Data science and machine learning for engineering applications/Reservoir geomechanics (Reservoir Geomechanics)

The course provides the fundamentals of rock behaviour in relation to field operations in reservoirs. The main objective of the course is to teach students: 1) how rocks respond to the modification of the underground state of stress in relation to oil and gas production and gas storage 2) the models and methods used to solve practical problems. To reach this objective the following subjects are explained during the course: fundamentals of continuum mechanics, the role of fluids in rock behaviour, drained and undrained conditions, interpretation of laboratory tests, elasto-plastic models for predicting rock behaviour and methods of analysis for evaluating rock failure in oil and gas reservoirs.

Data science and machine learning for engineering applications/Reservoir geomechanics (Reservoir Geomechanics)

Upon completion of the course, the student should be able to: 1) Identify the appropriate rock mechanical properties and select the tests necessary to characterize the rock material with reference to a given field problem; 2) Predict the hydro-mechanical response of porous rocks in field operations; 3) Solve practical problems: wellbore stability, hydraulic fracturing, stress change induced by reservoir production and gas injection.

Data science and machine learning for engineering applications/Reservoir geomechanics (Reservoir Geomechanics)

The student must know the fundamental principles of Linear Algebra, Physics I, and Resources Geology

Data science and machine learning for engineering applications/Reservoir geomechanics (Reservoir Geomechanics)

1) Continuum mechanics. >The state of stress and strain >Constitutive laws: Theory of elasticity and plasticity; Creep 2) Failure mechanics: Mohr-Coulomb, Hoek & Brown, Griffith, Jaeger strength criteria 3) Mechanical properties of rocks from lab tests 4) Elements of Critical state Soil Mechanics. Modified Cam Clay Model 5) In situ state of stress: geostatic and in fault regime 6) Compaction and subsidence of reservoirs during depletion 7) Stresses around boreholes. Stability during drilling: geomechanical aspects 8) Principles of hydraulic fracturing 9) Stress change during gas storage 9) Stress change during gas storage

Data science and machine learning for engineering applications/Reservoir geomechanics (Reservoir Geomechanics)

Data science and machine learning for engineering applications/Reservoir geomechanics (Reservoir Geomechanics)

The course is organized in theoretical and practical lessons. During the practical lessons the students have to solve exercises by applying the theory explained in lectures. The interpretation of lab tests and the solution of practical problems are developed in the Informatic Lab

Data science and machine learning for engineering applications/Reservoir geomechanics (Reservoir Geomechanics)

Reference Books: Fjaer, Holt, Horsrud, Raaen & Risnes, Petroleum related Rock Mechanics, 2nd edition, Elsevier, Oxford, 2008. Brady & Brown Rock Mechanics, 3rd edition, Kluwer Academic Publisher, Dordrecht, 2004 Lancellotta, 2009. Geotechnical Engineering, 2nd edition, Taylor & Francis, New York The slides presented during lectures will be periodically uploaded on the web site of the course.

Data science and machine learning for engineering applications/Reservoir geomechanics (Reservoir Geomechanics)

Slides;

Data science and machine learning for engineering applications/Reservoir geomechanics (Reservoir Geomechanics)

Modalita di esame: Prova orale obbligatoria;

Data science and machine learning for engineering applications/Reservoir geomechanics (Reservoir Geomechanics)

Exam: Compulsory oral exam;

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Data science and machine learning for engineering applications/Reservoir geomechanics (Reservoir Geomechanics)

Compulsory oral exam. The exam is aimed at evaluating knowledge, competences and skills acquired during the course. The student should be able to carry out stability analyses, to select strength parameters and to evaluate the effect of water pressure in a given case. The exam will be oral in a classroom of the Politecnico di Torino. A calendar will be published on the course page after the term for exam enrollment and every day a group of students will give the exam. The oral exam comprises 3 main questions. Questions are related to the topics explained in class. Questions consist of discussion of a given topic and/or the solution of a practical exercise. Rules during oral exam: >closed book; >the equation sheet provided in the course material is allowed; >pocket calculator and pen; >the student must show his/her identity document

Gli studenti e le studentesse con disabilita 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'Unita Special Needs, al fine di permettere al/la docente la declinazione piu idonea in riferimento alla specifica tipologia di esame.