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Cross-profile acquisition and cross-dip analysis for extracting 3D information from 2D surveys, a case study from the western Skellefte District, northern Sweden
Journal of Applied Geophysics 63 (2007) 1 – 12 www.elsevier.com/locate/jappgeo
Cross-profile acquisition and cross-dip analysis for extracting 3D information from 2D surveys, a case study from the western Skellefte District, northern Sweden Johiris Rodriguez-Tablante ⁎, Ari Tryggvason, Alireza Malehmir, Christopher Juhlin, Hans Palm Uppsala University, Department of Earth Sciences, Villavägen 16, SE-752 36 Uppsala, Sweden Received 31 January 2006; accepted 7 March 2007
Abstract Two nearly parallel seismic profiles were acquired in the Kristineberg area, located in the western part of the Skellefte ore district, in northern Sweden. A novel approach in the acquisition was that all shots from each profile were recorded onto both lines, resulting in a third CDP line halfway between the two profiles. The combination of geometry, acquisition parameters and geological complexity of the area required specific processing techniques to produce a stacked section that could be correlated with the two in-line processed seismic profiles. The processing sequence included a carefully designed frequency filter, optimized stack methods and pseudo 3D processing by applying cross-dip corrections. Due to the long offsets between the profiles, the resulting stacked section does not provide any information in the upper 1.2 s. Below 1.2 s, the upper crust shows a north-dipping event that correlates well with observations on the in-line data. Sub-horizontal reflectivity is also observed in the upper 4 s of the stack, similar to what is observed on the profile west of the cross-profile. Cross-dip analysis shows that the north-dipping event observed in all three profiles has a westerly dip component. Our study shows that additional information on the sub-surface may be obtained through cross-profile acquisition and processing. © 2007 Elsevier B.V. All rights reserved. Keywords: Hardrock environment; Signal-to-noise; Optimized stack; Crooked line; Cross-dip analysis; Skellefte VHMS District
1. Introduction Seismic reflection techniques have been used in studies of sedimentary environments for almost 80 years. However, in recent decades several independent research efforts have established that the seismic ⁎ Corresponding author. Now at: Geophysical Operations, Norsk Hydro ASA, Norway. Tel.: +47 22536346. E-mail address: [email protected] (J. Rodriguez-Tablante). 0926-9851/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.jappgeo.2007.03.001
reflection method can provide structural images for deep mineral exploration in crystalline environments (e.g. Eaton et al., 2002). In general, seismic data acquired on hardrock environments is often characterized by lowsignal-to-noise ratio and a lack of continuous reflections (Salisbury et al., 2002). Roberts et al. (2002) have presented a case study of the Manitouwadge Greenstone Belt in Canada. Results from their work show that seismic reflection techniques can be a significant aid for mineral exploration by delineating key marker horizons and by potentially direct detection of massive sulfide
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deposits. Another successful case study is from Western Australia. Drummond et al. (2002) show the efficiency of seismic techniques for imaging the mineral trap stage of ore systems. Based on these experiences and others, high-resolution reflection seismic data were acquired in the fall of 2003 along two north–south trending parallel
profiles in the western part of the Skellefte district, one of the largest Paleoproterozoic volcanogenic-hosted massive sulfide (VHMS) districts in the world (Fig. 1). As a way to maximize the 3D information that can be extracted from a 2D survey, all shots from each profile were recorded onto both lines, resulting in a third CDP
Fig. 1. Geological map of the area based on Antal et al. (2003) showing the location of the acquisition lines (black) and the stacking lines for all three profiles (light grey). The dark grey “cloud” shown between the profiles contains the midpoint locations for the cross-profile.
