PACIFIC
Passive seismic techniques for environmentally friendly and cost efficient mineral exploration
D1.1– Assessment of successful active seismic
processing workflows
Grant agreement number 776622 Due date of Deliverable 30/09/2018
Start date of the project 01/06/2018 Actual submission date 30/10/2018
Duration 36 months
Lead Beneficiary UGA Contributors SISP, DIAS
Description
Report listing and evaluating all currently active seismic processing workflows.
Dissemination Level
PU Public X
CO Confidential, only for members of the consortium (including the Commission Services)
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Table of content
Table of content ...................................................................................................................................... 2
List of figures ........................................................................................................................................... 3
List of tables ............................................................................................................................................ 4
Executive Summary ................................................................................................................................. 5
1 Introduction .................................................................................................................................... 6
2 Active (controlled source) seismic method .................................................................................... 7
2.1 Principles of active seismic as applied to mineral exploration ..................................................... 8
2.2 Mineral survey processing sequence (workflows) ........................................................................ 8
3 Conclusion ..................................................................................................................................... 13
Bibliography .......................................................................................................................................... 14
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List of figures
Figure 1. Sketch of seismic survey in a simple layer model (lower diagram) and resulting seismogram with appropriate seismic signals (upper diagram) adopted from Wiederhold (2007). Green shows direct travelling wave, blue shows refracted or head wave, and red shows reflected waves. ......................................................... 7 Figure 2: Comparison between a) Specific Mineral Survey Processing Sequence and b) common processing sequence. More details and higher frequency image is obtained from the specific MSPS (from Malehmir and Bellefleur, 2010) .................................................................................................................................................... 11 Figure 3. Seismic reflection image of the lithology and structures of the units that host the McLeay Ni-sulfide deposit in Western Australia. Clearly distinguished are the ultramafic host unit, a large fault, and the ore deposit itself (from http://www.hiseis.com). ....................................................................................................... 12
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List of tables
Table 1. Standard Mineral Survey Processing Sequence (Salisbury and Snyder, 2007). ......................................... 9 Table 2 Specific Mineral Survey Processing Sequence (Malehmir et al, 2006; Malehmir and Bellefleu, 2010). ... 10
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Executive Summary
Across the globe, the mineral industry is seeking new technologies to replace or complement existing
geological, geochemical and geophysical methods to improve exploration efficiency at depth and to
help design safer and more productive mines. These industries are increasingly using seismic methods
for a wide range of commodities including base metals, uranium, diamonds, and precious metals.
Seismic methods usually can be used for direct targeting of mineral deposits but particular care must
be taken during acquisition and processing of the data. To achieve the best results, different
processing sequences based on the target of the project are applied. Here we compare and discuss
how such workflows are used when treating active seismic data in order to provide a basis for their
use in the development of the passive seismic methods that form the basis of the PACIFIC project.
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1 Introduction
The mining industry has traditionally used geologic field mapping, electromagnetic and potential field
techniques, and drilling to explore for new mineral deposits, but with new discoveries of large near-
surface deposits becoming increasingly rare, it is clear that new deep exploration techniques are
required to meet the future needs of industry and society (Salisbury and Snyder, 2007).
With other geophysical methods unable to resolve targets beyond about 500 m, high-resolution
controlled source seismic techniques similar to those used by the petroleum industry, but modified
for the hardrock environment, have the greatest potential for extending exploration to depths of 3
km, the current maximum depth of mining (Salisbury and Snyder, 2007). Petroleum companies have
used such methods for many decades during their exploration for oil and gas reservoirs in sedimentary
settings. The technology has evolved considerably leading to current fully 3D surveys that are capable
of determining the structure of sedimentary sequences to depths of many kilometres. Active seismic
methods provide high-resolution images of geologic structures hosting mineral deposits and, in a few
cases, can be used for direct targeting of ore bodies, but a complete survey of this type may cost
thousands to millions of euros.
Salisbury and Snyder (2007) reported successful use of 2-D and 3-D surveys in detection of (1) large
massive sulphide deposits such as the magmatic and volcanic massive sulphide deposits, (2) massive
sedimentary exhalative deposits and (3) iron oxide copper gold deposits worldwide. In addition,
alteration haloes and the general geological setting can be used to explore for other types of deposits
such as lode gold and porphyry deposits, unconformity uranium deposits, and Mississippi Valley-type
deposits
The steadily increasing usage of reflection seismic methods demonstrates that they are finally
becoming recognized and established within the mining sector. However, because most economic
mineral deposits are found in "hard" (igneous or metamorphic) rocks, rather than sedimentary,
environments, and the impedance contrasts and reflection coefficients between most common
igneous and metamorphic rocks are smaller than those between sedimentary rocks. Because of this,
particular care must be taken during the acquisition and processing of seismic data.
