Session 14
Conceptual targeting
of mineral deposits
Close
Close
Chapter 14-1
14-1
Regional targeting of epithermal Au-Ag deposits
in a Miocene-Pliocene volcanic terrane:
Hauraki goldfield, New Zealand
A.B. Christie, R.L. Brathwaite
Institute of Geological and Nuclear Sciences, PO Box 31-312, Lower Hutt, New Zealand
Abstract. Production from adularia-sericite epithermal Au-Ag deposits
of the Hauraki goldfield has been mainly from deposits hosted in
andesite and dacite (the Kuaotunu and Waiwawa subgroups of the
Coromandel Group), although there is potential for low grade large
tonnage deposits in rhyolitic rocks (the Whitianga Group). Andesite-hosted and rhyolite-hosted epithermal mineral deposit models
are identified, and the former are subdivided into Waiwawa and
Kuaotunu subgroup hosted types. Digital regional data sets enable
GIS-based regional targeting of prospective areas for the different
mineral deposit models, on the basis of host rock lithology and age,
lineaments identified in DEM and satellite imagery, aeromagnetic
anomalies, gravity anomalies, distribution of known mineral deposits,
areas of hydrothermal alteration, and stream sediment and rock
geochemical anomalies. Analysis of the paleodepth of epithermal
gold deposition in relation to stratigraphy enables definition of
unprospective areas where Au-Ag deposits have been substantially
eroded or where they are buried under thick cover rocks.
ite and lesser dacite (the Coromandel Group), and rhyolite and ignimbrite (the Whitianga Group). The Coromandel Group is subdivided into the Kuaotunu (early to mid
Miocene), Waiwawa (late-mid to late Miocene), Omahine
(late Miocene to Pliocene) and Kaimai (late Miocene to
Pliocene) subgroups, which are separated by periods of
volcanic quiescence and erosion. The Whitianga Group
rhyolitic rocks are late Miocene to Pliocene in age and
most abundant in the eastern central and southern parts
of the Coromandel Peninsula, where they are broadly associated with several calderas (Figs. 1A and 1C).
3
Epithermal mineral deposit models
The Hauraki goldfield contains about 50 adularia-sericite
epithermal Au-Ag deposits, including the World-class
Martha deposit at Waihi (Brathwaite et al. 1989). In addition to geological mapping, exploration of the Hauraki
goldfield in the 1970-1990s mainly used regional stream
sediment geochemical and aeromagnetic surveys to target undiscovered deposits. Research on the deposits, the
development of mineral exploration models (Christie and
Brathwaite 2003a), and the availability of large geological
and exploration data sets in digital form (Anon 2003) have
recently enabled the use of GIS-based, weights of evidence
prospectivity analysis (Rattenbury and Partington 2003)
in a systematic approach to regional targeting. We have
further developed prospectivity criteria, including the
optimum paleodepth window of Au-Ag mineral deposition (Christie and Brathwaite 2003b) to help narrow the
search for undiscovered deposits.
Based on known occurrences of Au-Ag deposits in the
goldfield, two epithermal Au-Ag mineral deposit models,
andesite-hosted and rhyolite-hosted, are considered the
most prospective for future exploration (Christie and
Brathwaite 2003a).
Andesite-hosted deposits comprise about 95% of past
gold production. Gold and silver are localised in quartz veins
that range up to 30 m wide and approximately 800 m long.
Deposits hosted in the Waiwawa Subgroup (Fig. 2B) have
relatively low Au:Ag ratios, and their veins are typically
colloform and crustiform banded. They are characterized
by cryptocrystalline or finely crystalline quartz, and the
occurrence of adularia and calcite. In contrast, deposits
hosted in the Kuaotunu Subgroup, and basement greywacke
(Fig. 2A), are characterized by relatively high Au:Ag ratios,
and their veins typically have coarse comb or massive quartz.
Adularia is absent or rare. Some of these deposits are represented by bonanzas, as at Coromandel and Thames.
Rhyolite-hosted deposits (Fig. 2C) have produced less
than 5% of the total historic gold production, but they have
potential as low grade, large tonnage deposits. Gold and
silver occur in sheeted and stockwork quartz veins, breccia
pipes and disseminated in hydrothermally altered wall rocks,
typical of hot springs type epithermal gold deposits.
2
4
Keywords. Epithermal, gold, silver, Hauraki goldfield, exploration, targeting
1
Introduction
Regional geology
The geology of the Hauraki goldfield (Fig. 1A) consists
of a block-faulted basement of Jurassic greywacke (the
Mania Hill Group) overlain by a thick sequence of andes-
Regional data sets for use in targeting
The main digital data sets available for regional targeting
include a digital elevation model (DEM), geological map,
lineaments identified in the DEM and Landsat, Spot and
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1458
A.B. Christie · R.L. Brathwaite
Jers-1 SAR satellite images, aeromagnetic anomalies, gravity anomalies, mineral deposits, hydrothermal alteration
map, stream sediment and rock geochemistry, and radiometric ages (e.g. Malengreau et al. 2000; Anon 2003;
http://www.gsnz.org.nz/geochron.zip).
Paleodepths of the Au-Ag mineralisation have been estimated in many of the deposits using features including
paleosurface indicators (e.g. sinters), hydrostatic pressures
estimated from fluid inclusions homogenisation temperature measurements, hydrothermal alteration, ore mineralogy, and vein textures (Christie and Brathwaite 2003b).
Together with geological modelling, particularly of
paleosurface indicators in the stratigraphy (e.g. lacustrine
and alluvial sediments), these help to identify areas where
mineral deposits are likely to be buried or eroded.
5
Discussion and conclusions
Permissible stratigraphic units for andesite-hosted deposits include the Kuaotunu and Waiwawa subgroups of
the Coromandel Group, and basement greywacke. The
Omahine and Kaimai subgroups, and the Whitianga Group
are cover rocks. The largest historic deposits are found in
the Waiwawa Subgroup, suggesting that this is the most
prospective unit for future exploration. The bonanza deposits of Coromandel and Thames that are hosted in the
Kuaotunu Subgroup were significant producers, however,
they were characterised by the poddy occurrence of ore
in a large number of veins of diverse strike, thus making
them less attractive targets for a =1 Moz Au deposit than
the Waihi style vein deposits of the southern region.
Close
Chapter 14-1 · Regional targeting of epithermal Au-Ag deposits in a Miocene-Pliocene volcanic terrane: Hauraki goldfield, New Zealand
Within the andesite terranes, significant areas can
be excluded on the basis that the level of exposure is
too deep for the preservation of gold deposits of =1 Moz.
Within these areas, any gold deposits formed in the
1459
past will have been extensively (or totally) eroded,
reducing their Au-Ag resources below economic size.
Within prospective areas, areas of hydrothermal alteration and structural corridors (e.g. the Karangahake-
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1460
A.B. Christie · R.L. Brathwaite
Ohui structural trend; Fig. 1C) seem to offer the best
potential. Rattenbury and Partington (2003) identified
the most prospective areas based on geological, geochemical and structural factors, but considered only areas of outcropping andesite and dacite. There is potential for deposits buried under cover rocks, particularly
under the Whitianga Group rhyolite and ignimbrite in
the eastern part of the goldfield (Fig. 2B). The known
rhyolite-hosted Au-Ag deposits could extend into underlying andesite and dacite. Elsewhere, exploration for blind
deposits could be assisted by the identification of faults
that may represent reactivated structures that host
epithermal deposits in the underlying andesite (e.g. the
structural corridors), and/or areas where the rhyolite
cover is thin. Conversely, areas where the rhyolite cover
is thick can be excluded. This particularly applies to the
calderas, which are filled with substantial thicknesses of
rhyolitic rocks (Fig. 1; Skinner 1986; Malengreu et al. 2000;
Smith et al. 2003), implying that any deposits hosted in
the underlying andesite will be buried very deeply (approximately 1-2 km).
Permissible stratigraphic units for rhyolite-hosted
deposits are the Whitianga Group rhyolites and ignimbrites found mainly in the eastern part of the goldfield
(Figs. 1A and 2C). Structure is an important control on
the deposits on a local scale, but apart from the
Karangahake-Ohui structural trend (Fig. 1C), little is
known of regional scale structures controlling the
localisation of the deposits. Also, to date there is no
clear relationship between known deposits and the
calderas. Thus, targeting is still based on the occurrence
of geochemical anomalies, and in some instances,
coincident geophysical anomalies, and, on a more detailed scale, mapped areas of hydrothermal alteration and
quartz veining.
Acknowledgements
Funding for this research was provided by the New Zealand
Foundation for Research Science and Technology (PGST
contract C05X0406). Ian Graham provided constructive
comments on the manuscript.
References
Anon (2003) Epithermal gold in New Zealand: GIS data package and
prospectivity modeling, Ministry of Economic Development and
Institute of Geological and Nuclear Sciences
Braithwaite RL, Christie AB (1996) Geology of the Waihi area, part sheets
T13 and U13. Scale 1:50,000. Institute of Geological and Nuclear Sciences Geological Map 21
Braithwaite RL, Christie AB, Skinner DNB (1989) The Hauraki goldfield
– regional setting, mineralisation and recent exploration. In: Kear D
ed, Mineral deposits of New Zealand. Australasian Institute of Mining and Metallurgy Monograph 13: 45-56
Christie AB, Brathwaite RL (2003a) Epithermal gold in New Zealand:
mineral deposit models. Institute of Geological and Nuclear Sciences
Science Report 2003/11
Christie AB, Brathwaite RL (2003b) Paleodepth studies of epithermal
Au-Ag deposits in the North Island of New Zealand: progress toward a 4D model. Proceedings of the 36th annual conference 2003,
New Zealand Branch of the Australasian Institute of Mining and
Metallurgy: 219-230
Malengreau B, Skinner DNB, Bromley C, Black PM (2000) Geophysical
characterisation of large silicic volcanic structures in the Coromandel Peninsula, New Zealand. New Zealand Journal of Geology and
Geophysics 43: 171-186
Rattenbury MS, Partington GA (2003) Prospectivity models and GIS
data for the exploration of epithermal gold mineralization in New
Zealand: 68
Skinner DNB (1986) Neogene volcanism of the Hauraki Volcanic Region. In: Smith, IEM ed., Late Cenozoic volcanism in New Zealand.
Royal Society of New Zealand Bulletin 23: 21-47
Smith N, Cassidy J, Locke CA, Mauk JL, Christie AB (2003) A geophysical study of the Waihi Region, New Zealand. Proceedings of the 36th
annual conference 2003, New Zealand Branch of the Australasian
Institute of Mining and Metallurgy
Close
Chapter 14-2
14-2
Conceptual models in gold exploration
Greg Hall
Placer Dome Asia Pacific, PO Box 1907 West Perth, WA 6872, Australia
Abstract. Process-based conceptual models for gold exploration are
replacing empirical based conceptual models. Comparison of both
types of targeting shows process modelling to be more predictive,
fewer and more accurate targets.
Keywords. Gold, prospectivity mapping, Laverton, 3D modeling,
Jiaodong
1
Exploration teams utilize different technologies at different scales. The typical scales are:
Regional, choose the metallogenic terrain for search,
for example Yilgarn Province;
District, choose the location within the terrain, for example Eastern Goldfields;
Local, choose the search area, for example Laverton.
Introduction
Exploration has two separate components:
Predict deposit location
Detect deposit existence
Prediction involves the use of some form of conceptual model to define the search area. Detection involves
the use of technology in the search area to establish the
target to be tested by the discovery drill hole.
Conceptual models can be classified as two types:
Empirical
Process
Empirical models are lists of features that are temporally or spatially associated with known gold mineralization.
Process models contain a model of the ore forming
processes and ranks empirical criteria based on the understanding of those processes.
The focus in the Regional and District scales is: largely
about deciding where not to explore as much as it is about
deciding where to explore.
An example of the application of empirical conceptual models is the discovery of Granny Smith gold mine
in Western Australia. In 1979 a prospector, Ray Smith,
decided to base himself in the town of Laverton and prospect this region because of the existence of two one million ounce past gold producing mines, Lancefield and Mt
Morgans in that region of the Eastern Goldfields within
the Yilgarn Block. He used the Australian Government’s
recently released 1:250,000 geological and aeromagnetic
maps to infer the strike direction of regional scale shear
zones and chose as his search area a location that showed
a small granite outcrop beside folded banded iron formations. His previous experience of prospecting in the
Canadian Superior Province had taught him that iron formations adjacent to small granites in regionally extensive shear zones could host one million ounce gold deposits, for example the Hard Rock gold mine in the
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1462
Greg Hall
Beardsmore greenstone belt in Ontario. His prospecting
detected gold in this area near Laverton and he pegged
what was to become the Granny Smith gold mine 11 years
later. The 8 year delay in the discovery of the deposit within
the pegged search area was due to deep weathering, superficial cover of the main ore zone and inappropriate
search technology by the first three explorers. The prevailing orthodoxy at the time was all major gold deposits
in the Yilgarn are hosted by fractionated dolerite sills
within the basaltic section of the greenstone belt.
Learning 1 Choose terrains where one million ounce
gold deposits have already been identified Granny Smith
Gold Mines completed two GIS based prospectivity analyses of the Laverton area during the first ten years of operation. The first approach in 1991 used the Prospector
software which requires an expert to decide on the appropriate criteria to be used and to set the mathematical
probabilities to apply to these criteria. This analysis predicted the location of all major gold discoveries in the
search region in the next ten years. The positive search
area occupies less than 10% of the search area (Fig. 1). A
second approach in 1996 used all empirical criteria and
applied the Weights-of-Evidence software (Fig. 2). This
analysis did not predict the location of the Wallaby gold
deposit unlike the earlier 1991 analysis. Wallaby gold deposit was discovered in 1997.
An example of Process Oriented Target Selection is an
outcome of the Yilgarn Project within the Australian
Geodynamics Cooperative Research Centre (AGCRC) in
1996. This project involved a regional seismic traverse
through the Kalgoorlie District in the Yilgarn Province
followed by numerical modelling of the interpreted structure of the crust (Ord et al. 1998). The modelling was interpreted into a conceptual model for gold exploration
(Hall 1998). This conceptual model led to the identification of five targets in the Eastern Goldfields province
(Fig. 3). One of the targets was the site of the Wallaby
Discovery in 1997 and another target was adjacent to the
Thunderbox discovery in 1999. This mis-match of target
and discovery led to a revision of targets in the northern
half of the Eastern Goldfields. The current predictions of
the sites of one million ounce gold mineral systems are
shown in Figure 3.
Learning 2 Giant gold systems are located in the immediate hanging wall of structures that transect the entire crust 3D geological modelling and 3D geophysical
inversion technology have been applied to datasets in the
Jiaodong Peninsula of Shandong Province China to develop a conceptual model for targeting gold deposits in
this region. The model establishes the intersection of fault
fracture zones located deep in the crust with extensional
faults in the upper crust as the primary control on the
Close
Chapter 14-2 · Conceptual models in gold exploration
location of the Linglong Goldfield, China’s largest historical
hard rock gold producer. Other intersections define primary targets.
Other major gold mineral systems have been shown
to lie at similar intersections in the Carlin mineral field
in the USA (Muntean, et al. 2003), the Muruntau mineral
field in Uzbekistan (Wall et al. 2004) and Porgera in Papua
New Guinea (Hall 1993).
Learning 3 Giant gold systems are located in sedimentary sequences overlying transfer faults in thinned continental crust
References
Hall G (1993) The Porgera Exploration Model. Unpublished report
of Placer Dome Asia Pacific Limited, No WA 329/93: 28
1463
Hall G (1998) Autochthonous Model for gold metallogenesis and exploration in the Yilgarn. In: Proc. of Geodynamics and Gold Exploration in the Yilgarn Workshop, Australian Geodynamics Cooperative Research Centre, Perth, Western Australia, June 6: 32-35
Muntean J, Coward M, Tarnocai C (2005) Reactivated Pre-Antler
Normal Faults: Controls on the Formation of Lower Plate Windows, mineral Belts and Carlin-type Gold Deposits in North-Central Nevada. In Press
Ord A, Hobbs BE, Walshe JL, Zhao C (1988) Development in the simulation of geodynamic processes with direct application to Yilgarn
gold mineralization. In: Proc. of Geodynamics and Gold Exploration in the Yilgarn Workshop, Australian Geodynamics Cooperative Research Centre, Perth, Western Australia, June 6: 45-51
Wall V, Graupner T, Yantsen V, Seltmann R, Hall G (2004) Muruntau,
Uzbekistan: A giant thermal aureole gold (TAG) system. In: J.
Muhling et al. (eds), SEG 2004: Predictive Mineral Discovery
Under Cover; Extended Abstracts. Centre for Global Metallogeny,
The University of Western Australia, Publication 33:199-203
Close
Close
Chapter 14-3
14-3
Reflection extraction with wavelet package
transform in Vibroseis mineral deposit exploration
Z.J. Jiang, X.J. Qiu, H.W. Chen
State Key Laboratory of Modern Acoustics and Institute of Acoustics, Nanjing University, Nanjing, 210093, China
J. Lin, Z.B. Chen
Institute of Intelligent Instrument & Measurement Control Technology, Jilin University, Changchun, 130026, China
Abstract. Vibroseis is widely used in mineral deposit seismic exploration. In the vibroseis signal processing, the reflected sweep signals should be detected from the trace data and their time delay
should be estimated. The depth and thickness can be measured in
accordance to the time delay of the reflected sweep signals. The
conventional method of reflection detection and time delay estimation is cross correlation and deconvolution, but their performance
in denoising is unsatisfactory.
In this paper a time-frequency cross correlation algorithm (TFCC
algorithm) is put forward to detect the reflected sweep and estimate the time delay. In this method the source sweep and the trace
data are both transformed into time-frequency domain with wavelet package transform, then a two-dimensional cross correlation in
the time frequency domain between the source sweep and the trace
data is performed. The time-frequency correlation wavelet will peak
in the place of the reflected sweep indicating the corresponding
time delay. After application of the TFCC algorithm the trace data
are converted to a seismic section for interpretation. The results of
numerical experiment prove that the TFCC algorithm can estimate
the time delay more accurately and have a better performance in
suppressing ambient noise than the conventional algorithms.
Keywords. Vibroseis, sweep signal, mineral deposit exploration, wavelet package transform, TFCC algorithm, time delay estimation
1
Introduction
Vibroseis is a principal kind of seismic exploration, and
has been widely used in mineral deposit surveys. Sweep
signal is the source signal used in vibroseis, and it is a
linearly frequency-modulated signal whose instantaneous
frequency varies linearly versus time. In vibroseis, source
sweep signal is output downwards and propagates underground. When the sweep is confronted by a stratum
surface it will be reflected and received by the geophone.
Usually there are more than one reflected sweeps in the
trace data at different time delays. The principle of
vibroseis is illustrated in Figure 1.
In order to convert the trace data into a seismic section that can be interpreted, we should detect the reflected
sweeps from the trace data and estimate their time delay.