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line located in between the two conventional profiles. In this paper, we focus on the processing and interpretation of these cross-profile data. Challenges in the processing include irregular geometry, long offsets and low amplitudes from relatively small charges, resulting in low S/N (signal-to-noise) ratios. Thus, much of the processing effort was dedicated to maximizing the S/N ratios by data removal based on the noise content of the traces. The crooked line nature of the profile also allows cross-dip analysis of the data to be performed. We use this analysis to provide geometric constraints on the major zones of reflectivity and the large-scale structures of the area. 2. Geologic setting The Skellefte District is the most important metallogenic zone in Sweden. It is generally accepted that it formed as the result of Palaeoproterozoic, c. 1.9 Ga, volcanic arc magmatism (e.g., Weihed et al., 1992; Allen et al., 1996). The volcanic arc formed between a sedimentary basin (Bothnian Basin) and a continental landmass to the north (Allen et al., 1996). The surface geology in the Kristineberg area (Fig. 1) shows that volcanic rocks of the Skellefte Group are overlain by younger volcano-sedimentary rocks of the Vargfors Group (Bergström and Sträng, 1999). The Bothnian basin does not outcrop in the area. Several geological mapping studies have been carried out in the region (Weihed et al., 1992; Allen et al., 1996; Billström and Weihed, 1996). However, they have given little information about contacts between the main geological units at depth. No previous reflection seismic data exist in the entire Skellefte District, with the exception of a short (10 km) north–south trending profile in the Norsjö area in the south-central part of the district (Elming and Thunehed, 1991; Juhlin et al., 2002). The western part of the Skellefte District hosts the largest VHMS deposit currently mined, the Kristineberg area. This part of the district is the best-studied site in the region, and was, therefore, selected for the seismic acquisition. The objectives of the seismic venture were to produce nearsurface images that could be correlated with the surface geology, as well as deep sections that could provide information about the contacts between the main geological units at depth. 3. Data acquisition Data acquisition was carried out along two nearly parallel 25 km long North–South running profiles spaced approximately 8 km apart, Profile 1 and Profile
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5 (Fig. 1). Profile locations were chosen to address critical questions regarding the geology of the area and to cross perpendicular to major structures. However, logistics and cost constraints required that existing roads be followed, resulting in the profiles being acquired with a crooked line geometry. Since Uppsala University had at the time two reflection seismic systems available, the two profiles were acquired simultaneously at the same cost as if they had been shot sequentially with one system, and at half the time. An alternative would have been to record two crossing profiles, but this option was discarded for logistical reasons. The cross-profile acquisition strategy thus produced three subsets of data; the standard 2D crooked line data along Profile 1 and Profile 5 and a third dataset, in this paper referred to as the cross-profile, corresponding to the data produced by shooting on one line and recording along the other line. Although fan shooting has been previously used (e.g. Thouvenot et al., 1995), it is unconventional to acquire two parallel seismic lines simultaneously and, thus, special processing techniques are required to
Table 1 Data acquisition parameters Survey parameters Type of survey Recording system Nominal spread
2-D crooked line and fan shooting SERCEL 348, SERCEL 408 Asymmetric split spread (20 stations tailing)
Nominal fold: Profile 1 Profile 5 Cross-profile
17 25 35
Energy source parameters Source type Nominal shot spacing Charge size
Dynamite 100 m 1–3 kg
Recording parameters Receiver (group) interval Nominal number of active channels: Profile 1 Profile 5 Field low-cut filter Record length Sampling rate Maximum offset: Profile 1 Profile 5 Cross-profile Geophones: Profile 1 Bunch of six Profile 5 Single Total profile length
25 m 140 200 8 Hz 20 s 2 ms 4000 m 5000 m 12000 m 10 Hz 28 Hz 50 km
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handle the data. The cross-profile can be considered as a third CDP line centered between the two main profiles. However, this profile contains no near-offset data, the minimum offset being 6.5 km in the south and the maximum offset 12 km further north. The details of the seismic acquisition are given in Tryggvason et al. (2006) and are summarized in Table 1. The acquisition parameters were not identical for the two profiles. For instance, due to the different capacities of the acquisition systems, shots were recorded on 140 channels along Profile 1 and on 200 channels along Profile 5, resulting in a nominal fold of 17 for the former and of 25 for the latter. The nominal fold for the cross-profile is 35. Moreover, Profile 1 was recorded using arrays of six geophones with a natural frequency of 10 Hz, while along Profile 5 single geophones with a natural frequency of 28 Hz were used. 4. Data processing 4.1. Standard processing steps The main processing steps applied to the crossprofile is shown in Table 2. Due to the differences in the number of recording channels and the crookedness of Profile 1 and Profile 5, the cross-profile data is characterized by an irregular geometry and midpoint distribution (Fig. 1). In order to maintain nearly uniform
fold, it is common to define smoothly curved lines for stacking data acquired along crooked line profiles. However, this approach can reduce the effectiveness of CDP stacking (Wu et al., 1995). When straight lines are used, geometrical effects due to dipping and out-of-theplane reflections are reduced, resulting in stacks with enhanced signal-to-noise (S/N) ratios. Thus, a CDP line defined by four straight-line segments was used for the cross-profile (Fig. 1). The data were binned with a CDP spacing of 12.5 m (half receiver spacing) in the in-line direction and a maximum of about 1.5 km bin width in the perpendicular direction, resulting in 1867 CDPs. One difficulty of recording simultaneously along lines that run near roads is to guarantee low cultural noise for both lines at a given time. Thus, the first step in the processing was the selection and editing of noisy shots and traces, including editing of spikes. Low amplitudes of the first arrivals made it impossible to use automatic first break picking routines, resulting in a rather difficult and time consuming manual picking procedure of the first arrivals. Due to the uncertainty of the first arrival picks, occasionally on the order of 50– 100 ms, they were not used for the refraction static corrections. Instead, the refraction static corrections were extracted from the processing of the in-line data. Fig. 2, shows a shot from Profile 1 recorded along Profile 5 before and after applying refraction statics. The ellipses highlight the part of the shot where the
Fig. 2. Example of a shot gather with and without refraction static corrections. Ellipses enclose traces where the improvements from the refraction statics are more evident.
