Research

Our work

List of all publications

Journal Articles

  • [1]
    Geostatistical simulation of rock physical and geochemical properties with spatial filtering and its application to predictive geological mapping.
    Adeli, A. and Emery, X.
    In Journal of Geochemical Exploration, vol. 220, 2021.
  • [2]
    Algorithm 1013: An R Implementation of a Continuous Spectral Algorithm for Simulating Vector Gaussian Random Fields in Euclidean Spaces.
    Arroyo, D. and Emery, X.
    In ACM Transactions on Mathematical Software, vol. 47, no. 1, 2021.
  • [3]
    Assessing the impact of geologic contact dilution in ore/waste classification in the gol-gohar iron ore mine, Southeastern Iran.
    Masoumi, I., Kamali, G., Asghari, O. and Emery, X.
    In Minerals, vol. 10, no. 4, 2020.
  • [4]
    Geological Facies Recovery Based on Weighted $\ell _1$ - Regularization.
    Calderon, H., Santibañez, F., Silva, J.F., Ortiz, J.M. and Egaña, A.
    In Mathematical Geosciences, vol. 52, no. 5, pp. 593–617, 2020.
  • [5]
    A robust stochastic approach to mineral hyperspectral analysis for geometallurgy.
    Egaña, Á.F., Santibáñez-Leal, F.A., Vidal, C., Díaz, G., Liberman, S. and Ehrenfeld, A.
    In Minerals, vol. 10, no. 12, pp. 1–32, 2020.
  • [6]
    Simulating space-time random fields with nonseparable Gneiting-type covariance functions.
    Allard, D., Emery, X., Lacaux, C. and Lantuéjoul, C.
    In Statistics and Computing, vol. 30, no. 5, pp. 1479–1495, 2020.
  • [7]
    Geostatistics in the presence of geological boundaries: Exploratory tools for contact analysis.
    Maleki, M. and Emery, X.
    In Ore Geology Reviews, vol. 120, 2020.
  • [8]
    A spectral algorithm to simulate nonstationary random fields on spheres and multifractal star-shaped random sets.
    Emery, X. and Alegría, A.
    In Stochastic Environmental Research and Risk Assessment, vol. 34, no. 12, pp. 2301–2311, 2020.
  • [9]
    Stein hypothesis and screening effect for covariances with compact support.
    Porcu, E., Zastavnyi, V., Bevilacqua, M. and Emery, X.
    In Electronic Journal of Statistics, vol. 14, no. 2, pp. 2510–2528, 2020.
  • [10]
    Stochastic open-pit mine production scheduling: A case study of an iron deposit.
    Maleki, M., Jélvez, E., Emery, X. and Morales, N.
    In Minerals, vol. 10, no. 7, pp. 1–19, 2020.
  • [11]
    Operational mine planning in block cave mining: a simulation-optimisation approach.
    Paravarzar, S., Askari-Nasab, H., Pourrahimian, Y. and Emery, X.
    In International Journal of Mining, Reclamation and Environment, 2020.
  • [12]
    Variogram-Based Descriptors for Comparison and Classification of Rock Texture Images.
    Díaz, G.F., Ortiz, J.M., Silva, J.F., Lobos, R.A. and Egaña, Á.F.
    In Mathematical Geosciences, vol. 52, no. 4, pp. 451–476, 2020.
  • [13]
    Iterative algorithms for non-conditional and conditional simulation of Gaussian random vectors.
    Arroyo, D. and Emery, X.
    In Stochastic Environmental Research and Risk Assessment, vol. 34, no. 10, pp. 1523–1541, 2020.
  • [14]
    Regionalized Classification of Geochemical Data with Filtering of Measurement Noises for Predictive Lithological Mapping.
    Guartán, J.A. and Emery, X.
    In Natural Resources Research, 2020.
  • [15]
    The turning arcs: a computationally efficient algorithm to simulate isotropic vector-valued Gaussian random fields on the d-sphere.
    Alegría, A., Emery, X. and Lantuéjoul, C.
    In Statistics and Computing, vol. 30, no. 5, pp. 1403–1418, 2020.
  • [16]
    A semiparametric class of axially symmetric random fields on the sphere.
    Emery, X., Porcu, E. and Bissiri, P.G.
    In Stochastic Environmental Research and Risk Assessment, vol. 33, no. 10, pp. 1863–1874, 2019.
  • [17]
    Nonparametric Geostatistical Simulation of Subsurface Facies: Tools for Validating the Reproduction of, and Uncertainty in, Facies Geometry.
    Madani, N., Maleki, M. and Emery, X.
    In Natural Resources Research, vol. 28, no. 3, pp. 1163–1182, 2019.
  • [18]
    Simulating isotropic vector-valued Gaussian random fields on the sphere through finite harmonics approximations.
    Emery, X. and Porcu, E.
    In Stochastic Environmental Research and Risk Assessment, vol. 33, no. 8-9, pp. 1659–1667, 2019.
  • [19]
    A geostatistical approach to estimating the parameters of a 3D Cox-Boolean discrete fracture network from 1D and 2D sampling observations.
    Hekmatnejad, A., Emery, X. and Elmo, D.
    In International Journal of Rock Mechanics and Mining Sciences, vol. 113, pp. 183–190, 2019.
  • [20]
    A turning bands method for simulating isotropic Gaussian random fields on the sphere.
    Emery, X., Furrer, R. and Porcu, E.
    In Statistics and Probability Letters, vol. 144, pp. 9–15, 2019.