The conventional method of reflection detection and time
delay estimation is cross correlation (Carter 1993). This
operation is usually performed before vertical stacking
and CMP (common mid-point) stacking. Cross correlation is simple in realization and computationally efficient,
but it is extremely sensitive to distortion of the waveform
of reflected sweep, so it cannot present a satisfactory effect when the trace data are corrupted by ambient noise.
Deconvolution is an alternative tool of converting raw
trace data into seismic section (Brittle et al. 2001). This
algorithm can present a high resolution in its seismic section, but it is also sensitive to ambient noise so cannot
suppress ambient noise effectively.
Because the instantaneous frequency of the sweep varies with time, vibroseis trace data can well be analyzed
with methods based on time-frequency analysis, which
has been widely used in vibroseis signal processing in
recent years.
Short time Fourier transform (STFT) was successfully
used in the decomposition of vibroseis trace data (Okaya
et al. 1992), which transform the trace data with a fixed
rigid time-frequency window.
The multiple filter technique (MFT) has been used in
analysis of sweep signal harmonic distortion (Li et al. 1995;
Li 1997). The vibroseis data is transformed into a twodimensional function in time-frequency domain with a
family of narrow Gaussian filters, and the fundamental
sweep and its harmonic distortions can be presented
clearly.
The extended correlation has been applied in extracting the information of reflection in vibroseis signal pro-
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Z.J. Jiang · X.J. Qiu · H.W. Chen · J. Lin · Z.B. Chen
cessing, which consists of two types of algorithm, namely
the “fixed-bandwidth” algorithm and “self-truncating”
algorithm (David et al. 1989). The extended correlation
has been applied to get longer seismic profiles than conventional cross correlation while with the same raw trace
data (Oliver et al. 1977; Finckh et al. 1986), but this method
is only fit for the up sweep signals.
In this paper a new algorithm based on wavelet package transform is proposed to detect the reflected sweeps
in trace data and estimate their time delay. In this algorithm the source sweep and trace data are transformed
into time-frequency domain with wavelet package transform, then two-dimensional cross correlation in time-frequency domain is performed. In the calculation result
time-frequency correlated wavelets take the place of the
sweeps in the trace data, and this result can be used as a
seismic section to image the stratum underground and
show the depth and thickness of the mineral deposit. The
results of numerical experiments show that the new algorithms can present better performance than the conventional algorithm.
2
Wavelet package transform of vibroseis trace data
Wavelet package transform was developed by Wickerhauser
and Coifman et al. based on wavelet transform. It can focus
on any interesting frequency band of the trace data, so
not only can it decompose the trace data iteratively in a
low frequency band like wavelet transform, but also it can
decompose the trace data in a high frequency band with
more and more detail.
In binary wavelet package transform, wnj,k(t) is a decomposing function family deriving from the function
w(t), it can be represented as following (Peng 2002):
wnj,k(t) = 2–(j/2)wn(2–jt – k)
j,k ∈ Z
(1)
Here the j is discrete scale factor and the k is discrete
time shift factor. The parameter n denotes sequence of
the frequency bands in a same scale j from low frequency
to high frequency. The wnj,k(t) can be looked as a bandpass filters for frequency band
In wavelet package transform, the relation between
decomposing functions of two adjacent scales can be presented with a filter bank, gk and hk, which can be represented as (Peng 2002):
(3)
This equation set can be called a two-scale equation
set. The gk and hk are high frequency filter and low frequency filter respectively. After a long derivation, the relation between decomposing coefficients of two adjacent
scales can be represented as (Peng 2002):
(4)
This is the Mallat algorithm in wavelet package transform with which the decomposition coefficients can be
calculated efficiently.
From Eq. (4), for every decomposition the length of
the output is half that of the input. In this paper in order
to raise the liability of calculation, the Mallat algorithm
was modified as follows:
(5)
The algorithm based on Eq. (5) has a better effect than
Eq. (4) in reflection detection and time delay estimation,
and it can suppress environmental noise very effectively.
The wavelet package transform of a sweep signal is illustrated in Figure 2(a), which is evenly decomposed in frequency domain. Because the instantaneous frequency varies linearly versus time, its wavelet package transform is a
line in the time frequency domain. The wavelet package
transform of a trace data is given in Figure 2(b), in which
there are four reflected sweeps with different time delays.
3
Each frequency band of the signal can be decomposed
with wnj,k(t) as following:
Time frequency cross correlation algorithm
In order to detect the reflection from the trace data and
estimate their time delay, two-dimensional cross correlation in time-frequency domain (TFCC) is put forward in
this paper and it can be presented as following:
(2)
where cnj,k denotes the decomposing coefficients (Peng
2002). The x(t) is the decomposed signal such as the source
sweep or the trace data.
(6)
Close
Chapter 14-3 · Reflection extraction with wavelet package transform in Vibroseis mineral deposit exploration
4
The TFCC (τ) is a one-dimensional variable in time
domain and it is the result of TFCC algorithm. The WPTs
(j, k) and WPTx (j, k) are wavelet package transform of
the source signal s(t) and the trace data x(t) respectively.
The parameter τ represents the relative shift in time domain between WPTs (j, k) and WPTx (j, k). In the algorithm WPTs (j, k) shifts in time domain one by one, and
the two-dimensional cross correlation coefficient is calculated simultaneously. The TFCC (τ) will peak when τ is
equal to the time delay of any reflected sweep, which is
illustrated in Fig. 2(c). Results of every trace can be used
to compose the seismic section.
The Eq. (6) is complex and not efficient in computation, so the TFCC algorithm can also be performed as:
(7)
The result of this algorithm needs to be normalized,
which is more efficient in calculation. It is a pure linear
algorithm and usually presents a better performance than
the algorithm in Eq. (6), so the results of numerical experiments in this paper are worked out with Eq. (7).
From Figure 2 the virtues of time-frequency domain
analysis are presented clearly. When the trace data is represented in time-frequency domain, different embedded
sweeps are separated from each other, even noise can be
separated from the sweeps. In TFCC algorithm, the interference of the ambient noise to the embedded sweeps and
interference between every two embedded sweeps to each
other can both be avoided, so TFCC algorithm can suppress ambient noise very effectively.
1467
Numerical experiments
A numerical experiment has been performed with different algorithms including deconvolution, cross correlation and TFCC algorithm, and their results are compared with each other. The length simulating discrete series is 2048, and the simulated source signal is a sweep
signal whose frequency changed from 20 to 400Hz linearly. The simulated trace data consisted of six reflected
sweep signals of different time delays and additive colored Gaussian noise whose frequency band was 20 to
400Hz. For every dB Monte Carlo experiments were performed more than 500 times to get the statistical results.
The results of time delay estimation versus different
SNR are given in Fig. 3, in which the curves near “DECV”,
“CC” and “TFCC” are results of deconvolution, cross correlation and TFCC algorithm respectively. The detection
probability is given in Figure 3(a), and corresponding false
probability of the detection probability is 0. The rate of
estimation error, namely the ratio of standard deviation
of estimation to the real time delay is given in Figure 3(b).
The results show that the TFCC algorithm can suppress
ambient noise very effectively and estimate the delay accurately when SNR is higher than -55dB, while the cross
correlation and phase data algorithm are effective only
when the SNR is higher than -12dB and -5dB respectively.
5
Conclusions
In according to the characteristic of the frequency spectrum of sweep signal, a TFCC algorithm of sweep signal
time delay estimation is put forward based on wavelet
package transform. The source sweep signal and the trace
data are both decomposed with wavelet package transform, and two-dimensional cross correlation in time frequency domain is performed to estimate the time delay
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Z.J. Jiang · X.J. Qiu · H.W. Chen · J. Lin · Z.B. Chen
of the reflected sweep signals. The results of numerical
experiments prove that the performance of time delay
estimation of the TFCC algorithm is better than the conventional cross correlation and deconvolution.
References
Brittle KF, Lines LR, Dey AK (2001) Vibroseis deconvolution: a comparison of cross-correlation and frequency-domain sweep
deconvolution, Geophysical Prospection 49: 675-686
Carter GC (1993) Coherence and time delay estimation: an applied
tutorial for research, development, test, and evaluation engineering, IEEE Press
David AO, Craig MJ (1989) Extraction of deep crustal reflections from
shallow Vibroseis data using extended correlation, Geophysics
54: 555-562
Finckh P, Frei W, Fuller B, Johnson R, Mueller S, Smithson S, Sprecher
C (1986) Detailed crustal structure from a seismic reflection survey in northern Switzerland, in Barazangi, M., and Brown, L., Eds.,
Reflection seismology: a global perspective: Am. Geophys. Union,
Geodyn. Ser 13: 43-54
Li XP (1997) Decomposition of vibroseis data by the multiple filter
technique, Geophysics 62: 980-991
Li XP, Sollner W, Hubral P (1995) Elimination of harmonic distortion in vibroseis data, Geophysics 60: 503-516
Okaya DA, Karageorgi E, McEvilly ThV, Malin PE (1992) Removing
vibrator-induced correlation artifacts by filtering in frequencyuncorrelated time, Geophysics 57: 916-926
Oliver J, Kaufman S (1977) Complexities of the deep basement from
seismic reflection profiling, in Heacock JG, Ed, The earth’s crust:
Am. Geophys. Union Mono 20: 243-253
Peng YH (2002) Wavelet Transform and Application in Engineering,
Science Publish House, Beijing
Close
Chapter 14-4
14-4
Mineralisation potential mapping for ophiolitehosted volcanic massive sulphide (VHMS) deposits,
Troodos Ophiolite, Cyprus
S.M. Jowitt
University of Leicester, Department of Geology, University Road, Leicester, LE1 2HD, UK
F.M. McEvoy, J. P. Williamson, L. Bateson, J. Naden, A. G. Gunn
British Geological Survey, Kingsley Dunham Centre, Keyworth, Nottingham, NG12 5GG, UK
S. Nicolaides
Geological Survey Department, Ministry of Agriculture and Natural Resources, 1415, Nicosia, Cyprus
Abstract. Data from a variety of sources can be used to generate
realistic exploration targets for VHMS mineralisation in the Troodos
ophiolite, Cyprus. This project used a weights of evidence approach
with new data sources, in conjunction with older legacy data, to
define areas of high mineralisation potential and targets for future
exploration work. The final prospectivity map, identifying areas of
low, medium and high mineralisation potential, defined eight areas with high mineralisation potential. Three of these areas have
been outlined as possible targets for future exploration due to their
size, lack of previously known mineral occurrences, and proximity
to known mineral occurrences and mining districts on Cyprus.
Keywords. Spatial data modelling, ArcSDM, massive sulphide, weights
of evidence, Cyprus
1
Introduction
Mineralisation potential or prospectivity mapping is a
digital extension to traditional geochemical, geophysical
and geological exploration methodologies, replacing the
older, non-reproducible light-table method of overlaying
data. Mineralisation potential maps are constructed using statistical modelling techniques (e.g. weights of evidence, fuzzy logic) and use mineral deposit models and
spatial digital data. Mineral deposit models are a summary of the state of knowledge about a given mineral
deposit. Two types of deposit model are encountered (i)
empirical (descriptive), here, various attributes such as
host-rock lithology, deposit form (vein, stockwork), alteration, ore mineralogy etc. are considered to be essential to the model, even though their various relationships
may be unknown and (ii) theoretical (genetic), where
mineral deposit attributes are interrelated through fundamental mineralisation concepts such as fluid chemistry, temperature and metal precipitation mechanisms (Cox
and Singer 1986). The best are, however, an amalgamation of empirical information and genetic concepts—a
typical example would be that developed by Hedenquist
et al. (1996) for epithermal mineralisation. The mineral
deposit model controls the selection of the most appro-
priate input data themes and statistical methods are used
to integrate various data layers to produce the mineral
potential map.
2
Methodology
The mineral deposit model for cupriferous mineralisation
in the Troodos ophiolite was created from a literature review of Cyprus and other VHMS deposits. Its essential
parameters are:
1. Deposits are associated with spreading centres found
at ocean ridges and oceanic arcs. They occur in the
submarine environment and are controlled by fault
systems and grabens. Host rocks are mafic-dominated
extrusive lavas of variable age.
2. Deposit form is as massive sulphide lenses, disseminations and stockworks with stratigraphy, feeder structures and alteration envelopes controlling ore distribution.
3. Close to mineralisation, alteration comprises pyrite,
sericite, chlorite and silica, whilst away from mineralisation, alteration is dominantly argillic, propylitic or
carbonitic.
Digital geology (1:250 000) for the analysis was provided by the Geological Survey Department, Cyprus. Other
available digital data were ASTER satellite imagery, digital elevation models and regional gravity (Gass and
Masson-Smith, 1963). In addition, legacy map data
(1:31,680) were scanned and georeferenced to digitise
mineral occurrences, gossan locations and small-scale
faults. The satellite data were processed to give a single
tiled image for the whole island and parameters extracted
to highlight relative mineralisation-related alteration intensity (Sabins, 1999).
Geochemical data for the study area is available and
has been incorporated into the GIS, but spatial coverage
was limited and therefore it was not used in the
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S.M. Jowitt · F.M. McEvoy · J. P. Williamson · L. Bateson · J. Naden · A. G. Gunn · S. Nicolaides
prospectivity analysis. Similarly, geophysical data in the
form of low and high-resolution airborne magnetic surveys were not used in this regional study. However, future mineralisation potential mapping at the deposit and
district scales will make use of these data. Initial investigation of the magnetic data, in particular, has highlighted
a number of subsurface lineaments that relate closely to
mineral deposits and could be of further use in mineral
potential mapping on a more localised scale than the regional analysis presented here.
The following exploration model, which only utilises
available data, was developed:
1. Deposits are typically fault-associated and in some
cases these have acted as preferential hydrothermal
fluid conduits.
2. Economic deposits can be capped by gossans and are
commonly associated with umber, gold and ochre deposits.
3. Alteration assemblages identified using a Portable Infrared Mineral Analyser were used to ground-truth
ASTER imagery to indicate zones of mineralisationassociated alteration.
4. Deposits are preferentially associated with specific
lithological units and contacts that may represent hiatuses in magmatism.
5. Mineralisation is associated with regional Bouguer
anomaly values between 146.7 and 166.7 mGal.
analysing the spatial association between points of known
mineralisation (disused and working mines, prospects) and
the various rock units depicted on the geological map. This
simplifies the map into units associated with mineralisation
and units that are not. Similarly, the association between
faults and mineralisation was examined. Because faults are
lines, they are given additional thicknesses—buffers—to
enable the definition of the spatial extent of their association with mineralisation. A series of buffers are set at regular intervals of, say, 100 m around each fault. The analysis
procedure then calculates the distance where the spatial
association between faults and mineralisation breaks down.
This distance is then used to create a binary map of thickened faults, where the thickness is defined by the extent of
the spatial relationship between the dataset and mineralisation. Likewise, binary maps can be created for a variety
of other parameters, such as geological contacts and satellite lineaments.
The procedure of generalisation, as well as simplifying data to binary maps, also calculates how prospective
each theme is. When generalisation is complete, the individual binary map themes and their associated
prospectivity weightings are integrated to produce the
final prospectivity map. For detailed descriptions of the
statistical theory behind the methodology and use of the
software see Tangestani and Moore (2001) and Kemp et
al. (2001).
3
The process of binary weights-of-evidence prospectivity
analysis involved converting (generalising) individual data
themes (e.g. fault, geological and geophysical maps) into
binary maps that indicate prospective and unprospective
areas. For the geology, this was carried out by statistically
Results
The final prospectivity analysis (Fig. 1), using ArcView™
and the Spatial Data Modeller extension (Kemp et al. 2001),
was undertaken using seventeen data themes (Table 1). It
identified eight areas of high mineral potential, all lo-
Close
Chapter 14-4 · Mineralisation potential mapping for ophiolite-hosted volcanic massive sulphide (VHMS) deposits, Troodos Ophiolite, Cyprus
cated within 10 km of the boundary between the Troodos
ophiolite and the autochthonous sedimentary cover sequences draping the ophiolite. The exploration criteria
used in the prospectivity analysis are listed in Table 1.
4
Discussion
Areas with high mineral potential in Figure 1 are all related to clusters of known mineral occurrences. However,
areas with large numbers of mineral occurrences may
indicate that reserves have already been exploited. Area
H, and the northern extension of area A, located within
the 1:31,680-scale mapping area and with few known min-
1471
eral occurrences, are more attractive targets with little
mining history. Area D is also worthy of note. It is large in
size (approximately 10 by 10 km) and includes known
mineralisation at some localities. Although some of these
have been worked, it may indicate prospectivity in adjacent regions with sedimentary cover.
In contrast, the known Troulli and Limni—Kinousa—
Uncle Charles—Evloymeni (LKUCE) mining districts are
indicated as non-prospective (Figure 1). For these areas,
this may be because they are not covered by the
1:31,680-scale geological mapping. Therefore, as three
major exploration themes—high-resolution geology,
structure and gossan distribution—are absent over these
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S.M. Jowitt · F.M. McEvoy · J. P. Williamson · L. Bateson · J. Naden · A. G. Gunn · S. Nicolaides
two areas, they would not be indicated as prospective by
a weights-of-evidence approach. In this instance, a fuzzy
logic analytical methodology may be more appropriate.
Though most of the ASTER and Landsat band ratio
images seem unprospective (Table 1), the tiled ASTER
image does appear to highlight hydrothermal pathways
in the sheeted dyke complex. In the imagery, these are
visible as distinct linear structures that are coincident with
lineaments defined by the airborne magnetic data and
are also related to linear arrays of gossans. Further analysis
of individual ASTER images, rather than the single tiled
image, along with further PIMA ground-truthing is required to fully assess the significance of these trends.
Acknowledgements
This work is part of a collaborative research programme
between the Geological Survey Department (GSD), Cyprus
and the British Geological Survey (BGS) and is funded
by the Government of the Republic of Cyprus. The Hellenic Mining Company Ltd, Eastern Mediterranean Minerals (Cyprus) Ltd. and Oxiana Resources NL are also
thanked for access to a variety of proprietary information. Permission to publish for JN, LB, FMM, JPW & AGG
is by the Director, BGS, NERC, UK and for SN by the Director, GSD, Cyprus.
References
5
Conclusions
Mineralisation potential mapping has identified eight separate areas of high mineral potential. The areas are located
at or within 10-km of the boundary between the Troodos
ophiolite and the autochthonous sedimentary cover sequences. Areas A, C and H, and to a limited extent area D
are considered to be the most prospective. These include
relatively few mineral deposits, but have comparatively large
areas of high mineral potential, indicating unexploited
ground with the correct characteristics for massive sulphide
and stockwork mineralisation. Though not indicated directly, buried deposits in areas overlain by sediments but
adjacent to areas of high mineral potential should also be
considered, and may be highlighted by future more detailed
prospectivity mapping that includes the recently obtained
magnetic and geochemical data.