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improvement of the previously calculated refraction static corrections is clearly seen. Due to the difference in the acquisition equipment, signal amplitudes recorded along Profile 5 were significantly higher (∼ 103) than the data recorded along Profile 1. Hence, it was necessary to normalize the amplitudes so that the signal contribution from both profiles had the same weight in the stack. After normalization, the only additional amplitude correction applied was amplitude recovery with time. To deal with the differences in frequency resulting from using two types of geophones, we equalized the frequency bands by applying spectral whitening, we then performed separate spectral analyses of the data recorded along Profile 1 and Profile 5. This analysis was done in two steps: we first selected some representative shot gathers and defined different windows to identify the frequency range of the signal with time. Then, since no continuous reflections could be easily identified on the shot gathers, we compared stacked sections using narrow (∼10 Hz) bandpass filters. From these two analyses, we selected the range of frequencies that produced the best stack and designed the time-variant bandpass filters accordingly. Likewise, due to the lack of well-defined reflections, the velocity analysis was done by stacking the data with constant Table 2 Main processing steps applied to the cross-profile 1 Read SEG format files—20,000 ms 2 Reverse negative polarities 3 Spike and noise edit 4 Refraction statics based on information from in-line data Profile 5: 240 m datum, 1 layer model, 5700 m/s replacement velocity Profile 1: 300 m datum, 1 layer model, 5500 m/s replacement velocity 5 Spectral whitening 10-20-80-100 6 Band-pass filtering, time-variant t (ms) f (Hz) 0–2500 15-30-80-120 2000–4500 5-10-80-120 4000–6500 5-10-50-75 6000–8000 5-10-40-60 7500–20000 5-10-30-45 7 Sort to CDP domain 8 Velocity analysis using constant velocity stacks 9 NMO correction, 50% stretch mute t (ms) V (m/s) 0 5500 1200 6000 3000 6300 8000 7000 10 Optimized stack method 11 First arrival selection approach 12 Cross-dip analysis and corrections 13 Residual statics, maximum power autostatics 14 Stack
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velocities and using the velocities that produced the best image at different times. The velocity function used for the NMO correction is given in Table 2. 4.2. Optimized stack method Due to the long offset between profiles and relatively small charge size used, the signal-to-noise ratio of the cross-profile data is low compared to the in-line data. Thus, the main goal of the processing was to minimize the noise and enhance the signal as much as possible. To achieve this, a processing sequence similar to the optimized stack method described by Mayrand and Milkereit (1988) was applied. This method tries to maximize S/N ratio as expressed by: qn ¼
mS n X
!1=2
ð1Þ
r2i
i¼1
where ρn is the S/N ratio of a simple straight-line stack of n traces, S is the signal assumed to be constant and coincident on m traces, and σi2 is the estimated variance per trace. It is assumed that m out of n traces contribute to the signal in a CDP gather and that the remaining (n − m) traces are mostly noise. A function D(l) is defined for every CDP as !1=2 l X 2 DðlÞ ¼ ri =l ð2Þ i¼1
where the lowest possible noise in a CDP is obtained by finding the optimum value of l that minimizes the function D(l). The signal amplitudes in the window containing the first arrivals and the picked noise amplitudes were calculated by scanning the traces in a window between 0–500 ms before the first arrivals. The variance of the receivers was estimated and used for calculating the function D(l) and the optimum value of l for each CDP gather. By applying this method, 37% of the data were excluded from the stack. After editing the data using the optimized stack method, a new analysis for the first arrivals was done. Most of the noisy traces were successfully removed from the gathers. However, there were still several traces where first arrivals could not be clearly observed. Thus, in a second step all traces were excluded where first arrivals could not be identified. 67% of the data were now omitted as result of the combined editing due to the optimized stack method and first arrival existence criteria. The remaining signal is about 30 dB above the noise, compared to about 15 dB on average before the removal of noisy
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Fig. 3. Schematic plot showing the main components in the cross-dip analysis calculation. Stars are midpoint locations, and Yij is the distance of a CDP point to the CDP line. Traditionally all dip of reflector plane underneath a medium of velocity vi is assumed to be in the line of the profile, but if the plane dips an angle ϕi perpendicular to the line it will not stack coherently unless corrected for as in Eq. (3).
