Geostatistics Rio 2000: Proceedings of the Geostatistics Sessions of the 31st International Geological Congress, Rio de Janeiro, Brazil, 6–17 August 2000

234 Pages·2002·9.968 MB·English

by  M. Armstrong, C. Bettini, N. Champigny, A. Galli, A. Remacre (auth.), M. Armstrong, C. Bettini, N. Champigny, A. Galli, A. Remacre (eds.)

GEOSTATISTICS RIO 2000
Quantitative Geology and Geostatistics
VOLUME 12
The titles published in this series are listed at the end of this volume.
GEOSTATISTICS RIO 2000
Proceedings of the Geostatistics Sessions
of the 31 International Geological Congress,
sl
Rio de Janeiro, Brazil, 6-17 August 2000
Edited by
M. ARMSTRONG
Centre de Geostatistique,
Ecole des Mines de Paris, France
C. BETTINI
Department of Geology,
Universidade Federal do Rio de Janeiro, Brazil
N. CHAMPIGNY
Pricewaterhouse Coopers LLP,
Montreal, Canada
A. GALLI
Centre de Geostatistique,
Ecole des Mines de Paris, France
and
A. REMACRE
Institute of Geosciences,
UNICAMp, Campinas, Brazil
SPRINGER-SCIENCE+BUSINESS MEDIA, B.V.
A c.I.P. Catalogue record for this book is available from the Library of Congress.
Additional material to this book can be downloaded from http://extras.springer.com.
ISBN 978-90-481-5954-3 ISBN 978-94-017-1701-4 (eBook)
DOI 10.1007/978-94-017-1701-4
Printed on acid-free paper
All Rights Reserved
© 2002 Springer Science+Business Media Dordrecht
Originally published by Kluwer Academic Publishers in 2002
Softcover reprint of the hardcover 1st edition 2002
No part of the material protected by this copyright notice may be reproduced or
utilized in any form or by any means, electronic or mechanical,
including photocopying, recording or by any information storage and
retrieval system, without written permission from the copyright owner.
GEORGES MATHERON
This volume is dedicated to Professor Georges Matheron who passed away on 7 August
2000 during the week when the 31 International Geological Congress was being held.
st
While working for the French Geological Survey in Algeria, he came across the
pioneering work of Krige, Sichel, de Wijs on the gold deposits of the Witwatersrand,
from which he developed the theory for resource estimation that became known as
geos tatistics .
In 1968 he joined the Ecole des Mines de Paris and founded the Centre de Morphologie
Mathematiquefrom which the Centre de Gwstatistique grew. In Fontainebleau, Matheron
manifested an astounding creativity. With a team of collaborators including Andre
Journel, Alain Marechal, Pierre Delfiner and Jean-Paul Chiles, to cite some from the
first generation, he developed the key concepts of non-linear and non-stationary
geostatistics, in parallel with his work in mathematical morphology and the theory of
random sets.
Matheron, whose entire adult life was devoted to research, produced over 250 papers,
mostly internal to the Fontainebleau centers, and five books. The recurring theme behind
this enormous and varied output, was the use of probabilistic models. Matheron had an
extraordinary ability for solving apparently intractable problems by choosing the
appropriate methodology. The reason why the methods and concepts he elaborated have
endured so well is that they respond to real world problems.
An eloquent proof of this is the explosion in the fields of application of geostatistics.
Starting out from mining, it is now used in petroleum, forestry, agronomy,
oceanography ,meteorology, fishery, environmental sciences, etc.