Cox DP, Singer DA (1986) Mineral deposit models. Reston, VA, United
States, U. S. Geological Survey
Gass IG, Masson-Smith SD (1963) The geology and gravity anomalies of the Troodos Massif, Cyprus. Philosophical Transactions
of the Royal Society London, Series A: Mathematical and Physical Sciences, 255: 417-467
Hedenquist JW, Izawa E., Arribas A, White NC (1996) Epithermal
gold deposits; styles, characteristics, and exploration. Resource
Geology Special Publication 1, Society of Resource Geology. Tokyo, Japan, 70
Kemp LD, Bonham-Carter GF, Raines GL, Looney, CG (2001) ArcSDM: ArcView extension for spatial data modelling using
weights-of-evidence, logistic regression, fuzzy logic and neural
network analysis (software). http://ntserv.gis.nrcan.gc.ca/sdm/.
Sabins FF (1999) Remote sensing for mineral exploration. Ore Geology Reviews, 14: 157-183
Tangestani MH, Moore F (2001) Porphyry copper potential mapping using a weights-of-evidence model in a GIS, northern Shahre-Babak, Iran. Australian Journal of Earth Sciences, 48: 695-701
Close
Chapter 14-5
14-5
Probabilistic analysis for regional mineral potential
mapping with GIS for sedimentary ore deposits in the
Kangwondo Area, Korea
Kim In Joon, Lee Jae Ho, Lee Sa Ro, Kim Yu Dong
Korea Institute of Geoscience & Mineral Resources, 30 Gajeongdong, Yuseongku, Daejon 305-350, Korea
Abstract. The Kangwondo area consists of Precambrian metamorphic
complex, Paleozoic sedimentary rocks, Mesozoic sedimentary and
volcanic rocks and Mesozoic to Cenozoic pultonic rocks. Identified
mineralised areas of sedimentary ore deposits are composed of limestone, iron and bentonite. Techniques for mineral resources management, assessment and prediction must be developed for the exploitation of the mineral resources. The most common approach to mineral potential mapping is data-driven, and exploits knowledge about
how known deposits spatially relate to their surroundings. The aim
of this process is to analyse relationships between sedimentary mineral deposits and related factors to identify areas that have not been
subjected to the same degree of exploration. The relationship coefficient (R2) can be used for relating between mineral deposit and factor. So we used the coefficient value as the criteria.
In the study we set the criteria as follows:
1. R2 < 0.4: Weak relationship
2. 0.4 < R2 < 0.6: Normal relationship
3. R2 > 0.6: Strong relationship
From these criteria, the Fault density, alkali, As, Ca, conductivity,
Fe, HCO3, Mg, Mo, Na, Ni, NO3, Pb, pH and SO4, showed a strong relationship between sedimentary mineral deposits. However DEM, slope,
dis-tance from fault, Cd, Cr, Cu, K, NO2, V and W, showed a very weak
relationship between sedimentary mineral deposits.These results are
well matched with the sedimentary mineral deposits. Therefore, this
empirical approach assumes that all deposits share a common genesis and comprises of three main steps such as identification of spatial relationships and quantification of identified spatial relationships.
For this, a spatial database including sedimentary mineral deposit,
topographic, geologic, geophysical geochemical and satellite imagery data were constructed for Kangwondo area in Korea using GIS.
Using the constructed spatial database, the relationships between
metamorphic mineral deposit area and related factors were identified and quantified by a probabilistic model. The relationships can
be used for mapping of regional mineral potential using the overlay
method in GIS environment. A GIS was used to efficiently analyse the
vast amount of data and the frequency ratio and logistic regression
models proved to be an effective tool to analyse the mineral potential mapping.
Keywords. Kangwondo area, mineral potential mapping, sedimentary mineral deposits, coefficient (R2), GIS
1
Introduction
The most common approach to mineral potential mapping is data-driven, and exploits knowledge about how
known deposits spatially relate to their surroundings. The
aim of this process is to analyse relationships between sedimentary mineral deposits and related factors to identify
areas that have not been subjected to the same degree of
exploration.
This empirical approach assumes that all deposits share
a common genesis and comprises of three main steps such
as identification of spatial relationships, quantification
of identified spatial relationships and integration of multiple quantified spatial relationships. For this, a spatial
database including metallic mineral deposit, topographic,
geologic, geophysical, and geochemical data were constructed for Kangwondo area in Korea using GIS.
The 391 mineral deposits used were limestone, iron and
bentonite deposits, and as the related factors, topographic
data such as DEM and slope, geological data such as lithology and fault, geochemical data such as Al, As, Ba, Ca, Cd,
Co, Cr, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, Pb, Si, Sr, V, Zn, Cl-,
F-, PO42-, NO2-, NO3- and SO42-. Geophysical data such as
free air, bouguer and magnetic anomalies were used.
Using the constructed spatial database, the relationships between mineral deposit areas and related factors
were identified and quantified by probabilistic model.
Among the factors, distance from Faults, a, Fe, Mg, Ph,
SO42- and W were used for mapping of regional mineral
potential using overlay method in GIS environment because there was a close relationship (R2>0.6) between
mineral deposit and the factors. Then, the mineral potential map was verified. The verification results showed
satisfactory agreement between the mineral potential map
and the existing mineral deposit area.
A GIS was used to efficiently analyse the vast amount
of data, and the probability model proved to be an effective tool to analyse the mineral potential mapping.
2
Method
The aim of this study is to analyse relationships between
metallic mineral resources and related factors. The deposits used were limestone, iron and bentonite. As the related
factors, topographic data such as DEM and slope, geological data such as fault, geochemical data such as Al, As, Ba,
Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, Pb, Si, Sr, V,
Zn Cl-, F-, PO42-, NO2-, NO3- and SO42-, and geophysical data
such as free air, bouguer and magnetic anomaly were used.
The study area is Kangwondo. For the detail, 1:250,000
scale Gangreung Geological Sheets areas were selected for
Close
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Kim In Joon · Lee Jae Ho · Lee Sa Ro · Kim Yu Dong
the study area. The area has many mineral deposits. In addition the geochemical and geophysical survey data is available for the study area. The study steps are as follows:
1. The total of 391 mineral deposits, (which are composed
of three kinds of deposits - limestone, iron and bentonite) were constructed to spatial database using GIS.
2. Topographic map, geological map, geochemical map
and geophysical map were constructed to spatial database using GIS.
3. From the map database, the factors were extracted.
3
Relationship coefficients of mineral deposits
and related factors
The relationship coefficient (R2) can be used for relating
between mineral deposit and factor. So we used the coefficient value as the criteria. In the study we set the criteria such as followings:
1) R2 < 0.4: Weak relationship
2) 0.4 < R2 < 0.6: Normal relationship
3) R2 > 0.6: Strong relationship
From the criteria, the Fault density, alkali, As, Ca, conductivity, Fe, HCO3, Mg, Mo, Na, Ni, NO3, Pb, pH, and
SO4, showed a strong relationship between sedimentary
mineral deposits. However slope, distance from fault: Cd,
Cr, Cu, K, NO2, V, and W, showed a very weak relationship between sedimentary mineral deposits. These results are well matched with the sedimentary mineral deposits.
Therefore, this empirical approach assumes that all
deposits share a common genesis and comprises of three
main steps such as identification of spatial relationships
and quantification of identified spatial relationships. For
this, a spatial database including sedimentary mineral
deposits, topographic, geologic, geophysical and
geochemical; and satellite imagery data were constructed
for Kangwondo area in Korea using GIS.
Close
Chapter 14-6
14-6
Discussion on approximated estimation method of
the three-parameter lognormal distribution
Mengwen Li, Jingwen Mao, Mingguo Zhan, Huishou Ye
Institute of Mineral Resources, Chinese Academy of Geological Sciences, 26 Baiwanzhuang Rd., Beijing 100037, China
Baojian Guo, Fengmei Chai, Qinghong Xu
China University of Geosciences, 29 Xueyuan Rd., Beijing 100083, China
Abstract. Many regionalized variables in geostatistics often show
skew distributions. In this case it is possible to consider whether
they follow the lognormal distribution with three parameters. This
paper proposes a new method for the optimal estimation of the
three-parameters of these distributions. The test shows that the
approximated estimation is simple and effective for moderate and
large samples, so it is helpful to the statistical distribution testing
and statistical prediction of mineral resources.
Keywords. Geostatistics, regionalized variables, three-parameter lognormal distribution, general least square estimator, two-step iteration
1
Introduction
Suppose that the distribution of a regionalized variable
follows a three-parameter lognormal distribution with a
density function
(1)
let t ≥ µ and label it as T ~ LN(µ,θ,σ). The parameter space
is Θ = {(µ,θ,σ): –∞ < µ < ∞, θ > 0, σ > 0}. Let θ = log(η),
m = 1/σ. Then the distribution (1) can be expressed as
(2)
This paper discusses the method for estimating the
parameters µ, θ and σ in the three-parameter lognormal
distribution by using two local scale distribution families and asymptotic properties of the order statistics, that
is, the asymptotic mean and covariance of the three parameters in the large sample case. The estimation is done
via a two-step iteration (Tang 2001). First, assume the
shape parameter m in (2) (or σ = 1/m) as a given value
m0 (accordingly σ = 1/m0), like the maximum likelihood
estimator or the quantile estimator, or a value chosen by
experience. This value is taken as the beginning value of
m in the first step. The asymptotic generalized least square
estimators (AGLSE) of the other two parameters can be
obtained according to the asymptotic results of David
(1981) or Sen and Singer (1993) about the local scale distribution family. At the second step, we are given the location parameter µ as the estimator obtained in the first
step, say, µ0. Logarithmic transformation is then used to
transfer the distribution to a new local scale family distribution (3). The AGLSE of θ and σ can be easily got in
the first step. Next following the procedure in the first
step (which takes m as the AGLSE in the previous step)
and that in the second step (where µ is taken as the AGLSE
in the previous step), iteration proceeds repeatedly until
no improvement can be made of the parameter estimation. Sections 2 discusses the two-step AGLSE of the threeparameter lognormal distribution. Section 3 gives the
Monte Carlo simulation, which shows the feasibility of
the presented method.
2
Let t ≥ µ, which is still labelled as T ~ LN(µ,η,m). Note
that, if we take m as given, say m0, then the above distribution belongs to a location-scale family distribution.
Similarly, if µ is taken as given, say µ0, then Y = log(T – µ0)
has a distribution which
(3)
obviously belongs to a location-scale family distribution,
i.e. the family of normal distribution.
Two-step iterative estimation
Let T1, T2, …,Tn be a random sample from LN(µ,η,σ), and
the corresponding order statistics be Tn:1 ≤ Tn:2 ≤ … ≤ Tn:n.
Assume m(=1/σ) as a suitable value m0. Taking the standardized transformation
we have Tn:i = µ + ηT’n:i, i = 1, 2, …, n, the density of T’
(4)
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1476
Mengwen Li · Jingwen Mao · Mingguo Zhan · Huishou Ye · Baojian Guo · Fengmei Chai · Qinghong Xu
ϕ = (WnΓn–1Wn)–1WnΓ–1Tn
and the distribution function
(12)
With Cov(ϕ) = η 2(WnΓ–1Wn)–1, as
(13)
(5)
we know that
(14)
Suppose that ξpi is the pith = (i /n + 1)th quantile of
F0, such that F0(ξpi) = pi. From (5) we know
therefore
(6)
In other words, log(ξpi)/σ0 is the pith quantile of the
standard normal distribution N(0,1). Furthermore, we
have from the properties of sample quantile (Sen and
Singer 1993) for a large enough sample size n
(15)
where
(7)
(8)
That is, the AGLSE of µ and η are respectively
(16)
(9)
Thus they are all irrelevant to the parameters µ and η
to be estimated. Let
Tn = (Tn:1, Tn:2, …, Tn:n)t, ξn = (ξp1, ξp2, …, ξpn)t,
Γn = ((γij)), ϕ = (µ,η)t.
The estimator of θ is the logarithm of η~n, i.e.
(17)
By the way, we have
Then
(10)
(18)
where 1n is the all-1 n dimensional vector, Wn = (1n,ξn).
This leads to the linear model
Tn = Wnϕ + e
E(e) = 0
(11)
Cov(e) = η 2 Γn
We know that the AGLSE of θ has the form (Wang 1987)
For the second step in the iteration, take µ in (1) as the
estimator in the first step, simply expressed as µ0.
Let
Y=ln(T–µ0),
. Then
Close
Chapter 14-6 · Discussion on approximated estimation method of the three-parameter lognormal distribution
Yn:i = ln(Tn:i – µ0) = θ + σY’n:i, i = 1, 2, …, n,
1477
used to refine the estimators of σ and θ. This process is
repeated till no further improvement of estimation can
be achieved. In practice, this can be done by taking a certain small ε1 (say 10–4) and calculating the difference of
the two estimators of θ in the two steps
Y’ G0(y) = ϕ(t)
That is, Y’ follows N(0,1). Let ζpi be the pith = (i/n + 1)th
quantile of G0=N(0,1). Following the procedure in step
one, we have
If en < ε1, then stop iteration. Otherwise, as is often the
case, stop the repetition if two consecutive differences
(19)
(20)
are less than a certain sma11 ε2 (say 10–8). The final estimators of µ, θ and σ resolve at the last iteration. Under
the second supplementary checking conditions, the final
estimator of θ can be taken as the average of those in the
two steps, i.e.
(21)
(24)
regardless of the parameters θ and σ to be estimated. Let
However, Monte Carlo simulation in section 3 shows
that when the final estimator of θ is lower than the mean
square error, there is no need to make this kind of modification.
3
Test result
Assume that n = 40, µ = 100, θ = 4.0, and θ = 1.6. In the
complete sample case and 25% right censoring case, 1000
simulations are run separately. Table 1 gives the mean,
standard deviation (STD) and mean square error (MSE)
of parameter estimation (the values in the parentheses
are those for 25% censoring case). In the simulation, we
use ε1 = ε2 = 1.0 × 10–6.
We found through the above simulation:
Then the AGLSE of θ and σ are respectively
(22)
Analogously, we can write the variance and covariance
~
of θ n(2) and σ~n like (18). As a result, we now have an estimator of m = 1/ σ
1. For the moderate sample size, the estimators of σ, θ,
and µ have a rather high accuracy.
2. When n is large enough, the estimators of the three
parameters are asymptotically unbiased and normally
distributed.
3. The asymptotic estimators of σ, θ, and µ are almost
irrelevant to the choice of the beginning value of m,
i.e. m0.
(23)
Next, we return to the first step in which m is taken to
be the estimator in the second step. Then new estimators
of µ and η (or θ) can be obtained. The estimator of µ now
is taken to be given in the second step that follows and
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Mengwen Li · Jingwen Mao · Mingguo Zhan · Huishou Ye · Baojian Guo · Fengmei Chai · Qinghong Xu
4
Conclusions
The proposed method is effective in the case of moderate or large samples (n > 20) and at small censoring
ratios (m/n > 0.5). For small samples and large censoring ratios, the mean and covariance of the order statistics of the lognormal distribution LN(0,0,σ0) and
standard normal distribution N(0,1) need to be exactly
calculated.
From the generalized Gauss-Markov theorem (Wang
~
1987), the estimators of µ~n and hn or θn and ~sn are the best
asymptotic linear unbiased σ~n estimators for given m
or µ respectively.
Acknowledgements
This study was supported by the National Natural Science Foundation of China grant 40434011.
References
David HA (1981) Order Statistics, John Wiley, Sons, Inc
Sen PK, Singer JM (1993) Large Sample Methods in Statistics.
Chapman & Hall
Tang YC (2001) Approximated parameter estimation of three parameter lognormal distributions based on generalized least square
method. J Shanghai Teachers Univ (Natural Sciences) 30:14-20
Wang SG (1987) The Theory and Application of Linear Models.
Anhui Education Publishing House, Hefei (in Chinese)
Close
Chapter 14-7
14-7
Mapping of hydrothermal alteration and geochemical
gradients as a tool for conceptual targeting: St Ives
Gold Camp, Western Australia
Peter Neumayr, Klaus J. Petersen, Louis Gauthier, Joanna Hodge, Steffen G. Hagemann
School of Earth and Geographical Sciences, The University of Western Australia, 35 Stirling Highway, Crawley, Western
Australia 6009, Australia
John L. Walshe
CSIRO Exploration and Mining, ARRC, 26 Dick Perry Av, Kensingtom, Western Australia 6151, Australia
Kylie Prendergast, Karen Conners, Leo Horn, Peter Frikken
Gold Fields Australia, St. Ives Gold Mining Company Pty Ltd, Kambalda, Western Australia
Anthony Roache
School of Earth Sciences, University of Melbourne, VIC 3010, Australia
Richard Blewett
Geoscience Australia, Canberra ACT 2001, Australia
Abstract. Camp- to deposit-scale alteration halos at the kilometrescale are documented in the St. Ives gold camp, the Yilgarn Craton,
Western Australia. St. Ives has sulphide-oxide mineral footprints,
which are interpreted to represent different hydrothermal fluids, a
more reduced and a more oxidized fluid. Boundaries where reduced
and oxidized fluid domains border each other are particularly suitable for gold precipitation, suggesting a redox control on gold mineralization. Oxidized zones can be identified using detailed gravity
and aeromagnetic images as well as camp-scale, first-fresh-rock,
multielement whole-rock geochemistry and PIMA data. Stable isotope variations also match well spatially with reduced and oxidized
zones.
Keywords. Hydrothermal alteration, multiple fluids, gold, Archaean
1
Introduction
Traditionally hydrothermal alteration studies focused on
the ore shoot- to deposit-scale and were of limited value
for regional- to camp-scale exploration targeting, because
mineralogical alteration halos (e.g. biotite, chlorite) around
lodes are typically too small (e.g. <50 m). A number of
studies specifically targeted deposit- to camp-scale dispersion halos and determined pathfinder elements which
may be useful as vectors to mineralization (e.g. Eilu
Mikucki 1996). Importantly, it was recognized that only
very low detection analyses for critical elements (e.g. Te)
identified significant chemical dispersion halo patterns.
However, whilst the determined dispersion halos appeared
to be a useful guide to ore in the studied deposit they
tend to fail as a guide in some other deposits, indicating
that there are either different types of deposits, or a more
complex fluid flow pattern. These early studies assumed
single mineralization and fluid models and consequently
tried to identify concentric alteration and geochemical
dispersions around gold-bearing structures. In a series
of research projects in the last decade (Australian Minerals Industry Research Association project P511, Yilgarn 3
project of the predictive mineral discovery Cooperative
Research Centre and the Minerals and Energy Research
Institute of Western Australia M358 project) it has been
recognized that single fluid and mineralization models
for Archaean gold deposits do not adequately describe
observed hydrothermal alteration and geochemical dispersion patterns at a camp- to district-scale. It is now recognized that asymmetric, kilometre-scale alteration footprints can be identified in selected Archaean orogenic
gold deposits in the Yilgarn Craton of Western Australia
and gold mineralization occurs preferentially within or
subjacent to boundary zones between contrasting alteration domains (e.g. Neumayr et al. 2003, 2004).
2
Fluid reservoirs and chemical gradients in
Archaen terranes
Camp-scale variations in sulfide, oxide, and silicate mineralogy are interpreted in terms of fluids of different origins and contrasting chemistry on the basis of correlations between geological, geophysical, mineralogical and
geochemical data. At least three main fluid types/reservoirs are now recognized (ambient, magmatic, and mantle/
deep crustal fluids). Oxidized magmatic fluids were
sourced from 2665-2650 Ma mafic and syenitic granitemagmas. Chemically contrasting highly reduced fluids,
were sourced from the deep crust/ mantle. Walshe et al.
(2003) interpreted that these two fluids interacted to establish the significant chemical gradients, particularly
Close
1480
P. Neumayr · K.J. Petersen · L. Gauthier · J. Hodge · S.G. Hagemann · J.L. Walshe · K. Prendergast · K. Conners · L. Horn · P. Frikken · A. Roache · R. Blewett
redox gradients, at deposit to district scale. An emerging
understanding of the covariance of the S isotopes in pyrite
and C and O isotopes in carbonate is providing insight into
the interaction between the three major fluid types.
Fluid inclusion studies at St. Ives give evidence of rapidly changing fluid conditions with fluctuations from saline H2O rich fluids, prior to gold precipitation to CO2
rich fluids during gold precipitation, to extremely saline
H2O fluids post gold mineralization (Petersen 2005). Distinct fluctuations during the formation of the deposit from
CH4 rich, to H2O-CO2 fluids back to CH4 rich fluids at
New Celebration (Hodge et al. 2005) further emphasize
the importance of different hydrothermal fluids in the
system. Near surface environments potentially show the
influx of surface-derived, meteoric fluids, but their relationship to gold mineralization is unclear (Hagemann et
al. 1994).
3
Architecture and hydrothermal alteration
3.1 District-scale architecture
In the Kalgoorlie-Kambalda district of the Yilgarn Craton of Western Australia, the gold-mineralized corridor
lies along a NNW trend, bounded at its western side by
the Bardoc Fault System. Seismic reflection data across
the region reveal that faults dip both E and W with prominent faults, such as the Bardoc Fault System occurring as
a W-dipping structure.
Overall, the region is an antiform with major faults
dipping in opposing directions away from its apex. This
places the major Au deposits in the footwall of these master
faults and in two locations (e.g. Golden Mile, St. Ives) in
sub-parallel subsidiary faults to the master faults. At the
Golden Mile mineralization occurs within the steeply Wdipping Golden Mile Fault (sub-parallel to the Bardoc Fault
System), which could be interpreted as a minor fault linking to the Bardoc Fault System. At Kambalda the E-dipping Playa Shear appears to be related to the E-dipping
Lefroy Fault.
Orogenic gold mineralization in the Yilgarn Craton is
considered to be late during the orogenic event and was
dated in a number of Archaean gold deposits in the
Kalgoorlie-Kambalda corridor of the Yilgarn Craton at
around 2630 Ma (e.g. Groves 1993). However, recent structural studies indicate that Fimiston-style gold mineralization in the Golden Mile predates the regional D2 foliation (Gauthier et al. 2004), which indicates that the present
geometry does not match the geometry at the time of
mineralization. Similarly, earlier timing of gold mineralization has also been suggested for Kanowna Belle and
two gold events have been documented for the New Celebration gold deposits. Differentiating pre- and post-D2
gold mineralization is critical for the interpretation of
computer-based prospectivity maps of the terrane, that
assume the present map pattern reflects that of the time
of gold mineralization (e.g. Gardoll et al. 2000).
3.2 Camp-scale alteration zonations
Camp-scale alteration footprints have been identified in
the St. Ives, Kanowna Belle and Wallaby camps using mineralogical and geochemical criteria. In the St. Ives camp,
two different types of gold deposits are distinguished with
respect to the redox state of the hydrothermal fluids: 1)
reduced deposits (e.g. Argo, Junction), and 2) oxidized
deposits (e.g. all deposits in the Central Corridor, Bahama,
Santa Anna).
In the Central Corridor of the St. Ives camp, an oxidized magnetite-pyrite±hematite assemblage is spatially
associated with major gold deposits such as Victory-Defiance and Revenge. The oxidized mineral assemblage
forms alteration halos around shear zones. At a campscale, the oxidized mineral assemblage is focused on
kilometre-scale gravity lows which indicate abundant
porphyry intrusions at depth (about >500 m to 950 m
below present surface). A reduced assemblage of pyrrhotite-pyrite occurs within gently dipping shear zones and
disseminated in the wallrock, flanking the oxidized domains. Most importantly, high-grade gold intersections
(>100 ppm) and also most of the ore bodies at St. Ives
occur at the domain boundary between the oxidized and
reduced domains, but within the oxidized domain.
In the St. Ives camp, preliminary textural observations
indicate that oxidized magnetite-hematite-pyrite assemblage occurs broadly at the same time as the reduced pyrrhotite-pyrite assemblage at the domain boundary. Negative δ34S values in pyrite from the Victory-Defiance gold
deposits (down to -8‰) correlate spatially well with the
oxidized mineral domains, whereas zero to positive δ34S
values (up to 2‰) correlate spatially well with the reduced domains. Zones where both negative to positive
δ34S values on sulphides are observed host the gold deposits. Importantly, these zones also contain carbonates
with very low δ13C values (around -8‰). In combination,
δ34S and δ13C values indicate that sulphate or SO2 reacted
with CH4 or H2 establishing the presence of both oxidized
and reduced fluids in the system at about the time of gold
precipitation.
4
Exploration model
4.1 Geochemical gradients
District-scale mineralogical and geochemical data from
both diamond drill core and top of fresh rock samples
indicate the presence of kilometre-scale hydrothermal
alteration cells at St. Ives as well as in the Kanowna Belle
and Wallaby Camps. The mineral and geochemical data
are interpreted with respect to the physicochemical con-
Close
Chapter 14-7 · Mapping of hydrothermal alteration and geochemical gradients as a tool for conceptual targeting: St Ives Gold Camp, Western Australia
ditions of the hydrothermal fluids. Gold mineralization
occurs proximal to the boundaries of domains with oxidized and reduced assemblages, indicating that the chemical contrast between the different fluids has been critical
for the precipitation of gold.
“Fluid mixing” requires that oxidized and reduced fluids were transported in different structures and only interacted at the site of gold deposition. Further, both fluids have
to arrive at the site of interaction at the same time. Preliminary textural data from the St. Ives camp indicate a broadly
similar timing of reduced and oxidized alteration assemblages and δ34S and δ13C isotope data indicate that both
reductant and oxidant were in the system.
The mixing model does not exclude other processes
contributing to the observed patterns of alteration and
mineralization (e.g. interaction of a fluid with wall rocks
or with previously altered rocks). However, such processes
would be less efficient in precipitating gold mineralization than “fluid mixing”, sustaining the strongest chemical gradients at the time of gold deposition.
4.2 Practical exploration application
In the St. Ives gold camp, a range of critical geological
features which have a spatial relationship, and in some
cases a genetic relationship, to gold mineralization are:
Gravity lows, interpreted to represent felsic and intermediate intrusions at depth (>500 m – 950 m below
present surface).
Abundance of felsic and intermediate porphyry stocks.
Distinct magnetite-pyrite±hematite alteration halos
centred on gravity lows and abundance of porphyry
intrusions.
Pyrrhotite-pyrite alteration (reduced alteration assemblage) outboard to the SW and NE of the gravity low
and the oxidized alteration assemblage.
Strong magnetic response indicating presence of magnetite.
Weak magnetic response coincides spatially with pyrrhotite (reduced) domain.
S isotope zonation with strongly negative signals in
oxidized zones and zero to positive signals in the reduced zones.
Although all these geological features are straight forward to read in the individual data sets, some are more
complex and need to be analyzed in more detail to be
useful for exploration. For example, the magnetite halo is
readily detected using magnetic data sets either on a campor drill core scale. However, there are at least two, probably more generations of magnetite in the rock record.
Preliminary data sets on magnetite chemistry, using laser ICP-MS analytical techniques, suggest that magnetites, which immediately predate gold, are distinct in their
1481
chemical compositions (e.g. high V/Al ratio, high Zn and
Mn content). Similar identification criteria have also been
established in the whole-rock multielement data sets. For
example, early epidote alteration, which contains significant magnetite veins and disseminated magnetite, is
chemically distinct in whole-rock analyses with high Te,
Bi and Ge concentrations.
The fundamental structural controls on the distribution of the reduced mineral assemblage are less clear except that the structures appear to originate outboard of
the Central Corridor. There is some evidence for this hypothesis to the SW of the Conqueror area where pyrrhotite is controlled by a gently SW dipping structure. High
abundance of pyrrhotite, which spatially correlates with
E-W trending structures in the Revenge area, may also
indicate an E-W control on the reduced fluid flow.
In the St. Ives gold camp, redox domain boundaries
and high-grade gold intersections have a clear spatial relationship. This is particularly obvious in the VictoryDefiance, Britannia, Sirius, Conqueror and Orchin/North
Orchin gold deposits. In the Greater Revenge group of
deposits, reduced and oxidized domains are much more
complex which might mask some of the relationships.
However, even there, high-grade gold intersections are
located at redox domain boundaries.
In the Victory-Defiance group of deposits, the oxidized
domain is focused and envelopes all the deposits. The
reduced domain is located outboard of the oxidized domain. High-grade gold intersections (> 100 g/t) are located at the domain boundary within about 100 m in 2D,
but always within the oxidized domain. This is also supported by drill core observations at the domain boundary, where gold grades occur with magnetite halos and
locally with specular hematite. The reduced fluid conduits
contain only low levels of gold if any (< 1 g/t, mostly
around 0.1 g/t). Only high-grade intersections (>100 g/t)
are strongly focused at the domain boundary, but lower
grades are more dispersed from the domain boundary.The
main gold lodes occur also proximal to the domain boundary in 3D. Even though lower gold grades are dispersed
more than high grade zones, the main lodes occur within
the oxidized domain proximal to the domain boundary.
This suggests that the domain boundary has a strong control on the tonnage as well as the grade.
Acknowledgements
The authors thank St. Ives Gold Mining Company Pty Ltd,
Placer Dome Asia Pacific for financial support and all
exploration and mine staff for their support and contributions to this project. The predictive mineral discovery
Cooperative Research Centre (pmd*CRC) and the Minerals and Energy Research Institute of Western Australia
(MERIWA) are acknowledged for funding of the project
and permission to publish.
Close
1482
P. Neumayr · K.J. Petersen · L. Gauthier · J. Hodge · S.G. Hagemann · J.L. Walshe · K. Prendergast · K. Conners · L. Horn · P. Frikken · A. Roache · R. Blewett
References
Eilu P, Mikucki EJ (1996), Primary geochemical and isotopic dispersion haloes in Archaean lode-gold systems: assessment of
alteration indices for use in district and mine-scale exploration: Perth, Minerals and Energy Research Institute of Western
Australia, p: 65
Gardoll SJ, Groves DI, Knox-Robinson CM, Yun GY, Elliott N (2000)
Developing the tools for geological shape analysis, with regionalto local-scale examples from the Kalgoorlie Terrane of Western
Australia. Australian Journal of Earth Sciences 47: 943-953
Gauthier L, Hagemann SG, Robert F, Pickens G (2004) New constraints
on the architecture and timing of the giant Golden Mile gold deposit, Kalgoorlie, Western Australia. In SEG 2004: Predictive Mineral Discovery Under Cover, Perth: 353-356
Groves DI (1993) The crustal continuum model for late Archean lodegold deposits of the Yilgarn Block, Western Australia. Mineralium
Deposita 28: 36-374
Hagemann SG, Gebre-Mariam M, Groves DI (1994) Surface water
influx in shallow-level Archean lode-gold deposits in Western
Australia. Geology 22: 1067-1070
Hodge JL, Hagemann SG, Neumayr P (2005) Characteristics and evolution of hydrothermal fluids from the Archean orogenic New
Celebration gold deposits, Western Australia. this volume
Neumayr P, Hagemann SG, Horn L, Walshe J, Morrison RS (2004)
Camp- to deposit-scale spatial zonation and temproal succession of redox indicator sulfide-oxide minerals; vectors to Archaean orogenic gold deposits; an example from the St. Ives gold
camp, Yilgarn Craton, Western Australia. In 17th Australian Geological Convention, Hobart, Tasmania, Australia:105
Neumayr P, Hagemann SG, Walshe J, Morrison RS (2003) Camp- to
deposit-scale zonation of hydrothermal alteration in the St. Ives
gold camp, Yilgarn Craton, Western Australia: evidence for two
fluid systems? In Mineral Exploration and Sustainable Development, Seventh Biennial SGA Meeting, Athens: 799-802
Petersen KJ (2005) Palehydrologic evolution of the Kambalda gold
camp. this volume
Close
Chapter 14-8
14-8
Strategies for facilitating predictive discovery of blind
ore bodies in maturely mined districts
Sheng-Lin Peng, Liang-Ming Liu, Chongbin Zhao, Zhi-Ming Shu, Yong-Jun Shao
Computational Geosciences Research Centre, Central South University, Changsha 410083, China
Abstract. For facilitating predictive discovery of hidden ore deposits
in the maturely mined districts, the strategies we should adopt include innovation of exploration models, optimisation of exploration technologies and integration of information. The innovation
of the exploration models must incorporate the new metallogenic
concepts by considering the coupling geodynamic processes of
mineralisation systems. The optimisation of the exploration technologies must aim at the specialty and complexity of the geological setting and working environments in the maturely mined districts. The integration of information is by synthesising multiple sets
of data resulting in a more credible and visual prospectivity map
by use of the GIS and several mathematical methods such as weight
of evidence and fuzzy logic, which can extract as much useful information from every set of data as possible.
Keywords. Prediction of hidden ore bodies, exploration model, exploration technologies, information integration
1
Introduction
Exploration in maturely mined districts is very important for the development of the Chinese mineral industries and society. However, it is not easy to discover considerable new ore bodies in these districts, as extensive
and intensive exploration has been carried out. Undiscovered and ore bodies vary greatly and very difficult to
detect. It thus is necessary to create an exploration strategy for facilitating predictive ore discovery. This paper
presents our points are common principles about creating an exploration strategy, including innovation of the
exploration models, optimisation of the exploration technologies and integration of information.
2
Innovation of exploration models
Exploration models consist of some criteria being used
to assist in choosing exploration targets, which is vital
for exploration. It is necessary to adopt new models to
determine targets for re-exploration, because most locations being judged as favorable exploration targets by the
existing model, have been explored.
The novel models play an important role in exploration as they can provide a set of new concepts, and criteria by which we can target some new-type ore-deposits.
Novel models can also target some new favorable exploration locations the previous model found unfavorable
for mineralisation, and extract new metallogenic implication from the previous data. It is the option and judg-
ment according the novel modes that trigger the discovery of new deposits, even though the new discovered ore
deposit may be very different from the model described
in many aspects.
Although the innovation of the model is creation of new
criteria, the key is ‘creation’ rather than ‘new’. A new model
generated by abusing of the fashionable theories or hypothesis may not be helpful for exploration, which was called by
Hodgson as the “school of fads and fashions” and is one of
major pitfalls in the making of models[1]. The innovation is
not to modify the existing model to explain new-discovered features, but to construct a set of new criteria and new
concepts which must be distinctly different from the existing ones originated from the metallogenic researches.
The innovated exploration model must be conceptual,
being formed by considering mineralisation cause, genesis
and geological processes. Scientific discussion concerning
the processes going on within the earth today is still full of
controversy, and we have even less knowledge of such processes in the past, therefore, geological theories of ore formation are extremely difficult to prove and geological time
and earth processes difficult or impossible to duplicate in
the laboratory. This means the knowledge we have about
the mineralization and related geological processes is not
always enough to understand the real mineralisation system. The reliability and effectiveness of the new model is
dependant mostly on the understanding of the geodynamic
architecture and evolution of the exploration districts.
Mineralisation is the result of nonlinearly coupled
geoprocesses, mainly of the coupled mecha-hydrothermo-chemical processes, implying that, more than one
process may affect the others and therefore the behavior
of the system cannot be predicted by considering each
process independently. Little variation of the initial conditions could result in distinct outcome. This is the reason why the similar geological settings produced very
different deposits and the pure empirical model is usually less effective for prediction. This makes it necessary
to consider the coupled geodynamic processes for determining the most favorable mineralisation locations as the
exploration targets. As the coupled geodynamical processes are impossible to duplicate in the laboratory and
their dynamic equations are impossible to be solved by
analysis methods, the numerical simulation is the only
feasible way to reproduce these geodynamic processes and
output the results in the computer and conclude where the
Close
1484
Sheng-Lin Peng · Liang-Ming Liu · Chongbin Zhao · Zhi-Ming Shu · Yong-Jun Shao
geodynamical conditions are favorable for mineralisation.
Therefore, the new concepts supported by the results of
numerical geodynamic simulation are vital for constructing the novel and applicable exploration models. In fact,
some prominent progresses have been made in understanding mineralisation systems and facilitate predictive
exploration by numerical geodynamic modeling.
3
Optimization of exploration technologies
In the maturely mined districts, a great deal of potential
ore bodies undiscovered by the previous explorations is
assumed to be the deep-sited and/or difficult-identified,
which are not easily detected by the common used exploration technologies, because their related information is
weak and/or very complicated. This makes it difficult to
get enough information to conduct correct predictions
about their locations. For conducting predictions easily
and accurately, optimisation of exploration technologies
is necessary to adopt advanced technologies to collect and
analyze the weak and complicated information.
The advanced exploration technologies facilitating
predictive ore discovery in the maturely mined district
can be divided into the following four groups:
1. New information detecting technologies: for supplying evidence to predict ore deposits through detecting
the new information that was undetectable using the
previous technologies, such as the pesu-random triplefrequency induced polarization, the mobile metal ion
technique;
2. Strong noise-against geophysical technologies: for detecting the ore-related information in the strong noise
background which is a common obstacle for geophysical exploration in the maturely mined districts;
3. Weak information detectable technologies, for detecting weak information that may be related to the deepsited hidden ore bodies; and
4. Data processing technologies, for extracting beneficial
information from complicated data and giving more
perspicuous presentation, such as multidimensional
statistical technique.
The advanced exploration technologies are very important, but it must be emphasised that there is no “panacea-like” technology. The “cult of the panacea” is the common fashion school in the exploration field, which is blindfaith in the most expensive equipment. Although “the most
advanced technology” (often the most expensive) is used,
it must be based on the detail and correct geological data,
as in the words of Woodall: “No geological research is
more critical to the development of an understanding of
ore formation and the formulation of a sound exploration strategy than meticulous, surface mapping, mine
mapping and core logging”.
4
Integration of information
Although increasingly sophisticated geochemical,
geophysical techniques are being used for facilitating
predictive mineral discovery, unfortunately, it is clear
that no single dataset holds the key to discovering ore
bodies. Rather, each exploration dataset contains its
own small piece of the puzzle. Consequently, the key to
component modern exploration lies in the effective analysis of the datasets, the extraction of the explorationrelevant factors, and the integration of these factors into
a single prospectivity map. The synthesis of multi-sets
of information can integrate the superiorities of various
techniques to greatly decrease the chance of false prediction.
Geographic Information System (GIS), a computerbased environment designed to effectively store, interrogate and integrate diverse spatial and non-spatial datasets,
is an ideal vehicle with which to carry out quantitative
prospectivity analysis by data combination. There are several mathematical methods to calculate quantitatively the
comprehensive prospective index from various information, which can be divided into two groups: data driven
methods and knowledge driven methods. The common
used data-driven methods include weight of evidence,
logic regression and neural networks. The common used
knowledge-driven methods include Boolen operation,
index overlay and fuzzy logic.
For achieving credible prediction of hidden ore bodies, especially of the deep-sited, in the maturely mined
district, the integration methods of information should
develop to nonlinear integration and 3-D integration,
which clearly lags behind the demand of exploration.
5
Conclusions
To overcome special difficulties of exploration in maturely
mined districts and achieving more predictive discoveries of concealed ore bodies, we should innovate the exploration strategies through innovation of exploration
models, optimisation of exploration technologies and integration of information. The innovation of the exploration models must incorporate new metallogenic concepts
based on metallogenic studies. The numerical geodynamic
modeling can test the new concepts and is very helpful
for constructing applicable exploration models. The
optimisation of exploration technologies is to use advanced technologies to overcome the special difficulties,
but it must be based on the detailed geological investigation. The integration of information is by synthesizing
multiple sets of data resulting in a more credible and visual prospectivity map by use of the GIS and several mathematical methods such as weight of evidence and fuzzy
logic, which can extract as much useful information from
every set of data as possible.
Close
Chapter 14-8 · Strategies for facilitating predictive discovery of blind ore bodies in maturely mined districts
References
He JS (1991) Study on pesu-random triple- frequency induced polarization. Transaction of Nonferrous Metals Society of China 4: 1-7
Hobbs BE, Zhang Y, Ord A, Zhao C (2000) Application of coupled
deformation, fluid flow, thermal and chemical modeling to predictive mineral exploration. Journal of Geochemical Exploration
69-70: 505-509
Hodgson CJ (1990) Uses (and abuses) of ore deposit models in mineral exploration. Geoscience Canada 17: 79-89
Karger M, Sandomirsky S (2001) Multi- dimensional statistical technique for detect of low contrast geochemical anomalies. Journal
of Geochemical Exploration, 72: 47-58
1485
Liu LM, Peng SL (2004) Prediction of hidden ore bodies by synthesis
of geological, geophysical and geochemical information based
on dynamic model in Fenghuangshan ore field, Tongling district,
China. Journal of Geochemical Exploration 81: 81-99
Mann AW, Birrell RD, Mann AT, Humphreys DB, Perdrix JL (1998).
Application of the mobile ion technique to routine geochemical
exploration. Journal of Geochemical Exploration, 61: 87-102
Sorjonen-Ward P, Zhang Y, Zhao C (2002) Numerical modeling of
orogenic processes and gold mineralization in the southeastern
part of the Yilgarn craton, Western Australia. Australian Journal
of Earth Sciences 49: 935-964
Woodall R (1994) Empiricism and concept in successful mineral
exploration. Australian Journal of Earth Science 41: 1-10
Close
Close
Chapter 14-9
14-9
Structural pattern for normal faulting of west central Iran
Mortaza Pirouz
Geological Survey of Iran, Geodynamic Department, Tehran, Iran
Abstract. The studied area is situated in the North West Isfehan province in central Iran. The oldest outcropping rocks are upper Jurassic, the upper of which contacts are unconformable. Lower Cretaceous units are composed of conglomerate, sandstone and
orbitolina limestone (Aptian-Abian). Upper Cretaceous units are
composed of limestone and marl with interbeds of orbitolinaferous
limestone. According to a study of ETM data, systematic conjugate
mega-joints are generally observed in the whole area. These joints
are also observed in Jurassic and Cretaceous units. Jurassic units
are ductile and Cretaceous units are brittle. Transtensional faults
developed in Pre-Jurassic units. Activation these faults formed new
normal faults in Cretaceous units. Syntectonic Oligo-miocene limestone was deposited on the Cretaceous unit disconformably, so that
the lower Cretaceous units show normal faults and Oligomiocene
units show syncline structures. The fault system of the study area is
a part of the Alpine orogeny. Based on the ETM data, a clockwise
rotation could be observed in the whole area. Blocks between these
mega-joints have experienced and elongation.
Keywords. Normal fault, transtension, dominant structures, Central
Iran, Sanandaj -Sirjan zone
ates, sandstone, shales and orbitolina bearing limestone.
Intensive orogenic movements caused widespread erosional facies variations in upper Cretaceous. The paleogene
period began with marine transgression (i.e. formation
of Nummulitic limestones and volcanic rocks). Neogene
rocks were essentially formed in shallow continental basins (Talbot and Alavi 1996).
3
The oldest rocks include upper Triassic “green shale” formation. Lower Cretaceous basal units are composed of
conglomerate and sandstone. Gray orbitolina limestone
with interbeded carbonate conglomerates overlies the
sandstone. Upper units are composed of marl with
interbeds of orbitolina limestone. Oligomiocene limestone
rests with angular unconformity over the cretaceous units
(Pirouz and Karimi 2004).
4
1
Tectonic setting
Introduction
The study area is situated near the boundary of Central
Iran with the Arabian plate between the Orumieh-Dokhtar
volcanic arc and Sanandaj – Sirjan metamorphic belt.
There are many local sedimentary basins and strike-slip
faults between Orumeh – Dokhtar volcanic arc and
Sanandaj-Sirjan belt (Mohajjel and Fegussen 2000;
Mohajjel et al. 2003). These structures have experienced
a dextral shear (Mohajjel and Fegussen 2000), and in some
areas normal faulting (Pirouz and Karimi 2004; Pirouz et
al. 2004). The main subject of this article is about the formation of normal.
2
Stratigraphy of the study area
Geological setting
The old precamberian metamorphic rocks to younger
volcanic rocks exist in the Central Iranian micro plate.
Precambrian basement rocks are metamorphed by the
Katangean orogeny. Paleozoic epirogenic events caused
erosional unconformity. In some areas we can see evaporate deposits as a result of this. The thickness of lower
Camberian to Devonian deposits is nearly 7 km, which is
unique in the Middle East (Darvishzadeh 1991). The platform sequence is covered by Precambrian to Jurassic continental and shallow marine sediments. Due to the transgression of sea in lower Cretaceous, most parts of the
central Iranian micro plate are covered by conglomer-
According to the satellite photo maps and field studies,
dominant structures in the area are extensional and strike
slip faults (Fig. 1). Conjugate mega-joints that trend N22W
and N70E. There are present in the area with dips about
90°. Strike slip movement is visible in some of the conjugate mega-joints. Strike of normal fault planes are about
N46E, dipping 30-35NW. Displacement along the normal
faults is about to 350 to 400m. The best outcrop of the
normal faults is located in the northeast of Alavidjeh town.
Field study was focused on this region of northwest of
Isfehan province. Normal faults cut the cretaceous units
and terminate at the boundary between Cretaceous and
Triassic rocks. Most strike slip faults are observed in Triassic units. Occasionally, strike slip faults cut Paleogene
units. They sometimes show transtensional left lateral
movement with 1 km displacement. Syntectonic Paleogene sequence overlies the cretaceous units. Cretaceous
units are dissected due to normal faulting, but in the Paleogene sequence there are no traces of these faults.
5
Discussion and conclusion
Strike slip normal faults are found in ductile Triassic rock
unit, and normal strike slip faults are observed in brittle
lower Cretaceous rocks. On the other hand, in some areas,
dacitic domes show a NE-SW liner trend. Presence of strike
slip faults in the basement and ductile deformation of the
Close
1488
Mortaza Pirouz
(Virginie and Burn 1991). So far Jurassic layers are ductile
and Cretaceous layers are brittle in the study area. Consequently dominated structure can be result in transtensional
faults formation in the lower layers or basement.
Acknowledgements
basement may result in normal faulting in upper brittle levels.
The dissected blocks may have rotated. This rotation is controlled by the faulting shear sense in the basement. The rotate may have occurred along both vertical and horizontal
directions. Formation of normal faults occurred at the time
of sedimentation of Oligo-miocene rock units. Rotation of
Cretaceous fault blocks, lock of normal faults, and presence of strike slip faults in the Triassic formation indicate
that the basement was subjected to right lateral strike slip
faulting. These right lateral strike slip faults in the basement are probably related to the rotation of the central Iranian micro plate. Extension structures in the study area
include graben structures and normal faults. Evidences
from the structures, unconformities and syntectonic sediment of the study area indicate that activation of normal
faults occurred during the Alpine orogeny. The existence of
transtensional fault in the basement and lower layers can
be reason for normal fault form in the upper brittle layers
I thank from Prof. Paul Roberts and Dr. Yanhua Zhang
for his guidance.
References
Drvishzadeh A ( 1991 ) Geology of Iran. AmirKabir publish.
Mohajjel M, Fegussen LC ( 2000 ) Dextral transpertion in late cretaceous continental collision, Sanandaj-Sirjan Zone, Western
Iran. Journal of Structural Geology
No 22: 1125-1139
Mohajjel M, Fegussen LC, Sahandi MR (2003) Cretaceous tertiary
convergence and continental collision, Sanandaj-Sirjan Zone,
Western Iran. Journal of Asian Earth Science No.21: 397-412
Pirouz M, Karimi HR (2004) Listric normal faulting of West Central Iran. 22 Symposium Earth Science geological survey of Iran.
Pirouz M, Monsef R, Ghasemi MR (2004) Listric normal faulting of
West Central Iran. 32 International Geology Congress, Florence,
Italy
Talbot CJ, Alavi M (1996) The past of a syntaxis across the zagros.
Geology Society Publication No.100: 89-109
Virginie T, Burn JP (1991) Experiments on oblique rifting in brittle
– ductile systems. Elsevier Science Publisher BV Amesterdam:
71-84
Close
Chapter 14-10
14-10
Design of object-relational spatial databases for
mineral deposit research and targeting
L.D. Setijadji, K. Watanabe
Department of Earth Resources Engineering, Graduate School of Engineering, Kyushu University, 6-10-1 Hakozaki, Higashiku, Fukuoka 812-8581, Japan
Abstract. An object-relational database is the entry point for
geoinformatic exploration tools applied for mineral targeting. A data
model is proposed to establish standards for database contents that
enable information sharing across multidisciplinary fields, modeling geological processes a database, and to provid data for advanced
modeling tasks. An application-specific database model for mineral targeting was based largely on the generic North American
Data Model Conceptual Design 1.0 and the ESRI Geology Data Model
812. These data models were modified and extended to datasets
typically involved within research and exploration of mineral deposits. The development of a conceptual model into physical database was achieved through the integration of a relational database
and a geographic information system. The result is a highly visual
relational database in which database query, analysis, and visualization of subsurface geologic data can be performed visually on
computer screen via a feature interface. The case study shows that
navigation and access to the contents of database can be done
effectively through relational query protocols. Results of queries
become input data for advanced modeling tasks such as
geostatistical analysis, solid 3D modeling, and hydrothermal system modeling.
Keywords. Object-relational spatial database, mineral deposit targeting, data model, geographic information system, GIS
1
logic phenomena? (e.g. Raper 1989; Turner 2000). We argue that, as geology and geologic datasets are spatial in
nature, such geologic analysis system should be centered
on a geographic information system (GIS). But as GIS is
merely a collection of analytical tools for handling generic spatial data, specific geologic modeling GIS application should be equipped with many supporting systems
such as database management system, specialized geologic analysis tools, and visualization system. The name
of geoinformatics exploration tool refers to the whole system involved as applied for mineral targeting purpose.
Many experts have discussed different aspects of geologic modeling based on geoinformation technology such
as 2D map-based GIS modeling (Bonham-Carter 1994;
Porwal et al. 2004), geostatistical and 3D modeling (Raper
1989; Houlding 2000; Turner 2000) and hydrothermal modeling for predicting mineral deposits (Dugdale 2004; Oliver
et al. 2004). Meanwhile discussions on geologic modeling
inside a database are still very limited. Here we emphasize
discussion on designing database model to show its value
to support minerals exploration and research and to report state-of-the-art progress on its development.
Introduction
3
Dramatic flow of geoscientific data makes available huge
amount of geoscience data for mineral exploration. Delivering the best knowledge from data is the competitive key
for future exploration success. The geoinformatics exploration tools will be considered as a standard exploration
tool. In this case, data and data management system are
entry points the whole geoinformatics exploration tools.
As object-relational database management system
(ORDBMS) approach has been widely used in many fields
but geology, we try to apply this method to mineral targeting. This approach enables modeling natural behaviors of geo-objects within a database, in order to get better insights on relationship meaning among geologic data
types and to reveal (subsurface) geologic phenomena related with formation of mineral deposits
2
Geoinformatics exploration tools
Historically long discussions have been documented centered on a question ‘What is the computer-based technology that is most suitable for modeling subsurface geo-
Object-relational database design
Object-relational database analysis and design is definitely
not a new technology although its application for geoscience is just recently realized. Using this technology we
can potentially model natural behaviors of geologic objects according to their logical models such as rocks, faults,
boreholes, and ore deposits. In previous data models these
features were simply modeled as points, lines, and polygons (Zeiler 1999). Building a database model is also aimed
to enforce standards on contents, vocabulary, and rules.
Standardization facilitates interactions and information
sharing across geoscience fields, in order to take full advantage from the wealth of geoscience data.
Looking at benefits of information sharing, few international geoscience data models are now available such
as the North American Data Model Conceptual Design
1.0 (NADM-C1.0) and the ESRI Geology Data Model 812
(EGDM 812). These data models utilize an object-relational modeling approach and are implemented through
an integration of GIS and ORDBMS (Grise and Brodaric
2003; North American Geologic-map Data Model Steer-
Close
1490
L.D. Setijadji · K. Watanabe
ing Committee 2003). As these data models are merely
working on basic geologic map information, we adapt
their common basic designs to produce a new, applied
data model for mineral resources research and targeting.
4
Data model for mineral resources
The current version of our data model, called the Earth
Resources (Mineral) Data Model 2.0, contains of top level
classes of Concept, MetaData and Feature (Fig. 1). The Concept represents all kinds of geologic objects and is grouped
into sub-classes of EarthMaterial, GeologicStructure,
GeologicUnit, GeologicProcess, GeologicRelationship,
GeologicEvent, GeologicProperty, EarthResource,
GeologicSample, GeologicMeasurement and GeologicVocabulary. The MetaData represents concepts regarding
documentation of specific items of data in a database
and it contains of four sub-classes (ie NameDesc, TextDesciption, DataQuality and SourceReference). The Feature
is a spatial representation of data that is used by GIS to
visualize data through a map. Conceptually, GeologicConcept and Feature classes are optionally linked to the
MetaData.
All geologic concept object classes are further divided
into more specific classes. Each geologic concept class is
also linked each other, creating an interwoven relationships among object classes. Much attention on modeling
is currently given on concepts of GeologicSample and
Geologic Measurement (Fig. 2) for these concept classes
represent most of the existing data types for mineral deposits studies. GeologicSample represents concepts on physical materials (solid, fluid or gas) to be collected from the
earth, and is currently simply classified as stream sediment,
soil, rock, water and gas sample types. Intensive modeling
is given on GeologicMeasurement, such as drillhole survey,
structure measurement, spectrometry and elemental analysis, geophysical survey and descriptive techniques such as
petrography observation. GeologicMeasurement and
GeologicSample have an optional relationship? Meaning not
clear.
5
Evaluation through a case study
An evaluation on the capability of the model to support
mineral targeting was done on a case study of a gold project
in Java island, Indonesia (JICA-JOGMEC 2004). Evaluation
was done on navigational tasks within database, supporting tasks for advanced geologic analysis works (i.e.
geostatistical and 3D analysis), and visualization task.
The best way to utilize object-relational database is
through visualizing data contents using a GIS-based 3D
visualization system. Visualization on raw data gives first
insights on data availability and spatial distribution. The
impressions in turn drive questions whose answers are
to be searched through relational queries. For example,
the presence of drillhole map would raise few questions
such as what kinds of lithology intercepted by a hole, or
are there any mineralization zones intercepted and, if that
is the case, what are the grades etc. Most relational-spatial questions in our evaluation could be solved using many
ways of database navigation techniques. The key is to be
familiar with navigation tools of a relational GIS environment, such as relational identify tool, join, relation,
selection, intersection, and unity tools.
An example is shown on Figure 3, in which we searched
for relational information associated with a drillhole, such
as geologic samples taken along this hole. In turn, a geologic sample table is connected with other tables such as
sample descriptions and geologic measurements. In this
example we show the metallic trace-element analysis result from an ore sample. Of course this kind of data exploration can be applied for other purposes, such as understanding stratigraphic as well as cross-cutting relationships among different map units.
After data content and/or data relationship of interest
are found, those can be displayed as either polygon,
polyline or point maps through a georeference technique.
A special georeference technique is linear referencing system that is used for referencing datatasets associated with
linear features such as drillhole, stream, and fault (ESRI
2003; Setijadji et al. 2004; Setijadji and Watanabe 2004).
Close
Chapter 14-10 · Design of object-relational spatial databases for mineral deposit research and targeting
Derivative maps are used as data input for more advanced
analysis.
Figure 4 shows the results of database navigation and
analysis from the case study area. In this evaluation we
did query on Au, Ag, and As analytical results on soil
samples, from which on selected data we applied
geostatistical analysis to create contour anomaly and displayed the results as contour maps. Also on the drillhole
data we selected rock sample containing assays and displayed as point map using the linear referencing system.
This figure shows that we could still navigate relational.
data contents, doing analysis, and producing visualization within a 3D GIS environment.
6
1491
Conclusion
At current stage we have proven that the conceptual data
model on object-relational spatial database is successfully
implemented physically and is capable to support multiple
tasks such as data navigation, analysis and visualization.
All are done in a relational and 3D environment. Future
directions of this research will focus on refinements of data
model objects, vocabulary, and relationship rules in order
to make database navigation more effectively done. Integration with mineral targeting tools especially solid 3D and
hydrothermal system modeling is investigated.
