Alumni

The following table displays the CCG alumni that have graduated with M.Sc. and/or Ph.D. degrees under the supervision of Dr. Clayton Deutsch. Additional information is provided for select alumni in the left links.

YearDoctorate Masters
Total2629
2016Tolonbek Karpekov, Felipe Pinto, Yaroslav, Vasylchuk
2015Yevgeniy Zagayevskiy, Ryan Barnett, Daniel Silva, Saina Lajevardi, Jared DeutschEric Daniels, Patrick Donovan
2014VD, BK, MCMB
2013Mehdi Khajeh, MH, ENFR
2012MJM, MJ
2011YLAK, MV, Yevgeniy Zagayevskiy
2010JBB, Sahyun Hong, DFM, JGMBrandon Wilde
2009AH, Steven Lyster, NADF, TW
2008Olena Babak
2007Jason McLennan, KN, Weishan RenDB, HD, JBB, JGM, MH, Xingquan Zhang, ZL
2006CN
2005LZ
2004Michael PyrczPaula Larrondo, SZ
2003Julian Ortiz, TF, ZR, Oy Leuangthong
2002<Hahn Nguyen, BW, XW

Brandon WIlde

M.Sc. Graduate (2010)

Before joining CCG I graduated from U of A with Bachelors of Science in Mining Engineering.  Since completing my masters I have worked as a Research Associate and am now doing consulting full time with an emphasis on implementing advanced geostatistical techniqes as Petrel plugins.

Contact

brandonwilde_crop

Cole Mooney

M.Sc. Graduate (2015)

I studied my undergrad in geology at UBC and I graduated that in 2010.  Prior to joining the CCG, I worked for Pretivm Resources as an exploration geologist and an underground mine geologist.  Since leaving the CCG, I’ve returned to work with Pretivm Resources as a resource geologist.

Research

  • Modeling heavy-tailed gold deposits with a spatial point process.
CCG Cole Mooney

Publications

  1. Mooney, C.R., Board, W., Boisvert, J.B. (2015) Modelling heavy-tailed coarse gold deposits with a spatial point process. CIM Journal, Vol. 6 (2), 118-131.
  2. Mooney, C.R., Board, W., Boisvert, J.B. (2016) Using a discrete fracture network and spatial point process to characterize veins in a coarse gold deposit. Natural Resources Research, Vol. 25 (3), 255–268

Contact

Daniel Silva

Ph.D. Graduate (2015)

Silva Maureira, D.A., 2015, Enhanced Geologic Modeling with Data-Driven Training Images for Improved Resources and Recoverable Reserves, Ph.D. Thesis, University of Alberta, Edmonton, Canada

Dr. Silva is a mining engineer from Universidad de Chile currently pursuing Ph.D. in mining engineering at the University of Alberta. Prior to joining the Centre for Computational Geostatistics Mr. Silva worked as Geostatistician at AMEC based on Santiago, Chile conducting mineral resource-reserves evaluations and technical reports for pre-feasibility and feasibility projects in South and Centre America.

Research

The main area of research comprises developing advanced numerical modeling techniques for improved uncertainty characterization in mineral deposits. My particular interest lies on:

  • Theory and applications of multiple point statistics algorithms to modeling complex geological settings in mineral deposits
  • Hybrid multiple point statistics models incorporating and integrating multiple training images for an accurate forecasting of recoverable resources and reserves

Publications

  1. Silva DA, Emery X (2008) Geological control in grade simulation: A comparative study. In: Ortiz J, Emery X (eds) Eighth International Geostatistics Congress, Santiago. Gecamin, pp 789-798.
  2. Emery X, Silva DA (2009) Conditional co-simulation of continuous and categorical variables for geostatistical applications. Computers & Geosciences 35:1234-1246.
  3. Silva DA, Deutsch CV (2009) A multiple training image approach for spatial modeling of geologic domains. Mathematical Geosciences, DOI 10.1007/s11004-014-9543-0.

Contact

Eric Daniels

M.Sc. Graduate (2015)

Daniels, E., 2015, Prediction of Local Uncertainty for Resource Evaluation, M.Sc. Thesis, University of Alberta, Edmonton, Canada

Originally from Connecticut, USA, Eric received his Bachelor’s degree in geology from Colorado College in 2009. Since finishing his undergraduate degree Eric has gained experience as a professional geologist with a focus in hard rock mining and exploration. His work as a mine geologist at Cripple Creek and Victor Gold Mine served as an introduction to geostatistics. In his free time, Eric enjoys getting outside to the mountains or the ocean whenever possible.

Research

Eric’s research is focused on managing uncertainty in a mining context, including:

  • Software development for a flexible localization process
  • Artifact reduction in localized models
  • Local volume variance correction
  • Utilizing multiple realizations in mine planning

Contact

Hanh Nguyen

M.Sc. Graduate (2002)

hanhnguyen

Jared Deutsch

Ph.D. Graduate (2015)

Deutsch, J., 2015, Multivariate Spatial Modeling of Metallurgical Rock Properties, Ph.D. Thesis, University of Alberta, Edmonton, Canada

Background Before Joining the CCG

Jared graduated with a BSc in Materials Engineering from the University of Alberta focusing on mineral processing and extractive metallurgy. He then completed a MASc in Materials Engineering at the University of British Columbia studying hydrometallurgy and a PhD at the Centre for Computational Geostatistics with a focus on geometallurgy. The focus of his research included the spatial modeling of metallurgical variables and application of these models.

Occupations Since Leaving the CCG

Jared is currently a geostatistician at Newmont Mining Corporation.

