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  • AUSIMM
    Geostatical Production Grade Estimation in Mount Isa's Copper Orebodies

    This paper describes a detailed geostatistical study of producing copper orebodies at Mount Isa Mines Limited in Queensland, Australia. As a result of this work, kriging has been adopted for grade est

    Jan 1, 1982

  • AUSIMM
    Geostatistical analyses of cone penetration testing data of a tailings storage facility in a semi‐arid setting

    By P Chapman, B Moosapoor

    The objective of this paper is to present the potential applications of geostatistical analyses in planning CPTu investigations, as well as interpolation of CPTu data. The paper presents a case study

    Jul 1, 2021

  • AUSIMM
    Geostatistical Analysis Of 18cc Stope Blcok, C.S.A. Mine, Cobar, N.S.W.

    By Leach B. G

    A geostatistical study was made of diamond drill hole intersections within 18CC stope block at the C.S.A. Mine, Cobar, N.S.W. The stope block is located in 18CC orebody which is a massive sulphide

    Jan 1, 1979

  • AUSIMM
    Geostatistical Applications in the Athabasca Tar Sands

    By Royle A. G

    The paper describes a geostatistical structural analysis of an 80 square mile lease of the Athabasca tar sands. Each step of the analysis is presented with the ultimate objective of condensing the

    Jan 1, 1977

  • AUSIMM
    Geostatistical Calculations using True and Estimated Values from a Simulated Deposit

    Knowledge of true block grades is obtained from a mathematical model of an orebody, simulated with sample grades normally distributed and spatially correlated according io a spherical semi-variogram m

    Jan 1, 1978

  • AUSIMM
    Geostatistical Estimation at Porgera: The Disjunctive Kriging Approach

    By Armstrong M

    The highest grades of the Porgera gold deposit, Papua New Guinea, are contained in Zone 7 due to the presence of the Roamane fault, which acted as channelway of the gold-bearing fluids. Prior to the d

    Jan 1, 1990

  • AUSIMM
    Geostatistical Estimation of the Southern Lignites

    In the estimation of reserves the known values of the variables of interest from surrounding drill holes are used to compute or estimate the unknown value of the orebody over a given region or at a gi

    Jan 1, 1983

  • AUSIMM
    Geostatistical Evaluation of A Beach Sand Rutile Deposit

    This study begins with the semivario- gram modelling of variables rutile grade and clay content from a beach sand rutile deposit. This is followed by two dimensional block kriging. The deposit was

    Jan 1, 1986

  • AUSIMM
    Geostatistical modelling of geometallurgical classes

    By W Patton, I Minniakhmetov, H Talebi, U Mueller

    The sustainability of mining projects is linked to informed investment decisions based on public reporting of exploration and mineral resource estimation results. In Australia, public reporting guidel

    Mar 22, 2022

  • AUSIMM
    Geostatistical Modelling of Geometallurgical Variables - Problems and Solutions

    By C V. Deutsch

    "Geometallurgical variables often cause problems to conventional geostatistical workflows. There are many variables; some are compositional and some are non-additive. They often show: complex multiva

    Sep 29, 2013

  • AUSIMM
    Geostatistical Modelling of Hydraulic Fracturing Pressures at El Teniente Mine

    By P Landeros, D Benado, J Cornejo, A Pinochet, C Caviedes

    In 2005, El Teniente mine began preconditioning the primary rock mass by hydraulic fracturing (HF). The major perceived benefits of this process are a decrease in the magnitude of the expected maximum

    May 9, 2016

  • AUSIMM
    Geostatistical Modelling of the Hilton and Mount Isa Lead-Zinc Orebodies, Mount Isa, Australia

    By Raymond G. F

    Geostatistics - a tool used by geologists and mine planning engineers to estimate grades and rapidly evaluate alternative mining strategies has reached an advanced stage of development for the silver-

    Jan 1, 1993

  • AUSIMM
    Geostatistical Ore Reserve Estimation For The Warrego Mine, Northern Territory

    By Leahey T. A

    The variability of gold mineralization in the Warrego Gold Pod is described by classical statistical techniques using sample distrib- utions and analysis of variance; and by the use of geostatistic

    Jan 1, 1979

  • AUSIMM
    Geostatistical Parametrisation for Grade Control of Stratiform Banded Iron Formation in 'Singhbhum - Keonjhar - Bonai' Belt of India

    By Sarkar B. C, Sen A. K

    India is well endowed with vast reserves of banded hematite ore, about 12 billion tonnes, estimated by some conventional methods. Various authors have assessed this huge reserve using some advanced

    Jan 1, 1995

  • AUSIMM
    Geostatistical Prediction of Grade Fluctations of Bahariya Iron Ore Components after Blasting a Certain Volume (Western Desert, Egypt)

    By Sirayanone S, Rashad MZ

    An important problem occurring in the iron and steel industry of Egypt is the presence of manganese oxide and chlorine with different percentages in the Bahariya Iron Ore Deposit, Western Desert,

    Jan 1, 1986

  • AUSIMM
    Geostatistical Recognition of Structure in Beach Sand

    Types of structure found in 'Jest Australian beach sands are described. Their recognition by geostatistical methods follows nth a discussion of the effectiveness of sampling patterns. Examples

    Jan 1, 1977

  • AUSIMM
    Geostatistical Simulations of Kimberlite Orebodies and Application to Sampling Optimisation

    By M Field

    Kimberlite pipes, as opposed to dykes, sill and secondary deposits, are the primary target for diamond exploration companies because they have simple geometries and can contain large volumes of potent

    Jan 1, 2006

  • AUSIMM
    Geostatistical Study of a Lower Proterozoic Iron Orebody in the Pilbara Region of Western Australia

    By Shrivastava P

    The iron orebodies of the Pilbara region are formed by supergene enrichment of banded iron formation and rarely do such processes produce orebodies with uniform grade distrib- utions. The orebodies

    Jan 1, 1977

  • AUSIMM
    Geostatistical Texture Modelling in Enhancing Ore Reserve Estimation in Base Metal Deposits

    By Dimitrakopoulos R

    Ore textures in base metal deposits are an important factor in the liberation of the economic components of the ore, metal recovery and reagent consumption during beneficiation. Optimising the mine

    Jan 1, 1997

  • AUSIMM
    Geostatistical, Spectral and Fractal Simulation of Sulphur Distribution in a Coal Seam

    By Ramani R. V

    In this paper, a comparative performance evaluation of geostatistical, spectral, and fractal methods is made for short-scale variability prediction. The algorithms compared are: sequential Gaussian

    Jan 1, 1995