Close
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L.D. Setijadji · K. Watanabe
References
Bonham-Carter GF (1994) Geographic Information System for Geoscientists: Modelling with GIS. Delta Printing, Ontario
Dugdale LJ (2004) Gold is where you predict it: reducing time and
cost to discovery in western Victoria. In: Muhling J et al (eds)
SEG 2004: Predictive Mineral Discovery Under Cover; Extended
Abstract. Centre for Global Metallogeny, The University of Western Australia, Publication No. 33: 6-11
ESRI (2003) Linear referencing in ArcGIS: practical considerations
for the development of an enterprisewide GIS. ESRI Technical
Paper, Redlands
Grise S, Brodaric B (2003) ArcGIS Geology Data Model. http://
support.esri.com/data- models
Houlding SW (2000) Practical Geostatistics: Modeling and Spatial
Analysis. Springer-Verlag, Berlin-Heidelberg
JICA-JOGMEC (2004) Report on the Mineral Exploration in the East
Java Area, the Republic of Indonesia – Consolidated Report. Japan International Cooperation Agency and the Japan Oil, Gas
and Metals National Corporation Report, Tokyo
North American Geologic-map Data Model Steering Committee
(2003) NADM Conceptual Model 1.0, A Conceptual Model for
Geologic Map Information. http://geology.usgs.gov/dm/
Oliver NHS, Cleverley JS, Bastrakov EN (2004) Modeling hydrothermal systems: a future for exploration geochemistry. In: Muhling
J et al (eds) SEG 2004: Predictive Mineral Discovery Under Cover;
Extended Abstract. Centre for Global Metallogeny, The University of Western Australia, Publication No 33: 62-66
Porwal A, Carranza EJM, Hale M (2004) A hybrid neuro-fuzzy model for
mineral potential mapping. Mathematical Geology 36: 7, 803-826
Raper JF (1989) The 3-dimensional geoscientific mapping and modeling system: a conceptual design. In Raper JF (ed) Three dimensional applications in Geographic Information Systems. Taylor
& Francis, London: 11-19
Setijadji LD, Imai A, Watanabe K (2004) GIS-linked object-oriented
database for earth resources. Proceedings of the 2nd International
Workshop on Earth Science and Technology, Fukuoka: 433-440
Setijadji LD, Watanabe K (2004) Spatially enabling relational geologic database of Java island, western Sunda arc of Indonesia: a
step to the geoscience and mining data model. Proceedings of
the PACRIM 2004 Conggress, Adelaide: 263-271
Turner AK (2000) Geoscientific modeling: past, present, and future.
In Coburn TC and Yarus JM (eds) Geographic Information Systems in Petroleum Exploration and Development. AAPG Computer Applications in Geology No. 4: 27-36
Zeiler M (1999) Modeling Our World: the ESRI Guide to Geodatabase
Design. ESRI Press, Redlands
Close
Chapter 14-11
14-11
Application of conceptual targeting approaches in
porphyry copper exploration: Examples from the
Cordillera de Domeyko, northern Chile
Jorge Skarmeta
Gerencia Corporativa de Exploraciones, Codelco-Chile, Huerfanos 1270, Santiago, Chile
Abstract. The Cordillera de Domeyko of northern Chile has been traditionally interpreted as a major sinistral strike-slip fault system that
controlled the emplacement of the Paleocene – Oligocene age giant porphyry Cu deposits of the region. New field studies combined
with construction of cross-sections and re-evaluation of new and
existing thermochronological data show that the Cordillera de
Domeyko is dominated by N-S striking, moderate to steeply dipping inverted extensional faults, thrusts and associated folds, with
no evidence of significant sinistral strike-slip faulting. The Cu bearing porphyry intrusions are controlled by these inverted extensional
fault systems. A new model of inversion of pre-existing, Triassic –
Cretaceous, back-arc extensional faults for the tectonic control on
the emplacement of these giant porphyry Cu deposits in northern
Chile is proposed, and its application to areas covered by post-mineral sedimentary deposits is presented.
Keywords. Northern Chile, Cordillera de Domeyko, inversion tectonics, porphyry copper deposits, dilation, post-mineral cover
1
Introduction
Decades of mineral exploration for Upper Eocene – Lower
Oligocene porphyry copper systems in northernmost Chile
indicate that these deposits have strong structural controls
(i.e. Lopez 1942; Perry 1952). Tectonic models for the control of emplacement of these porphyry copper deposits generally invoke magma migration along releasing bends and
stepovers within a crustal scale strike-slip fault zone. Here,
the results of a detailed structural and chronological reevaluation of the structure of the Cordillera de Domeyko
orogen and its associated Upper Eocene – Lower Oligocene
porphyry copper deposits is presented. The proposed new
model, which suggests that porphyries are emplaced in local dilational sites within contractional and inverted foldthrust belts, has important implications for exploration in
covered areas. To predict and target covered porphyry copper deposits it is essential to understand the fault geometry, fault displacement distribution, fault size and linkage
interaction, and fluid flow dynamics during faulting.
2
Geometry and structural evolution of the
Cordillera de Domeyko
The Cordillera de Domeyko is a complex Mesozoic-Tertiary structural belt inboard of the present-day northern
Chile subduction margin. Giant porphyry copper-molyb-
denum deposits including those from the Chuquicamata,
Collahuasi and La Escondida districts (Boric et al. 1990),
with ages similar to the host intrusions (40-30 Ma, Camus
2003), are aligned N-S within this structural belt. Field
observations indicate that the structure of the Cordillera
is dominated by several elongate, N-S trending, basement
ridges that are bounded by steep reverse faults deforming the Triassic-Cainozoic cover (Amilibia 2002; Amilibia
et al. 2003; McClay et al. 2002; Skarmeta et al. 2003). The
dominant structural style is that of inversion of Palaeozoic
(?) and Triassic through Lower Cretaceous back-arc basin extensional faults (related to Triassic-Jurassic extensional events, Coira et al 1992; Mpodozis and Ramos 1989)
by margin-normal contraction. The vergence of the system changes from west to east along the trend giving a
doubly-vergent “pop-up” geometry to the axial zone, a
conclusion well supported by thermochronology (Olivares
2001; McInnes et al 1999; Maksaev and Zentilli 1999). Basement short-cut faults uplift Palaeozoic rocks and shorten
the footwall Mesozoic cover, showing a strong genetic relationship between thin- and thick-skinned structures.
Tertiary porphyry intrusions are aligned N-S, and are
strongly controlled by basement-involved reverse faults
that facilitated ascension of the magma and intrusion into
the Mesozoic sedimentary cover as sills, mainly located
in hanging-wall anticlines (McClay et al. 2002).
Tectonic models for the control of the Cordillera de
Domeyko porphyry copper deposits have invoked magma
emplacement along releasing bends and stepovers within
a crustal scale strike-slip fault zone (Reutter et al. 1991,
1996; Dilles et al. 1997; Maksaev and Zentilly 1999;
McElderry et al. 1997; Tosdal and Richards 2001, 2003;
Tomlinson and Blanco 1997a, b). Structural and chronological work developed during this work has found little
evidence for major (10’s km) strike-slip displacement on
any of these fault systems.
The inverted extensional fault system controlled the
emplacement of porphyry magmas in a contractional tectonic environment (Amilibia and Skarmeta 2003; Amilibia
et al. 2003; McClay et al. 2002; Skarmeta et al. 2003). The
fertile porphyries and associated barren intrusives were
emplaced within structural traps, commonly at relay tips
or soft linkage accommodation zones within the major
inversion structures.
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1494
Jorge Skarmeta
3
Fault geometry and fluid flow
Analyses of outcrops and sections allow the identification of fault geometries at depth and along strike
(Watterson 1986; Walsh and Watterson 1988, 1991). The
establishment of 2D and 3D fault geometry permits us to
infer the trap location and to model the flow dynamics of
magmas and/or hydrothermal mineralising fluids within
the fault controlled system. Several key aspects of these
fault systems proved to be relevant for generating the structural control model for porphyry system trap location:
(1) fault segmentation, (2) zones of soft fault linkage within
the low displacement segments, (3) generation of high
permeability and fluid migration at the tips or fault terminations, (4) inversion-contraction structural style, (5)
back-arc basin architecture and dimensions, and (6) fault/
fracture related deformation and permeability.
The exploration and targeting for covered porphyry copper deposits requires the construction, restoration and extrapolation of 2D and 3D cross-sections and fault geometry (including the geological mapping of the aeromagnetic
data), scaled physical modelling, theoretical analyses, and
the relative and absolute timing of fault activity and intrusion events (Andriessen and Reutter 1994, Ballard et al. 2001;
Ladino et al. 1999; McInnes et al. 1999; Olivares 2001).
The essential geometric and hydraulic concept applicable for exploring covered porphyries is that of the enhanced permeability developed in the link zones within
fault systems, where individual faults connect and develop
a fracture mesh that accommodates and balances the displacement profile differences (Walsh and Waterson 1991).
Soft link zones correspond to fracture and deformation
mesh zones developed at the fault terminations, in which
the major central displacements of individual faults are accommodated by low displacement-high dilation structures
(Xing Zang and Sanderson 1996). This will create a strong
stress-directional along-strike permeability that will induce
significant lateral fluid movement and redistribution away
from the high mean stress-high displacement failed segments, in a sort of suction pump (Sibson 2001).
4
Analogue scale models
The results of these detailed field studies have been evaluated by scaled analogue modelling of oblique subduction
orogens. Sandbox modelling of orthogonal (90°) and oblique (<90°) subduction produces doubly vergent Coulomb wedges where the internal thrust geometries and
topographic character of the wedge are dependent on the
subduction obliquity (McClay 1989, 1996). Modelling of
oblique subduction clearly shows that for obliquities from
90° (orthogonal) to 45° (moderately oblique) the dominant structures within the pro-wedge are margin-normal
thrust faults that form a classical imbricate fold and thrust
belt. At 45° obliquity, minor en echelon oblique-slip faults
are formed within the orogenic core but without throughgoing strike slip. In strongly oblique subduction models
(37.5° - 15°) steep narrow orogenic wedges are formed
with through-going strike-slip faults formed in the orogenic core. The model results support the field studies
indicating that in northern Chile, where subduction obliquity throughout the Tertiary was typically near orthogonal (~ 70°, Pardo-Casas and Molnar 1987; Cole 1990;
Scheuber et al. 1994), the resulting dominant structures
were margin-normal reverse faults and inverted extensional faults, and strike-slip displacements were minor.
5
Intrusion mechanics
The shape of intrusions, essentially horizontal sills in the
Mesozoic strata and mostly vertical cylinders in the
Cainozoic strata, indicates that emplacement developed
in an overall contractional regime with local extensional
domains (Grocott and Williams 1997). The lower flat lying sill type bodies formed through contractional reactivation of faults at an angle equal to or greater than the
mechanical frictional lock-up angle which required the
development of pre-failure supralithostatic fluid pressures
(Sibson 1990; Skarmeta and Castelli 1997). The upper
cylindrical bodies formed in a local extensional stress
regime. Numerical modelling of the inverted syn-extensional wedge type basin stratigraphy (Jurassic sediments
and Cretaceous volcanics) shows that within the resultant antiformal inversion structure, a detachment surface
develops, and that this surface coincides well with the
characteristic neutral surface that in folded systems separates the contractional from the extensional domains.
6
Conclusions
Field sections and analogue and numerical models suggest that the inversion tectonics deformation style of the
Cordillera de Domeyko was strongly dependent on preexisting structures and the Mesozoic basin stratigraphy
(McClay 1989, 1996) rather than on the degree of subduction obliquity. In addition, the direct link that exists
between thick-skinned basement and thin-skinned cover
structures suggests that any late basement uplifts were
not formed in flower structures related with strike-slip
faults (Reutter et al. 1996; Tomlinson and Blanco 1977a).
These results indicate that a complete re-evaluation of the
tectonic setting and structural controls on giant porphyry
copper deposits in western South America (Peru and Chile)
is warranted. The proposed new model for porphyry emplacement into local dilational sites within contractional and
inverted fold-thrust belts has wide implications for exploration in covered settings. To predict the location of blind porphyry copper deposits it becomes essential to understand
the fault geometry, displacement distribution, size and linkage interaction, and fluid flow dynamics during faulting.
Close
Chapter 14-11 · Application of conceptual targeting approaches in porphyry copper exploration: Examples from the Cordillera de Domeyko, northern Chile
Acknowledgements
This paper summarises aspects of the ongoing research
carried out by the Exploration Group of Codelco Chile.
Eric Nelson is thanked for his revision of the abstract
and Francisco Camus, Codelco’s Exploration Manager for
providing the authorisation and facilities to present this
paper.
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Close
Chapter 14-12
14-12
The effect of sedimentary cover on submarine
hydrothermal processes – some simple numerical
simulations and applications
P. Sorjonen-Ward1, Y. Zhang, P. Alt-Epping2, A. Ord, T. Cudahy
CSIRO Exploration and Mining, PO Box 1130, Bentley, WA 6102, Australia
1
2
currently at Geological Survey of Finland, PO Box 1237, Fin-70211, Kuopio, Finland
currently at Institute of Geological Sciences, University of Bern, Baltzerstrasse 1-3, CH-3012 Bern, Switzerland
U. Kuronen
Polar Mining Oy, P.O. Box 15, FIN-83501 Outokumpu, Finland
Abstract. Conductive and convective thermal numerical models are
used to demonstrate the potential effect of sedimentary sequences
on the formation and containment of hydrothermal systems in underlying oceanic lithosphere. Blanketing sediments appear to be
effective in promoting subseafloor hydrothermal convection (and
by inference, replacement style mineral deposits).
These results should be relevant not just to near-axis environments but also longer term lower temperature hydrothermal alteration in a range of submarine environments. Moreover, the results
emphasize the significance of the stratigraphical transition from
volcanic-dominated to epiclastic sediments, which should be amenable to targeting by lithofacies mapping, as well as geophysical
and geochemical detection. The concept is applied to several ancient examples, including the Archean Panorama Zn deposit in the
Pilbara craton of Western Australia.
Keywords. Numerical modelling, hydrothermal processes, submarine
alteration, Pilbara, Outokumpu
1
up to 60 Ma (Morton and Sleep 1985; Schultz and
Elderfield 1999).
Depending on geodynamic setting, it is probable that
some of these low-temperature systems will be buried
beneath sedimentary sequences; four general settings that
assure significant sediment supply can be envisaged:
1. Passive continental margin to ocean floor transitions
buried by either proximal orogenically derived sediments or prograding deltas supplying sediments from
a remote source
2. Slow-spreading and aborted ridges still in close proximity to continental margins;
3. Fast-spreading ridges propagating into orogenic terrain;
4. Post-collisional, rapidly subsiding submarine rifted arc
basins;
Introduction
Understanding of submarine hydrothermal processes and
associated mineral deposits has advanced rapidly as more
and more active systems are discovered and documented
(Dilek et al. 2000; Binns et al. 2002). Combined information from modern systems and ancient analogs also permits the recognition of hydrothermal deposits in three
broad types of environments – back arc basins, and slowspreading and fast-spreading ridge settings, of which the
latter appear to be less endowed with major deposits
(Fouquet 1999). Theoretical analysis of flow patterns and
fluid-rock reactions is also well established, following pioneering studies such as Cathles (1983).
Many submarine hydrothermal systems are initiated
and sustained by focused of high temperature discharge
in rift axial settings, or proximity to intrusive bodies.
However, the observed disparity between measured
heat flow and that calculated from magma production
at oceanic ridges, implies that lower temperature and
long-term diffusive processes are significant over wide
areas of ocean basins and may persist lithosphere of age
The first two settings would be characterized by lower
temperature hydrothermal activity near the sedimentocean crust interface, with a thermal regime defined by
distribution of heat production between sediments, continental margin and mantle heat flux. The latter two situations could have additional local heat and fluid sources
directly related to proximal magmatic activity.
Theoretical studies of fluid flow patterns initiated by
density and thermally driven buoyancy in porous rocks
(Garven et al. 2001) as well as tectonically driven fracturing (Sibson 2001) indicate the importance of low-permeability layers in localizing and containing hydrothermal
systems which, under appropriate conditions, can promote efficient convective flow (Zhao et al. 1999). In addition, sedimentary sequences with low thermal conductivities overlying basement with high heat flow can influence both the thermal regime and rheological state of
the underlying lithosphere (Sandiford and Maclaren 2002).
Similarly, the distribution of heat-production elements
exerts some control on the thermal evolution of accretionary and collisional orogens (Jamieson et al. 1999; Goffé
Close
1498
P. Sorjonen-Ward · Y. Zhang · P. Alt-Epping · A. Ord · T. Cudahy · U. Kuronen
2
et al. 2003). We might therefore also expect that submarine sediments prograding over an oceanic substrate
would to some extent influence the formation, confinement and modification of hydrothermal alteration and
mineralization patterns.
Here we report results from some simple numerical
models that investigate the effects of sedimentary cover
on regional scale conductive geotherms in the oceanic
lithosphere and also on the development of local scale
convective flow cells. We then consider application of the
results with reference to several ancient deposits, at different scales and degrees of preservation.
Model methodologies and results
We have simulated the conductive thermal evolution of
lithospheric scale models using the finite difference code,
FLAC (Fast Lagrangian Analysis of Continua; Cundall and
Board 1988; Itasca 1998), based on a Mohr-Coulomb
crustal rheology overlying a viscous mantle lithosphere
and asthenosphere. A tapering turbidite wedge extends
half way across the upper surface of the models. A range
of static and extensional deformational scenarios were
studied, with systematic variations in strain rate, radiogenic heat production and distribution of thermal anomalies, in order to simulate the effects of gabbroic intrusions at different emplacement depths (Fig. 1). While
prominent thermal perturbations decay rapidly and are
proximal to the intrusions, there is a small but perceptible and persistent thermal asymmetry in the upper crust,
with slightly elevated temperatures beneath the sediment
wedge.
Thermal convective modelling has been done with the
reactive transport code OS3D (Steefel and Yabusaki 1996).
The 2-D model (Fig. 2a-c) represents a simplified section
simulating the permeability structure of oceanic lithos-
Close
Chapter 14-12 · The effect of sedimentary cover on submarine hydrothermal processes – some simple numerical simulations and applications
phere, with a fixed mantle heat flux maintaining a thermal gradient sufficient to drive convective flow. As in the
thermal conductive models a tapering wedge of sediment,
with low permeability is modelled across one half of the
model (Fig. 2a). It is clear from the solution for steady
state Darcyflow (Fig. 2b) and the temperature distribution (Fig. 2c) that the sediments have a critical influence
on the formation and efficiency of convective flow cells
in the underlying basement.
3
Applications and discussion
A general inference that can be made from the model
results is that the lithostratigraphic transition from a volcanic-dominated facies association to an epiclastic
turbiditic or hemipelagic succession is potentially significant with regard to subseafloor hydrothermal alteration.
Empirical observations support this, for example in the
Paleoproterozoic Skellefte district of Sweden (Allen et al.