Research Interests

  • Geostatistical modeling of nonlinear metallurgical variables
  • Downscaling large metallurgical indices for high resolution modeling
  • Application and optimization of spatial geometallurgical models

Publications

  1. Deutsch, J.L., Palmer, K., Deutsch, C.V., Szymanski, J. and Etsell, T.H. (2015) Spatial Modeling of Geometallurgical Properties: Techniques and a Case Study, Accepted for publication in Natural Resources Research, 21 pp.
  2. Deutsch, J.L., Szymanski, J. and Deutsch, C.V. (2014) Checks and measures of performance for kriging estimates, Accepted for publication in the Journal of the Southern African Institute of Mining and Metallurgy, 8 pp.
  3. Deutsch, J.L., and Deutsch, C.V. (2013) A multidimensional scaling approach to enforce reproduction of transition probabilities in truncated plurigaussian simulation, Stochastic Environmental Research and Risk Assessment, 2013.
  4. Deutsch, J.L., and Dreisinger, D.B. (2013) Silver Sulfide Leaching with Thiosulfate in the Presence of Additives Part I: Copper-Ammonia Leaching, Hydrometallurgy 137, 156-164.
  5. Deutsch, J.L., and Dreisinger, D.B. (2013) Silver Sulfide Leaching with Thiosulfate in the Presence of Additives Part II: Ferric Complexes and the Application to Silver Sulfide Ore, Hydrometallurgy 137, 165-172.
  6. Deutsch, J.L. (2012) Fundamental aspects of thiosulfate leaching of silver sulfide in the presence of additives, MASc Thesis, University of British Columbia, Vancouver, 126 pp.
  7. Deutsch, J.L., Boisvert, J.B. and Deutsch, C.V. (2011) A New Dimension to Account for Data Error and Scale, 2011 Transactions of the Society of Mining, Metallurgy, and Engineering 330, 598-605.
  8. Deutsch, J.L and Deutsch, C.V. (2011) Latin Hypercube Sampling with Multidimensional Uniformity, Journal of Statistical Planning and Inference 142(3), 763-772.
  9. Deutsch, J.L. and Deutsch, C.V. (2011) Plotting and checking the bivariate distributions of multiple Gaussian data, Computers and Geosciences 37(10), 1677-1684.

Contact

Jason McLennan

Ph.D. Graduate (2007)

Background Before Joining the CCG

BSc in Mining Engineering, University of Alberta

jasonmclennan

Occupations Since Leaving the CCG

  • CD5 Project Integration Manager, ConocoPhillips, August 2015 – Present, Anchorage, Alaska Area
  • Senior Reservoir Engineer, ConocoPhillips, August 2011 – Present, Anchorage, Alaska Area
  • Analyst, ConocoPhillips, February 2010 – July 2011, Houston, Texas Area
  • Senior Geomodeler, ConocoPhillips, May 2007 – January 2010, Houston, Texas Area

Publications

  1. Mooney, C.R., Board, W., Boisvert, J.B. (2015) Modelling heavy-tailed coarse gold deposits with a spatial point process. CIM Journal, Vol. 6 (2), 118-131.
  2. Mooney, C.R., Board, W., Boisvert, J.B. (2016) Using a discrete fracture network and spatial point process to characterize veins in a coarse gold deposit. Natural Resources Research, Vol. 25 (3), 255–268

Contact

Julian Ortiz

Ph.D. Graduate (2003)

Ortiz, J., 2003, Characterization of High Order Correlation for Enhanced Indicator Simulation, Ph.D. Thesis, University of Alberta, Edmonton, Canada

jortiz

Career Highlights

  • Significant experience in Research and Development, generating research funds, directing large research grants and leading multidisciplinary teams. Participated as deputy director of Advanced Mining Technology Center at Universidad de Chile.
  • Extensive experience in teaching and training professionals, with over 70 short courses taught, in Chile, Argentina, and Australia. Past head of Department of Mining Engineering at Universidad de Chile, has been involved as academic coordinator of M.Sc. and Ph.D. programs in Mining Engineering.
  • 18 years of consulting experience in geostatistical assessment of geological resources in copper, gold, silver, iron ore, with clients such as Codelco, BHP Billiton, Antofagasta Minerals, Anglo American, Peñoles, and Barrick. International experience with projects in Chile, Argentina, Mexico, Uruguay, Brazil, Peru, and Canada.
  • Member of technical board at Escondida, the largest operating copper mine in the world.

Research

  • Mining geostatistics
  • Multiple-point geostatistics
  • Geological modeling
  • Statistical data analysis

Publications

Peer review journal articles:

  1. Díaz, G., Mariethoz, G., Ortiz, J. M., (2016) Optimization-Based Texture Synthesis for Geostatistical Simulation with Training Images, submitted to Mathematical Geosciences (ISI).
  2.  Peredo, O., Ortiz, J. M., Herrero, J. R., (2015) Acceleration of the Geostatistical Software Library (GSLIB) by Code Optimization and Hybrid Parallel Programming, Computers & Geosciences (ISI), 85(A):210-233.
  3. Peredo, O., Ortiz, J. M., Leuangthong, O., (2015) Inverse Modeling of Moving Average Isotropic Kernels for Non-parametric Three-Dimensional Gaussian Simulation, Mathematical Geosciences (ISI), online first.
  4. Calderón, H., Silva, J. F., Ortiz, J. M., Egaña, A., (2015) Reconstruction of Channelized Geological Facies based on RIPless Compressed Sensing, Computers & Geosciences (ISI), 77: 54-65.
  5. Ortiz, J. M., Magri, E. J., (2014) Designing and Advanced RC Drilling Grid for Short-Term Planning in Open Pit Mines: Three Case Studies, The Journal of the Southern African Institute of Mining and Metallurgy (ISI), 114: 631-637.
  6. Rezaee, H., Asghari, O., Koneshloo, M., Ortiz, J. M., (2014) Multiple-Point Geostatistical Simulation of Dykes: Application at Sungun Porphyry Copper System, Iran, Stochastic Environmental Research and Risk Assessment (ISI), 28: 1913-1927.
  7. Pérez, C., Mariethoz, G., Ortiz, J. M., (2014) Verifying the high-order consistency of training images with data for multiple-point geostatistics, Computers & Geosciences (ISI), 70: 190-205.
  8. Peredo, O., Ortiz, J. M., Herrero, J. R., Samaniego, C., (2014) Tuning and Hybrid Parallelization of a Genetic-based Multi-Point Statistics Simulation Code, Parallel Computing (ISI), 40: 144-158.
  9. Cuba, M., Leuangthong, O., Ortiz, J. M., (2012) Transferring Sampling Errors into Geostatistical Modeling, Journal of the Southern African Institute of Mining and Metallurgy (ISI), 112(11): 971-983.
  10. Ortiz, J. M., Magri, E. J., Líbano, R., (2012) Improving financial returns from mining through geostatistical simulation and the optimized advance drilling grid at El Tesoro Copper Mine, Journal of the Southern African Institute of Mining and Metallurgy (ISI), 112 (1): 15-22.
  11. Emery, X., Ortiz, J. M., (2012) Enhanced coregionalization analysis for simulating vector Gaussian random fields, Computers & Geosciences (ISI), 42: 126-135.
  12. Cuba, M., Leuangthong, O., Ortiz, J. M., (2012) Detecting and Quantifying Sources of Non-Stationarity via Experimental Semivariogram Modeling, Stochastic Environmental Research and Risk Assessment (ISI), 26(2): 247-260.
  13. Parra, A., Ortiz, J. M., (2011) Adapting a Texture Synthesis Algorithm for Conditional Multiple Point Geostatistical Simulation, Stochastic Environmental Research and Risk Assessment (ISI), 25(8): 1101-1111.
  14. Peredo, O., Ortiz, J. M., (2011) Parallel implementation of simulated annealing to reproduce multiple-point statistics, Computers & Geosciences (ISI), 37(8): 1110-1121.
  15. Emery, X., Ortiz, J. M., (2011) Two approaches to direct block-support conditional co-simulation, Computers & Geosciences (ISI), 37(8): 1015-1025.
  16. Emery, X., Ortiz, J. M., (2011) A Comparison of Random Field Models Beyond Bivariate Distributions, Mathematical Geosciences (ISI), 43(2):183-202
  17. Emery, X., Ortiz, J. M., and Cáceres, A. M., (2008) Geostatistical modeling of rock type domains with spatially varying proportions: Application to a porphyry copper deposit, Journal of the South African Institute of Mining and Metallurgy (ISI), 108(5): 285-292.
  18. Boisvert, J. B., Leuangthong, O., Ortiz, J. M., and Deutsch, C. V., (2008) A methodology to construct training images for vein type deposits, Computers & Geosciences (ISI), 34(5): 491-502.
  19. Emery, X. and Ortiz, J. M., (2007) Weighted sample variograms as a tool to better assess the spatial variability of soil properties, Geoderma (ISI), 140(1-2): 81-89.
  20. Ortiz, J. M., Lyster, S., and Deutsch, C. V., (2007) Scaling multiple-point statistics to different univariate proportions, Computers & Geosciences (ISI), 33(2): 191-201.
  21. Ortiz, J. M., and Emery, X., (2006) Geostatistical estimation of mineral resources with soft boundaries: a comparative study, Journal of the South African Institute of Mining and Metallurgy (ISI), 106(8): 577-584.
  22. Emery, X., Ortiz, J. M., and Rodríguez, J. J., (2006) Quantifying Uncertainty in Mineral Resources by Use of Classification Schemes and Conditional Simulation, Mathematical Geology (ISI), 38(4): 445-464.
  23. Jara, R., Couble, A., Emery, X., Magri, E., and Ortiz J., (2006) Block size selection and its impact on open pit mine design and planning, Journal of the South African Institute of Mining and Metallurgy (ISI), 106(3): 205-211.
  24. Emery, X., and Ortiz, J. M., (2005) Estimation of mineral resources using grade domains: critical analysis and a suggested methodology, Journal of the South African Institute of Mining and Metallurgy (ISI), 105(4): 247-255.
  25. Emery, X., and Ortiz, J. M., (2005) Histogram and Variogram Inference in the Multigaussian Model, Stochastic Environmental Research and Risk Assessment (ISI), 19(1): 48-58.
  26. Ortiz, J. M., and Deutsch, C. V., (2004) Indicator Simulation Accounting for Multiple-Point Statistics, Mathematical Geology (ISI), 36(5): 545-565.
  27. Ortiz C., J., and Deutsch, C. V., (2002) Calculation of Uncertainty in the Variogram, Mathematical Geology (ISI), 34(2): 169-183.

Contact

Mehdi Khajeh

Ph.D. Graduate (2013)

After Finishing BSc (2001-2005) and MSc (2005-2007), both in Petroleum Engineering, I Started my PhD at University of Alberta, Department of Civil and Environmental Engineering and in Reservoir Geomechanics Research Group (RG2). As Geological Modelling and uncertainty analysis of stochastical Geological Modelling processes was always my passion, I decided to consider Geostatistical Techniques in my PhD Research, but from Geomechanical Engineering side of view. I investigated how heterogeneity of in rock mechanical properties (in addition to heterogeneity of petrophysical properties which conventionally was considered in geological modelling process) have effect in SAGD. Additionally,  I developed Ranking Technique to rank geological realizations based on Geomechanical Response and also developed  Numerical Upscaling Technique for upscaling of rock mechanical properties.

CCG team and specifically Dr. Jeff Boisvert were great help and great support during my PhD. From February 2013 so far, I am working with Cenovus Energy as Geomechanical Engineer. “

mehdikhajeh

Contact

Michael J. Pyrcz

Ph.D. Graduate (2004)

Pyrcz, M.J., The Integration of Geologic Information into Geostatistical Models, Ph.D. Thesis, University of Alberta, 2004, 250 pages.

Background Before Joining the CCG

  • Mining Engineering B.Sc.(Co-op) with Distinction, University of Alberta (2000)
  • Awarded APEGGA Gold Medal (graduated top of engineering class)
  • Mining Engineer (Internship) at Manalta Coal LTD. Highvale Mine, Wabamun, AB  (May, 1998 – Aug., 1998)
  • Mining Engineer (Internship) at Obed Mountain Coal LTD., Hinton, AB (May, 1997 – Dec., 1997
michaelpyrcz

Occupations Since Leaving the CCG

  • Team Leader, Reservoir Modeling R&D, Chevron Energy Technology Company (Jan., 2014 – Present)
  • Research scientist, Reservoir Modeling R&D, Chevron Energy Technology Company (Sept. 2004 – Present)

Research

  • Process-mimicking geostatistics
  • Geostatistics for unconventional plays
  • Multiscale and multivariate modeling
  • Optimum decision making in the presence of uncertainty
  • Model post-processing, updating and QC
  • Connectivity quantification

Publications

Books:

  1. Pyrcz, M.J., and Deutsch, C.V., 2014, Geostatistical Reservoir Modeling, 2nd Edition, Oxford University Press, New York, p. 448
  2. Pyrcz, M.J., and Deutsch, C.V., 2014, Uncertainty is Inevitable, in Matt Hall, Kara Turner (eds.) Agile Libre, p. 132

Peer reviewed journal articles:

  1. Faechner, T., Pyrcz, M.J., and Deutsch, C.V., 2000, Prediction of Yield Response to Soil Remediation: Geoderma, Elsevier, v. 97, pp. 21-38.
  2. Pyrcz, M.J., and Deutsch, C.V., 2001, Two Artifacts of Probability Field Simulation: Math Geology, Vol. 33, No. 7, pp. 775-799.
  3. Pyrcz, M.J. and Deutsch, C.V., 2003, “The Whole Story on the Hole Effect: in Searston, S. (eds.) Geostatistical Association of Australasia, Newsletter 18, May (reviewed by editor).
  4. Pyrcz, M.J. and Deutsch, C.V., 2003, Declustering and Debiasing: in Searston, S. (eds.) Geostatistical Association of Australasia, Newsletter 19, October (reviewed by editor).
  5. Pyrcz, M.J. and Deutsch, C.V., 2005, Conditional Event-based Simulation: in O. Leuangthong and C.V. Deutsch (eds.), Geostatistics Banff 2004 Peer Reviewed Proceedings, Springer, Netherlands, pp 135-144.
  6. Pyrcz, M.J., Catuneanu, O. and Deutsch, C.V., 2005, Stochastic Surface-based Modeling of Turbidite Lobes: American Association of Petroleum Geologists Bulletin, Vol. 89., No. 2, pp 177-191.
  7. Pyrcz, M.J., and Deutsch, C.V., 2006, Semivariogram Models Based On Geometric Offsets: Math Geology, Vol. 38, No. 4, pp. 475-488.
  8. Pyrcz, M.J., and Deutsch, C.V., 2006, Spectrally Corrected Semivariogram Models: Math Geology, Vol. 38, No. 7.
  9. Pyrcz, M.J., Gringarten, E., Frykman, P., and Deutsch, C.V., 2006, Representative Input Parameters for Geostatistical Simulation, in T.C. Coburn, R.J. Yarus and R.L. Chambers, eds., Stochastic Modeling and Geostatistics: Principles, Methods and Case Studies, Volume II: AAPG Computer Applications in Geology 5, pp. 123-137.
  10. Pyrcz, M.J and Strebelle, S., 2006, Event-based Geostatistical Modeling of Deepwater Systems: Reservoir Characterization: Integrating Technology and Business Practices: Gulf Coast Section-SEPM Twenty-Sixth Annual Research Conference Peer Reviewed Proceedings, pp. 893-922.
  11. Pyrcz, M.J., Clark, J, Drinkwater, N., Sullivan, M., Fildani, A and McHargue, T., 2006, Event-based Models as a Quantitative Laboratory for Testing Quantitative Rules Associated with Deepwater Distributary Lobes: Reservoir Characterization: Integrating Technology and Business Practices: Gulf Coast Section-SEPM Twenty-Sixth Annual Research Conference Peer Reviewed Proceedings, pp. 923-950.
  12. Pyrcz, M.J., Boisvert, J. and Deutsch, C.V., 2007, A Library of Training Images for Fluvial and Deepwater Reservoirs and Associated Code: Computers and Geosciences, doi:10.1016/j.cageo.2007.05.015.
  13. Boisvert, J., Pyrcz, M.J., and Deutsch, C.V., 2007, Multiple Point Selection of Training Images: Natural Resources Research, doi: 10.1007/s11053-008-9058-9. http://www.springerlink.com/content/k9843627l327lx02/
  14. Khan, D., Strebelle, S., Hanggoro, D., Willis, B., and Pyrcz, M.J., 2008, Non-stationary Multiple Point simulation to model complex deltaic deposits for flow simulation: in Ortiz, J. and Emery, X. (eds.), Geostatistics Santiago 2008 Peer Reviewed Proceedings, Springer, Netherlands.
  15. Zhang, K., Pyrcz, M.J., and Deutsch, C.V., 2008, Advanced Stochastic Surface-based Modeling: in Ortiz, J. and Emery, X. (eds.), Geostatistics Santiago 2008 Peer Reviewed Proceedings, Springer, Netherlands.
  16. Pyrcz, M.J. and Strebelle, S., 2008, Event-based Geostatistical Modeling: in Ortiz, J. and Emery, X. (eds.), Geostatistics Santiago 2008, Springer, Netherlands.
  17. Zhang, K., Pyrcz, M.J., and Deutsch, C.V., 2009, Stochastic Surface-based Modeling for Integration of Geological Information in Turbidite Reservoir Model: Petroleum Geoscience and Engineering. http://dx.doi.org/10.1016/j.petrol.2009.06.019.
  18. Pyrcz, M.J. Boisvert, J. and Deutsch, C.V., 2009, Alluvsim: a Conditional Event-based Fluvial Model: Computers & Geosciences.doi:10.1016/j.cageo.2008.09.012.
  19. Boisvert, J., Pyrcz, M.J., and Deutsch, C.V., 2010, Multiple Point Metrics to Assess Categorical Variable Models: Natural Resources Research, (19) 3, pages 165-174.
  20. McHargue,T., Pyrcz,M.J., Sullivan, M.D.,  Clark, J., Fildani, A., Romans, B., Covault, J., Levy, M., Posamentier, and H., Drinkwater,N., 2010, Architecture of turbidite channel systems on the continental slope: patterns and predictions: Marine and Petroleum Geology, Marine and Petroleum Geology, doi:10.1016/j.marpetgeo.2010.07.008.
  21. Pyrcz, M.J., Sullivan, M.D., McHargue, T.R., Fildani, A., Drinkwater, N.J., Clark, J., and Posamentier, H.W., 2011, Numerical Modeling of Channel Stacking from Outcrop: in Martinsen, O., Pulham, A., Haughton, P., and Sullivan, M. (eds.), SEPM special publication –  Outcrops Revitalized: Tools,  Techniques and Applications.
  22. McHargue, T.R., Pyrcz, M.J., Sullivan, M.D., Clark, J., Fildani, A., Drinkwater, N.J., Levy M., Posamentier, H.W., Romans, B. and Couvalt, J.,  2011, Numerical Modeling of Channel Stacking from Outcrop: in Martinsen, O., Pulham, A., Haughton, P., and Sullivan, M. (eds.), SEPM special publication –  Outcrops Revitalized: Tools,  Techniques and Applications.
  23. Cavelius, C., Pyrcz, M.J and Strebelle, S., 2012, Continuous Trends in Multiple Point Statistics: 2012 Geostatistical Congress Peer Reviewed Proceedings, Oslo, Norway
  24. Pyrcz, M.J., McHargue, T., Clark, J.,  Sullivan, M. and Strebelle, S., 2012, Event-based Geostatistical Modeling: Description and Applications, 2012 Geostatistical Congress Peer Reviewed Proceedings, Oslo, Norway, peer reviewed proceedings.
  25. Hassanpour, M., Pyrcz, M.J., and Deutsch, C.V., 2013, Improved Geostatistical Models of Inclined Heterolithic Strata for McMurray Formation: Alberta, Canada, AAPG Bulletin, v. 97, no. 7, p. 1209-1224.
  26. Boisvert, J.B., Pyrcz, M.J., 2014, Conditioning 3D Object Based Models to a Large Number of Wells: A Channel Example: Mathematics of Planet Earth Peer Reviewed Proceedings, 575-579
  27. Sprunt, E., Howes, S. and Pyrcz, M.J., 2014, Talent & Technology — Impact of the Big Crew Change on Employee Retention, Journal of Petroleum Technology: V. 66,  No. 3,
  28. Pyrcz, M.J., White, C.D., 2015, Uncertainty in Reservoir Modeling: Interpretation 3 (2), SQ7-SQ19
  29. Pyrcz, M.J., Sech, R., Covault, J. A., Willis, B.J., Sylverster, Z. and Sun, T., 2015, Stratigraphic Rule-based Reservoir Modeling, Bulletin of Canadian Petroleum Geologists.
  30. Pyrcz, M.J., 2016, Mareitoz and Caers: Multiple-Point Geostatistics: Stochastic Modeling with Training Images, Invited Book Review, Mathematical Geosciences.
  31. Kaplan, R., Pyrcz, M.J., Strebelle, S., in prep, Insights into Connectivity of Multiple Point and Process-mimicking Geostatistical Reservoir Models: 2016 Geostatistical Congress Peer Reviewed Proceedings, Valencia, Spain.
  32. Pyrcz, M.J., Janele, P., Weaver, D., Strebelle, S., in prep, New Uncertainty Modeling Methods for Unconventionals: 2016 Geostatistical Congress Peer Reviewed Proceedings, Valencia, Spain.
  33. Strebelle, S., Pyrcz, M.J., Vitel, S., in prep, Rapid Geological Model Updating: 2016 Geostatistical Congress Peer Reviewed Proceedings, Valencia, Spain.