traces. This is still low compared to the inline data, where the signal is about 50 dB and 40 dB above the noise for Profile 1 and 5, respectively.
this distance in order for standard CDP stacking to function properly, which is highly unlikely for this area. Therefore, we applied a pseudo-3D data processing technique for cross-dip analysis on straight stacking lines (Wu et al., 1995) to determine the cross-dip component of some of the more clear reflections. Crossdip is defined as the component of reflector dip in the vertical plane perpendicular to the seismic profile (Larner et al., 1979; Wu et al., 1995; O'Dowd et al., 2004). Given constant crossdip and medium velocity, the reflection times in the seismic traces within a CDP gather will vary according to the distance between the midpoint and the effective stacking line (Wu et al., 1995). These delays are neither surface consistent nor hyperbolic, hence, they cannot be corrected for by standard residual statics and reflection energy will not stack in phase after conventional NMO corrections (Larner et al., 1979; O'Dowd et al., 2004). Fig. 3 shows a schematic three-dimensional diagram illustrating the geometry of a reflector having a significant cross-dip component relative to the survey and stacking line. Using Fig. 3 as a reference, the crossdip correction, Δtij, is given by:
4.3. Cross-dip analysis and corrections Dtij ¼ CDP bins have a width of about 1.5 km perpendicular to the profile. This implies that there should be neither lateral velocity variations nor geological structure over
2sinui Yij Vi
ð3Þ
where ϕi is the cross-dip angle at the ith common depth point, Vi is the velocity above the shallowest dipping
Fig. 4. Velocity and cross-dip analysis for window ranging from CDP 1160 to 1240 and 2.4 to 3.0 s TWT. Top panels show constant velocities in m/s, and the lower panels shows the crossdip using a constant velocity of 6200 m/s. Positive number means a dip to the west, whereas negative numbers a dip to the east. The angle is sinus of the number in the window, e.g. the optimal number of 0.1 corresponds to an angle of 6° west.
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layer, Yij is the transverse offset between the midpoint and the stacking line and j is the trace number within a CDP gather (Larner et al., 1979). By stacking data with
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different cross-dip corrections at a given stacking or NMO velocity, an estimate of the cross-dip component can be made. If the strike of the reflector is not parallel to
Fig. 5. Stacked section of the cross-profile in a) without optimized stack and cross-dip analysis and in b) after the full processing sequence. W1 indicates north-dipping reflectivity that can be correlated on the three data sets discussed in this paper.
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Fig. 6. a) Line drawing of the cross profile based on coherent reflectivity, and b) a geometric migration of the line drawings. W1 marks a north-dipping feature separating more reflective crust below from less reflective crust above it.
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the CDP stacking line then the cross-dip correction also depends upon its dip (Nedimovic and West, 2003). Therefore, the cross-dip angle obtained should be considered with caution, but is reasonably accurate for gently dipping reflections at all strikes. This simplified correction enables a quick and efficient analysis of outof-the-plane reflections. Cross-dip analysis was applied to normal moveoutcorrected CDP gathers. Fig. 4 shows a velocity analysis (top panels) from CDP 1160 to 1240, and a cross-dip analysis (bottom panels) over the same CDP range using a velocity of 6200 m/s. A constant velocity of 6200 m/s and crossdip of 0.1 (6° to the west) are best for this section. As the CDP line consists of four straight line segments, it is expected that different angles would be needed to achieve the most coherent section for a given subsurface crossdip along each segment. This was not done due to the approximate nature of the analysis when the S/N ratio is low. Fig. 5a shows the stacked section resulting from the processing sequence up to step 10 in Table 2 (i. e. without optimized stack and cross-dip corrections), and Fig. 5b shows the stack obtained after the full processing sequence was performed. 5. Results By comparing Fig. 5a and b, it is clear that the processing including optimized stack and cross-dip corrections successfully enhanced the signal-to-noise ratio and produced a more coherent image. Fig. 5b shows a north-dipping reflectivity pattern, clearly observed between CDPs ∼ 900 to 1500. This pattern can also be identified, although not as clearly, between CDPs 600 to 800 at earlier times (1.75–2.25 s). Further interpretation is difficult, but presented as line drawings from an automatic event-picking algorithm based on coherent reflectivity, several features of the stacked data is accentuated in Fig. 6a. Below 3 s the observed reflectivity is almost horizontal. From about 1.5 s TWT at CDP 800 a band of south-dipping reflectivity is observed crossing the north-dipping reflectivity. Southdipping reflectivity is also observed at 1.5 s at CDP 1400. Geometric migration of the linedrawings proved difficult due to the sparseness of the reflectivity and the Table 3 Velocity profile used for the line drawing migration t (ms)
V (m/s)
0 2000 14,000
5000 5500 6500