  • [21]
    A comparison of search strategies to design the cokriging neighborhood for predicting coregionalized variables.
    Madani, N. and Emery, X.
    In Stochastic Environmental Research and Risk Assessment, vol. 33, no. 1, pp. 183–199, 2019.
  • [22]
    Change of support using non-additive variables with Gibbs Sampler: Application to metallurgical recovery of sulphide ores.
    Garrido, M., Ortiz, J.M., Villaseca, F., Kracht, W., Townley, B. and Miranda, R.
    In Computers & Geosciences, vol. 122, pp. 68–76, 2019.
  • [23]
    Geostatistics in the presence of geological boundaries: Application to mineral resources modeling.
    Emery, X. and Maleki, M.
    In Ore Geology Reviews, 2019.
  • [24]
    5D geostatistics for directional variables: Application in geotechnics to the simulation of the linear discontinuity frequency.
    Sánchez, L.K., Emery, X. and Séguret, S.A.
    In Computers and Geosciences, vol. 133, 2019.
  • [25]
    Comparing linear and non-linear kriging for grade prediction and ore/waste classification in mineral deposits.
    Hekmatnejad, A., Emery, X. and Alipour-Shahsavari, M.
    In International Journal of Mining, Reclamation and Environment, vol. 33, no. 4, pp. 247–264, 2019.
  • [26]
    Robust estimation of the fracture diameter distribution from the true trace length distribution in the Poisson-disc discrete fracture network model.
    Hekmatnejad, A., Emery, X. and Vallejos, J.A.
    In Computers and Geotechnics, vol. 95, pp. 137–146, 2018.
  • [27]
    On a continuous spectral algorithm for simulating non-stationary Gaussian random fields.
    Emery, X. and Arroyo, D.
    In Stochastic Environmental Research and Risk Assessment, 2018.
  • [28]
    Simulation of intrinsic random fields of order k with a continuous spectral algorithm.
    Arroyo, D. and Emery, X.
    In Stochastic Environmental Research and Risk Assessment, vol. 32, no. 11, pp. 3245–3255, 2018.
  • [29]
    Admissible nested covariance models over spheres cross time.
    Peron, A., Porcu, E. and Emery, X.
    In Stochastic Environmental Research and Risk Assessment, vol. 32, no. 11, pp. 3053–3066, 2018.
  • [30]
    Modelling geotechnical heterogeneities using geostatistical simulation and finite differences analysis.
    Pinheiro, M., Emery, X., Miranda, T., Lamas, L. and Espada, M.
    In Minerals, vol. 8, no. 2, 2018.
  • [31]
    Geological modelling and validation of geological interpretations via simulation and classification of quantitative covariates.
    Adeli, A., Emery, X. and Dowd, P.
    In Minerals, vol. 8, no. 1, 2018.
  • [32]
    A path-level exact parallelization strategy for sequential simulation.
    Peredo, O.F., Baeza, D., Ortiz, J.M. and Herrero, J.R.
    In Computers & Geosciences, 2018.
  • [33]
    Recovering Latent Signals from a Mixture of Measurements Using a Gaussian Process Prior.
    Tobar, F., Rios, G. and Valdivia, T.
    In IEEE Signal Processing Letters, vol. 24, pp. 231–235, 2017.
  • [34]
    A comparison between ACO and Dijkstra algorithms for optimal ore concentrate pipeline routing.
    Baeza, D., Ihle, C.F. and Ortiz, J.M.
    In Journal of Cleaner Production, vol. 144, pp. 149–160, 2017.
  • [35]
    Textural image classification of foams based on variographic analysis.
    Mesa, D., Kracht, W. and Diaz, G.
    In Minerals Engineering, vol. 98, pp. 52–59, 2016.
  • [36]
    Joint Simulation of Grade and Rock Type in a Stratabound Copper Deposit.
    Maleki, M. and Emery, X.
    In Mathematical Geosciences, vol. 47, no. 4, pp. 471–495, 2015.
  • [37]
    Application of joint conditional simulation to uncertainty quantification and resource classification.
    Tajvidi, E., Monjezi, M., Asghari, O., Emery, X. and Foroughi, S.
    In Arabian Journal of Geosciences, vol. 8, no. 1, pp. 455–463, 2015.
  • [38]
    Comparing sequential Gaussian and turning bands algorithms for cosimulating grades in multi-element deposits.
    Paravarzar, S., Emery, X. and Madani, N.
    In Comptes Rendus Geoscience, vol. 347, no. 2, pp. 84–93, 2015.
  • [39]
    Reconstruction of channelized geological facies based on RIPless compressed sensing.
    Calderon, H., Silva, J.F., Ortiz, J.M. and Egana, A.
    In Computers & Geosciences, vol. 77, pp. 55–65, 2015.
  • [40]
    Stochastic rock type modeling in a porphyry copper deposit and its application to copper grade evaluation.
    Talebi, H., Asghari, O. and Emery, X.
    In Journal of Geochemical Exploration, vol. 157, pp. 162–168, 2015.
  • [41]
    Fast update of conditional simulation ensembles.
    Chevalier, C., Emery, X. and Ginsbourger, D.
    In Mathematical Geosciences, pp. 1–19, 2014.
  • [42]
    Simulation of the lately injected dykes in an Iranian porphyry copper deposit using the plurigaussian model.
    Talebi, H., Asghari, O. and Emery, X.
    In Arabian Journal of Geosciences, vol. 7, no. 7, pp. 2771–2780, 2014.