1996). Another potential and spectacular example, where
the presence or absence of overlying turbidites is not yet
constrained, is the Meso-Archean Panorama Zn system
in the Pilbara craton (Brauhart et al. 1998). In that case, a
subvolcanic heat source in the form of the Strelley Granite is also implicated (Fig. 2d), but we may also consider
the implications of the models for lower temperature (100250°) alteration processes recorded in more mature oceanic lithosphere.
References
Allen RL, Weihed P, Svenson SÅ (1996) Setting of Zn-Cu-Au-Ag massive sulfide deposits in the evolution and facies architecture of a
1.9 Ga marine volcanic arc, Skellefte district, Sweden. Economic
Geology 91: 1022-1053
Binns RA., Barriga FJAS, Miller DJ (2002) Proceedings of the Ocean
Drilling Program, Initial reports: 193
1499
Brauhart CW, Groves DI, Morant P (1998) Regional alteration system associated volcanogenic massive sulfide mineralization at
Panorama, Pilbara, Western Australia. Economic Geology 93:
292-302
Cathles LM (1983) An analysis of the hydrothermal system responsible for massive sulfide deposition in the Hokuroku Basin of
Japan. In: Ohmoto H. & Skinner B. J. eds. The Kuroko and Related Volcanogenic Massive Sulfide Deposits. Economic Geology
Monograph 5: 439-487
Cudahy T (2004) Mapping alteration zonation associated with massive sulphide mineralisation using airborne hyperspectral data.
In McConachy TF, McInnes BIA (eds.) Copper-zinc massive sulphide deposits in Western Australia. CSIRO Explores 2: 113-120
Cundall PA, Board M (1988) A microcomputer program for modelling large-strain plasticity problems. In: Swoboda, G (Ed.), Proceedings of the Sixth International Conference on Numerical
Methods in Geomechanics. Numerical Methods in Geomechanics
6: 2101-2108
Dilek Y, Moores EM, Elthon D, Nicholas A. (eds.) (2000) Ophiolites
and oceanic crust: New insights from field studies and the Ocean
Drilling Program, Geological Society of America Special Paper
349
Fouquet Y (1999) Where are the large hydrothermal deposits in the
oceans? In: Cann JR, Elderfield H, Laughton A eds., Mid-Ocean
Ridges. Dynamics of processes associated with creation of new
ocean crust. Cambridge University Press: 211-224
Garven G, SW Bull, RR Large (2001) Hydrothermal fluid flow models of stratiform ore genesis in the McArthur Basin, Northern
Territory, Australia: Geofluids, 1: 289-312
Goffé B, Bousquet R, Henry P, Le Pichon X (2003) Effect of chemical
composition of the crust on the metamorphic evolution of orogenic wedges. Journal of Metamorphic Geology 21: 123-141
Itasca (1998) FLAC: Fast Lagrangian Analysis of Continua, user
manual, version 3.4. Itasca Consulting Group, Inc., Minneapolis
Jamieson RA, Beaumont C, Fullsack P, Lee B (1999) Barrovian regional metamorphism: where’s the heat? In: Treloar PJ, O’Brien
PJ (eds.) What Drives Metamorphism and Metamorphic Reactions? Geological Society of London Special Publication, 138:
23-51
Morton JL, Sleep NH (1985) A mid-ocean ridge thermal model: constraints on the volume of hydrothermal heat flux. Journal of Geophysical Research B90: 11345-11353
Close
Close
Chapter 14-13
14-13
New exploration developments using a new
exploration parameter (alteration remote sensing
anomaly) for metallic deposits in East Tianshan
Yang Jianmin
Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China
Zhang Yujun
Aero-Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083, China
Wu Hua, Deng Gang
6th Geological Team, the Xinjiang Bureau of Geology and Mineral Resources, Hami, 839000, China
Li Mengwen
China University of Geosciences, Beijing 100083, China
Abstract. The application of space-flight remote sensing technology
for mineral exploration and the comprehensive processing of geological-geophysical-geochemical and remotely-sensed information
on the GIS platform are the leading-edge problems of the modern
science and technology. The technology for extraction of the alteration remote sensing information from ETM+ data was improved in
2003. Besides the principal component analysis (PCA), spectral angle
mapping (SAM) and anomaly level slicing were included for quick
minimizing the exploration targets with different ore types. Together
with the 6th geological exploration team of the Xinjiang geological
bureau we have accomplished field check for more than 400 anomalies and found 4 Cu-mineralized spots 1 Pb-Zn-Ag mineralized spot
and several Au-mineralized spots in east Tianshan. And the prospecting potential of a series of known deposits was expanded in
their peripheral areas.
Keywords. Alteration remote sensing anomaly, ETM+, metallic deposits, East Tianshan, Geographical Information System (GIS), mineral
resources prediction
1
Introduction
In recent years, with the development at full speed of space
and computer technology, the application of quantificational
remote sensing for the mineral resources prediction is appraised unusually (Li and Zhang 1997; Zhang and Yang 1998;
Zhang et al. 2002, 2003). And a new era of the remote sensing for ore exploration with great potentiality was opened.
The alteration effect of near-ore-country-rocks has been
used as the ore indicator in a history of several hundred
years (Kurek 1954; Crosta and Moore 1989; Loughlin 1991).
The geologists affirm most of endogenous mineral deposits are accompanied by alteration of their country rock. And
the size of alteration zones is much greater than the size of
ore body. Near ore country rock alteration is the signatures
of the progressive enrichment of mineral substance.
ETM+ alteration remote sensing method, utilizing the
technology of the modern computers, extracts the alteration information, as the minor part of the total infor-
mation (approximately 1-0. 5%). This makes it possible
to appraise the prospecting success and to apply the remote sensing anomaly for regional prediction and evaluation of potential mineral resources.
In addition, the principal component analysis (PCA),
spectral angle mapping (SAM) and anomaly level slicing
were included. We have carried on the extraction of alteration remote sensing information from ETM+ data of
an area of more than 150,000km2 in east Tianshan. A area
of about 100,000km2 was investigated and verified by fieldwork. In the region from Dadonggou to Chihu (about
20,800 km2), there are 71 copper, copper-molybdenum,
gold, iron, iron-manganese, lead , nickel deposits or mineralized spots. Among them 61 are accompanying with
remote sensing anomalies. The identical rate is as big as
85.9%. It is especially need pointing out, that for the known
mineral deposits the identify rate is 100%.
2
New development of exploration in East
Tianshan
In 2003 and 2004, we investigated and verified more than
400 alteration remote sensing anomaly spots in east
Tianshan. We find 4 copper mineralized spots, 1 lead zinc
mineralized spots and several gold mineralized spot. Many
ETM hadroxylate anomalies were found in the periphery
of known Cu, Au and other mineral deposits, which should
quite be expanded. The Xinjiang sixth geologic team registers the reconnoitring areas of 5 sectors, carried out exploration projects and produced the result as follows:
2.1 Saquanzi lead zinc mineralized spot
On the Saquanzi lead zinc mineralized spot there is a good
concord between the 3rd level hydroxylate anomaly (OHA)
and the marble, and the 1st level OHA is coincident with
the mineralized altered zone(See Figure 1 A).
Close
1502
Yang Jianmin · Zhang Yujun · Wu Hua · Deng Gang · Li Mengwen
Saquanzi lead zinc mineralized spot lies approximately
4 kilometers in the south of the Saquanzi major fault zone.
Lead zinc ore alteration is distributed between marble
and diorite in the middle part of the mining area. The
length of the lead zinc mineralized alteration belt is more
than 2 kilometers, and the width is about 30 meters (the
largest width is more than 50 meters, See Figure 1 B), inclined to the south, at about 60-70°. The Shaquanzi OHA
was investigated by in-situ sampling and then by prospecting trench. It was provn to be a Pb-Zn mineralized
occurrence. The metallic grades are quite significant (Pb:
0.59-3.48%, Zn: 1.75-2.32%, Ag: 5.5ppm).
2.2 Bijiashan copper mineralized body
The Bijiashan OHA was proved to be Cu mineralized spot
with a length of 1000m, and the Cu concentration of 0.651.38%.
2.3 Luodong sulfide mineralized ultra-basic body
On the Luodong sulfide mineralized ultra-basic body there
is a good concord between the 3rd level hydroxylate
anomaly and the peridotite and olivine pyroxenite(See
Figure 2 A).
The Luodong copper nickel mineralized ultra-basic
body lies in the southwest, 12km from the Poshi copper
nickel ultra-basic rock, and in the northwest of the Baidiwa
major fault zone. The Luodong mineralized ultra-basic
body is 2200 m long, 1200 m wide. There are some differ-
ent lithofacies zones in the Luodong ultra-basic body. It
is easily to distinguish peridotite, olive pyroxenite, olivine gabbro, gabbro and amphibole gabbro (See Figure.
2B). Epidotization, chloritization, ampibolitization, clinoantigoritization and limonite were discovered. Malachite
and metal sulphide were found in peridotite and olive
pyroxenite. The result of the electronic probe show there
are nickel pyrites in the olive pyroxenite (Fe 30. 982, S 33.
78, Ni 35. 03, Cu 0. 10, As 0. 06). In the two prospecting
trenches constructed, a 10.30 meter length of the TCYQ1 trench revealed the Ni grade of 0. 2-0. 23%. And a 11.90
meter length of the TCYQ-2 trench revealed the Ni grade
is 0. 14-0. 18%. This is a good copper nickel deposit correlated with mafic-ultramafite.
3
Summary
At present, we basically use the traditional technologies for
investigating and appraising resources. Efficiency and precision are low. To conduct of the modern mineral resources
exploration, there must be new thinking and use of new
technology. Application of ETM + alteration remote sensing
endowment exploration has the following characteristic:
a OHA and ferric contamination anomaly (FCA) represent direct prospecting information;
b In most cases the anomaly is concentrated in some pixels and not drifted away from the ore body.
c ETM+ data has the same precision and full coverage
even for places difficult to get to;
Close
Chapter 14-13 · New exploration developments using a new exploration parameter (alteration remote sensing anomaly) for metallic deposits in East Tianshan
d Low costs;
e Suitable for both quick coverage and detailed investigation;
f Good for environmental conservation.
The alteration remote sensing anomaly should be studied as an independent key parameter:
a It is based on special physical and chemical properties;
b The result could not be obtained from methodologies;
c There is still great potential for improving this technology.
Using ETM+ data, the above remotely sensed alteration
mapping, has produced very useful results that make it
an extremely cost-effective approach to delineate altered
areas and map the spatial distribution of hydrothermal
alteration within large regions in a short time.
Acknowledgements
This paper is financially supported by the 305 project
(No:2003BA612A-06-4) of China’s state science and technology fund.
1503
References
Crosta AP, McM Moore J (1989) Enhancement of Landsat Thematic
Mapper Imagery for Residual Soil Mapping in SW Minais Gerrain.
In: Proceedings of the 7th (ERIM) Thematic conference: Remote
Sensing for Exploration Geology,Calgary: 1173-1187
Kurek NN (1954) Altered Near-Ore- Rocks and Their Exploration
Sense. Moscow, Geotechizdat.
Li ChG, Zhang YJ (1997) The Probation of Extraction of the Cu-mineralized Alteration Remote Sensing Information in LancangjiangLanping Area using Principal Component Analysis (PCA) for. Journal of Remote Sensing for Land & Resources 1: 30-36 (in Chinese
with an English abstract)
Loughlin WP (1991) Principal Component Analysis for Alteration
Mapping, In: Proceedings of the 8th Thematic conference on Geologic Remote Sensing, Denver, USA: 293-306
Zhang YJ, Yang JM (1998) Extraction Methods for the Alteration Remote Sensing Information in the Area with Outcropping Rocks.
Journal of Remote Sensing for Land & Resources 2: 46-53 (in Chinese with an English abstract).
Zhang YJ, Yang JM, Chen W (2002) The Methods for Extraction of the
Alteration Remote Sensing Anomaly from ETM+(TM) Data and
Their Application: Geological Basis and Spectral Precondition.
Journal of Remote Sensing for Land & Resources, 4,: 30-36 (in
Chinese with an English abstract)
Zhang YJ, Zeng ZhM, Chen W (2003) The Methods for Extraction of
the Alteration Remote Sensing Anomaly from ETM+(TM) Data
and Their Application: Method Selection and Technological flowcart, Journal of Remote Sensing for Land & Resources 2: 44-49 (in
Chinese with an English abstract)
Close
Close
Chapter 14-14
14-14
Application of the EH4 image system to the detection
of blind gold deposits, China
Q.D. Zeng, J.M. Liu, H.T. Liu, G.M. Li, T.B. Liu, C.M. Yu, P. Shen, J. Ye
Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China
Abstract. The EH4 image system (Stratagem) can detect depth ranges
from meters, to greater than one kilometer. It has been successfully
used in exploring for ore deposits in China. Buried gold mineralising
belts (or gold orebodies) of the altered rock type can be defined by
the resistivity value of less than 150 Ωm. Experimental studies show
that the EH4 image system is one of the most advanced applications, and is a flexible, portable and effective way of exploring gold
ore deposits.
Keywords. EH4 image system, resistivity, gold deposit, China
1
Introduction
Mineral exploration techniques have been well developed
globally since 1990. For example, seimic methods and
CSAMT techniques have both been successfully applied
to ore exploration (Drummond and Goleby 1993; Poole
et al. 1995; Takakuru 1995; West and Witherly 1995;
Milkereit et al. 1996). China has also achieved obvious
development in mineral exploration in the last ten years
(Jang et al. 1997; Yu 1999; Shi et al. 1999; Xu et al. 1999).
These techniques can be used to define the location and
shape of the deep ore-controlling structures in
metallogenitic belts, although they are less precise in exploring for concealed ore bodies. We have been exploring ore deposits by the Stratagem method (called EH-4
image system in China) since 2001 and acquired many
good results.
The EH4 image system by GEOMATRICS and EMIS is
a unique magnetotelluric (MT) system used for measuring the electrical resistivity of the Earth. More than 30
EH-4 instruments are being used in hydrogeologic surveys, coal geology, uranium geology, petroleum geology,
engineering geology and metal mineral exploration (Wu
et al. 1998; Wu 1999; Liu et al. 2002; Sun et al. 2001). We
developed EH-4 image system exploration in 11 gold deposits and 3 lead-zinc deposits in China (Fig. 1). After
acquiring the data, IMAGEM software was applied to the
data from each survey line. The model was modified several times to reach convergence. The contour map was
achieved by Surfer 6.0 software.
The results show that EH-4 image system not only can
clearly reflect the shape and scale of the buried mineralising
body, but can also display its deep geological structure. The
system can provide important and direct evidence for location forecasts of concealed ore bodies. It is one of the
most advanced electrical survey methods.
2
Example: Kuoerzhenkuola gold deposit,
Xinjiang, China
2.1 General situation of the gold deposit
The Kuoerzhenkuola gold deposit is situated in the north
– western Xinjiang (Fig. 1). The gold deposit is hosted by
the middle Devonian Sawuer Group (D2S) andesite, volcanic agglomerate and volcanic breccia. The west-northwest trending intrusions are thought to have supplied the
thermal drive for the hydrothermal system. Five ore veins
are mainly controlled by the east-west striking regional
fault and the caldera fractures (Yin et al. 1996; Zhang 1998)
(Fig. 2). The main mineralising belt is about 2000m long,
with a width of 10-35m. The gold ore bodies can be di-
Close
1506
Q.D. Zeng · J.M. Liu · H.T. Liu · G.M. Li · T.B. Liu · C.M. Yu · P. Shen · J. Ye
vided into two groups, based on their controlling structures. The east-west trending V1 and V2 veins, controlled
by regional faults, are larger than other veins which strike
north-east and north–west-north and controlled by
caldera fissures.
The most important of the east-west striking vein has
been traced for 1700m along strike, and ranges in thickness from 1 to 5m. Average gold values range from 2.38 to
8.23 g/t (Li, 2002). The ore is mainly composed of sulfides, quartz and a minor amount of altered minerals.
Sulfides include pyrite, pyrohotite, chalcopyrite and
sphalerite. The content of the sulfides in ores is approximately 30-50%. The gangue minerals are quartz, sericite,
chlorite, calcite and epidote. The alteration includes silicification, pyritisation, sericitisation, chloritisation and
carbonitisation.
2.2 EH4 image system survey
Three EH4 profiles (E1 and E2) were measured in the
Kuoerzhenkuola gold deposit in 2002 (Fig. 2). The purpose of the EH4 exploration was to investigate the detailed resistivity structure of the main gold mineralisation
belt (V1). A total of 78 measurements sites were located
at 20m intervals along the north-south trending survey
lines that cross the west part of the V1 vein (Fig. 2). The
two EH4 survey lines coincide with the 77th and 95th exploration lines, respectively. The final models for the three
typical survey lines, E1 and E2 are shown in Figures 3a
and 3b. The resistivity model for E1 (Fig. 3a) shows that
there is a relatively small resistivity anomaly zone present
at the shallow of the gold-bearing mineralisation belt. The
ore body extends to a depth of 100m. A stronger and bigger resistivity anomaly (dark shading, less than 150 Ωm)
occurs at the depth from 350m to 780m under surface. It
may represent the location of the buried ore body.
The resistivity model for the line E2 is similar to that
of the E1 line, the difference being that the scale of the
resistivity body appears bigger on E2 (Fig. 3b). Three small
resistivity bodies of less than 150 Ωm can be seen in the
south at a depth from 50m to 250m and these may be
other small ore bodies.
3
Conclusions
1. EH4 image system can measure the sequence resistivity of the geologic body at the different depths. The
measured results can be displayed by the 2D model
map (resistivity-depth map). The resistivity difference
among the different geologic bodies is the major influence factor of the EH4 application. Metal sulfidesbearing mineralisation belts have the lower resistivity
than wallrock such as intrusive, volcanic, metamorphic
rock and other types of unaltered rock. There is a big
resistivity difference between the wallrock and the
mineralizing body.
Close
Chapter 14-14 · Application of the EH4 image system to the detection of blind gold deposits, China
2. The electric resistivity anomalies measured by EH4
image system survey can be divided into three types:
low resistivity anomaly (1-300Ωm), middle resistivity
anomaly (300-1000Ωm) and high resistivity anomaly
(1000-1500Ωm). The resistivity anomaly value is confirmed by the resistivity of the representative rocks
(ores), the range of the special anomaly value in 2D
model map and the corresponding degree between the
geophysical anomaly and the known ore body. It indicates that the electric resistivity value causing ore and
mineralisation anomaly is lower. The mineralising
anomaly can be confirmed by contrasting the known
ore anomaly value with the discovered anomaly value.
The distribution range of the geophysical anomaly
corresponds with the mineralising belt, but it is larger
than the range of the ore body. The ratio (geophysical
anomaly width/ore body width) is about 10:1.