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acquisition geometry, and was done without taking the bends of the CDP line into account. The 1D velocity function shown in Table 3 (similar to the velocity functions used for migration of the inline data) was used for the migration shown in Fig. 6b. The reflectivity at 1.5 s at CDP 1400 is focused after migration. Similarly, the south-dipping reflectivity at CDP 800 is focused above the W1 reflectivity and does not cross it now. 6. Interpretation Though the S/N ratio of the cross-profile is lower than in the inline profiles, the main features of the images in Fig. 6 agree well with what is observed along Profile 1 and Profile 5 (Tryggvason et al., 2006). Similar to what has been observed on these profiles, the reflectivity south and underneath the W1 horizon in Fig. 6 appears different than the reflectivity observed above it. The W1 horizon was interpreted by Tryggvason et al. (2006) as representing the contact between the Bothnian Basin and the Skellefte Group, an interpretation further supported by potential field modeling (Malehmir et al., 2006) and geologic modeling (Malehmir et al., submitted for publication). In Fig. 7 the migrated line drawings of all the three profiles are shown together in a 3D view. The red stippled line marks the north dipping W1 reflectivity band observed in all three profiles. Estimating the dip of the W1 horizon from the three profiles gives a dip of about 9° to the west, which is in good agreement with the 6° estimated from the cross-dip analysis. Our processing of the cross-profile, thus, supports the interpretation that the change in reflectivity pattern across the W1 horizon observed on all three profiles originates from the same feature. The 3D view of the three profiles in Fig. 7 allows for further correlation of the main reflectivity packages between the profiles. The strong near surface reflectivity observed along Profile 5 at about km 7220N has been interpreted as resulting from mafic dykes. Similar reflectivity is not observed along Profile 1, which was interpreted as due to that these dykes are positioned in a stratigraphic level that may have been eroded away along Profile 1 (Tryggvason et al., 2006). This reflectivity is also not observed along the cross profile, most likely due to that nothing is imaged above 1.2 s TWT or 3.5 km depth there. It was hypothesized that the bright spot reflectivity observed at about km 7225N along Profile 5 could possibly be related to the Kristineberg sulfide mineralization in the top 1.5 km of the crust along Profile 1 at about km 7220N. However, no similar bright spot reflectivity as on Profile
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Fig. 7. 3D view from the east of migrated line-drawings of the cross profile and the inline Profile 1 and 5 (cf. Tryggvason et al., 2006). The red stippled line marks the W1 horizon. Scale is in km. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
5 is observed on the cross-profile, suggesting that the two regions are not connected. Along Profile 1 a weak reflectivity package is observed at km 7230N. This is similar to the reflectivity observed along the crossprofile that focuses at 4 km after migration at CDP 1600–1700 (cf. Fig. 6b). Little is known about the stratigraphic orientation of the Skellefte Group volcanics in this region as they are covered by a thin layer of Revsund granites (Malehmir et al., 2006), but it is possible that the observed southwesterly plunge of about 30° continues underneath the Revsund granites. If there is a connection between the reflectivity observed at km 7230N along Profile 1 and the cross-profile, then this reflectivity is not originating from the same stratigraphic level. It has been hypothesized that the Skellefte Shear Zone (separating two major metamorphic phases in the region) may be crossed by the profiles at this location (Bergman Weihed, 2001), thus, the observed reflectivity may provide some very speculative support for this idea. 7. Discussion Due to the long offset between the profiles (6500– 12000 m), the first arrivals recorded for the cross-profile data are first observed at approximately 1.2 s on the shot
gathers. This implies that the cross-profile does not image the upper 3–4 km of crust in the area, where the stacks from Profile 1 and Profile 5 show most of the reflectivity (Fig. 7). The lack of near-offset data is the main reason for the low S/N ratio of the cross-profile compared to the inline profiles, despite the fold being that of the two inline profiles combined. This emphasizes the importance of efficient processing of nearoffset data (often contaminated by source-generated noise) in conventional reflection seismic processing. In order to increase the S/N ratio the optimized stack method (Mayrand and Milkereit, 1988) was not sufficient in reducing noise, but had to be complemented by a removal of traces where first arrivals could not be clearly identified. Other complicating factors in the data processing include the different frequency contents caused by the differences in instrumentation used on the two profiles. This was largely compensated for by the use of spectral whitening in the processing, that is using overlapping windows to equalize the frequency contents of the data. Though a CDP point in this case only extends 12.5 m along the profile, it collects data with true midpoints spread out over several km laterally. Therefore, our acquisition geometry of two closely separated parallel profiles allows comparing the result of the cross-dip analysis method of Wu et al. (1995) with
