Grad Students

CCG Grad Students

The core of the CCG is our graduate students. We have 20 current students, split almost evenly between PhD and MSc programs. Students start their program with a “warm up” project that often becomes the their thesis. There is strong encouragement to participate in industry projects wherever there is an opportunity and student research may often receive member company input.

Resources for Grad Students

Download documents for grad students: Thesis Criteria, for students for submitting a thesis at CCG, and Presentation Criteria, for students for preparing and delivering a presentation at CCG.

Thesis Criteria (PDF)

Presentation Criteria (PDF)

Ana Paula Chiquini

M.Sc. Student

Ana Paula Chiquini completed her B.Sc. in Geology from the University of São Paulo, Brazil, in 2011. Ana has 4 years of experience in the mining industry, having worked as a Resources Geologist at Yamana Gold Inc., before starting her M.Sc. studies at CCG in September 2016. As a Resources Geologist at Yamana, her main activities include mineral resources evaluation of gold, copper, polymetallic and porphyritic deposits and geological and ore modelling for underground and open pit mines, on both short and long terms.

anachiquini

Research

  • Probabilistic Resource Reporting
  • Resource Calculations with Mining Selectivity and Information Effect

Publications

CCG Report

  1. Chiquini, A.P. & Deutsch, C.V. (2017). Resource Calculations with Mining Selectivity and Information Effect (CCG Annual Report 19). Edmonton, AB: University of Alberta.
  2. Chiquini, A.P. & Deutsch, C.V. (2017). Mining Selectivity Models for Different Deposit Types (CCG Annual Report 19). Edmonton, AB: University of Alberta.
  3. Chiquini, A.P. & Deutsch, C.V. (2017). Case Study on Probabilistic Resource Reporting (CCG Annual Report 19). Edmonton, AB: University of Alberta.

Contact

Bo Zhang

Ph.D. Candidate

Bo received his MSc in Petroleum Engineering at the University of Alberta with two publications about modelling bypassed oil recovery in EOS compositional simulation in June 2014. Bo also holds a BSc degree from China University of Petroleum (Beijing) in Petroleum Engineering. After 7 years academic backgroundin petroleum society, Bo decided to pursue his PhD in Geotechnical Engineering under co-supervision of Dr. Chalaturynk and Dr. Boisvert from July 2014. He will focus on developing a local numerical upscaling technique to describe the macroscopic plastic behavior of complex heterogeneous media.

ZhangBo

Research

My current research interests include:

  • Coupled reservoir-geomechanical simulation
  • Upscaling of reservoir and geomechanical properties in heterogeneous reservoir
  • Thermal recovery method
  • Compositional simulation
  • Phase behavior

Publications

Peer-review Journal

    1. Zhang, B. and Okuno, R., Modeling of capacitance flow behavior in EOS compositional simulation. Journal of Petroleum Science and Engineering, Volume 131(2015):96-113.

Conference Proceedings

      1. Zhang, B. and Okuno, R., A New Method for Modeling Bypassed Oil Recovery in EOS Compositional Simulation, SPE Annual Technical Conference and Exhibition to be held September 30 – October 2, 2013, New Orleans, LA, USA.

Thesis:

      1. Modeling of Bypassed Oil Recovery in EOS Compositional Simulation, 2014. Master Thesis. , Department of Civil Engineering. University of Alberta.

Contact

Carlos Prades

M.Sc. Student

Carlos completed his B.Sc. with specialization in Geology from the University of Chile in 2008. He has worked for 8 years in the mining industry: 3 years as production geologist, 2 years as exploration geologist and 3 years as resource estimation geologist. He has worked for important mining companies like BHP Billiton (Minera Escondida) and Antofagasta Minerals S.A.

Research

      • Prediction and data mining for multivariate datasets using state-of-the-art machine learning methods.
      • Applying tree-ensemble machine learning methods —random forests and gradient tree-boosted models— in geostatistical problems.
      • Multivariate geostatistics focused on gemetallurgical modelling.
carlosprades

Publications

      • C. Prades and C. Deutsch (2016). Comparison of Machine Learning Techniques for Predicting and Learning from Geometallurgical Multivariate Databases. CCG Paper 2016-308, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      • C. Prades and C. Deutsch (2016). Presentation of Uncertainty and Sensitivity Analysis. CCG Paper 2016-408, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.

