School of Mining and Geosciences
School of Mining and Geosciences
School of Mining and Geosciences
Overview
The PhD program in Petroleum Engineering (PhD-PE) in the School of Mining and Geosciences (SMG) (further in the text: PhD program) is designed to provide advanced skills and a sophisticated knowledge base at the expert level for individuals planning a career in academic, industry and research settings in engineering, especially Petroleum Engineering. The program focuses on the enhancement of Petroleum Engineering knowledge by advanced courses and development of research skills at high level. The PhD program in Petroleum Engineering especially focuses on priority areas for Kazakhstan as described in the “Kazakhstan upstream oil and gas roadmap”.
By the completion of the PhD program, students will be capable of designing and conducting independent, innovative, original and high-quality research related to a variety of topics in Petroleum Engineering and also interdisciplinary topics. In addition, program graduates will be prepared for working in industrial and academic environments including positions of university faculty members, senior researchers, engineers and product developers. The PhD-PE degree program is a specialized degree program offered by the School of Mining and Geosciences (SMG) at Nazarbayev University (NU). Students are required to complete 240 ECTS credits, in 4 years, which is in line with the Regulatory Framework for Graduate Programs and Courses of Nazarbayev University (2019). The program consists of taught as well as research components. Advanced level core courses enable students acquire advanced knowledge in Petroleum Engineering. After passing a comprehensive exam and PhD proposal defense, students are required to develop and practice novel research and make an original contribution within the area of Petroleum Engineering or interdisciplinary fields related to Petroleum Engineering. All research components of the program including seminars and dissertation defense must be passed by each student to complete the program and graduate.
General information
- Campus: Astana, Kazakhstan
- Language: English
- Delivery mode: Full time, on-campus
- Duration: 4 years
- Total ECTS credit: 240
Program Aims
The program aims to prepare:
- To prepare specialists for advanced careers in (national and international) industry and academia in Kazakhstan, in neighboring countries and internationally.
- To prepare future policy and decision makers for careers in governmental agencies, public service and the socio-economic environment in Kazakhstan, and globally, especially in the energy sector.
- To prepare entrepreneurs who will be able to promote advanced and innovative science-rich technologies in the oil/gas/energy disciplines anywhere in the world.
- To prepare new generation of commercially aware and technologically advanced scientists and technologists to lead future developments in the energy discipline.
- To prepare future academics and researchers in Petroleum Engineering and related disciplines for careers as specialists in universities in the country and internationally.
Key Advantages
- 95%+ job placement rate within 1–2 months of graduation1
- Work in companies: KazMunaiGas, Schlumberger, Chevron, University and more2
- Access to modern labs and industry-standard software for reservoir modeling and well performance analysis.3
- Thesis projects connected with real industry needs4
- Diverse, supportive academic environment with professors from around the world5
- Opportunities to publish research and present at international conferences6
Learning Outcomes
On successful completion of the program students will be able to:
- Explain and analyze the contemporary research literature in their field of study.
- Critically evaluate all major types of research in their field of study.
- Identify appropriate research topics in their field of study, and generate hypotheses about such topics.
- Plan, conduct, analyze and communicate research in writing and verbally independently.
- Make an original contribution to the knowledge in their area of specialization.
- Explain their research and research findings to others both orally and in written form.
- Present and explain the connections between their research outcomes and the broader field of knowledge in their discipline.
- Disseminate their research findings and to develop their academic/scholarly career through presentations, publications, and national and international networking.
Engages in in-depth research on:
- Complex reservoir modeling
- Advanced geomechanical modeling
- Application of AI and machine learning
- Unconventional resources and frontier drilling
- Innovative technologies for carbon management and sustainability
- Students publish in journals, contribute to global conferences, and work on cutting-edge industry challenges
Curriculum
Handbook
Core modules
The list of core modules
Main topics required in drilling and production engineering will be covered in this course. In the production section, major applications of production engineering to design, estimate, and optimize production from oil and gas wells will be covered.
Course learning outcomes
1. Recognize the objectives of well planning and the overall process.
2. Perform the various methods of predicting or determining the formation pressure and fracture gradient.
3. Design elements of drilling operation such as drilling fluid, cementing, casing, and drill string and the well profile.
4. Analyze governing equations of a production system and main parameters of different elements such as well, pipelines, and surface facilities.
Course learning outcomes
1. Recognize the objectives of well planning and the overall process.
2. Perform the various methods of predicting or determining the formation pressure and fracture gradient.
3. Design elements of drilling operation such as drilling fluid, cementing, casing, and drill string and the well profile.
4. Analyze governing equations of a production system and main parameters of different elements such as well, pipelines, and surface facilities.
A research plan is developed by the student in collaboration with the Program Advisor or Research Supervisor at the start of the semester outlining the research goals to be accomplished. At the end of the semester the student files a research report which is graded (P/F) by the Program Advisor or Research Mentor (when selected). The “in-progress” grade is submitted and maintained on the student’s transcript; credit is awarded on successful completion of thesis requirements.
Course learning outcomes
1. Practice academic writing appropriate to the discipline and learn how to participate in the peer review process.
2. Prepare accurate research progress reports.
Course learning outcomes
1. Practice academic writing appropriate to the discipline and learn how to participate in the peer review process.
2. Prepare accurate research progress reports.
Statistics course will focus on the statistical and data analytics techniques applied for onshore and marine petroleum and gas & mining industry. This course will provide PhD students with the practical skills and theoretical knowledge on how to collect, analyze, interpret and present different types of data and research results for onshore and marine petroleum and gas & mining industry. Different data types will be addressed and used in this course to cover broad range of research interests by PhD students. Moreover, along with the standard statistical techniques, this course will introduce the aspects of spatial statistics. The scientific research and publication skills will also be strengthened in the process of this course. This course will be targeted to the research interests of PhD students so that they can practically apply what they learnt out of this course and demonstrate the research results in their finalizing projects. The interdisciplinary research principles will also be promoted so that PhD students are able to consider and integrate more aspects in their statistical analysis from different petroleum and gas & mining disciplines.
Course learning outcomes
1. Perform exploratory and descriptive analyses of statistical data.
2. Analyze statistical relationships using regression techniques.
3. Quantitatively compare differences and visualize statistical data.
Course learning outcomes
1. Perform exploratory and descriptive analyses of statistical data.
2. Analyze statistical relationships using regression techniques.
3. Quantitatively compare differences and visualize statistical data.
This course will help PhD students to become more familiar with the literature of the research direction and research topic they choose as their PhD thesis. This course will help students to prepare their research proposal.
Course learning outcomes
1. Evaluate and critique existing research sources and materials in their field.
2. Construct a coherent literature review organized in themes and appropriate sub-topics.
3. Articulate a clear and focused research question.
4. Present a well-argued rationale for the selection of a particular methodology and combination of methods.
Course learning outcomes
1. Evaluate and critique existing research sources and materials in their field.
2. Construct a coherent literature review organized in themes and appropriate sub-topics.
3. Articulate a clear and focused research question.
4. Present a well-argued rationale for the selection of a particular methodology and combination of methods.
Introduction to fundamental concepts in reservoir engineering; Defining reserves; Different methods to estimate oil and gas reserves; Material balance equations for different types of oil and gas reservoirs; Definition and classification of water aquifers and basic concepts for water influx; Well performance behavior and calculation of productivity index; Decline curve analysis; Improved oil recovery methods and Enhanced oil recovery methods.
Course learning outcomes
1. Assess the reservoir characteristics by advanced interpretation for complex reservoir engineering problems.
2. Estimate hydrocarbon originally in place in the reservoir using modern reservoir techniques and tools.
3. Evaluate the reservoir performance using different techniques.
Course learning outcomes
1. Assess the reservoir characteristics by advanced interpretation for complex reservoir engineering problems.
2. Estimate hydrocarbon originally in place in the reservoir using modern reservoir techniques and tools.
3. Evaluate the reservoir performance using different techniques.
Elective Courses
In this course, fluid flow types and mechanisms in the porous media will be discussed. Classifications of flow and descriptions of fluid flow in porous media will be studied. Conservation laws, constitutive relations of fluid flow, and equation of transient fluid flow in porous media will be analyzed in details. Different types of fluid flow such as steady, pseudo-steady, and transient flow in linear, radial and spherical systems will be discussed and analyzed.
Course learning outcomes
1. Classify different types and levels of fluid flow.
2. Apply flow potential, stream functions, and iso-potential lines in porous media.
3. Derive microscopic/macroscopic conservation equations.
4. Develop dispersion-advection equation.
5. Solve diffusion equations for liquid, gas, and multiphase systems.
6. Apply Buckley-Leverett theory/Welge’s method to two phase fluid flow in porous media.
Course learning outcomes
1. Classify different types and levels of fluid flow.
2. Apply flow potential, stream functions, and iso-potential lines in porous media.
3. Derive microscopic/macroscopic conservation equations.
4. Develop dispersion-advection equation.
5. Solve diffusion equations for liquid, gas, and multiphase systems.
6. Apply Buckley-Leverett theory/Welge’s method to two phase fluid flow in porous media.
In this course different concepts and methods will be presented to enhance the capability of students to analyze the performance of chemical/thermal/solvent EOR methods. Mechanisms behind the performance of each method and ways to improve and optimize each approach will be discussed and analyzed in this course.