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geometrical estimates from the adjacent profiles. Despite the low S/N ratio of the cross-profile, the different dip-estimates agree well with one another, showing the robustness of the cross-dip method. 8. Conclusions Seismic reflection data acquired in the fall 2003 in the Skellefte Ore district, northern Sweden, along two parallel profiles also involved the recording of shots from one profile into the other. This resulted in a nonstandard third profile with CDP points halfway between the two seismic profiles. Despite a fold of about twice that of the individual profiles, the S/N ratio of this cross-profile is rather low. The optimized stack method (Mayrand and Milkereit, 1988) in combination with criteria for removing traces where first arrivals cannot be properly picked gave the best results in enhancing the S/N ratio. Cross-dip analysis of a north-dipping reflectivity package similarly observed on the two inline profiles gave a dip of about 6° west, which is similar to the 9° obtained from geometrical estimates from all three profiles. This observation further supports that this reflectivity constitutes an important structure in the region, and has been interpreted as evidence for a structural basement for the Skellefte Volcanics. The bright-spot reflectivity observed on the reflection profile 3 km to the west is not observed on the cross-profile, thus there is no evidence for a connection to the sulfide mineralizations mined at Kristineberg further east. Despite that the cross-profile does not image the upper 1.2 s of crust, our results show that cross-profile acquisition geometries and cross-dip analysis can maximize the amount of information that can be obtained from an area when small budgets and equipment limitations do not allow for 3D seismic. Acknowledgements The data acquisition was funded by the GEORANGE consortium. We also thank Boliden Mineral AB for support in the field. This manuscript was conscientiously reviewed by three anonymous reviewers. We thank them for their constructive suggestions and criticism. References Allen, R.L., Weihed, P., Svensson, S., 1996. Setting of Zn–Cu–Au– Ag massive sulphide deposits in the evolution and facies architecture of a 1.9 Ga marine volcanic arc, Skellefte District, Sweden. Economic Geology 91, 1022–1053.
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Cross-profile acquisition and cross-dip analysis for extracting 3D information from 2D surveys, a case study from the western Skellefte District, northern Sweden Johiris Rodriguez-Tablante ⁎, Ari Tryggvason, Alireza Malehmir, Christopher Juhlin, Hans Palm Uppsala University, Department of Earth Sciences, Villavägen 16, SE-752 36 Uppsala, Sweden Received 31 January 2006; accepted 7 March 2007
Abstract Two nearly parallel seismic profiles were acquired in the Kristineberg area, located in the western part of the Skellefte ore district, in northern Sweden. A novel approach in the acquisition was that all shots from each profile were recorded onto both lines, resulting in a third CDP line halfway between the two profiles. The combination of geometry, acquisition parameters and geological complexity of the area required specific processing techniques to produce a stacked section that could be correlated with the two in-line processed seismic profiles. The processing sequence included a carefully designed frequency filter, optimized stack methods and pseudo 3D processing by applying cross-dip corrections. Due to the long offsets between the profiles, the resulting stacked section does not provide any information in the upper 1.2 s. Below 1.2 s, the upper crust shows a north-dipping event that correlates well with observations on the in-line data. Sub-horizontal reflectivity is also observed in the upper 4 s of the stack, similar to what is observed on the profile west of the cross-profile. Cross-dip analysis shows that the north-dipping event observed in all three profiles has a westerly dip component. Our study shows that additional information on the sub-surface may be obtained through cross-profile acquisition and processing. © 2007 Elsevier B.V. All rights reserved. Keywords: Hardrock environment; Signal-to-noise; Optimized stack; Crooked line; Cross-dip analysis; Skellefte VHMS District
1. Introduction Seismic reflection techniques have been used in studies of sedimentary environments for almost 80 years. However, in recent decades several independent research efforts have established that the seismic ⁎ Corresponding author. Now at: Geophysical Operations, Norsk Hydro ASA, Norway. Tel.: +47 22536346. E-mail address: [email protected] (J. Rodriguez-Tablante). 0926-9851/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.jappgeo.2007.03.001
reflection method can provide structural images for deep mineral exploration in crystalline environments (e.g. Eaton et al., 2002). In general, seismic data acquired on hardrock environments is often characterized by lowsignal-to-noise ratio and a lack of continuous reflections (Salisbury et al., 2002). Roberts et al. (2002) have presented a case study of the Manitouwadge Greenstone Belt in Canada. Results from their work show that seismic reflection techniques can be a significant aid for mineral exploration by delineating key marker horizons and by potentially direct detection of massive sulfide
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deposits. Another successful case study is from Western Australia. Drummond et al. (2002) show the efficiency of seismic techniques for imaging the mineral trap stage of ore systems. Based on these experiences and others, high-resolution reflection seismic data were acquired in the fall of 2003 along two north–south trending parallel
profiles in the western part of the Skellefte district, one of the largest Paleoproterozoic volcanogenic-hosted massive sulfide (VHMS) districts in the world (Fig. 1). As a way to maximize the 3D information that can be extracted from a 2D survey, all shots from each profile were recorded onto both lines, resulting in a third CDP
Fig. 1. Geological map of the area based on Antal et al. (2003) showing the location of the acquisition lines (black) and the stacking lines for all three profiles (light grey). The dark grey “cloud” shown between the profiles contains the midpoint locations for the cross-profile.