Awards and Honours

      • WAAIME —The Woman’s Auxiliary to the American Institute of Mining, Metallurgical, and Petroleum Engineering— scholarship award (2006 and 2007).
      • Humberto Fuenzalida award by the Chilean Professional Geologist Association, for being the University of Chile´s most outstanding geology undergraduate between 2006 and 2008.
      • Geologist professional degree obtained with “Highest Distinction” in University of Chile (2008).
      • Ranked 8/540 when graduated (2008), among a total of 540 students admitted to University of Chile engineering faculty in 2001.
      • University of Alberta Master’s recruitment scholarship award (2015).
      • Qualified by University of Alberta for membership in the Golden Key International Honour Society for outstanding academic achievements (2016).

Contact

Chenyu Jiang

M.Sc. Student

Chenyu Jiang completed her B.Sc. in Mineral Resources Prospecting Engineering from China University of Geosciences (Beijing). She joined CCG group since September 2013, and now pursuing her master degree in mining engineering.

Research

      • Reservoir modeling for mineral deposits with the application of multiple point statistics
      • Parameters optimizations for SNESIM program
      • Solving the ordering issues in hierarchical simulation

Publications

CCG Report

      1. Jiang and J.B. Boisvert, 2014, MPS modeling of a Porphyry Cu-Mo deposit with a large number of rock types, CCG Paper 2014-312, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      2. Jiang and J.B. Boisvert, 2014, The impact of ordering on hierarchical simulation using multiple point statistics, CCG Paper 2014-121, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.

Contact

 

Dhaniel Carvalho

M.Sc. Student

I received my BSc in Geology from the University of São Paulo, Brazil. For 5 years I’ve worked as a Resource Geologist (at Yamana Gold and Votorantim Metais) developing activities involving geological and ore modeling for underground and open pit mines, on both short and long terms; mineral resources evaluation of zinc, lead, nickel, aluminum, gold, copper, polymetallic gold and silver deposits; geostatistical simulation to support mineral resources classification; drill hole spacing analysis and drill hole planning. I joined the Centre for Computational Geostatistics (CCG) in 2016 to start my M.Sc.

dhanielcarvalho

Research

      • Vein Type Deposit Modeling
      • Tonnage and Metal Uncertainty
      • Unstructured Gridding

Publications

CCG Report

      1. Carvalho, D.A., Deutsch, C.V. (2017). A Framework for Tabular Vein Type Deposit Modeling. Centre for Computational Geostatistics Annual Report 19, Paper 308
      2. Carvalho, D.A., Deutsch, C.V. (2017). Developments on Tabular Vein Geometry Modeling. Centre for Computational Geostatistics Annual Report 19, Paper 309
      3. Carvalho, D.A., Deutsch, C.V. (2017). Imputation of Tabular Vein Geometry Data for Tonnage Uncertainty Assessment. Centre for Computational Geostatistics Annual Report 19, Paper 313

Contact

Diogo Silva

Ph.D. Student

Completed his B.Sc. in Mining Engineering in 2011 at School of Engineering of the Federal University of Minas Gerais – Brazil where he was awarded with silver medal of academic merit. During his undergraduate studies he worked mostly with mineral processing from variability studies to processing route definition. Completed his M.Sc. in Mining Egineering at University of Alberta in 2014 and is currently Ph.D. student at the University of Alberta at the Centre for Computational Geostatistics (CCG) research group.

CCG Diogo Silva

Research

      • Categorical Modeling with Hierarchical Truncated Pluri-Gaussian
      • Mineral Resource Classification
      • Multivariate Geostatistical Modeling

Publications

Peer-review Journal

      1. Silva, D. S. F., and Boisvert, J. B., 2014. Mineral resource classification: a comparison of new and existing techniques. Journal of the Southern African Institute of Mining and Metallurgy, 114(3), 265-273.
      2. Silva, D. S., & Deutsch, C. V. Multiple imputation framework for data assignment in truncated pluri-Gaussian simulation. Stochastic Environmental Research and Risk Assessment, 1-13.
      3. Silva, D. S., & Deutsch, C. V. (2016). Multivariate data imputation using Gaussian mixture models. Spatial Statistics.