  • [43]
    Capping and kriging grades with long-tailed distributions.
    Maleki, M., Madani, N. and Emery, X.
    In Journal of the Southern African Institute of Mining and Metallurgy, vol. 114, no. 3, pp. 255–263, 2014.
  • [44]
    Simulating large Gaussian random vectors subject to inequality constraints by Gibbs sampling.
    Emery, X., Arroyo, D. and Pelaez, M.
    In Mathematical Geosciences, vol. 46, no. 3, pp. 265–283, 2014.
  • [45]
    Verifying the high-order consistency of training images with data for multiple-point geostatistics.
    Perez, C., Mariethoz, G. and Ortiz, J.M.
    In Computers & Geosciences, vol. 70, pp. 190–205, 2014.
  • [46]
    Tuning and Hybrid Parallelization of a Genetic-based Multi-Point Statistics Simulation Code.
    Peredo, O., Ortiz, J.M., Herrero, J.R. and Samaniego, C.
    In Parallel Computing, vol. 40, no. 5, pp. 144–158, 2014.
  • [47]
    Simulation of Intrinsic Random Fields of Order k with Gaussian Generalized Increments by Gibbs Sampling.
    Arroyo, D. and Emery, X.
    In Mathematical Geosciences, pp. 1–20, 2014.
  • [48]
    Multiple-Point Geostatistical Simulation of Dykes: Application at Sungun Porphyry Copper System, Iran.
    Rezaee, H., Asghari, O., Koneshloo, M. and Ortiz, J.M.
    In Stochastic Environmental Research and Risk Assessment, pp. 1–15, 2014.
  • [49]
    Can a training image be a substitute for a random field model?
    Emery, X. and Lantuejoul, C.
    In Mathematical Geosciences, vol. 46, no. 2, pp. 133–147, 2014.
  • [50]
    Designing and Advanced RC Drilling Grid for Short-Term Planning in Open Pit Mines: Three Case Studies.
    Ortiz, J.M. and Magri, E.J.
    In The Journal of the Southern African Institute of Mining and Metallurgy, vol. 114, no. 8, pp. 631–639, 2014.
  • [51]
    Geostatistics applied to cross-well reflection seismic for imaging carbonate aquifers.
    Parra, J. and Emery, X.
    In Journal of Applied Geophysics, vol. 92, pp. 68–75, 2013.
  • [52]
    A stochastic approach for measuring bubble size distribution via image analysis.
    Kracht, W., Emery, X. and Paredes, C.
    In International Journal of Mineral Processing, vol. 121, pp. 6–11, 2013.
  • [53]
    Application of plurigaussian simulation to delineate the layout of alteration domains in Sungun copper deposit.
    Talebi, H., Asghari, O. and Emery, X.
    In Open Geosciences, vol. 5, no. 4, pp. 514–522, 2013.
  • [54]
    Integration of crosswell seismic data for simulating porosity in a heterogeneous carbonate aquifer.
    Emery, X. and Parra, J.
    In Journal of Applied Geophysics, vol. 98, pp. 254–264, 2013.
  • [55]
    Simulation of mineral grades and classification of mineral resources by using hard and soft conditioning data: application to Sungun porphyry copper deposit.
    Tehrani, M., Asghari, O. and Emery, X.
    In Arabian Journal of Geosciences, vol. 6, no. 10, pp. 3773–3781, 2013.
  • [56]
    Parallel-distributed model deformation in the fingertips for stable grasping and object manipulation.
    Garcia-Rodriguez, R. and Diaz-Rodriguez, G.
    In Mathematical Problems in Engineering, vol. 2012, 2012.
  • [57]
    Detecting and Quantifying Sources of Non-Stationarity via Experimental Semivariogram Modeling.
    Cuba, M.A., Leuangthong, O. and Ortiz, J.M.
    In Stochastic Environmental Research and Risk Assessment, vol. 26, no. 2, pp. 247–260, 2012.
  • [58]
    Transferring Sampling Errors into Geostatistical Modeling.
    Cuba, M.A., Leuangthong, O. and Ortiz, J.M.
    In Journal of the Southern African Institute of Mining and Metallurgy, vol. 112, no. 11, pp. 971–983, 2012.
  • [59]
    Cokriging random fields with means related by known linear combinations.
    Emery, X.
    In Computers & Geosciences, vol. 38, no. 1, pp. 136–144, 2012.
  • [60]
    M. Armstrong, A. Galli, H. Beucher, G. Le Loc’h, D. Renard, B. Doligez, R. Eschard, F. Geffroy: Plurigaussian Simulations in Geosciences.
    Emery, X.
    In Mathematical Geosciences, vol. 44, no. 2, pp. 239–240, 2012.
  • [61]
    Enhanced coregionalization analysis for simulating vector Gaussian random fields.
    Emery, X. and Ortiz, J.M.
    In Computers & Geosciences, vol. 42, pp. 126–135, 2012.
  • [62]
    Co-simulating total and soluble copper grades in an oxide ore deposit.
    Emery, X.
    In Mathematical Geosciences, vol. 44, no. 1, pp. 27–46, 2012.
  • [63]
    Reducing the number of orthogonal factors in linear coregionalization modeling.
    Emery, X. and Pelaez, M.
    In Computers & Geosciences, vol. 46, pp. 149–156, 2012.
  • [64]
    Using two-point set statistics to estimate the diameter distribution in Boolean models with circular grains.
    Emery, X., Kracht, W., Egana, A. and Garrido, F.
    In Mathematical Geosciences, vol. 44, no. 7, pp. 805–822, 2012.
  • [65]
    Improving financial returns from mining through geostatistical simulation and the optimized advance drilling grid at El Tesoro Copper Mine.
    Ortiz, J.M., Magri, E.J. and Libano, R.
    In Journal of the Southern African Institute of Mining and Metallurgy, vol. 112, no. 1, pp. 15–22, 2012.
  • [66]
    An enhanced Gibbs sampler algorithm for non-conditional simulation of Gaussian random vectors.
    Arroyo, D., Emery, X. and Pelaez, M.
    In Computers & Geosciences, vol. 46, pp. 138–148, 2012.
  • [67]
    Multivariate resource modelling for assessing uncertainty in mine design and mine planning.
    Montoya, C., Emery, X., Rubio, E. and Wiertz, J.
    In Journal of the Southern African Institute of Mining and Metallurgy, vol. 112, no. 5, pp. 353–363, 2012.
  • [68]
    A Comparison of Random Field Models Beyond Bivariate Distributions.
    Emery, X. and Ortiz, J.M.
    In Mathematical Geosciences, vol. 43, no. 2, pp. 183–202, 2011.
  • [69]
    Parallel implementation of simulated annealing to reproduce multiple-point statistics.
    Peredo, O. and Ortiz, J.M.
    In Computers & Geosciences, vol. 37, no. 8, pp. 1110–1121, 2011.
  • [70]
    Adapting a Texture Synthesis Algorithm for Conditional Multiple Point Geostatistical Simulation.
    Parra, A. and Ortiz, J.M.
    In Stochastic Environmental Research and Risk Assessment, vol. 25, no. 8, pp. 1101–1111, 2011.
  • [71]
    Two approaches to direct block-support conditional co-simulation.
    Emery, X. and Ortiz, J.M.
    In Computers & Geosciences, vol. 37, no. 8, pp. 1015–1025, 2011.
  • [72]
    Local Recoverable Reserves Prediction with Block LU Simulation.
    Boisvert, J., Ortiz, J.M. and Deutsch, C.V.
    In International Journal of Mining and Mineral Engineering, vol. 1, no. 1, pp. 3–21, 2008.
  • [73]
    On the challenge of using sequential indicator simulation for the estimation of recoverable reserves.
    Machuca-Mory, D.F., Ortiz, J.M. and Deutsch, C.V.
    In International Journal of Mining, Reclamation and Environment, vol. 22, no. 4, pp. 285–299, 2008.
  • [74]
    A methodology to construct training images for vein type deposits.
    Boisvert, J.B., Leuangthong, O., Ortiz, J.M. and Deutsch, C.V.
    In Computers & Geosciences, vol. 34, no. 5, pp. 491–502, 2008.
  • [75]
    Geostatistical modeling of rock type domains with spatially varying proportions: Application to a porphyry copper deposit.
    Emery, X., Ortiz, J.M. and Caceres, A.M.
    In Journal of the South African Institute of Mining and Metallurgy, vol. 108, no. 5, pp. 285–292, 2008.
  • [76]
    FITS Files and Regular Grammars: A DMaSS Design Case Study.
    Cooke, A., Egana, A. and Lowry, S.
    In Astronomical Data Analysis Software and Systems XVI, vol. 376, p. 499, 2007.
  • [77]
    Case for geometric criteria in resources and reserves classification, Society for Mining.
    Deutsch, C.V., Leuangthong, O. and Ortiz, J.M.
    In Transactions Society for Mining Metallurgy and Exploration Incorporated, vol. 322, pp. 1–11, 2007.
  • [78]
    Weighted sample variograms as a tool to better assess the spatial variability of soil properties.
    Emery, X. and Ortiz, J.M.
    In Geoderma, vol. 140, no. 1, pp. 81–89, 2007.
  • [79]
    Scaling multiple-point statistics to different univariate proportions.
    Ortiz, J.M., Lyster, S. and Deutsch, C.V.
    In Computers & Geosciences, vol. 33, no. 2, pp. 191–201, 2007.
  • [80]
    Geostatistical Simulation of Optimum Mining Elevations for Nickel Laterite Deposits.
    McLennan, J.A., Ortiz, J.M. and Deutsch, C.V.
    In CIM Magazine, vol. 1, no. 6, 2006.
  • [81]
    Quantifying Uncertainty in Mineral Resources by Use of Classification Schemes and Conditional Simulations.
    Emery, X., Ortiz, J.M. and Rodriguez, J.J.
    In Mathematical Geology, vol. 38, no. 4, pp. 445–464, 2006.
  • [82]
    Geostatistical estimation of mineral resources with soft boundaries: a comparative study.
    Ortiz, J.M. and Emery, X.
    In Journal of the South African Institute of Mining and Metallurgy, vol. 106, no. 8, pp. 577–584, 2006.
  • [83]
    Block size selection and its impact on open pit mine design and planning.
    Jara, R., Couble, A., Emery, X., Magri, E. and Ortiz, J.
    In Journal of the South African Institute of Mining and Metallurgy, vol. 106, no. 3, pp. 205–211, 2006.
  • [84]
    Estimation of mineral resources using grade domains: critical analysis and a suggested methodology.
    Emery, X. and Ortiz, J.M.
    In Journal of the South African Institute of Mining and Metallurgy, vol. 105, no. 4, pp. 247–255, 2005.