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line located in between the two conventional profiles. In this paper, we focus on the processing and interpretation of these cross-profile data. Challenges in the processing include irregular geometry, long offsets and low amplitudes from relatively small charges, resulting in low S/N (signal-to-noise) ratios. Thus, much of the processing effort was dedicated to maximizing the S/N ratios by data removal based on the noise content of the traces. The crooked line nature of the profile also allows cross-dip analysis of the data to be performed. We use this analysis to provide geometric constraints on the major zones of reflectivity and the large-scale structures of the area. 2. Geologic setting The Skellefte District is the most important metallogenic zone in Sweden. It is generally accepted that it formed as the result of Palaeoproterozoic, c. 1.9 Ga, volcanic arc magmatism (e.g., Weihed et al., 1992; Allen et al., 1996). The volcanic arc formed between a sedimentary basin (Bothnian Basin) and a continental landmass to the north (Allen et al., 1996). The surface geology in the Kristineberg area (Fig. 1) shows that volcanic rocks of the Skellefte Group are overlain by younger volcano-sedimentary rocks of the Vargfors Group (Bergström and Sträng, 1999). The Bothnian basin does not outcrop in the area. Several geological mapping studies have been carried out in the region (Weihed et al., 1992; Allen et al., 1996; Billström and Weihed, 1996). However, they have given little information about contacts between the main geological units at depth. No previous reflection seismic data exist in the entire Skellefte District, with the exception of a short (10 km) north–south trending profile in the Norsjö area in the south-central part of the district (Elming and Thunehed, 1991; Juhlin et al., 2002). The western part of the Skellefte District hosts the largest VHMS deposit currently mined, the Kristineberg area. This part of the district is the best-studied site in the region, and was, therefore, selected for the seismic acquisition. The objectives of the seismic venture were to produce nearsurface images that could be correlated with the surface geology, as well as deep sections that could provide information about the contacts between the main geological units at depth. 3. Data acquisition Data acquisition was carried out along two nearly parallel 25 km long North–South running profiles spaced approximately 8 km apart, Profile 1 and Profile
3
5 (Fig. 1). Profile locations were chosen to address critical questions regarding the geology of the area and to cross perpendicular to major structures. However, logistics and cost constraints required that existing roads be followed, resulting in the profiles being acquired with a crooked line geometry. Since Uppsala University had at the time two reflection seismic systems available, the two profiles were acquired simultaneously at the same cost as if they had been shot sequentially with one system, and at half the time. An alternative would have been to record two crossing profiles, but this option was discarded for logistical reasons. The cross-profile acquisition strategy thus produced three subsets of data; the standard 2D crooked line data along Profile 1 and Profile 5 and a third dataset, in this paper referred to as the cross-profile, corresponding to the data produced by shooting on one line and recording along the other line. Although fan shooting has been previously used (e.g. Thouvenot et al., 1995), it is unconventional to acquire two parallel seismic lines simultaneously and, thus, special processing techniques are required to
Table 1 Data acquisition parameters Survey parameters Type of survey Recording system Nominal spread
2-D crooked line and fan shooting SERCEL 348, SERCEL 408 Asymmetric split spread (20 stations tailing)
Nominal fold: Profile 1 Profile 5 Cross-profile
17 25 35
Energy source parameters Source type Nominal shot spacing Charge size
Dynamite 100 m 1–3 kg
Recording parameters Receiver (group) interval Nominal number of active channels: Profile 1 Profile 5 Field low-cut filter Record length Sampling rate Maximum offset: Profile 1 Profile 5 Cross-profile Geophones: Profile 1 Bunch of six Profile 5 Single Total profile length
25 m 140 200 8 Hz 20 s 2 ms 4000 m 5000 m 12000 m 10 Hz 28 Hz 50 km
