MDN730 - ADVANCED MINERAL RESOURCE ESTIMATION
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| ADVANCED MINERAL RESOURCE ESTIMATION | MDN730 | Any Semester/Year | 3 | 0 | 3 | 10 |
| Prequisites | - | |||||
| Course language | Turkish | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Discussion Question and Answer Case Study Problem Solving | |||||
| Instructor (s) | Instructor (s) Prof. Dr. A. Erhan TERCAN | |||||
| Course objective | To describe important issues and commonly used statistical and geostatistical tools for mineral resource estimation | |||||
| Learning outcomes |
| |||||
| Course Content | National and international mineral resource estimation reporting standarts. Construction of borehole data base. Statistical analysis of raw data. Domaining. Statistical and geostatistical analysis of domains. Basic principles, tools and methods for block and resource modeling. | |||||
| References | Mineral Resource Estimation, M.E. Rossi and C.V. Deutsch, 332 pp. 2014, Springer. Applied Mining Geology, M, Abzalov, 2016, 448 pp. Springer. Applied Mineral Inventory Estimation, A.J. Siclair and G.H. Blackwell, 377 pp. Cambridge Univeristy Press. | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | National and international reporting standarts such as JORC, NI 43-101, SME, CRIRSCO |
| Week 2 | Principles for constructing borehole data base |
| Week 3 | Methods for statistical analysis of raw data |
| Week 4 | Case study (SGeMS, Netpro/Mine, Surpac) |
| Week 5 | Defining domains by indicator kriging and CART |
| Week 6 | Statistical and geostatistical analysis of domains |
| Week 7 | Case study (SGeMS, Netpro/Mine, Surpac) |
| Week 8 | Block modeling, compositing, declustering and statistical analysis, outlier value detection and treatment, variogram analysis, unfolding |
| Week 9 | Estimation plan, selection of estimation metods, block model test, resource classification and grade-tonnage curves |
| Week 10 | Case study (SGeMS, Netpro/Mine, Surpac) |
| Week 11 | Evaluation of assignments |
| Week 12 | Modifying factors, identification and management of risks, reporting |
| Week 13 | Case study (SGeMS, Netpro/Mine, Surpac) |
| Week 14 | Case study (SGeMS, Netpro/Mine, Surpac) |
| Week 15 | Case study (SGeMS, Netpro/Mine, Surpac) |
| Week 16 | Student presentations |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 0 | 0 |
| Laboratory | 0 | 0 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 1 | 25 |
| Presentation | 1 | 25 |
| Project | 1 | 50 |
| Seminar | 0 | 0 |
| Midterms | 0 | 0 |
| Final exam | 0 | 0 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 0 | 50 |
| Percentage of final exam contributing grade succes | 0 | 50 |
| Total | 100 | |
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 14 | 5 | 70 |
| Presentation / Seminar Preparation | 1 | 40 | 40 |
| Project | 1 | 100 | 100 |
| Homework assignment | 1 | 40 | 40 |
| Midterms (Study duration) | 0 | 0 | 0 |
| Final Exam (Study duration) | 0 | 0 | 0 |
| Total Workload | 31 | 188 | 292 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. An ability to design, solve and improve the problems related to mining engineering by using extensively the basic and engineering sciences. | X | ||||
| 2. An ability to develop a new view, scientific method, design or application which innovate in the field of mining engineering or an ability to apply a known view, scientific method or design to the field of mining engineering. | X | ||||
| 3. An ability to design, apply, conclude and supervise an original research process related to mining engineering. | X | ||||
| 4. An ability to reach new knowledge in the field of mining engineering and to assess them systematically. | X | ||||
| 5. An ability to publish the outcomes of the academic studies related to the field of mining engineering in reputable academic environments. | X | ||||
| 6. An ability to assess scientific, technological, social and cultural developments and to transfer them to public by considering scientific objectivity and ethical responsibility. | X | ||||
| 7. An ability to assess, synthesis and analysis critically the views and developments in the field of mining engineering. | X | ||||
| 8. An ability to communicate verbally and in written form with the colleagues in the field of mining engineering and in wider scientific and social environments and to defend her/his own views. | X | ||||
| 9. An ability to make leadership in environments in which original and interdisciplinary problems are solved. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest