Quantitative interpretation of airborne gravity gradiometry data for mineral exploration

218 Pages·2015·6.42 MB·English

by  Cericia D. Martinez

QUANTITATIVE INTERPRETATION OF AIRBORNE
GRAVITY GRADIOMETRY DATA FOR
MINERAL EXPLORATION
by
Cericia D. Martinez
(cid:13)c Copyright by Cericia D. Martinez, 2015
All Rights Reserved
A thesis submitted to the Faculty and the Board of Trustees of the Colorado School
of Mines in partial fulfillment of the requirements for the degree of Doctor of Philosophy
(Geophysics).
Golden, Colorado
Date
Signed:
Cericia D. Martinez
Signed:
Dr. Yaoguo Li
Thesis Advisor
Golden, Colorado
Date
Signed:
Dr. Terry Young
Professor and Head
Department of Geophysics
ii
ABSTRACT
In the past two decades, commercialization of previously classified instrumentation has
provided the ability to rapidly collect quality gravity gradient measurements for resource
exploration. In the near future, next-generation instrumentation are expected to further
advance acquisition of higher-quality data not subject to pre-processing regulations. Con-
versely, the ability to process and interpret gravity gradiometry data has not kept pace with
innovations occurring in data acquisition systems. The purpose of the research presented
in this thesis is to contribute to the understanding, development, and application of pro-
cessing and interpretation techniques available for airborne gravity gradiometry in resource
exploration. In particular, this research focuses on the utility of 3D inversion of gravity
gradiometry for interpretation purposes. Towards this goal, I investigate the requisite com-
ponents for an integrated interpretation workflow. In addition to practical 3D inversions,
components of the workflow include estimation of density for terrain correction, processing
of multi-component data using equivalent source for denoising, quantification of noise level,
and component conversion. The objective is to produce high quality density distributions for
subsequent geological interpretation. I then investigate the use of the inverted density model
in orebody imaging, lithology differentiation, and resource evaluation. The systematic and
sequential approach highlighted in the thesis addresses some of the challenges facing the use
ofgravitygradiometryasanexplorationtool, whileelucidatingaprocedureforincorporating
gravity gradient interpretations into the lifecycle of not only resource exploration, but also
resource modeling.
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TABLE OF CONTENTS
ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xx
ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxi
CHAPTER 1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Gravity gradient tensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 Summary of 3D inversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
CHAPTER 2 TERRAIN AND BATHYMETRY DENSITY ESTIMATION IN
GRAVITY GRADIOMETRY USING SPATIAL STATISTICS . . . . . . . 9
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2 Terrain Effect in Gravity Gradiometry . . . . . . . . . . . . . . . . . . . . . . 13
2.3 Density Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3.1 Field Data Illustration . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3.2 Moran’s I and Geary’s c . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3.3 Local I and c Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.3.4 Global I and c Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.4 Validation of Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.5 Test Case with Dipping Dyke and Coincident Topography . . . . . . . . . . . 26
2.5.1 Component Density Estimates . . . . . . . . . . . . . . . . . . . . . . . 30
2.5.2 Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
iv
2.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
CHAPTER 3 DENOISING AND PROCESSING OF GRAVITY GRADIENT
DATA USING AN EQUIVALENT SOURCE TECHNIQUE . . . . . . . 44
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.2 Equivalent source construction . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.2.1 Generalized cross-validation (GCV) criterion . . . . . . . . . . . . . . . 49
3.2.2 L-curve criterion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.3 De-noising using equivalent source . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.3.1 Field example: Leghorn, Gulf of Mexico . . . . . . . . . . . . . . . . . 57
3.3.2 Regional-residual separation . . . . . . . . . . . . . . . . . . . . . . . . 63
3.3.3 Calculating converted components . . . . . . . . . . . . . . . . . . . . . 67
3.4 Estimating error level in equivalent source processed data . . . . . . . . . . . . 70
3.4.1 Synthetic example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3.4.1.1 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3.4.1.2 Direct construction of L . . . . . . . . . . . . . . . . . . . . . 75
3.4.2 Field Example: McFaulds Lake, Ring of Fire . . . . . . . . . . . . . . . 77
3.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
3.6 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
CHAPTER 4 COMPONENT CONVERSION . . . . . . . . . . . . . . . . . . . . . . . 80
4.1 Vredefort Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.2 Vredefort Gravity Gradient Data . . . . . . . . . . . . . . . . . . . . . . . . . 84
4.3 Vredefort Inversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
4.3.1 T inversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
zz
v
4.3.2 T and T inversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
xy uv
4.4 Vredefort Conceptual Interpretation . . . . . . . . . . . . . . . . . . . . . . . . 89
4.5 Vredefort Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
4.6 Kauring Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
4.7 Kauring Observed and Calculated Datasets . . . . . . . . . . . . . . . . . . . . 96
4.7.1 Observed Ground Gravity Data . . . . . . . . . . . . . . . . . . . . . . 97
4.7.2 Observed Gravity Gradient Data . . . . . . . . . . . . . . . . . . . . . 97
4.7.3 Equivalent Source Conversion . . . . . . . . . . . . . . . . . . . . . . . 97
4.8 Kauring Inversion of Observed Data . . . . . . . . . . . . . . . . . . . . . . . 101
4.9 Kauring Inversion of Converted Data . . . . . . . . . . . . . . . . . . . . . . 103
4.9.1 T and T data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
xy uv
4.9.2 Five component tensor data . . . . . . . . . . . . . . . . . . . . . . . 104
4.10 Kauring Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
4.11 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
CHAPTER 5 3D INVERSION OF AIRBORNE GRAVITY GRADIOMETRY
DATA IN MINERAL EXPLORATION: A CASE STUDY IN THE
´ ´
QUADRILATERO FERRIFERO, BRAZIL . . . . . . . . . . . . . . . 109
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
5.2 Deposit geology and gravity gradiometry survey . . . . . . . . . . . . . . . . 112
5.2.1 Geology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
5.2.2 Gravity gradiometry survey . . . . . . . . . . . . . . . . . . . . . . . 115
5.3 Inversion results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
5.3.1 Single Component Inversion (T ) . . . . . . . . . . . . . . . . . . . . 120
zz
5.3.2 Three-component Inversion (T , T , and T ) . . . . . . . . . . . . . 123
xz yz zz
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5.3.3 Five-component Inversion (T , T , T , T , and T ) . . . . . . . . 124
xx xy xz yy yz
5.3.4 Six-component Inversion (T , T , T , T , T , T ) . . . . . . . . . 126
xx xy xz yy yz zz
5.3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
5.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
5.5 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
CHAPTER 6 LITHOLOGIC CHARACTERIZATION USING AIRBORNE
GRAVITY GRADIENT AND AEROMAGNETIC DATA FOR
MINERAL EXPLORATION: A CASE STUDY IN THE
´ ´
QUADRILATERO FERRIFERO, BRAZIL . . . . . . . . . . . . . . . 131
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
6.2 Deposit Geology and Geophysical Data . . . . . . . . . . . . . . . . . . . . . 135
6.2.1 Gravity gradient data . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
6.2.2 Aeromagnetic data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
6.2.2.1 Regional-residual separation . . . . . . . . . . . . . . . . . . 138
6.3 Lithologic Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
6.3.1 Density contrast and susceptibility models . . . . . . . . . . . . . . . 142
6.3.2 Lithology assignment using generic constraints . . . . . . . . . . . . . 144
6.3.3 Lithology assignments using geologic constraints . . . . . . . . . . . . 152
6.3.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
6.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
6.5 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
CHAPTER 7 QUANTITATIVE INTEGRATION OF GEOPHYSICAL MODELS
IN MINERAL RESOURCE MODELING . . . . . . . . . . . . . . . . 163
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
7.2 Kriging and Cokriging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
vii
7.2.1 Semi-variogram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
7.2.2 Cross-variogram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
7.2.3 Variogram Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
7.3 Synthetic Example Based on Beltana Zinc Deposit . . . . . . . . . . . . . . . 169
7.3.1 Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
7.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
7.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
7.6 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
CHAPTER 8 CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
8.1 Future Research Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
8.2 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
REFERENCES CITED . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
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LIST OF FIGURES
Figure 2.1 Nettleton’s method of correlating gravity anomaly corrected with
various densities with the topography. From Milsom and Eriksen. . . . . 12
Figure 2.2 Observed gravity gradient data. . . . . . . . . . . . . . . . . . . . . . . . 15
Figure 2.3 Calculated terrain effect displayed using a density of 1.0 g/cc. . . . . . . . 15
Figure 2.4 Topography over the entire survey area with black box outlining the
smaller area of interest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Figure 2.5 Local Moran’s I for T using various density values to remove the
zz
terrain effect. Color displays the value of I at each location. . . . . . . . . 18
Figure 2.6 Blue represents values of 0, indicating a lack of or no spatial
autocorrelation. Red represents values of 1, indicating spatial
autocorrelation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Figure 2.7 Global proportioned Moran’s I statistic of all six components plotted
against their corresponding density value on the abscissa. . . . . . . . . . 22
Figure 2.8 Global proportioned Geary’s c statistic of all six components plotted
against their corresponding density value on the abscissa. . . . . . . . . . 23
Figure 2.9 Anomalous gravity gradient data with terrain effect removed with a
density of 2.84 g/cc. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Figure 2.10 (a) Top of the dipping dyke is centered beneath the elongated hill at a
depth from 53m down to 20m. (b) Top of dipping dyke is centered
within the elongated hill at a depth from 61m down to 25m. (c)
Dipping dyke is offset from center of the elongated hill by 30m to the
east at a depth from 53m down to 20m. . . . . . . . . . . . . . . . . . . . 27
Figure 2.11 Observation height with locations denoted in white for (a) North
trending lines with 370 observation locations (b) East trending lines
with 370 observation locations and (c) North-east trending lines with
781 observation locations. . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
ix