Course learning outcomes
1. Analyze macroscopic and microscopic sweep efficiency parameters in porous media.
2. Recommend methods to improve sweep efficiencies.
3. Screen the appropriate EOR method based on the oil reservoir condition.
4. Design main aspects of different EOR methods and the main governing mechanisms and parameters.
5. Recommend suggestions for improvement of the performance of an EOR method in oil fields.
Course learning outcomes
1. Analyze macroscopic and microscopic sweep efficiency parameters in porous media.
2. Recommend methods to improve sweep efficiencies.
3. Screen the appropriate EOR method based on the oil reservoir condition.
4. Design main aspects of different EOR methods and the main governing mechanisms and parameters.
5. Recommend suggestions for improvement of the performance of an EOR method in oil fields.
Different aspects of reservoirs simulation will be presented and analyzed in this lecture. Governing equations of fluid flow in reservoirs, numerical modeling of them, and solving methods will be discussed by black oil and compositional approaches. Different case studies will be solved by appropriate commercial simulator in lab sessions.
Course learning outcomes
1. Understand the importance of reservoir simulation in oil and gas industry.
2. Derive the equations of conservation of mass and momentum and energy balance.
3. Explain the physical laws that govern fluid flow for single-phase and multi-phase flow.
4. Discretize equation systems using finite difference methods and to solve them.
5. Demonstrate ability to build reservoir models to simulate water flooding problems.
6. Develop practical experience through parameter tuning in reservoir simulation studies.
7. Apply reservoir simulation knowledge and skills to more complex case studies.
8. Demonstrate ability to finish a complex reservoir simulation case study using different approaches, analyze results, write a report, and present the results in group of 2 or 3 students (Final Project).
Course learning outcomes
1. Understand the importance of reservoir simulation in oil and gas industry.
2. Derive the equations of conservation of mass and momentum and energy balance.
3. Explain the physical laws that govern fluid flow for single-phase and multi-phase flow.
4. Discretize equation systems using finite difference methods and to solve them.
5. Demonstrate ability to build reservoir models to simulate water flooding problems.
6. Develop practical experience through parameter tuning in reservoir simulation studies.
7. Apply reservoir simulation knowledge and skills to more complex case studies.
8. Demonstrate ability to finish a complex reservoir simulation case study using different approaches, analyze results, write a report, and present the results in group of 2 or 3 students (Final Project).
The content of this course will focus on analyzing datasets generated in oil and gas industry using various analytical techniques. PhD students are expected to understand the fundamental principles and master different data analytics techniques after attending this course. Knowledge and skills will enable students to quickly adapt to petroleum engineer or researcher roles in both industry and academia.
Course learning outcomes
1. Understand the role and objectives of digital oilfield.
2. Explain system thinking and the application of digital techniques in digital oilfield.
3. Demonstrate the ability to extract and manage data related to petroleum engineering.
4. Master fundamental knowledge and skills of statistics and data analyses.
5. Develop programming skills of building and testing data analytics models.
6. Gain hands-on experience of tuning models for solving realistic example problems.
7. Identify data analytics problems and potential models in petroleum engineering.
8. Demonstrate ability to solve a complex data analytics problem using different data analytics techniques, analyze results, make a comparison, and write a report.
Course learning outcomes
1. Understand the role and objectives of digital oilfield.
2. Explain system thinking and the application of digital techniques in digital oilfield.
3. Demonstrate the ability to extract and manage data related to petroleum engineering.
4. Master fundamental knowledge and skills of statistics and data analyses.
5. Develop programming skills of building and testing data analytics models.
6. Gain hands-on experience of tuning models for solving realistic example problems.
7. Identify data analytics problems and potential models in petroleum engineering.
8. Demonstrate ability to solve a complex data analytics problem using different data analytics techniques, analyze results, make a comparison, and write a report.
Where do our graduates work?
- Career opportunities
- Oil and gas companies (exploration and production, national/international oil companies)
- Service companies (oilfield services, drilling/production contractors)
- Engineering and consulting companies
- Energy related government sectors
- Renewable energy sectors
- Engineering procurement and construction
- Safety engineering
- Groundwater engineering
- Environmental engineering
- Academy as an educational and research faculty
- Where?Companies: KMG Engineering, SLB (Schlumberger), Chevron, KazMunaiGas, Shell, TengizChevrOil (TCO), Haliburton, KPO (Karachaganak Petroleum Operating)
and others in Kazakhstan, UAE, UK, India, and beyond
Admissions
Our Contacts
Feel free to write, call, and visit us.
Regarding consultation on admissions
On academic issues
Address:
Address: 53, Kabanbay batyr Ave., Astana, 010000, Kazakhstan.
Phone numbers
+7 (7172) 64 25 84
+7 747 094 02 30
+7 747 094 02 30
Fees and Funding:
For more detailed information about tuition fees, please contact the Bursar's Office:
For more detailed information about tuition fees, please contact the Bursar's Office:
- Phone: +7 (7172) 70 60 32, 70 91 99
- Email: bursars_office@nu.edu.kz
- Office: 1.248B Block 1
- Address: 53, Kabanbay batyr Ave., Astana, 010000, Kazakhstan
Call or email us:
Admissions Manager (MSc PhD programs):
Admissions Manager (MSc PhD programs):
+7(7172)69-4628