  • [85]
    Resource and reserve evaluation in the presence of imprecise data.
    Emery, X., Bertini, J.P. and Ortiz, J.M.
    In CIM Bulletin, vol. 98, no. 1089, p. 2000, 2005.
  • [86]
    Histogram and Variogram Inference in the Multigaussian Model.
    Emery, X. and Ortiz, J.M.
    In Stochastic Environmental Research and Risk Assessment, vol. 19, no. 1, pp. 48–58, 2005.
  • [87]
    Shortcomings of Multiple Indicator Kriging for Assessing Local Distributions.
    Emery, X. and Ortiz, J.M.
    In Applied Earth Science (Transactions of the Institutions of Mining and Metallurgy: Section B), vol. 113, no. 4, pp. 249–259, 2004.
  • [88]
    Indicator Simulation Accounting for Multiple-Point Statistics.
    Ortiz, J.M. and Deutsch, C.V.
    In Mathematical Geology, vol. 36, no. 5, pp. 545–565, 2004.
  • [89]
    Calculation of Uncertainty in the Variogram.
    Ortiz, J. and Deutsch, C.V.
    In Mathematical Geology, vol. 34, no. 2, 2002.

Conference Articles

  • [1]
    Automatic selection of fracture sets using clustering techniques.
    Soto, F., Hekmatnejad, A., Emery, X. and Elmo, D.
    In 2nd International Discrete Fracture Network Engineering Conference, DFNE 20182018.
  • [2]
    Natural Gamma Rays to assist Geo Modelling.
    Farfan, L., Garrido, M. and Mendez, M.
    In International Convention, Trade Show & Investors Exchange PDAC, Toronto, Canada2018.
  • [3]
    Simulation of preparation time of a TBM in the underground mining development considering rock mass variability.
    Garrido, M. and Silva, C.
    In GEOMIN-MINEPLANNING, 5th International Seminar on Geology for the Mining Industry 2017, Santiago, Chile2017.
  • [4]
    Optimization of planning and scheduling of ore body with open pit extraction considering homogeneity in clays as geometallurgical variables.
    Garrido, M., Sepulveda, E. and Navarro, F.
    In GEOMIN-MINEPLANNING, 5th International Seminar on Geology for the Mining Industry 2017, Santiago, Chile2017.
  • [5]
    Restauración 3D de Modelos Geologicos basados en un sistema Masa-Resorte.
    Ojeda, M., Vicencio, A., Baeza, D., Navarro, F. and Arriagada, C.
    In Actas XX Congreso Geologico Argentino, San Miguel de Tucuman, Argentina2017.
  • [6]
    Geometallurgical Variables Characterization Using Hyperspectral Images and Machine Learning Technics.
    Ehrenfeld, A., Egana, A., Guerrero, P., Liberman, S., Hanna, V., Voisin, L. and Adams, M.
    In 38th Application of Computers and Operations Research in the Mineral Industry, pp. 61–66, 2017.
  • [7]
    Rapid Multivariate Resource Assessment.
    Soto, F., Garrido, M., Diaz, G. and Silva, C.
    In GEOMIN-MINEPLANNING, 5th International Seminar on Geology for the Mining Industry 2017, Santiago, Chile2017.
  • [8]
    The impact of geometric variation on the resource estimation quality using an unfolding methodology.
    Vicencio, A., Ojeda, M., Baeza, D. and Navarro, F.
    In Geomin Mineplanning 2017, 5to seminario Internacional de Geologia para la Industria Minera, 5to seminario Internacional de Planificacion Minera, Santiago, Chile2017.
  • [9]
    New human-computer interfaces to capture expert geological knowledge.
    Navarro, F., Diaz, G., Garrido, M., Ortiz, J.M. and Egana, A.
    In MININ 2016 – 6th International Conference on Innovations in Mine Operations2016.
  • [10]
    Incorporation of geological information on unfolding and restoration of veins for ore body evaluation.
    Garrido, M., Silva, C., Becerra, J., Navarro, F. and Townley, B.
    In MININ 2016 – 6th International Conference on Innovations in Mine Operations2016.
  • [11]
    Time Dependence of Shear Wavespeeds in Northern Chile Related to the 2014 Mw8. 3 Pisagua Earthquake.
    Comte, D., Arriaza, R. and Roecker, S.
    In AGU Fall Meeting Abstracts2016.
  • [12]
    Progress towards Data-driven Mine Planning via a Virtual Geometallurgical Laboratory.
    Lopez, A., Barberan, A., Alarcon, M., Vargas, E., Ortiz, J.M., Morales, N., Emery, X., Egana, A., McFarlane, A. and Friedrich, C.
    In GEOMET 2016 - The Third AusIMM International Geometallurgy Conference2016.
  • [13]
    U-Fo: An Innovative Successful Case of Geological Resource Assessment on Gold Deposits Under Complex Geometries.
    Navarro, F., Garrido, M., Gonzalez, C., Baeza, D., Soto, F., Egana, A., Herreros, D. and Valencia, M.
    In MINEXCELLENCE 2016 – 1st International Seminar on Operational Excellence in Mining2016.
  • [14]
    Abeja VGML: geometallurgical applications on cloud services.
    Barberan, A., Lopez, A., Friedrich, C., Navarro, F., Gonzalez, C., Morales, N. and Egana, A.
    In MININ 2016 – 6th International Conference on Innovations in Mine Operations2016.
  • [15]
    Resource assessment with unfolding methodology: A case study.