Contact

Oy Leuangthong

Ph.D. Graduate (2003)

Leuangthong, O., 2003, Stepwise Conditional Transformation for Multivariate Geostatistical Simulation, Ph.D. Thesis, University of Alberta, Edmonton, Canada

Olena Babak

Ph.D. Graduate (2008)

Dr. Olena Babak, P.Eng., works as a Sr. Geostatistician / Geomodeler with Cenovus Energy Inc. (Geoscience Center of Excellence), where she carries-out and supervises quantitative geological evaluations and geostatistical analysis, as well as conducts research into improvement of methodologies and tools for better modeling of heterogeneity and uncertainty in petroleum reservoirs and mineral deposits. She is a recipient of 2015 & 2014 Canadian Society for Petroleum Geologists (CSPG) Service Awards and a winner of 2011 Andrei Borisovich Vistelius Research Award from the International Association for Mathematical Geosciences.

Dr. Babak holds an M.Sc. degree in Statistics from the Ivan Franko National University of Lviv (2004), an M.Sc. in Industrial Engineering from the University of Iceland (2005) and a Ph.D. degree in Geostatistics from the University of Alberta (2008). From Sept. 2008 to Aug. 2013, Olena was working as a Geostatistics Specialist & Geomodeler for Total E&P Canada Ltd. Prior to joining Total, she was a geostats consultant (March 2007 to Aug. 2008) for Surmont project that is jointly operated by ConocoPhillips and Total.

Dr. Babak has published 24 journal papers and more than 30 conference articles and technical papers/reports. She is a member of Geomodeling Committee at CSPG. Olena was awarded more than 10 prestigious scholarships and awards, including Alberta Ingenuity Scholarship, Andrew Stewart Memorial Graduate Prize (best doctoral research), and 2010-2013 CSPG Volunteer Awards.

olenababak

Publications

Refereed Journal Publications:

  1. Babak, O. and Resnick, J. (2016) A Workflow for Vertical and Horizontal Near-Wellbore Permeability Modeling in the McMurray Formation. Petroleum Geoscience (accepted), doi:10.1144/petgeo2015-063.
  2. Babak, O., and Resnick, J. (2016) On the Use of Particle Size Distribution Data for Permeability Modeling. SPE Reservoir Evaluation & Engineering, 19(01): 163-180.
  3. Garner, D., Babak, O. and Deutsch, C.V. (2015) Introduction to the Special Edition from the 2014 Gussow Conference on Advances in Applied Geomodeling. Bulletin of Canadian Petroleum Geology, 63(4): 275-276.
  4. Babak, O. (2015) A Discussion of the Importance of Particle Size Distribution Data for Characterizing Athabasca Oil Sands. Bulletin of Canadian Petroleum Geology, 63(4): 318-332.
  5. Lajevardi, S., Babak, O., and Deutsch, C.V. (2015) Estimating Barrier Shale Extent and Optimizing Well Placement in Heavy Oil Reservoirs. Petroleum Geoscience, 21: 332-332.
  6. Babak, P., Henriquel, P., Insalaco, E., and Babak, O. (2015) Multivariate Data Cleaning and Re-Classification of Particle Size Distribution Data for Joslyn Lease. CIM Journal, 6(2): 75-90.
  7. Babak, O., Bergey, P., and Deutsch, C.V. (2014) Trend Modeling for Surmont Lease. Journal of Petroleum Science and Engineering, 119: 85-103.
  8. Babak, O. (2014) Inverse Distance Interpolation for Facies Modeling. Stochastic Environmental Research & Risk Assessment, 28: 1373-1382.
  9. Manchuk, J.G., Babak, O., and Deutsch, C.V. (2014) Numerical Modeling of Mining Selectivity for Oil Sands. CIM Journal, 5(3): 1-12.
  10. Manchuk, J.G., Babak, O., and Deutsch, C.V. (2013) Geostatistical Modeling of Particle Size Distributions in the McMurray Formation. CIM Journal, 4(2): 1-16.
  11. Babak, O., Cuba,, and Leuangthong, O. (2013) On Direct Upscaling of Semivariograms and Cross Semivariograms for Scale Consistent Geomodeling. SME Transactions 334: 544-552.
  12. Babak, O., Manchuk, J.G., and Deutsch, C.V. (2013) Accounting for Non-Exclusivity in Sequential Indicator Simulation of Categorical Variables. Computers & Geosciences, 51: 118-128.
  13. Babak, O., Machuca M.D.F., and Deutsch, C.V. (2010) An Approximate Method for Joint Simulation of Multiple Spatial Variables. Stochastic Environmental Research & Risk Assessment, 24: 327-336.
  14. Babak, O., and Deutsch, C.V. (2009) New Kriging Method for Estimation from Strings of Data in a Finite Domain. SME Transactions, 326: 10-15.
  15. Babak, O., and Deutsch, C.V. (2009) Improved Spatial Modeling by Merging Multiple Secondary Data for Intrinsic Collocated Cokriging. Journal of Petroleum Science and Engineering, 69: 93-99.
  16. Babak, O., and Deutsch, C.V. (2009) Collocated Cokriging based on Merged Secondary Attributes. Mathematical Geosciences, 41: 921-926.
  17. Babak, O., and Deutsch, C.V. (2009) Statistical Approach to Inverse Distance Interpolation. Stochastic Environmental Research & Risk Assessment, 23: 543-553.
  1. Babak, , and Deutsch, C.V. (2009) An Intrinsic Model of Coregionalization that Solves Variance Inflation in Collocated Cokriging. Computers & Geosciences, 35: 603-614.
  2. Babak, O., and Deutsch, C.V. (2009) Accounting for Parameter Uncertainty in Reservoir Uncertainty Assessment: the Conditional Finite-Domain (CFD) Approach. Natural Resources Research, 18: 7-17.
  3. Babak, O., and Deutsch, C.V. (2008) Uncertainty as the Overlap of Alternate Conditional Distributions. Computational Geosciences, 12(4): 503-512.
  4. Babak, O., and Deutsch, C.V. (2008) Reserves Uncertainty Calculation accounting for Parameter Uncertainty. Journal of Canadian Petroleum Technology, August 2008: 41-49.
  5. Machuca M.D.F., Babak, O., and Deutsch, C.V. (2008) Flexible Change of Support Model Suitable for a Wide Range of Mineralization Styles. Mining Engineering, February 2008: 63-72.
  6. Babak, O., Hrafnkelsson, B. and Palsson, O.P. (2007) Estimation of Length Distribution of Marine Populations in the Gaussian-Multinomial Model Setting using Method of Moments. Journal of Applied Statistics, 34(8): 985-991.
  7. Domans’kyy , P.P. and Soroka, I. (2002) Optimization of Form of Highly Supported Pivots in Problems of their Stability in Two Measures. Mat. Metody Fiz.-Mekh. Polya. (Mathematical Methods and Physical-Mechanical Fields), 45(3): 148-154.

Contact

Patrick Donovan

M.Sc. Graduate (2015)

Donovan, P.N., 2015, Resource Estimation with Multiple Data Types, M.Sc. Thesis, University of Alberta, Edmonton, Canada

Growing up in St. John’s, Newfoundland I completed my undergraduate degree at Memorial University obtaining BSc. in Earth Sciences. I have background as a professional geologist in greenfield/brownfield exploration, grade control, and resources estimation. I have experience in several different locations within Canada moving between uranium exploration, nickel-copper production & supervision, and gold production. In 2013 I decided to expand my knowledge base by joining the CCG and beginning my MSc. in Applied Geostatistics. I am an active member of the research group in the latter portion of degree completion.

CCG Patrick Donovan

Research

My research includes directions in application of unequally sampled data for prediction. Topics consist of:

  • Bias and error and removal.
  • Effective drill spacing definition and optimization using unequally sampled data.
  • Further directions in prediction with multiple data types.

Contact

Paula Larrondo

M.Sc. Graduate (2004)

Larrondo, P., 2004, Non Stationary Boundary Modeling in Geostatistics, M.Sc. Thesis, University of Alberta, Edmonton, Canada

Background Before Joining the CGG

  • M.Sc., Geology, Universidad de Chile, 2002
  • Geologist, Universidad de Chile, 1995

Occupations Since Leaving the CGG

  • Director of the Geology School, Universidad Mayor, Chile, 2013 to present
  • Independent resource modelling consultant, 2011 to present
  • AMEC, Principal Geostatistician, 2010 to 2011
  • Golder Associates, Senior Geostatistician, 2005 to 2009
paulalarrondo

Research

  • Undergraduate Education for Geoscience
  • Risk Modelling
  • Geometallurgy

Contact

Ryan Barnett

Ph.D. Graduate (2015)

Barnett, R, 2015, Managing Complex Multivariate Relations in the Presence of Incomplete Spatial Data, Ph.D. Thesis, University of Alberta, Edmonton, Canada

Ryan  completed his Ph.D. in 2015 with a thesis titled Managing Complex Multivariate Relations in the Presence of Incomplete Spatial Data. Before joining the CCG, Ryan graduated with a B.Sc. in geology from the University of Calgary. He also worked as a field geologist and geomodeler in the Athabasca oil sands.

Capture

Current Occupation

Ryan is a research associate with the Centre for Computational Geostatistics, while also conducting geostatistical consulting in industry.