Conference

      1. Silva, D. S. F., and Boisvert, J. B., 2013. Mineral resource classification (NI 43-101): an overview and a new evaluation Technique. In 36th International Symposium on the Application of Computers and Operations Research in the Mineral Industry (APCOM 2013) , 315-323.
      2. Jewbali, A., Silva, D., Inglis, R., and Allen, L., 2017. Developing an Optimization Framework for Drill Hole Planning. In 38th International Symposium on the Application of Computers and Operations Research in the Mineral Industry (APCOM 2017) .

CCG Report

      1. Diogo S. F. Silva and Jeff B. Boisvert, 2013, Mineral Resource Classification (NI 43-101): An Overview and a New Evaluation Technique, CCG Paper 2013-307, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      2. Diogo S. F. Silva and Jeff B. Boisvert, 2013, Mineral Resource Classification with Simulation at SMU Scale, CCG Paper 2013-308, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      3. Diogo S. F. Silva and Jeff B. Boisvert, 2013, Infill Drilling Optimization for Maximizing Resource Tonnage, CCG Paper 2013-314, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      4. Diogo S. F. Silva and Miguel A. Cuba, 2013, SpectralSim A program for Unconditional Spectral Simulation, CCG Paper 2013-410, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      5. D. S. F. Silva and J. B. Boisvert, 2014, Evaluating the Impact of Low Quality Horizontal Well Data on Facies Modeling, CCG Paper 2014-208, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      6. D. S. F. Silva and J. B. Boisvert, 2014, A Case Study on 3D Infill Drilling Optimization, CCG Paper 2014-304, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      7. D. S. F. Silva and J. B. Boisvert, 2014, A Case Study on Resource Classification, CCG Paper 2014-305, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      8. D. S. F. Silva and J. B. Boisvert, 2014, A Program for 3D Infill Drilling Optimization, CCG Paper 2014-403, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      9. D. S. F. Silva and J. B. Boisvert, 2014, Two New Tools: Directional Survey to GSLIB XYZ Format and Drill Hole Spacing, CCG Paper 2014-404, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      10. D. S. F. Silva and C. V. Deutsch, 2015, Multivariate Data Imputation using Gaussian Mixture Models, CCG Paper 2015-104, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      11. D. S. F. Silva and C. V. Deutsch, 2015, Transformation for multivariate modeling using Gaussian mixtures with exhaustive secondary data, CCG Paper 2015-105, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      12. D. S. F. Silva and C. V. Deutsch, 2015, Tool for univariate KDE with optimal bandwidth based on bootstrap, CCG Paper 2015-133, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      13. D. S. F. Silva and C. V. Deutsch, 2015, Well / Drill Hole Prediction Tool, CCG Paper 2015-204, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      14. D. S. F. Silva and C. V. Deutsch, 2015, Program for fitting Gaussian mixture models based on EM algorithm and geostatistical applications, CCG Paper 2015-407, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      15. Diogo S.F. Silva and Clayton V. Deutsch, 2016, Hierarchical Approach to Truncated PluriGaussian Simulation, CCG Paper 2016-102, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      16. Diogo S.F. Silva and Clayton V. Deutsch, 2016, Multiple Imputation Framework for Data Assignment in Truncated PluriGaussian Simulation, CCG Paper 2016-109, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      17. Diogo S.F. Silva, Arja J. Jewbali, Jeff B. Boisvert and Clayton V. Deutsch, 2016, Drill Hole Placement Tool for Maximization of Resource Conversion, CCG Paper 2016-315, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      18. Diogo S.F. Silva and Clayton V. Deutsch, 2016, Software for Gaussian Data Assignment in Truncated PluriGaussian Simulation, CCG Paper 2016-402, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      19. Diogo S.F. Silva and Clayton V. Deutsch, 2016, Variogram Inference in Truncated PluriGaussian Simulation, CCG Paper 2016-409, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      20. D. S. F. Silva and C. V. Deutsch, 2017, Multivariate Categorical Modeling using Hierarchical TPG, CCG Paper 2017-102, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      21. D. S.F. Silva and C. V. Deutsch, 2017, Effects of Data Correlation on Multivariate Categorical Modeling, CCG Paper 2017-103, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      22. D. S.F. Silva and C. V. Deutsch, 2017, Non-Stationarity and Variogram Reproduction for HTPG, CCG Paper 2017-128, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      23. D. S.F. Silva and C. V. Deutsch, 2017, Tool for Grid Sensibility Analysis Utilizing DCHV, CCG Paper 2017-207, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      24. D. S.F. Silva and C. V. Deutsch, 2017, Software Package for Hierarchical TPG, CCG Paper 2017-401, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada

Contact

Efrain Ugarte

M.Sc. Student

Efrain graduated with a B.Sc. in Geological Engineering from the National University of San Antonio Abad of Cusco-Peru, and completed a Professional Master’s degree in Mineral Exploration at Colorado School of Mines in 2011. He worked more than 13 years as an exploration, mining and modelling geologist for some prestigious mining companies, Barrick and Newmont, Freeport-McMoRan and Southern Peru. Efrain has experience in a variety of geological settings and commodities principally in gold, silver, copper and molybdenum. He joined the CCG group since September 2015 and started a Master’s degree in Mining Engineering (Geostatistics).

CCG_Efrain_photo_2015

Research

      • Optimal Extraction Layout for Block Caving with a Set of Stochastic Realizations

Publications

      1.  E.Ugarte ,Y. Pourrahimian. J. Boisvert (2016). Comparison of Recoverable Reserves between Simulation and Kriging for Block Caving with Optimized Drawpoints. CCG Paper 2016-304, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      2. E.Ugarte,Y. Pourrahimian and  J. Boisvert (2016). Optimizing Drawpoints in Block Caving Layouts over a Set of Stochastic Realizations. CCG Paper 2016-305, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.

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Enrique Gallardo (Under Construction)

Ph.D. Student

Biography coming Soon!

Research

Coming Soon!

Publications

Coming Soon!

Contact

Felipe Alfredo Cabral Pinto

Ph.D. Student

I started my studies in Geology in the Federal University of Ouro Preto (MG, Brazil), changing few months later to Mining Engineering in the Federal University of Minas Gerais (MG, Brazil) where I graduated in 2013. During my undergraduate studies, I attended the last year of the Geology program in the École Nationale Supérieure de Géologie de Nancy (France) where I fell in love for Geostatistics and resource modeling. I complete my M.Sc. in Mining Engineering at University of Alberta in August of 2016. I currently work as a Geostatistical Summer Student at Teck Resources Limited.

Research

      • Data spacing and uncertainty
      • Factors and parameters affecting data spacing and uncertainty
      • The Value of Information

Publications

Conference

      1. Pinto, F.A.C. and Deutsch, V.C. (2015) Expected Uncertainty as a Function of the Variogram, Data Spacing and Other Factors, presented at 37th International Symposium on Application of Computers and Operations Research in the Mineral Industry (APCOM ) in Fairbanks, Alaska, USA, 1149 pp.

CCG Report

      1. F. A. C. Pinto and Clayton V. Deutsch, 2015, Methodology and Interpretation of Data Spacing and Uncertainty, CCG Paper 2015-302, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      2. F. A. C. Pinto, Kevin Palmer and Clayton V. Deutsch, 2015, Case Study on Data Spacing and Uncertainty, CCG Paper 2015-303, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      3. F. A. C. Pinto and Clayton V. Deutsch, 2015, Software Useful for Data Spacing Analysis, CCG Paper 2015-406, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      4. F. A. C. Pinto , 2015, Guide to Data Spacing and Uncertainty Analysis, CCG Guidebook Volume 19, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      5. F. A. C. Pinto & C. V. Deutsch, 2014, Factors Influencing Data Spacing and Uncertainty, CCG Paper 2014-117, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      6. F. A. C. Pinto & C. V. Deutsch, 2014, Thoughts on Data Spacing, Uncertainty and the Value of Information, CCG Paper 2014-118, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
      7. F. A. C. Pinto & C. V. Deutsch, 2014, Calculating the Proportional Effect Based on the Univariate Distribution, CCG Paper 2014-407, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada

Contact

George Barros

Ph.D. Student

George graduated with a Bachelor Degree in Geology from the University of Sao Paulo, Brazil. In 2001, he completed his Master Degree in Mineral Resources at the same university.
George has more than ten years of experience in the oil/gas industry as a reservoir geologist at the Research Center in the Brazilian Oil Company (Petrobras), Rio de Janeiro, Brazil.
In March 2015, George joined the Centre for Computational Geostatistics (CCG) at University of Alberta as a PhD student and his main research focus is Petroleum Geostatistics.

georgebarros_crop

Research

      • Geostatistical Reservoir Modeling
      • Reservoir Characterization
      • Static and Dynamic Data Integration

Publications

      1. G. de Barros and C. V. Deutsch (2015). Optimal Ordering of Realizations for Visualization and Presentation , CCG Paper 2015-102, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      2. G. de Barros and C. V. Deutsch (2016). Some Thoughts on Using All Realizations for Reservoir Management, CCG Paper 2016-202, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      3. G. de Barros and C. V. Deutsch (2016). Rejection Sampling for Large Scale Averages – Proof of Concept, CCG Paper 2016-208, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.
      4. G. de Barros and C. V. Deutsch (2016). Rejection Sampling to Well Test Data – an Extension, CCG Paper 2016-209, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada.

Contact

Jianan Qu

Ph.D. Student

Master, China University of Geosciences (Beijing), 09/2010-07/2013
Ph.D, University of Alberta, 09/2013-Now

Research

      • Trend Modeling
      • Sequential Gaussian Simulation on Trends

Publications

      1. Wang, G., Pang, Z., Boisvert, J. B., Hao, Y., Cao, Y., & Qu, J. (2013). Quantitative assessment of mineral resources by combining geostatistics and fractal methods in the Tongshan porphyry Cu deposit (China). Journal of Geochemical Exploration, 134, 85-98.

Contact

Matt Samson

M.Sc. Student

I received my BSc in the Mining Engineering Co-op program from the University of Alberta in April 2016. On my work terms: I had the opportunity to work as a Heavy Equipment Operator at Suncor and see the day to day operation of a mine first had, for my second work term I worked as a Project Manager Assistant at Emeco Canada working on cost analysis, equipment maintenance optimization, and contract bidding, for my final work term I worked at KMC Mining as a Mine Performance Analyst working on optimizing and monitoring day to day mine operations and costing. In my undergraduate degree, I took an application of geostatistics course and decided to pursue a Master of Science in Civil and Environmental Engineering focusing on geostatistics and joined the Center For Computational Geostatistics in September 2016 after receiving my BSc.

SamsonMattCrop1

Contact

Paolo Kumara

Paolo Kumara completed his bachelor degree in Mine Geology from Bandung Institute of Technology, Bandung, Indonesia on 2013. He has 2 years experiences as grade control geologist in open pit gold mine in North Sulawesi, Indonesia. And has experience as exploration geologist and geophysicist when he was doing undergraduate study. Joined the group as a Master of Science in mining engineering student in CCG since 2017.

