and interpretation techniques. Familiarity with the orders of magnitude of the most relevant quantities (fluid properties, petrophysical characteristics, fluid-rock interaction properties, hydrocarbon recovery factors) is required.
- Material balance for oil and gas reservoirs
- Productivity tests
> well damage
> oil well productivity
> gas well deliverability
- Water and gas injection
> immiscible displacement
> operational issues
- Reservoir numerical modelling
> static modelling
> dynamic modelling
> set-up and calibration of a reservoir model, and simulation of the reservoir dynamic behavior under different development scenarios
- Impact of geomechanics on reservoir behavior
- Decline curve analysis
- Productivity tests
> procedures and equipment
> productivity for oil wells
> deliverability for gas wells
> well damage
- Material balance
> water encroachment
> gas reservoirs
> oil reservoirs
- Water and immiscible gas injection
> Buckley-Leverett equation
> Frontal advance equation
> Microscopic efficiency
> Sweep efficiency
> vertical sweep efficiency
- EOR
- Decline Curve Analysis
- Reservoir numerical modeling
> Fundamentals of 3D reservoir static modeling
Input data, data QC, integrated petrophysical characterization, volumetric calculations
> Multiphase flow models: diffusivity equation in pressure and saturation;
Fundamentals on Finite Difference Methods
Treatment of non-linearities
Transmissibility
> 3D dynamic modeling
set up
initialization
aquifer definition
calibration
simulation of the reservoir dynamic behavior under different development scenarios and evaluation of results
impact of geomechanics on reservoir behavior
Some of the theoretical lessons will be held with the collaboration of highly qualified technical staff from oil and/or service companies, who will give lectures on applications to real cases.
Some theoretical lessons might be held in collaboration with experts from oil and/or service companies, who will present real data and/or innovative technologies and discuss case histories.
Exercises will include application of the methodologies presented and discussed during lectures to case studies based on synthetic and real data, with increasing degree of complexity. The software commonly adopted in the oil industry for well test analysis and for reservoir simulation will be used. During the course the complete workflow of characterization, history match and production forecast of an oil reservoir with gas cap and water drive will be developed through static and dynamic modeling. Under the guidance of the professor, students will be encouraged to work independently.
Exercises will include applying the methodologies presented and discussed during lectures to case studies based on synthetic and real data, with increasing complexity. The software commonly adopted in the oil industry for reservoir simulation will be used. During the course, the complete workflow of characterization, history match and production forecast of an oil reservoir with gas cap and water drive will be developed through static and dynamic modeling. Under the guidance of the professor(s), students will be encouraged to work independently.
Reference books:
Tarek H. Ahmed, 2006. Reservoir engineering handbook, Elsevier/Gulf Professional
L. P. Dake, 1983. Fundamentals of reservoir engineering, Elsevier
Petroleum Engineering Handbook, Volume V, 2007, Society of Petroleum Engineers (SPE)
Technical Papers will be provided (unlimited free download from the SPE One-Petro library is also available)
The slides presented during lectures will be periodically posted on the course website
Reference books:
- Tarek H. Ahmed, 2006. Reservoir engineering handbook, Elsevier/Gulf Professional
- Dake L. P., 1983. Fundamentals of reservoir engineering, Elsevier Science
- Dake L. P., 1994. The Practice of Reservoir Engineering, Elsevier Science
- Petroleum Engineering Handbook, Volume V, 2007, Society of Petroleum Engineers (SPE)
- Mattax C., Dalton R., 1990. Reservoir Simulation (Monograph), Society of Petroleum Engineers (SPE)
Technical Papers will be provided (unlimited free download from the SPE One-Petro library is also available)
The slides presented during lectures will be periodically posted on the course website.
Slides;
Lecture slides;
Modalità di esame: Prova scritta (in aula); Prova orale obbligatoria;
Exam: Written test; Compulsory oral exam;
...
The assessment of acquired knowledge and technical skills occurs through written exams on the theoretical parts and on applicative aspects. The capability to integrate knowledge gained in other courses and contexts, to critically examine a technical problem and to select models and methods to reach the solution is expected.
The exam will comprise true/false options, multiple choice questions, open questions, and problem solving. The exam is closed books. Each answer will be assigned marks depending on the complexity of the question.
Oral integration is up to the students, provided that the minimum marks for passing the exam (18/30) have been reached. The oral integration can modify the score of the written exam by plus or minus 2 point maximum.
Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.
Exam: Written test; Compulsory oral exam;
The ability to critically examine a technical problem – also by integrating knowledge gained in other courses and contexts if needed -, to select the appropriate models and methods and correctly calculate the solution is expected.
The exam comprises a written test and an oral interview.
The written test (25 points maximum) comprises two parts:
- Part I: a set of questions on fundamental knowledge and concepts. This part can comprise true/false options, multiple choice questions, and very synthetic open questions (10 points).
- Part II: dedicated to applicative aspects and problem-solving. In this part, students will have to answer questions on a simplified case history by analyzing the data and making calculations and/or plots using the most appropriate approaches and methods (15 points).
The written test is closed notes and closed books.
The duration of the written test will be 3 hours or less.
Students must prove to have gained fundamental knowledge by scoring at least 7/10 in Part I of the exam to have Part II corrected.
A score of 6/10 or less in Part I of the written test implies that the exam is failed.
Students must score a total of 15 points minimum (cumulative score) from Parts I and II to access the oral interview.
The oral part (7 points maximum) is concerned with the theoretical parts, description and analysis of the methods for reservoir characterization and simulation, and discussion of approaches to be taken for problem-solving. The score is attributed by taking into account the correctness and completeness of the answers to the questions, the ability to elaborate the topics presented and discussed in class for problem-solving, the ability to support the discussion with the correct language and clear form and with graphs (when relevant/required).
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.