Research

In his past role as a CCG student and ongoing role as a CCG research associate, Ryan’s research includes:

  • Multivariate geostatistical modeling
  • Multivariate decorrelation and Gaussian transformations
  • Multivariate data imputation
  • Multivariate data analysis
  • Data Spacing and Uncertainty

Publications

Peer-review Journal

  1. Barnett, R. M., Manchuk, J.G. and Deutsch, C. V., 2015. Projection Pursuit Multivariate Transformation. Mathematical Geosciences, 46, 337-359.
  2. Barnett, R. M. and Deutsch, C. V., 2014. Multivariate imputation of unequally sampled geological variables. Mathematical Geosciences, 47, 791-817.

Peer-review Conference

  1. Barnett, R. M. and Deutsch, C. V., 2012. Practical implementation of non-linear transforms for modeling geometallurgical variables. In Abrahamsen, P., Hauge, R., and Kolbjornsen, O., editors, Geostatistics Oslo 2012, pages 409{422. Springer, Netherlands.

CCG Guidebook Series

  1. Barnett, R.M., 2011. Tools for Multivariate Geostatistical Modeling, CCG Guidebook Series, Vol.14, University of Alberta, 107p.
  2. Barnett, R.M. and Neufeld, C.T., 2012. Basic Scripting Methods, CCG Guidebook Series, Vol.16, University of Alberta, 49p.
  3. Barnett, R.M. and Deutsch, C.V., 2015. Guide to Multivariate Modeling with the PPMT, CCG Guidebook Series, Vol.20, University of Alberta, 107p.

CCG Report

  1. Barnett, R.M., 2011. Conditional standardization: a multivariate transformation for the removal of non-linear and heteroscedastic features, CCG Annual Report 13, paper 310.
  2. Barnett, R.M. and Deutsch, C.V., 2012. Multivariate Standard Normal Transform: Advances and Case Studies, CCG Annual Report 14, paper 102.
  3. Barnett, R.M. and Deutsch, C.V., 2012. Non-parametric Gibbs Sampler with kernel based conditional distributions, CCG Annual Report 14, paper 102.
  4. Barnett, R.M., Manchuk, J.G., and Deutsch, C.V., 2012. Projection Pursuit Multivariate Transform, CCG Annual Report 14, paper 103.
  5. Barnett, R.M. and Deutsch, C.V., 2012. Missing data replacement in a multiGaussian context, CCG Annual Report 14, paper 112.
  6. Barnett, R.M. and Deutsch, C.V., 2012. Missing data replacement in a complex multivariate context, CCG Annual Report 14, paper 113.
  7. Barnett, R.M. and Deutsch, C.V., 2013. Imputation of geologic data, CCG Annual Report 15, paper 102.
  8. Barnett, R.M., Manchuk, J.G, and Deutsch, C.V., 2013. Advances in the Projection Pursuit Multivariate Transform, CCG Annual Report 15, paper 106.
  9. Barnett, R.M. and Deutsch, C.V., 2013. Why the log in logratios? CCG Annual Report 15, paper 108.
  10. Barnett, R.M. and Deutsch, C.V., 2013. Checking the multivariate reproduction of geostatistical models, CCG Annual Report 15, paper 125.
  11. Barnett, R.M. and Deutsch, C.V., 2013. Alternative to Bayesian Updating/P-field Mapping, CCG Annual Report 15, paper 203.
  12. Barnett, R.M. and Deutsch, C.V., 2013. Optimized long term well planning, CCG Annual Report 15, paper 303.
  13. Barnett, R.M. and Deutsch, C.V., 2013. Tutorial and tools for ACE regression and transformation, CCG Annual Report 15, paper 401.
  14. Barnett, R.M. and Deutsch, C.V., 2013. Assessing the uncertainty and value of ACE transformations, CCG Annual Report 15, paper 402.
  15. Barnett, R.M. and Deutsch, C.V., 2014. Multivariate Transformations with Exhaustive Secondary, CCG Annual Report 16, paper 103.
  16. Barnett, R.M. and Deutsch, C.V., 2014. PPMT Back-transformations, CCG Annual Report 16, paper 104.
  17. Barnett, R.M., Deutsch, J.L. and Deutsch, C.V., 2014. Practical Workflows for Geostatistical Modeling with Mean Uncertainty, CCG Annual Report 16, paper 113.
  18. Barnett, R.M. and Deutsch, C.V., 2014. A Compressed Binary Format for Large Geostatistical Models, CCG Annual Report 16, paper 413.
  19. Barnett, R.M. and Deutsch, C.V., 2015. Linear Rotations: Options for Decorrelation and Analysis, CCG Annual Report 17, paper 107.
  20. Deutsch, J.L., Barnett, R.M. and Deutsch, C.V. 2015, Latest Kriging Program, CCG Annual Report 17, paper 402.
  21. Barnett, R.M., Deutsch, J.L., and Deutsch, C.V., 2015. Summary of Some Useful Software and Tools, CCG Annual Report 17, paper 403.
  22. Barnett, R.M., Deutsch, J.L., and Deutsch, C.V., 2015. Conventional Clustering Algorithms and a Program for their Application, CCG Annual Report 17, paper 404.

Contact

Sahyun Hong

Ph.D. Graduate (2010)

Hong, S., 2010, Multivariate Analysis of Diverse Data for Improved Geostatistical Reservoir Modeling, Ph.D. Thesis, University of Alberta, Edmonton, Canada

Dr. Hong is a geologist and geomodeler, working for ConocoPhillips in Houston TX.

Contact

Saina Lajevardi

Ph.D. Graduate (2015)

Lajevardi, S., 2015, Improved Probabilistic Representation of Facies through Developments in Geostatistical Practice, Ph.D. Thesis, University of Alberta, Edmonton, Canada

Saina Lajevardi has completed her PhD under supervision of Clayton V. Deutsch, in September, 2015. She is currently involved with the research studies at the CCG. She holds an M.Sc. degree in Electrical and Computer Engineering (Communications) from the University of Alberta (2011) and a B.Sc. in Electrical Engineering from the Eastern Mediterranean University (2008).