Acknowledgements
The authors thankful for the assistance we have received
at all stages of this study from our collaborators. This study
1507
was financed by the innovative project of Chinese Academy of Sciences (KZCX3-SW-138, KZCX3-SW-137) and
the important project of the National Science and Technology (2001BA609A07-08).
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1508
Q.D. Zeng · J.M. Liu · H.T. Liu · G.M. Li · T.B. Liu · C.M. Yu · P. Shen · J. Ye
Milkereit B, Eaton D, Wu J, Perron G, Salisbury M, Berrer EK (1996)
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Close
Chapter 14-15
14-15
Numerical modelling of coupled deformation and
fluid flow in mineralisation processes
Y. Zhang, A. Ord, P.A. Roberts, P. Sorjonen-Ward1
Predictive Mineral Discovery Cooperative Research Centre, CSIRO Exploration and Mining, PO Box 1130, Bentley, WA 6102,
Australia
1
currently at Geological Survey of Finland, PO Box 1237, Fin-70211, Kuopio, Finland
Ge Lin, Y.J. Wang
Guangzhou Institute of Geochemistry, the Chinese Academy of Sciences, Guangzhou 510640, China
Abstract. Coupled deformation and fluid flow modelling represents
a powerful computational tool, that has great potential in studying
deformation and fluid flow interaction during epigenetic
mineralisation processes, and in assisting exploration geologists to
perform efficient scenario tests during mineral exploration campaign. To advocate this view, this paper describes the methodologies of coupled deformation and fluid modelling, and presents the
results of two case studies. The first case study demonstrates that
utilisation of the modelling approach in the Kanjiawan Au-Ag-PbZn deposit (China) has facilitated our understanding of rock brecciation and associated fluid flow during mineralisation in the area.
The second case study illustrates how we have used the computational method to explore basin scale fluid flow during structural
inversion of the Isa Superbasin (Australia).
and generate a replay of deformation-fluid flow interacting
processes. The ability to vary geometry, boundary conditions and spatial-time scale also allows us to easily explore
many different scenarios for a district or deposit.
In this paper, we first briefly describe the basis of our
numerical methodologies. We then present the results of
two numerical modelling case studies, illustrating the
utilisation of modelling in ore deposit studies. These case
studies are modelling of: (1) Rock brecciation and associated fluid flow in the Kangjiawan Au-Ag-Pb-Zn deposit,
China; and (2) Deformation and fluid flow during structural inversion of the Isa Superbasin, Northern Australia.
Keywords. Numerical modelling, deformation and fluid flow,
mineralisation, Kangjiawan, Isa Superbasin
2
1
Introduction
Deformation and fluid flow are two of the most important processes controlling epigenetic mineralisation under a wide range of tectonic settings. This covers situations such as mineralisation associated with basin structural inversion and fluid migration, the development of
crustal-scale plumbing system in orogenic belts, and magmatic intrusion-deformation-fluid transport. At a deposit
scale, deformation may lead to localised rock damage and
brecciation in specific stratigraphic horizons. The sites
of such damage and brecciation zones often attract
mineralising fluids and this in turn often determines the
location of ore bodies or mineralised sites.
Understanding of deformation and fluid flow during
mineralisation is traditionally based on field structural
analysis and studies of fluid inclusion geochemistry and
ore/alteration zone mineral assemblages. Recent development of coupled deformation and fluid flow numerical
modelling and its application to studies of formation of
ore deposits (e.g. Ord and Oliver 1997; Schaubs and Zhao
2002; Sorjonen-Ward 2002; Zhang et al. 2003) have expanded
our capability to unravel the complexity of feedback interactions between rock deformation and mineralising fluid
flow. In particular, numerical modelling methods enable
forward simulation of the mineralising history in a district,
Methodologies
A finite difference code, FLAC (Fast Lagrangian Analysis
of Continua; Cundall and Board 1988; Itasca 1998), has
been used in the current models. Materials are represented
by a grid of elements fitting the geometries of the structures to be simulated. The numerical grid behaves according to prescribed mechanical and hydraulic laws in response to the applied boundary conditions, and can yield,
flow/deform, and move with the material. This explicit,
Lagrangian, computation scheme, together with the
mixed-discretisation technique adopted in FLAC, ensure
that plastic failure and flow are modelled correctly.
The mechanical behaviour of the current model is governed by the Mohr-Coulomb elastic-plastic constitutive
law (Jaeger and Cook 1979). A Mohr-Coulomb material
undergoing deformation behaves elastically until the stress
reaches the yield surface, at which point it begins to deform plastically, and irreversibly. The yield of such material is governed by the Mohr-Coulomb criterion, that is,
failure occurs if:
|τs| = C - σn tanφ
(1)
where τs and σn are the shear and normal stresses across
arbitrary planes within the material space; C is cohesion
and φ is friction angle. A Mohr-Coulomb elastic-plastic
material undergoing plastic deformation may change in
volume. The amount of dilation (plastic volume increase)
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Y. Zhang · A. Ord · P.A. Roberts · P. Sorjonen-Ward · Ge Lin · Y.J. Wang
is controlled by a dilation angle that is a constant material parameter used in the model.
Fluid flow in these models is governed by Darcy’s Law
(see Bear and Verruijt 1987), given by
qi = -kij/µ ∂/∂xj (P - ρwgkxk)
(2)
where qi is the specific discharge vector or Darcy fluid
velocity (m s-1), kij is the permeability (m2), µ is the fluid
viscosity, P is the fluid pressure, ρw is the fluid density, g
is gravity, and xi is the position of a material point. Therefore, fluid velocities are mainly a function of gradients in
pore fluid pressure or hydraulic head with gravity present
and permeability.
Deformation and fluid flow are coupled throughout
modelling. This interaction is reflected in the following
ways:
1) Pore fluid pressure affects effective stresses and thus
plastic yielding;
2) Volumetric strain is instantaneously related to fluid
pore pressure changes (dilation leads to a pore pressure decrease, while contraction results in pore pressure increase) and hence the fliud flow;
3) The development of any topographic elevation or depression can also lead to changes in fluid flow patterns.
The model requires the specification of material properties including density, elastic moduli (bulk and shear
moduli), cohesion, tensile strength, friction angle, dilation
angle, fluid density, permeability and porosity. Deformation and hydrological boundary conditions (e.g. loading
velocity and initial pore pressure) must also be defined.
3
Rock brecciation and associated fluid flow in the
Kangjiawan deposit, China
The Kangjiawan Au-Ag-Pb-Zn deposit is one of the major deposits in the Shuikoushan district, Hunan, China
(see Liu and Tan 1996; Zhang 1999). Mineralisation here
occurred at or after about 172 Ma, under the setting of
the Yanshannian tectonic event (ca. 180 – 90 Ma). Structural analyses in the deposit show that lens-shaped ore
bodies are predominantly hosted in the brecciation zones
developed in the silicified section of the Permian limestone, particularly at intersecting sites between a main
fault (F22), the silicified zone and fold hinges. The breccia
zones along the unconformity at the base of the early Jurassic unit are another favourable ore location, particularly where the silicified limestone zone is in direct contact with the unconformity. The interest for pursuing numerical modelling is to generate understanding of:
1. How brecciation develops in the stratigraphic system
of the deposit;
2. What are the associated fluid flow patterns.
The initial geometry of the 2D coupled deformation
and fluid flow model (Fig. 1) is based on the structures of
the P104 exploration profile through the deposit. However backward geometrical modelling (based on cross
section balancing principles) has been carried out to recover some shortening deformation along the profile, and
this is incorporated in the model. Model properties are
chosen based on rock types and data in literature. For
example, the silicified section of the Permian limestone
is defined as a strong (high cohesion) and brittle (low
tensile strength) unit, and the main fault (F22) is specified as a weak and highly permeable zone in the section.
The model is horizontally shortened by about 5%. The
locations of tensile failure, the associated high permeability development and Darcy fluid flow velocities for
the central area of the model are shown in Figure 2. It is
noted that tensile failure (representing brecciation) and
high permeability creation are dominantly localised in
the fold hinge/core area where the silicified zone and Permian limestone intersect with the F22 fault. The overturned
limb of the fold shows more tensile failure. Fluids are
strongly focused towards these locations; maximum flow
rate is 1.67×10-7 m s-1. In the meantime, some downward
fluid flow along the F22 fault is also directed towards these
locations. Such fluid flow patterns represent an ideal scenario for fluid mixing, favourable for mineralisation. These
rock tensile failure features are consistent with the observation of severe fracturing-brecciation at corresponding structural locations in the Kangjiawan deposit. Locations of intensive fluid focusing and mixing also match
the locations of ore bodies along the P104 profile (see
inset in Fig. 2).
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Chapter 14-15 · Numerical modelling of coupled deformation and fluid flow in mineralisation processes
1511
The results of the current deformation and fluid flow
models highlight that rock brecciation in the Kangjiawan
deposit is characterised by: 1) combination of fold hinge and
fault intersection locations (structural) and 2) the silicified
zone and limestone unit (lithological). Such brecciation
zones are associated with extensive fluid focusing and mixing, and therefore represent the most favourable locations
for mineralisation in the areas adjacent to the deposit.
4
Deformation and fluid flow during structural
inversion of the Isa Superbasin, Northern Australia
Proterozoic rocks of Isa Superbasin in northern Australia
host globally-significant Pb-Zn-Ag deposits as well as a series of Cu, Cu-Au and U deposits. Background information
on the geological setting, geodynamic history and metallogeny of the Isa Superbasin can be found in Betts and Lister
(2002), Williams (1998) and Southgate (2000). Results of a
fluid flow and thermal transport model on the McArthur
Basin, Northern Australia, in which density-driven free convection dominates, can be found in Garven et al. (2001). The
current numerical model focuses on basin-scale fluid flow
patterns during shortening deformation in the initial stages
of structural inversion of the Isa Superbasin at ca. 1575 Ma.
The geometry of the model is based on the P1 profile
through the Isa Superbasin, the compilation of which integrates the results of extensive regional, geophysical and
geological studies (Scott et al. 1998, 2005). This profile
represents a reconstruction of the architecture and structure for the Isa Superbasin at ca. 1575 Ma. Figure 3a illustrates the outline of model architecture and Figure 3b show
the simplified permeability structure of the model. The
model is subject to horizontal shortening to simulate N-S
shortening at the start of the Isan Orogeny.
Figure 4 illustrates the distributions of fluid flux volumes
derived from coupled deformation and fluid flow simulation after 8% bulk horizontal shortening. In one model
(Fig. 4a) where permeabilities are kept constant and no external strong lateral flow along the Mt Guide and
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Y. Zhang · A. Ord · P.A. Roberts · P. Sorjonen-Ward · Ge Lin · Y.J. Wang
Westmoreland horizon (aquifer) in the north part of
the model, in contrast to strong vertical upward flow along
steep faults in the south part of the model. There is little
across layer flow due to the presence of multiple low permeability layers. These patterns reflect controls of primary basin permeability structures under the setting of
contractional deformation.
The second model (Fig. 4b) incorporates a mechanism
that allows permeability increase at the locations undergoing tensile failure and also considers dehydration-related fluid production from the Eastern Creek Volcanics.
The model results at 8% bulk shortening (Fig. 4b) exhibit
two major changes: 1) Strong cross layer flow, particularly through low permeability units near the Eastern
Creek volcanics levels, reflecting extensive tensile failure
and permeability enhancement in these units; 2) Greater
fluid flux values than in the first model, representing enhanced flow both in aquifer units or units experiencing
extensive tensile failure and through major basin faults
(e.g. the Termite Range fault). Such fluid flow regimes are
more favourable for concentrated mineralisation near the
basin-scale faults and may also lead to widespread
mineralisation in the rock units that experienced severe
tensile failure or hydrofracturing. This helps our understanding why most known deposits in the region occur
near major basin-scale faults (e.g. the Termite Range Fault).
5
Concluding remarks
Interaction between deformation and fluid flow is one of
the most important coupled processes during epigenetic
mineralisation. This process can be efficiently simulated
by coupled deformation and fluid flow modelling. Recent
advancement of modelling technologies allows the modelling of complex geometries and a range of mechanicalfluid flow-thermal-chemical processes, though the current paper does not cover the aspects of thermal and
chemical modelling. Application of such quantitative, computational methods to specific regions, as demonstrated
here for the Kangjiawan deposit and the Isa Superbasin,
provides one way to test geological scenarios and generate ideas for understanding a mineralising system.
Acknowledgements
The Predictive Mineral Discovery Cooperative Research
Centre, the Chinese Academy of Sciences (grant no.
GIGCX-03-02/), the Australia-China Special Fund for Scientific and Technological Cooperation, and AMIRA International are thanked for financial support. We thank
PN Southgate, BE Hobbs, G Hall, YQ Peng and ZY Tan for
their contribution and assistance. Heather Sheldon is
thanked for her constructive review and comments.
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Chapter 14-16
14-16
A new exploration parameter for metallic deposits::
The alteration remote sensing anomaly
Yujun Zhang
Aero-Geophysical Survey and Remote Sensing Center for Land and Resources, 31 Xueyuanlu Rd., Beijing 100083, China
Jianmin Yang
Institute of Mineral Resources, Chinese Academy of Geological Sciences, 26 Baiwanzhuang Rd., Beijing 100037, China
Abstract. A new parameter for the prediction of the mineral
resources,the alteration remote sensing anomalies, is proposed. The
geological basis and the spectral presupposition for the alteration
anomalies are discussed. An advanced system for extraction of hydrothermal alteration assemblages, using ETM+ and Aster data, was
developed. The simplified flow chart of this system, “De-interfered
Anomalous Principal Component Thresholding Technique”, is shown
below.
Some new terms are defined. The RM (Ratio Method), SAM
(Spectral Angle Mapper) and PCA (Principle Component Analysis) are compared by the analysis of their principle and by model
test. PCA is selected as the main method with SAM as the supplementary one. The essential conceptions of the probability theory
were quoted. The standard deviation s is used as the measure for
anomaly slicing (Thresholding).
Keywords. Alteration remote sensing anomaly, multi-spectral remote
sensing technique, ETM+, Aster
1
Introduction
2
ETM+ data
An advanced system for extraction of hydrothermal alteration assemblages from ETM+ and Aster data, “De-interfered Anomalous Principal Component Thresholding
Technique”, is illustrated in Figure 1. It consists of 5 main
blocks: preprocessing, normalizing, extraction, post-processing and thresholding. The necessity of the normalization is for improvement of the comparison between
the adjacent images and the images at different times. To
get the relative reflectance, the normalization includes the
corrections for sensitivity, magnification, sun-earth distance, sun elevation, and radiation above atmosphere. The
RM, SAM and PCA are compared by the analysis of their
principles and the modeling test. The pre- and post- processing have been done for limiting the interference of
water, ice, cloud, snow, vegetation, relief shadow, cloud
shadow, and salt-lick.
Since the 1990s the application of multi-channel remote
sensing (RS) data for exploration of metallic deposits has
been attracting more and more attention throughout the
world (Crosta and McM Moore 1989; Loughlin 1991). A
big project on alteration anomaly extraction for vast territories (> 2 million km2) of West China was completed
in 2001-2005.We study the alteration remote sensing
anomaly as an independent parameter (Zhang et al. 2002,
2003; Zhang and Yang 1998; Li and Zhang 1997). The alteration RS anomaly is considered an independent parameter based on the following 3 reasons:
1. It is based on special physical and chemical property;
2. Its result could not be obtained from other parameters
using other methods;
3. There is still big room for improving the technology
as a sub-branch of the RS discipline.
By the end of 2004th year more than 15 new metallic
deposits or mineralization spots were found already using the alteration remote sensing anomalies that we got.
The excellent results of this project show the potential
power of multi-channel. RS data (ETM+ and Aster) for
alteration mapping is by far not exhausted.
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Yujun Zhang · Jianmin Yang
3
According to the Central Limiting Theory, if a random
variable is caused by a lot of random independent between each other factors, and each individual factor plays
an insignificant effect to the total one, the random variable usually obeys or nearly obeys the normal distribution (Kendall 1975; Zhuang and Wu 2002).
The information entropy for 3 occasions was calculated to
identify the improvement of their quality. To evaluate the normality of the histograms, the asymmetry and peak-factor are
calculated using the special forms (Yuan and Zhou 2003).
The 3rd histograms are the closest to the normal probability curve. On this basis we can use the standard deviation σ for slicing of the anomaly principle component,
as the quantitative measure of thresholding. We take 3
levels for OHA and 3 levels for FCA.
The detection limit or sensitivity of PCA for OHA was
evaluated by the modeling as one 20000th part or 50 PPM.
The vegetation interference limits the possibility of extraction for the alteration RS anomaly. Our modeling shows
the upper limit (or vegetation interference tolerance) is 50%
of vegetation for mixed pixels. This means when the mixed
pixels consist of more than 50% vegetation, the remote sensing anomaly cannot be extracted properly from them. This
can limit the use of the technology in the vegetated area.
However, apart from these areas, there are always some local arid areas, for which the extraction is no problem.
Aster data
Aster (Advanced Space-borne Thermal Emission and
Reflection Radiometer) data has a unique combination
of wide spectral coverage and high spatial resolution in
visible near-infrared (VNIR), short-wave infrared (SWIR),
and thermal infrared (TIR) regions.
Satellite Terra, carrying Aster instrument, was launched
in December 1999. There are 14 spectra channels for Aster data: 3 VNIR, 6 SWIR and 5 TIR. The additional SWIR
and TIR channels make it possible to recognize some rock
and deposit types. For example, we have obtained big success in distinguishing the deposit types for the Mongolian Oyu-Tolgoi porphyry Cu deposit and the Chinese LuoDong ultra basic Cu-Ni deposit using the additional SWIR
data (see Figs. 2, 3) The Luo-Dong ultra basic Cu-Ni deposit was discovered in July 2004 by the alteration RS
anomaly achieved in June 2004 using ETM+ data (139/
32) by PCA and SAM. The spectral characteristics of minerals with Al-OH or with Mg-OH contents are illustrated
in Figure 4. It is obvious that the porphyry Cu deposit
contains more Al-OH minerals, and on the contrary, the
ultra basic Cu-Ni deposit contains more Mg-OH minerals. This is the reason why the Oyu-Tolgoi deposit has
better OHA, extracted by PCA using 1, 3, 4, 5 channels,
and the Luo-Dong deposit has better OHA extracted by
PCA using 1, 3, 4, 8 channels. The spectral ranges of the
5th and 8th channels are 2.145-2.185µm and 2.295-2.365µm,
respectively. The spectral characteristics for both examples
in Figure 3 and 4 clearly explain this result. The 5 TIR
channels were used for rock classification.
We can conclude that the Aster data can play an important complementary role in extraction of alteration
remote sensing anomaly from ETM+ data facing the possibility of high spectra resolution of hyper-spectra data
in determination of minerals and deposit types.
Acknowledgements
This paper is financially supported by the Chinese geological exploration project (200215000008) and 305 project (2003BA612A-06-4) of China’s state science and technology fund.
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