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2 Active (controlled source) seismic method
In controlled source seismic studies, receiver networks record seismic waves from an artificial source,
allowing detailed views of fine-scale structures (Figure 1). Betsy guns and weight drop systems,
dynamite in shallow boreholes, airguns in water-filled pits or fluid-filled pans attached to vehicles, and
vibroseis trucks are used as the seismic source, based on the requirements and the purpose of the
study.
Reflection and refraction seismology, both active seismic methods, are complementary imaging
techniques, that yield high-resolution images especially suitable for detecting and imaging seismic
interfaces showing a strong contrast in seismic velocity (Wagner et al, 2012). Reflection seismic
methods have been used worldwide to target mineral deposits. Important seismic studies that were
designed to guide exploration programs include Adam et al. (2003), Pretorius et al. (2003), Bellefleur
et al. (2004), Malehmir and Bellefleur (2009), Malehmir et al. (2006), Tryggvason et al. (2006),
Malehmir et al. (2010) and Dehghannejad et al. (2010).
Figure 1. Sketch of seismic survey in a simple layer model (lower diagram) and resulting seismogram with appropriate seismic signals (upper diagram) adopted from Wiederhold (2007). Green shows direct travelling wave, blue shows refracted or head wave, and red shows reflected waves.
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2.1 Principles of active seismic as applied to mineral exploration
Two basic factors govern whether or not a potential reflector can be detected and imaged by seismic
reflection techniques: (1) the difference in acoustic impedance (velocity-density products) between
the deposit or horizon and its surroundings, and (2) its geometry, especially its size and depth of burial
(Salisbury and Snyder, 2007). Since ore-forming process changes the density, acoustic velocity or
strength of the rocks, a mineral deposit can be detected using seismic reflection methods.
At the regional scale, 2D transects can define major crustal boundaries associated with metalliferous
provinces, and can also image lithosphere-scale faults that act as conduits for ore-forming fluids. At
the camp scale (10s of km) seismic methods can image structures such as folds, unconformities and
faults that control ore deposition, and in some cases can distinguish lithologies such as intrusions or
favourable sedimentary units that host the mineralization. At the deposit scale (< 10km) 2D and 3D
seismic surveys can accurately define the geometry of ore surfaces or key marker reflectors. Offsets
and truncations of the ore due to faults and intrusions are also detectable. Large bodies of sulphide
ore constitute excellent seismic targets.
2.1.1 Special considerations for mineral exploration
When applying seismic reflection methods during mineral exploration, special care must be taken
during the fieldwork deployment and also afterward during data processing.
In "hard" (igneous or metamorphic) rocks, the impedance contrasts and reflection coefficients are
smaller than those found in sedimentary rocks, and the signal-to-noise (S/N) ratio in minerals surveys
will be low, making it more difficult to image structures. Particular care must thus be taken during
acquisition and processing to maximize the S/N ratio (Salisbury and Snyder, 2007). During field
acquisition, this is typically achieved by using explosives in shallow boreholes filled with water or
tamped with sand to ensure good source coupling to bedrock, and by using cemented or clamped
geophones whenever possible. Furthermore, during the data processing, in order to improve the
signal-to-noise ratio of the extracted reflected arrivals, the common mid-point gather technique is
used to facilitate data stacking and noise reduction. These reflections can be further migrated at
depth, using a refraction-based velocity model, in order to obtain a full surface distance-over-depth
reflectivity section of the studied area. When interfaces are steep, as is common in mineral resource
exploration, great care must be taken during this step of migration, which requires state-of-the-art
seismic modelling and inversion procedures.
In addition, since some types of ores only have small impedance contrasts with many common host
rocks, it is often advisable to conduct laboratory measurements of the velocities and densities of the
ores and host rocks in a potential survey area to determine whether reflections are even possible and
the survey worth conducting (Salisbury and Snyder, 2007).