CCG Saina Lajevardi

 Research

  • Model post-processing
  • Ranking (mutli-scale ranking)
  • Model Re-gridding/Downscaling

Publications

Peer reviewed papers:

  1. Lajevardi, S., Babak, O., and Deutsch, C. V. (2015). Estimating barrier shale extent and optimizing well placement in heavy oil reservoirs. Petroleum Geoscience: 22(4):322-332.
  2. Lajevardi, S., and Deutsch, C. V. (2015). Stochastic Regridding of Geological Models for Flow Simulation. Bulletin of Canadian Petroleum Geology: 63(4):225–243.
  3. Lajevardi, S. and Deutsch, C. V. (2016). A Measure of Facies Mixing in Data Upscaling to Account for Information Loss in Estimation of Petrophysical Properties. Petroleum Geoscience: 22(3):190-201.

Conferences:

  1. Lajevardi, S., and Deutsch, C. V. (Sep, 2015). Lateral Continuity of Stochastic Shales. EAGE event: Petroleum Geostatistics 2015, Biarritz, France (oral presentation)

Contact

Steven Lyster

Ph.D. Graduate (2009)

Lyster, S., 2009, Simulation of Geologic Phenomena Using Multiple-Point Statistics in a Gibbs Sampler Algorithm, Ph.D. Thesis, University of Alberta, Edmonton, Canada

Contact

Tolonbek Borisovich Karpekov

M.Sc. Graduate (2016)

Tolonbek graduated with a BSc in Mining Engineering from the Moscow State Mining University, Moscow, Russia. He also studied Natural Resources Management at the North Dakota State University, Fargo, USA. Prior to joining the CCG, Tolonbek worked in different positions, primarily in health & safety and environmental protection divisions in mining companies, as well as for the Government of the Kyrgyz Republic. Tolonbek is currently pursuing his MSc in Geostatistics at the University of Alberta.

Tolonnek

Research

  • Mining mineral resources uncertainty estimation

Contact

Weishan Ren

Ph.D. Graduate (2007)

Ren, W., 2007, Exact Downscaling in Reservoir Modeling, Ph.D. Thesis, University of Alberta, Edmonton, Canada

Contact

Xingquan “Kevin” Zhang

M.Sc. Graduate (2007)

Zhang, L., 2005, Production Data Integration in Geostatistical Reservoir Modeling, M.Sc. Thesis, University of Alberta, Edmonton, Canada

Contact

Yevgeniy Zagayevskiy

Ph.D. Graduate (2015)

Zagayevskiy, Y., 2015, Multivariate Geostatistical Grid-Free Simulation of Natural Phenomena, Ph.D. Thesis, University of Alberta, Edmonton, Canada

Zagayevskiy, Y., 2012, Constraining 3D Petroleum Reservoir Models to Petrophysical Data, Local Temperature Observations, and Gridded Seismic Attributes with the Ensemble Kalman Filter (EnKF), M.Sc. Thesis, University of Alberta, Edmonton, Canada

Yevgeniy Zagayevskiy is a geostatistician at research and development department in Landmark division of Halliburton, Abingdon, UK. His main professional interests are related to the geomodeling of petroleum reservoirs and assessment of the associated uncertainty. In June 2015, he graduated from the University of Alberta with Ph.D. degree in mining engineering focusing on the geostatistical applications to solving engineering problems. During his course of studies, Yevgeniy underwent two summer internships in the position of a geomodeler for Husky Energy in 2011 and for Statoil in 2012, both Calgary. He was also a geomodeling consultant between 2011 and 2012 for Surmont project that is jointly operated by ConocoPhillips and Total.

yevgeniy_zagayevskiy

Research

  • Geostatistics
  • Geomodeling
  • Petroleum reservoir characterization

Background Before Joining the CCG

  • BSc in Petroleum Engineering with honors (2005-2009), Kazakh-British Technical University, Almaty, Kazakhstan
  • 2012 summer intern as a geomodeler at Statoil, Calgary, Canada
  • 2011-2012 part-time geomodeling consultant at Clayton Deutsch Consultants Ltd, Edmonton, Canada
  • 2011 summer intern as a geomodeler at Husky Energy, Calgary, Canada
  • 2009 summer intern as a petroleum reservoir engineer at Buzachi Operating Ltd, Aktau, Kazakhstan
  • 2008 summer intern as a field operator at China National Logging Corporation, Kumkol oil field, Kazakhstan
  • 2007 summer intern as a petroleum engineer at Transneft, Omsk, Russia

Occupations Since Leaving the CCG

Geomodeler at a research and development group of Landmark (Halliburton), Abingdon, England, UK

Publications

Peer reviewed papers:

  1. (Under review) Zagayevskiy, Y and Deutsch, CV. 2016. Multivariate Geostatistical Grid-Free Simulation of natural Phenomena. Mathematical Geosciences
  2. (Online) Zagayevskiy, Y and Deutsch, CV. 2016. Application of Grid-Free Geostatistical Simulation to a Large Oil Sands Reservoir. SPE Reservoir Evaluation & Engineering-Formation Evaluation

(https://www.onepetro.org/journal-paper/SPE-180917-PA)

  1. (Accepted) Zagayevskiy, Y and Deutsch, CV. 2016. Petroleum Reservoir Characterization with Grid-Free Simulation: Hekla Case Study. Petroleum Geoscience
  2. (Online) Zagayevskiy, Y and Deutsch, CV. 2015. Multivariate Grid-Free Geostatistical Simulation with point or Block Scale Secondary Data. Stochastic Environmental Research and Risk Assessment, published online

(http://rd.springer.com/article/10.1007%2Fs00477-015-1154-x)

  1. Zagayevskiy, Y and Deutsch, CV. 2015. Assimilation of Time-Lapse Temperature Observations and 4D-Seismic Data With the EnKF in SAGD Petroleum Reservoirs. Journal of Canadian Petroleum Technology, 54(3), 164 – 182

(https://www.onepetro.org/journal-paper/SPE-174547-PA)

  1. Zagayevskiy, Y and Deutsch, CV. 2014. A Methodology for Sensitivity Analysis Based on Regression: Applications to Handle Uncertainty in Natural Resources Characterization. Natural Resources Research, 24(3), 239 – 274

(http://link.springer.com/article/10.1007/s11053-014-9241-0?sa_campaign=email/event/articleAuthor/onlineFirst)

  1. Zagayevskiy, Y and Deutsch, CV. 2013. Impact Map for Assessment of New Delineation Well Locations. Journal of Canadian Petroleum Technology, 52(6), 441 – 462

(https://www.onepetro.org/journal-paper/SPE-168222-PA)

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