Fall 2020
| Course Title | Computational Geosciences and Optimization |
|---|---|
| 계산지구과학 및 최적화 | |
| Course No. | G17613 |
| Keywords | Uncertainty, Proxy, Optimization, Data Assimilation, Machine Learning |
| 불확실성, 대리모델, 최적화, 자료동화, 머신러닝 | |
| Description (교과목기술) |
This course aims at training graduate students to practice a variety of algorithms covering surrogate modeling, optimization (global- and multi-objective optimization), data assimilation, and machine learning that have been utilized for modeling geosciences in the areas of subsurface, ocean, and atmosphere. |
| 본 교과목은 다양한 지구과학(지질, 해양, 기상) 분야에서 불확실성 분석을 위하여 활용하여 온 대리 모델, 최적화, 자료 동화, 기계학습 알고리듬 등을 소개하고, 수강생들이 본인 분야에서의 활용방안 탐색을 유도한다. |
- Syllabus: Fall 20
| Course Title | CESE Graduate Seminar |
|---|---|
| 기후에너지시스템공학과 대학원 세미나 | |
| Course No. | G16511 |
| Keywords | Climate system, Energy system, Invited Talks |
| 기후 시스템, 에너지 시스템, 초청 강연 | |
| Description (교과목기술) |
One aim of the course is to expand and keep up to date our understanding in climate and energy systems engineering. Throughout the course, we will have a series of weekly seminars presented by invited speakers from a wide range of field in climate and energy systems engineering. |
| 매주 대학원생 발표 및 초청강연으로 진행한다. |
- Schedule: Go to Dept. Colloquium
Spring 2020
| Course Title | Applied Geostatistics |
|---|---|
| 응용 지구통계학 | |
| Course No. | G17604 |
| Keywords | probability, random variable, variogram, kriging, sequential simulation |
| 확률, 확률변수, 베리오그램, 크리깅, 순차 시뮬레이션 | |
| Description (교과목기술) |
This course covers basic statistics for spatial analysis in the first half. Then, students will learn variogram and its modeling for spatial data analysis with separation distance, and several geostatistical kriging and non-kriging methods. Each student or team will have a class project and presentation. |
| 크리깅 및 순차 시뮬레이션 등 지구통계학 기법의 활용법을 배운다. |
| Course Title | CESE Graduate Seminar |
|---|---|
| 기후에너지시스템공학과 대학원 세미나 | |
| Course No. | G16468 |
| Keywords | Climate system, Energy system, Invited Talks |
| 기후 시스템, 에너지 시스템, 초청 강연 | |
| Description (교과목기술) |
One aim of the course is to expand and keep up to date our understanding in climate and energy systems engineering. Throughout the course, we will have a series of weekly seminars presented by invited speakers from a wide range of field in climate and energy systems engineering. |
| 매주 대학원생 발표 및 초청강연으로 진행한다. |
- Schedule: Go to Dept. Colloquium
Fall 2019
| Course Title | Petroleum Production Systems |
|---|---|
| 석유 생산 시스템 | |
| Course No. | G16519 |
| Keywords | Production Engineering, Pipe Flow, Nodal Analysis |
| 생산공학, 관유동, 노달 분석 | |
| Description (교과목기술) |
This course aims at providing skills in the development and use of mathematical and computer models for flow through the various parts of an oil and gas production system. |
| 본 교과목은 석유가스공학 분야에서 저류층에서 생산된 다상유체(오일, 가스, 물)의 생산관 및 수송관 내에서 발생하는 유체유동 분석에 관한 이론을 학습하고, 수학 및 컴퓨터 모델을 활용하여 유체 유동을 모사한다. |
Spring 2019
| Course Title | Fundamentals on Petroleum and Gas Engineering |
|---|---|
| 석유가스공학통론 | |
| Course No. | G17674 |
| Keywords | Petroleum Engineering, Reservoir Engineering, Material Balance, Darcy's Law, Well Testing |
| 석유공학, 저류공학, 물질수지, 다시의 법칙, 유정 시험 | |
| Description (교과목기술) |
This class covers fundamentals of petroleum reservoir engineering including PVT analysis, material balance, radial flow equations, and well testing. Each student is encouraged to give a term project presentation related to reservoir engineering. |
| 본 교과목은 석유공학, 그 중에서도 저류공학 분야의 기본 이론(예: 압력-부피-온도 분석, 물질평형방정식, 환형 유동 방정식, 유정 시험)을 다룬다. 각 학생들은 학기말 저류공학과 관련된 프로젝트 발표를 수행하여야 한다. |
Fall 2018
| Course Title | Computational Geosciences and Optimization |
|---|---|
| 계산지구과학 및 최적화 | |
| Course No. | G17613 |
| Keywords | Uncertainty, Proxy, Optimization, Data Assimilation, Machine Learning |
| 불확실성, 대리모델, 최적화, 자료동화, 머신러닝 | |
| Description (교과목기술) |
This course aims at training graduate students to practice a variety of algorithms covering surrogate modeling, optimization (global- and multi-objective optimization), data assimilation, and machine learning that have been utilized for modeling geosciences in the areas of subsurface, ocean, and atmosphere. |
| 본 교과목은 다양한 지구과학(지질, 해양, 기상) 분야에서 불확실성 분석을 위하여 활용하여 온 대리 모델, 최적화, 자료 동화, 기계학습 알고리듬 등을 소개하고, 수강생들이 본인 분야에서의 활용방안 탐색을 유도한다. |
- Syllabus: Fall 18
- Term Project (Oral Presentation): Fall 18 (*.zip)
Spring 2018
| Course Title | Applied Geostatistics |
|---|---|
| 응용 지구통계학 | |
| Course No. | G17604 |
| Keywords | probability, random variable, variogram, kriging, sequential simulation |
| 확률, 확률변수, 베리오그램, 크리깅, 순차 시뮬레이션 | |
| Description (교과목기술) |
This course covers basic statistics for spatial analysis in the first half. Then, students will learn variogram and its modeling for spatial data analysis with separation distance, and several geostatistical kriging and non-kriging methods. Each student or team will have a class project and presentation. |
| 크리깅 및 순차 시뮬레이션 등 지구통계학 기법의 활용법을 배운다. |
| Course Title | CESE Graduate Seminar |
|---|---|
| 기후에너지시스템공학과 대학원 세미나 | |
| Course No. | G16468 |
| Keywords | Climate system, Energy system, Invited Talks |
| 기후 시스템, 에너지 시스템, 초청 강연 | |
| Description (교과목기술) |
One aim of the course is to expand and keep up to date our understanding in climate and energy systems engineering. Throughout the course, we will have a series of weekly seminars presented by invited speakers from a wide range of field in climate and energy systems engineering. |
| 매주 대학원생 발표 및 초청강연으로 진행한다. |
- Schedule: Go to Dept. Colloquium
Fall 2017
| See the course description open in Spring 2018 |
|---|