    Garrido, M., Navarro, F., Ortiz, J. and Moreira, J.
    In 6th International conference on innovation in mine operations (MININ2016). Santiago: Gecamin Publications2016.
  • [16]
    An immersive 3D geological and mining data visualization environment.
    Gonzalez, C., Navarro, F., Rojas, C., Gonzalez, M., Pardo, S., Comte, D., Carrizo, D., Diaz, M. and Salvo, J.
    In MININ 2016 – 6th International Conference on Innovations in Mine Operations2016.
  • [17]
    Effect of frother type on froth texture and gas holdup.
    Mesa, D., Kracht, W. and Diaz, G.
    In Copper 2016, Kobe, Japan2016.
  • [18]
    Rock texture discrimination: A new tool for geological characterization.
    Diaz, G., Egana, A., Cortes, M. and Ortiz, J.M.
    In MININ 2016, Santiago, Chile2016.
  • [19]
    A case study of geometallurgical modeling of metal recovery with unequal sampling.
    Garrido, M., Navarro, F., Sepulveda, E. and Townley, B.
    In GEOMET 2016 – 3rd International Seminar on Geometallurgy2016.
  • [20]
    Channelized facies recovery based on weighted compressed sensing.
    Calderon, H., Santibanez, F., Silva, J.F., Ortiz, J.M. and Egana, A.
    In Sensor Array and Multichannel Signal Processing Workshop (SAM), Rio de Janeiro, Brazil, pp. 1–5, 2016.
  • [21]
    Applying data science techniques to metallurgical characterization.
    Baeza, D., Navarro, F. and Townley, B.
    In GEOMET 2016 – 3rd International Seminar on Geometallurgy, Lima, Peru2016.
  • [22]
    Calculating ore resources on complex geology using a geometric restitution methodology: from modeling to the estimation.
    Navarro, F., Baeza, D., Herreros, D. and Valencia, M.
    In U-Mining 2016: First International Conference on Underground Mining2016.
  • [23]
    Elastic Wavespeed Images of Northern Chile Subduction Zone from the Joint Inversion of Body and Surface Waves: Structure of the Andean Forearc and the Double Seismic Zone.
    Comte, D., Carrizo, D., Roecker, S.W., Peyrat, S., Arriaza, R.C., Chi, R.K. and Baeza, S.
    In AGU Fall Meeting Abstracts2015.
  • [24]
    Analysis and Classification of Natural Rock Textures based on New Transform-based Features.
    Lobos, R., Silva, J.F., Ortiz, J.M., Diaz, G. and Egana, A.
    In Mathematical Geosciences. Vol. 48(7), Pp. 835–8702015.
  • [25]
    CUDA-Based Implementation of GSLIB: The Geostatistical Software Library.
    Baeza, D., Peredo, O. and Ortiz, J.M.
    In GPU Technology Conference, San jose, California2015.
  • [26]
    Practical Aspects of Resources Modeling in presence of Locally Varying Anisotropy.
    Peredo, O., Garrido, M. and Ortiz, J.M.
    In IAMG 2015, Freiberg, Germany2015.
  • [27]
    The September 16, 2015 Illapel (Mw 8.3) Earthquake: Comprehensive Analysis from Seismic and Geodetic Observations.
    Comte, D., Carrizo, D., Peyrat, S., Russo, R.M., Roecker, S.W., Opazo, T., Pena, G., Baeza, S., Arriaza, R.C., Ortega-Culaciati, F. and Others.
    In AGU Fall Meeting Abstracts2015.
  • [28]
    U-Fo: software para la evaluacion de recursos en presencia de fallas y pliegues.
    Soto, F., Ortiz, J.M. and Garrido, M.
    In Geomin 2015, Antofagasta, Chile2015.
  • [29]
    High performance computing in geostatistics.
    Soto, F.
    In Big Data and Environment Workshop 20152015.
  • [30]
    A Flexible Strategy for Distributed and Parallel Execution of a Monolithic Large-Scale Sequential Application.
    Navarro, F., González, C., Peredo, Ó., Morales, G., Egaña, Á. and Ortiz, J.M.
    In High Performance Computing, Berlin, Heidelberg, pp. 54–67, 2014.
  • [31]
    GPU parallelization of geostatistical simulation for mineral reserves quantification.
    Baeza, D., Peredo, O., Navarro, F. and Ortiz, J.M.
    In NVIDIA GPU Technology Conference2014.
  • [32]
    Geometallurgical Modelling and Mine Planning, CSIRO Chile Program 2.
    Ortiz, J.M.
    2014.
  • [33]
    Resurrecting GSLIB by code optimization and multi-core programming.
    Peredo, O. and Ortiz, J.M.
    In Geostatistical and geospatial approaches for the characterization of natural resources in the environment: Challenges, Processes and Strategies, New Dehli, India2014.
  • [34]
    Water/rock interactions and physicochemical controls on mineral processing: being predictive based on geology.
    Lois, P., Kracht, W., Townley, B. and Ortiz, J.M.
    2014.
  • [35]
    Challenges in analysis of geo-metallurgical data: Linking numbers with interpretations.
    Ortiz, J.M.
    2014.
  • [36]
    Geochemical quantitative mineral characterization for geometallurgical applications in porphyry copper deposits.
    Cardenas, E., Townley, B., Ortiz, J.M. and Kracht, W.
    2014.
  • [37]
    Inverse modeling of moving average kernels for 3D Gaussian simulation.