Research

  1. Geometallurgical modeling

Contact

Ryan Martin

Ph.D. Student

I received my MSc studying the geochemistry and petrogenesis of a syenite hosted gold deposit in northern Ontario. During the following year I completing several deterministic geological modeling projects which set my sights firmly on learning more about the computational geosciences. I joined the CCG in 2014, and have worked on various topics, all relating to modeling complex geometries that are present in ore deposits. I am currently interested in spatial classification techniques that can be used to group similar data based on location and the multivariate properties.

ryanmartin

Research

My current research interests include:

  • Modeling the components of an LVA field
  • LVA in implicit geological modeling
  • Spatial clustering
  • Pygeostat and mixed python and Fortran programming

Publications

CCG report:

  1. Ryan Martin, David Machuca, Oy Leuangthong and Jeff Boisvert, 2015, Evaluating LVA methods with locally varying magnitudes , CCG Paper 2015-114, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
  2. Ryan Martin, John Manchuk, and Jeff Boisvert, 2015, Automatic LVA field generation in 3D, CCG Paper 2015-111, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
  3. Ryan Martin and Jeff Boisvert, 2015, New Method to Estimate the Locally Varying Magnitudes in an LVA Field, CCG Paper 2015-113, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
  4. Ryan Martin and Jeff Boisvert, 2015, Review of Radial Basis Functions and Domain Decomposition for Implicit Geological Modelling, CCG Paper 2015-118, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada

Peer-Reviewed:

  1. Structural setting of the Young-Davidson syenite-hosted gold deposit in the western Cadillac-Larder Lake deformation zone, Abitibi Greenstone Belt, Superior Province, Ontario. 2014. Lin, S., Zhang, J., Linnen, R.L., and Martin, R. Precambrian Research, v. 248, 39-59.
  2. Paleoproterozoic hydrothermal reactivation in a neoarchean orogenic lode-gold deposit of the southern Abitibi subprovince: U-Pb monazite geochronological evidence from the Young-Davidson mine, Ontario. 2014. Zhang, J., Linnen, R., Lin, S., Davis, D., and Martin, R. Precambrian Research, v. 249, 263-272.

Thesis:
Syenite-hosted gold mineralization and hydrothermal alteration at the Young-Davidson deposit, Matachewan, Ontario. 2012. Martin, R. Master Thesis of the University of Waterloo, pp. 172.

Misc Reports:
Synthesis of the Structure, Petrology, Geochronology and Geochemistry of the Young–Davidson Gold Deposit and Surrounding Area, by R.L. Linnen, S. Lin, J. Zhang, R.D. Martin, N. Naderi, D.W. Davis, M.A. Hamilton, R.A. Creaser, B.R. Berger, N.R. Banerjee, B.A. Wing and C. Wu. 2013. Ontario Geological Survey, Miscellaneous Release-Data 294.

Contact

Samer Hmoud

M.Sc. Student

Samer Hmoud is an Exploration Geologist with more than four years’ experience in the field of mining and Oil/Gas industries. He received both of his Bachelor and Mater Degrees with distinction in Geology from the Hashemite University in Jordan (Ranked the first among his colleagues). His Master thesis research aimed to model Surficial Uranium Deposits at Central Jordan. In September 2015, Samer joined the Centre for Computational Geostatistics (CCG) at University of Alberta as an MSc student of Mining Engineering and his main research focus is Petroleum Geostatistics.

samer

Research

  • Applying new Multivariate Geostatistical Modeling techniques to Unconventional Hydrocarbon Reservoirs

Publications

Peer-review Journal

Conference

CCG Report

Contact

Yaroslav Vasylchuk

Ph.D. Student

Completed Master’s degree in mining with distinction at Kryvyi Rih Technical University, Ukraine in 2010. From 2010 to 2013, worked for a Ukrainian blasting company as a surveyor and blasting engineer. In 2016, graduated from the Master of Science program at the University of Alberta being a member of the CCG. Later in 2016, decided to start a PhD program and am currently working on my doctoral research.

yaroslavvasylchuk

Research

  1. Improving grade control in open pit mines using simulation and estimation methods
  2. Modeling blast movement of grades
  3. Truck-based selection of mined material