2.2 Mineral survey processing sequence (workflows)
Since even rich ore deposits are often fairly small (<1 km across) or have small impedance contrasts
with the host rocks, the processing of reflection data from mineral surveys plays an important role to
image the structures. Different studies have suggested different workflows for the processing of
reflection data (Table 1 and 2). In general, there is no unique way for processing the reflection data
and the approach to be adopted must be based on the geology, survey characteristics and the nature
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of the study. Salisbury and Snyder (2007) suggested the Mineral Survey Processing Sequence as shown
in Table 1 for mineral surveys that involves two processing streams, one to image structures such as
folds or faults in country rock and another to locate, enhance, and trace diffractions to their sources
using unmigrated data. Malehmir et al. (2006) and more recently Malehmir and Bellefleur (2010)
suggested a more detailed processing procedure for reflection data in active seismic survey (Table 2)
and they applied this approach for several case studies.
The reflection data processing includes several major steps, as shown in Figure 2. After setting up the
field geometry and collecting the data, these data are converted to an appropriate format (usually
SEG-Y or SEG2); then after selecting the first pick, a series of trace statistics is applied on the trace. In
the next phase, different filters are applied to obtain a clearer signal and to prepare the data for
velocity analysis. After applying Normal-moveout and Dip-moveout corrections, all the traces
are stacked. At the end, by filtering the resultant data to remove the noise and do the
migration, the results are ready for interpretation (Figure 3).
Table 1. Standard Mineral Survey Processing Sequence (Salisbury and Snyder, 2007).
1. Pre-processing (Geometric spreading correction, Set up field geometry, Application of field statics)
• Demultiplex
• Set up field geometry
• Edit
• True amplitude recovery
2. Deconvolution
3. Band-pass filtering
4. Gain control
5. First break mute
6. Refraction statics corrections
7. Residual statics corrections
8a.Unmigrated Stack
• Dip moveout (DMO) corrections
• Velocity analysis
• NMO correction (Muting, Stacking)
• Stacking
• Band-pass filter
8b. Migrated Stack
• Prestack migration
• Velocity analysis
• Scaling
• Band-pass filter
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Table 2 Specific Mineral Survey Processing Sequence (Malehmir et al, 2006; Malehmir and Bellefleu, 2010).
1. Read (window)-s data
2. Build geometry data: Extract and apply geometry (several tests to obtain optimum bin size)
3. Trace editing and polarity reversal
4. Pick first breaks: full offset range, automatic neural network algorithm but manually inspected and corrected
5. Refraction static and elevation static corrections
6. Geometric-spreading compensation
7. Band-pass filtering
8. Surface-consistent deconvolution
9. Top mute
10. Direct shear-wave attenuation (near-offset)
11. Air blast attenuation
12. Trace balance using data window
13. Velocity analysis (iterative)
14. Residual static corrections (iterative)
15. Normal moveout corrections (NMO)
16. Dip moveout (DMO) corrections (iteratively link to velocity analysis)
17. Stack
18. Fx-deconvolution (post-stack coherency filter)
19. Trace balance: 0–1500 ms
20. Phase-shift migration: using smoothed stacking velocities,
21. Time-to-depth conversion: constant 5500 m/s
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Figure 2: Comparison between a) Specific Mineral Survey Processing Sequence and b) common processing sequence. More details and higher frequency image is obtained from the specific MSPS (from Malehmir and Bellefleur, 2010)
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Figure 3. Seismic reflection image of the lithology and structures of the units that host the McLeay Ni-sulfide deposit in Western Australia. Clearly distinguished are the ultramafic host unit, a large fault, and the ore deposit itself (from http://www.hiseis.com).
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3 Conclusion
The steadily increasing usage of reflection seismic methods demonstrates that they are finally
becoming recognized and established within the mining sector. Due to the small size of most deposits,
the structural complexity of hard rock terranes and their low signal-to-noise ratios, the best results
are obtained from carefully designed surveys using high frequency sources and customized processing
sequences. To have a better and clearer image for the interpretation in reflection surveys, based on
what has been shown in Table 1 and 2 and Figure 3, the processing sequence requires that a series of
major steps are applied on the collected data. PACIFIC will use this information for the collection of
data from the reflection passive seismic survey in Marathon.
Using different filters to increase the S/N ratio, applying the NMO and DMO corrections and finally
stacking and migrating the data to have a clear image are the most important steps in seismic data
processing. PACIFIC will use this information for the collection and treatment of data from the
reflection passive seismic survey in Marathon.
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Bibliography
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