    Peredo, O., Ortiz, J.M. and Leuangthong, O.
    Paris, France2014.
  • [38]
    Physicochemical modeling of the behavior of different mineralogical units in milling and flotation.
    Lois, P., Townley, B., Kracht, W. and Ortiz, J.M.
    2013.
  • [39]
    Categorical variables simulation incorporating local varying anisotropy.
    Gutierrez, R., Ortiz, J.M. and Townley, B.
    2013.
  • [40]
    Geometric restitution for improving mineral resource estimation applied to Peumo deposit.
    Soto, F., Ortiz, J.M., Herreros, D. and Valencia, M.
    In GEOMIN 20132013.
  • [41]
    Implementation of parallelized conditional simulation in GPU for generating large resources models.
    Baeza, D., Sepulveda, E. and Ortiz, J.M.
    2012.
  • [42]
    Modelamiento y simulacion del sistema de cargu{\backslash’\backslashi}o y transporte en Mina Chuquicamata.
    Yarmuch, J.L. and Ortiz, J.M.
    2012.
  • [43]
    Parallelization of simulation algorithm with GPU for constructing highresolution models of Earth Sciences variables.
    Baeza, D., Sepulveda, E. and Ortiz, J.M.
    Valencia, Spain2012.
  • [44]
    Parallel implementation of multiple-point simulation based on texture synthesis.
    Parra, A. and Ortiz, J.M.
    2012.
  • [45]
    Training image selection for multiple-point geostatistical simulation.
    Perez, C., Mariethoz, G. and Ortiz, J.M.
    2012.
  • [46]
    Improve an efficient simulation of multidimensional Gaussian random fields in GPU.
    Baeza, D., Sepulveda, E. and Ortiz, J.
    In V Latin American Symposium on High Performance Computing HPCLatAm, Buenos Aires, Argentina2012.
  • [47]
    Improving an efficient simulation of multidimensional Gaussian random fieldsin GPU.
    Baeza, D., Sepulveda, E. and Ortiz, J.M.
    Buenos Aires, Argentina2012.
  • [48]
    Multiple-point geostatistical simulation based on genetic algorithms implemented in a shared-memory supercomputer.
    Peredo, O. and Ortiz, J.M.
    Oslo, Norway, pp. 103–114, 2012.
  • [49]
    Inferring a representative distribution of soluble copper grade in the presence of a preferential sampling.
    Saa, J., Ortiz, J.M., Magri, E.J. and Emery, X.
    Santiago, Chile2011.
  • [50]
    Stepwise Conditional Transformation of linearly transformed variables for multivariate geostatistical simulation.
    Pizarro, S.H.A. and Ortiz, J.M.
    Santiago, Chile2011.
  • [51]
    Mine-scale modeling of lithologies with multiple-point geostatistical simulation.
    Perez, C. and Ortiz, J.M.
    Salzburg2011.
  • [52]
    A Novel Approach to Estimate the Gap Between the Middle and Short-Term Plans.
    Yarmuch, J.L. and Ortiz, J.M.
    WA, Australia2011.
  • [53]
    Geological modelling and metallurgical prediction supported by linear and non-linear statistics.
    Carmona, S. and Ortiz, J.M.
    Santiago, Chile, pp. 459–470, 2010.
  • [54]
    The economic optimisation of advanced drilling grids for short term planning and grade control at El Tesoro Copper Mine.
    Magri, E.J., Ortiz, J.M. and Libano, R.
    Santiago, Chile, pp. 89–98, 2010.
  • [55]
    Multiple-point conditional unilateral simulation for categorical variables.
    Parra, A. and Ortiz, J.M.
    Santiago, Chile, pp. 413–422, 2010.
  • [56]
    Conditional multiple point simulation with texture synthesis.
    Parra, A. and Ortiz, J.M.
    2010.
  • [57]
    Quantifying uncertainty in resources tonnage using multiple point geostatistical simulation.
    Hurtado, S. and Ortiz, J.M.
    Santiago, Chile, pp. 423–432, 2010.
  • [58]
    Conditional multiple point simulation with texture synthesis.
    Ortiz, J.M.
    2010.
  • [59]
    Distributed-multiprocess implementation of kriging for the estimation of mineral resources.
    Sepulveda, E. and Ortiz, J.M.
    Santiago, Chile, pp. 433–442, 2010.
  • [60]
    Mine planning considering uncertainty in grades and work index.
    Contreras, R., Ortiz, J.M. and Bisso, C.
    Santiago, Chile, pp. 129–136, 2010.
  • [61]
    Image segmentation for mineral identification in oxide copper deposit.
    Egana, A.F. and Ortiz, J.M.
    Santiago, Chile, pp. 405–412, 2010.
  • [62]
    Adding flexibility to support vector classification for modelling categorical variables.
    Cuba, M.A., Leuangthong, O. and Ortiz, J.M.
    Santiago, Chile, pp. 479–489, 2010.
  • [63]
    Conditional multiple-point simulation with a texture synthesis algorithm, Computational Methods for the Earth, Energy and Environmental Sciences.
    Parra, A. and Ortiz, J.M.
    2009.
  • [64]
    Conditional multiple-point simulation with a texture synthesis algorithm.
    Parra, A.J. and Ortiz, J.M.
    2008.
  • [65]
    Geostatistics applied to geotechnical parameters.
    Egana, M., Arancibia, E., Villegas, F. and Ortiz, J.M.
    , pp. 137–146, 2008.
  • [66]
    Innovations in Software Development for Resource Evaluation.