Publications

    Scientific publication in international mining journals (2016/2017 years):
  1. Vasylchuk Y. V. & Deutsch C. V. (2016). Improved Grade Control in Open Pit Mines, Mining Engineering (preprint), Englewood, CO.
    CCG conference papers (2016/2017 study year):
  2. Vasylchuk Y. V. & Deutsch C. V. (2016). Kriging with different search plans. CCG Paper 2016-307, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
  3. Vasylchuk Y. V. & Deutsch C. V. (2016). A short note on combined ordinary and simple kriging for improved estimation of mineral resources. CCG Paper 2016-306, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
  4. Vasylchuk Y. V. & Deutsch C. V. (2016). Optimal Linear Estimation under Different Circumstances, CCG Paper 2016-131, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
  5. Vasylchuk Y. V. & Deutsch C. V. (2016). Nonlinear estimation in mining, CCG Paper 2016-132, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada

CCG Conference papers (2014/2015 study year

  1. Vasylchuk Y. V. & Deutsch C. V. (2015). A Short Note on Optimal Kriging Grid Size Relative to Data Spacing, CCG Paper 2015-308, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
  2. Vasylchuk Y. V. & Deutsch C. V. (2015). Assessing the Effectiveness of Using Estimation Methods versus Simulation in Ore/Waste Selection, CCG Paper 2015-310, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
  3. Vasylchuk Y. V. & Deutsch C. V. (2015). A Program for Calculating an Approximate Blast Movement for Improved Grade Control, CCG Paper 2015-311, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada
  4. Vasylchuk Y. V. & Deutsch C. V. (2015). A Short Note on Truck-by-Truck Selection versus Polygon Grade Control, CCG Paper 2015-312, Centre for Computational Geostatistics, University of Alberta, Edmonton, Canada

Scientific publication in international mining journals (2011-2014 years):

  1. Shapurin, O. V., & Vasylchuk, Y. V. (2014). Comprehensive algorithm of the optimization of drilling and blasting parameters. Mining Journal, Yekaterinburg, №3, 55-62.
  2. Shapurin, O. V., & Vasylchuk, Y. V. (2013). Prediction of the granulometric composition of blasted rocks. Vzryvnoe delo. Moscow, 109/66.
  3. Vasylchuk Y. V. (2013). The method of blasting with inclined boreholes and its practical implementation. Visnyk KNU. Kryvyi Rih, 35.
  4. Shapurin O. V., Vasylchuk, Y. V., & Nosov, V. N. (2012). A mathematical model for predicting the granulometric composition of blasted rocks, Visnyk KDU. Kremenchuk, №4, 94-100.
  5. Vasylchuk Y. V. (2012) Mathematical modeling of blasts in rocks. Visnyk KNU, Kryvyi Rih, 32, 18 -20.
  6. Nosov, V. N. Vasylchuk, Y. V. $ Murshits, D. A. (2012). The influence of borehole diameter on the technical and economic indicators of blast. The newsletter of UUEE, 2, 9-12.
  7. Shapurin, O.V. & Vasylchuk, Y. V. (2011). The quality of blasting considered as a result of the combined effect of various factors. Visnyk KNU. Kryvyi Rih, 29, 13 – 17.

Contact

Yimin (Connor) Wang

Ph.D. Student

Connor Wang started his M.Sc. degree in 2014, before which he spend one year in Mine Planning and Simulation Optimization at the University of Alberta. Connor obtained a B.Sc. in Mineral Resource Engineering in 2013 from the University of Science and Technology Beijing in China.
During his B.Sc. Degree, Connor did internships with mining-related international companies such as Jilin Banmiaozi Gold Company Limited (Eldoradogold Corp), Beijing General Research Institute of Mining &Metallurgy, and Shanghai Meishan Mining Limited (Baosteel Corp).

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Research

  • Modifying SNESIM program such that rotating training image slightly creates more samples as input and makes simulations more stable
  • Optimization for conditioning object based models

Contact

Yi Shang

M.Sc. Student

Yi Shang joined the CCG in September 2015 and is currently pursuing his M.Sc. in Geostatistics. He completed his B.Sc. in Petroleum Engineering in 2009 at China University of Petroleum, Beijing, and then graduated with a MEng in Petroleum Engineering from University of Alberta in 2011. He spent the next 4 years as a safety engineer in the China Petrochemical Corporation.

Yi

Research

  • Geostatistical reservoir modeling for SAGD

Contact