v
TABLE OF CONTENTS
Foreword IX
Ricardo Olea
Introduction
M. Armstrong, C. Bettini, N Champigny, A. Galli and A. Remacre
Petroleum Papers
Chapter 1
Using Quantitative Outcrop Databases As a Guide for Geological
Reservoir Modelling 7
R. Eschard, B. Doligez and H. Beucher
Chapter 2
Quantification of facies relationships via proportion curves 19
C. Ravenne, A. Galli, B. Doligez, H. Beucher and R. Eschard
Chapter 3
Geologic Modelling of External and Internal Reservoir Architecture of
Fluvial Depositional Systems 41
P.E. Patterson, T.A. Jones, c.J. Donofrio, A.D. Donovan and J.D. Ottmann
Chapter 4
Impact of Seismic Constraints on a Stochastic Reservoir Model and Fluid
Flow Simulation 53
I. Azpiritxaga, A. Correa, E. Hernandez, A. Galli, C. Ravenne, Z. Jiminez,
C. Castillo and G. Gedler
Chapter 5
Practical Workflows for Reservoir Modelling 69
J.M. Yarus, K. Yang and K. Kramer
Mining Papers
Chapter 6
Simulating the Geometry of a Granite-hosted Uranium Orebody 85
T. Skvortsova, H. Beucher, M. Armstrong, J. Forkes, A. Thwaites and
R. Turner
Chapter 7
Simulation of Weathered Iron Ore Facies: Integrating Leaching Concepts
and Geostatistical Models 101
D. T. Ribeiro and R.M. Carvalho
viii Table of Contents
Chapter 8
Geostatistical Simulation of Structurally Controlled Low Grade High
Tonnage Gold Ores: A Strategy for Targeting Genuine Enriched Zones 117
A.H.M Silva, A.Z. Remacre and CR. De Souza Filho
Chapter 9
Geostatistical Frameword for Modelling Clay Deposits: Nova Veneza Case
Study in Southern Brazil 133
R.L. Stangler, A.J. Strieder, J.C Koppe, J.F. Costa and M Armstrong
Chapter 10
Risk Assessment of Reserve Calculation during Milestones of a Mine Life 149
F. Silva, A. Soares and D. Caupers
Chapter 11
Successfull Incorporation of Geological Controls into Reserve Evaluation:
Recent Examples from Giant Copper Mines in Chile 163
N Champigny, P. Cuadra, F. Ferraz and A. Moraga
Chapter 12
Geological Conditions for a Correct Geostatistical Evaluation: Example
from the Elatsite Copper Deposit in Bulgaria 177
J. Todorov, K. Popov, S. Shanov and A. Boykova
Chapter 13
Evaluation of Kriging and Cokriging for Asbestos Ore Reserve Estimation
at the Cana Brava Mine, Goias, Brazil 191
R.P. Conde and J.K. Yamamoto
Chapter 14
Geostatistical Evaluation of the Mineral Resources of the Cajati Mine,
State of Sao Paulo, Brazil 205
G. Barros and J.K. Yamamoto
Chapter 15
Variographic Trends of Gold in the Alluvial Sediments Associated with the
Quartz Lodes in the Princesa Isabel Region, Paraiba, Brazil 215
S.R. Lanusse and T.R. Gopinath
Index 225
List of color figures 231
CD-Rom ordering color images: inside backcover
FOREWORD
Every four years, the International Union of Geological Sciences (lUGS) organises a
world congress in which the common theme is geology. This volume is a partial
proceedings comprising fifteen papers on geostatistics presented at three sessions
organised by the International Association of Mathematical Geologists (IAMG) during
the 31st International Geological Congress held in Rio de Janeiro, August 6-17,2000.
Since its inception in 1968, the IAMG has been responsible for organising symposia on
quantitative aspects of geology during the lUGS congresses as part of its wider objective
to advance quantitative methods in the earth sciences.
Of all the quantitative methods applied in geology by the year 2000, geostatistics has
been one of the most successful approaches, both in terms of results and variety of
techniques developed. In a nutshell, geostatistics is a generalisation of classical statistics
for the purpose of capturing aspects that are important in the study of geological
processes: spatial auto-correlation of individual attributes and cross-correlation in the
case of the simultaneous study of multiple properties; and size, orientation, and shape
of the volumes commonly associated with measurements taken to characterise geological
bodies. The main aspect that geostatistics continues to have in common with classical
statistics is the quantification of the uncertainty that a very limited sampling always
yields when characterising those predominant locations not considered in the sampling.
Characterisations based on geostatistics have been slow to gain acceptance by mainstream
geologists due both to difficulties in understanding the mathematics behind the methods
and to the inability of geostatistics to produce realistic results in the opinion of most
experienced geologists. The fact that this is the first time a volume of papers on
geostatistics has come out of an International Geological Congress is a tribute to the
advancement of geostatistics as a science and its acceptance by non-specialists.
Ricardo A. Olea
1996-2000 President, IAMG
IX
INTRODUCTION
M. ARMSTRONG\ C. BETIINIZ, N. CHAMPIGNy3, A. GALLt & A. REMACRE4
1) Centre tfe ljeostatistique, 35 rue St-!JIonmi, 77305 !Fontaine6fmu, !France
2) tJJepto tfe ljeofogia,l(1niversitfatf !Fetferaf tfo !l{w fie Janeiro, !l{w tfe Janeiro, tlJrazi{
3) PriceuJaterfwuseCoopers ££fP, 10 l)'ork9.fiffs !!(patf 'Eilst, Toronto, Canatfa
4) Institute of ljeoscie1t,w, t[jg{J~ P.O. 'lJo~ 6152, CampinasSP, tlJrazif
The 31" International Geological Congress held in Rio de Janeiro, Brazil from 6-17 August
2000 attracted several thousand participants from allover the world. The technical program
included more than 70 special symposiums (where authors were invited to present papers)
in addition to 160 general sessions. Two sessions focussed specifically on geostatistics:
Special Symposium 1-3: Stocfuzstic ljeofogica{9Jotfefs jorOif!l(fservoirs
General Session 11-2: ljeostatistic.a[ '£vaEuation of 9lini11fJ Ore6otfies accortfi11fJ to
tlieir ljeofo9!J
This volume contains most of the papers presented in these two sessions together with one
on a closely related topic (vertical proportion curves) that was presented in General Session
24-8: ~tJ1ieories ani!Metfwtfs of Matfiematica{ ljeofo9!J ani tIieir .9IppBcations. All three sessions
were sponsored by the IAMG. Special thanks are extended to Hemani A.F. Chaves, Special
IGC councillor. Without his untiring efforts, these sessions would never have taken place.