    Ortiz, J.M., Sepulveda, E., Magri, E.J., Emery, X. and Barberan, A.
    In MININ 2008 - 4th International Conference on Innovations in Mine Operations, Santiago, Chile2008.
  • [67]
    Outlier detection and consistent h-scatter plot smoothing for robust variogram estimation.
    Ortiz, J.M. and Leuangthong, O.
    2008.
  • [68]
    An Overview of the Challenges of Multiple-Point Geostatistics.
    Ortiz, J.M.
    Santiago, Chilevol. 1, , pp. 11–20, 2008.
  • [69]
    Analysis of fiber optics BOTDR data to predict rock mass behavior in panel caving.
    Ortiz, J.M., Manasevich, R., Silva, D., Calderon, C. and Molina, R.
    2007.
  • [70]
    An Optimization Algorithm to Asses Different Resource Models for Open Pit Short Term Planning.
    Ortiz, J.M., Rubio, E. and Yarmuch, J.L.
    , pp. 721–732, 2007.
  • [71]
    Integration of Disparate Data with Logratios of Conditional Probabilities.
    Hong, S., M., O.J. and Deutsch, C.V.
    2007.
  • [72]
    A practical approach to validate the variogram reproduction from geostatistical simulation.
    Ortiz, J.M. and Leuangthong, O.
    , pp. 121–127, 2007.
  • [73]
    VOTable Construction and a Simple, Lazy, Expression Evaluator: Two Technical Aspects of the DMaSS.
    Egana, A.
    In Astronomical Data Analysis Software and Systems XVIvol. 376, , p. 506, 2007.
  • [74]
    Conditional simulation as a tool for assessing mining selectivity.
    Emery, X. and Ortiz, J.M.
    , pp. 79–85, 2007.
  • [75]
    Geostatistical simulation of mineral grades in the presence of spatial trends.
    Robles, L., Emery, X. and Ortiz, J.M.
    In 33rd International Symposium on Applications of Computers and Operations Research in the Mineral Industry APCOM, pp. 87–93, 2007.
  • [76]
    A comparative study of three data-driven Mineral Potential Mapping techniques.
    Caumon, G., Ortiz, J.M. and Rabeau, O.
    Belgium2006.
  • [77]
    Evaluacion de la incertidumbre en la variabilidad espacial de la precipitacion usando un modelamiento multiGaussiano.
    Dussaubat, S., Vargas, X. and Ortiz, J.M.
    2006.
  • [78]
    Multivariate geostatistical and GIS methods for mineral exploration.
    Ortiz, J.M. and Caumon, G.
    Santiago, Chile2006.
  • [79]
    Multivariate p-field simulation.
    Ortiz, J.M.
    2006.
  • [80]
    On the Scaling and Use of Multivariate Distributions in Geostatistical Simulation.
    Leuangthong, O., Ortiz, J.M. and Deutsch, C.V.
    Toronto, Canada2005.
  • [81]
    Estimacion de la variabilidad espacial de eventos de precipitacion usando metodos geoestadisticos.
    Dussaubat, S., Vargas, X. and Ortiz, J.M.
    2005.
  • [82]
    Internal Consistency and Inference of Change-of-support isofactorial Models.
    Emery, X. and Ortiz, J.M.
    In Geostatistics Banff 2004vol. 2, , pp. 1057–1066, 2005.
  • [83]
    A Step by Step Guide to Bi-Gaussian Disjunctive Kriging.
    Ortiz, J.M., Oz, B. and Deutsch, C.V.
    In Geostatistics Banff 2004vol. 2, , pp. 1097–1102, 2005.
  • [84]
    Simulacion geoestadistica por campos de probabilidad para evaluacion de reservas mineras.
    Ortiz, J.M.
    Buenos Aires, Argentina2005.
  • [85]
    Integrating Multiple-Point Statistics into Sequential Simulation Algorithms.
    Ortiz, J.M. and Emery, X.
    vol. 2, , pp. 969–978, 2005.
  • [86]
    A MultiGaussian Approach to Assess Block Grade Uncertainty.
    Ortiz, J.M., Leuangthong, O. and Deutsch, C.V.
    2004.
  • [87]
    Geostatistical Simulation of Optimum Mining Elevations for Nickel Laterite Deposits.
    McLennan, J.A., Ortiz, J.M. and Deutsch, C.V.
    2004.
  • [88]
    Modelamiento Geoestadistico de la Razon de Solubilidad en un Yacimiento de Oxidados de Cobre.
    Emery, X., Carrasco, P. and Ortiz, J.M.
    , pp. 198–208, 2004.
  • [89]
    Categorizacion de Recursos y Reservas Mineras.
    Ortiz, J.M. and Emery, X.
    , pp. 226–236, 2004.
  • [90]
    Hierarchical Indicator Simulation.
    Ortiz, J. and Deutsch, C.V.
    Phoenix, Arizona, pp. 275–284, 2002.
  • [91]
    Estimation of Economic Losses due to Poor Blast Hole Sampling in Open Pits.
    Magri, E.J. and Ortiz, J.M.
    In Geostatistics 2000, Cape Town, South Africavol. 2, , pp. 732–741, 2000.

Miscellaneous

  • [1]Implementation of synthetic scenarios for the study of the ambient noise tomography technique. Universidad de Chile, 2017
  • [2]Tecnicas y aplicaciones de separacion de senales aplicadas en imagenes hiper espectrales. Universidad de Chile, 2016