Five papers related to oil reservoirs are grouped together in the first half of the book; the
second half contains 10 papers on mining ore-bodies. In both sections the key theme is
simulation. Another important topic in mining is reconciling the production figures with
predictions made beforehand. As this was a geological congress rather than a geostatistical
one, all the papers focus on the geological controls and their incorporation in the evaluation
of mineral deposits or reservoir under study.
The figures in the volume are printed in black & white; colour copies of most are available
in a CD-ROM located in the back cover.
Petroleum Papers
Proper reservoir characterisation is essential for optimum hydrocarbon recovery. The five
petroleum papers presented here focus on different aspects of this topic but all use
stochastic simulations to generate 3D numerical models that reproduce the key features of
the reservoirs. When simulations were first introduced in the oil industry, people simulated
reservoir properties such as porosity and permeability directly. Experience has shown that
it is better to simulate the geology of the reservoir first, then infill the properties as a
function of the geology. This gives models that are more realistic from a geological point
of view as well as providing better history matches.
M. Armstrong et al. (eds.), Geostatistics Rio 2(J()(), 1-5.
© 2002 Kluwer Academic Publishers.
2 Introduction
The first paper by Eschard, Doligez and Beucher shows how to use outcrop data as a
guide for modelling reservoirs. They focus on choosing the simulation technique to suit the
geological characteristics of the reservoir. Three case-studies are presented:
• Deltaic reservoirs are illustrated by the Cretaceous series of the Mesa Verde
(Colorado). As coastal plain sediments interfinger with shoreface series, they used
nonstationary sequence-based algorithms to simulate the rapid lateral facies changes.
• The Paradox basin (Utah) is an example of complex facies transitions in mixed silici
clastic and carbonate shelf systems. Several sequences are stacked vertically and algal
mounds interfinger in shallow marine carbonates and clastics. A combination of the
truncated gaussian and plurigaussian methods gave good results.
• The Permian series in Utah is an eolian and fluvial reservoir. The truncated gaussian
and boolean methods were combined to reproduce the incision of fluvial channels in
the eolian dunes.
The second paper by Ravenne, Galli et al is on proportion curves. Although these were
initially developed for modelling nonstationarities encountered in oil reservoirs due to
changing depositional environments, they have proved to be one of the key tools for
sequence stratigraphy analysis and for quantifying the spatial distribution of lithofacies.
This paper presents examples of vertical and horizontal proportion curves (vpC and HPC
for short) coming from analogue studies or from real oil fields. The VPC provide
information on sequential evolution; the HPC correspond to the lateral evolution of facies.
Typical signatures are obtained from different environments; for example, those from
meandering systems in a low accommodation can be distinguished from high
accommodation ones. The authors show that the choice of the horizon chosen to flatten the
system is critical to modelling proportion curves and understanding the sequence
stratigraphy.
Patterson et al present an integrated study of a petroleum reservoir that was conducted to
delineate the facies and sequence-stratigraphic architectures of fluvial depositional systems.
The proximal (up-dip) fluvial-facies belts in their study were interpreted as lowstand fluvial
sandstones characterised by amalgamated channel complexes that form widespread sheets,
the medial fluvial-facies belts correspond to lowstand sandstones of amalgamated to semi
amalgamated fluvial-bar complexes that are thinner and less laterally persistent, and the
distal (down-dip) fluvial-facies belts are lowstand sandstones characterised by thin, yet
laterally extensive, fluvial-bar complexes.
The internal architecture of the reservoir intervals was modelled by means of two
techniques. Object based methods were used to generate the proximal fluvial. Medial and
distal fluvial facies, however, were modelled by populating the zones with discrete, user
defined, fluvial-bar elements. These are distributed along thalwegs which are clustered to
form amalgamated to semi-amalgamated bar complexes. The resulting geologic models are
better because they describe the lowstand fluvial sandstones and the mudstones more
accurately.
The paper by Azpiritxaga et al. focuses on the impact of seismic constraints on a
stochastic reservoir model and on the resulting fluid flow simulations. Using a block in the
Eocene-C6 reservoir in Lake Maracaibo as an example, they compare the models obtained
using only well data with those where seismic information was incorporated, from a