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handle the data. The cross-profile can be considered as a third CDP line centered between the two main profiles. However, this profile contains no near-offset data, the minimum offset being 6.5 km in the south and the maximum offset 12 km further north. The details of the seismic acquisition are given in Tryggvason et al. (2006) and are summarized in Table 1. The acquisition parameters were not identical for the two profiles. For instance, due to the different capacities of the acquisition systems, shots were recorded on 140 channels along Profile 1 and on 200 channels along Profile 5, resulting in a nominal fold of 17 for the former and of 25 for the latter. The nominal fold for the cross-profile is 35. Moreover, Profile 1 was recorded using arrays of six geophones with a natural frequency of 10 Hz, while along Profile 5 single geophones with a natural frequency of 28 Hz were used. 4. Data processing 4.1. Standard processing steps The main processing steps applied to the crossprofile is shown in Table 2. Due to the differences in the number of recording channels and the crookedness of Profile 1 and Profile 5, the cross-profile data is characterized by an irregular geometry and midpoint distribution (Fig. 1). In order to maintain nearly uniform
fold, it is common to define smoothly curved lines for stacking data acquired along crooked line profiles. However, this approach can reduce the effectiveness of CDP stacking (Wu et al., 1995). When straight lines are used, geometrical effects due to dipping and out-of-theplane reflections are reduced, resulting in stacks with enhanced signal-to-noise (S/N) ratios. Thus, a CDP line defined by four straight-line segments was used for the cross-profile (Fig. 1). The data were binned with a CDP spacing of 12.5 m (half receiver spacing) in the in-line direction and a maximum of about 1.5 km bin width in the perpendicular direction, resulting in 1867 CDPs. One difficulty of recording simultaneously along lines that run near roads is to guarantee low cultural noise for both lines at a given time. Thus, the first step in the processing was the selection and editing of noisy shots and traces, including editing of spikes. Low amplitudes of the first arrivals made it impossible to use automatic first break picking routines, resulting in a rather difficult and time consuming manual picking procedure of the first arrivals. Due to the uncertainty of the first arrival picks, occasionally on the order of 50– 100 ms, they were not used for the refraction static corrections. Instead, the refraction static corrections were extracted from the processing of the in-line data. Fig. 2, shows a shot from Profile 1 recorded along Profile 5 before and after applying refraction statics. The ellipses highlight the part of the shot where the
Fig. 2. Example of a shot gather with and without refraction static corrections. Ellipses enclose traces where the improvements from the refraction statics are more evident.
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improvement of the previously calculated refraction static corrections is clearly seen. Due to the difference in the acquisition equipment, signal amplitudes recorded along Profile 5 were significantly higher (∼ 103) than the data recorded along Profile 1. Hence, it was necessary to normalize the amplitudes so that the signal contribution from both profiles had the same weight in the stack. After normalization, the only additional amplitude correction applied was amplitude recovery with time. To deal with the differences in frequency resulting from using two types of geophones, we equalized the frequency bands by applying spectral whitening, we then performed separate spectral analyses of the data recorded along Profile 1 and Profile 5. This analysis was done in two steps: we first selected some representative shot gathers and defined different windows to identify the frequency range of the signal with time. Then, since no continuous reflections could be easily identified on the shot gathers, we compared stacked sections using narrow (∼10 Hz) bandpass filters. From these two analyses, we selected the range of frequencies that produced the best stack and designed the time-variant bandpass filters accordingly. Likewise, due to the lack of well-defined reflections, the velocity analysis was done by stacking the data with constant Table 2 Main processing steps applied to the cross-profile 1 Read SEG format files—20,000 ms 2 Reverse negative polarities 3 Spike and noise edit 4 Refraction statics based on information from in-line data Profile 5: 240 m datum, 1 layer model, 5700 m/s replacement velocity Profile 1: 300 m datum, 1 layer model, 5500 m/s replacement velocity 5 Spectral whitening 10-20-80-100 6 Band-pass filtering, time-variant t (ms) f (Hz) 0–2500 15-30-80-120 2000–4500 5-10-80-120 4000–6500 5-10-50-75 6000–8000 5-10-40-60 7500–20000 5-10-30-45 7 Sort to CDP domain 8 Velocity analysis using constant velocity stacks 9 NMO correction, 50% stretch mute t (ms) V (m/s) 0 5500 1200 6000 3000 6300 8000 7000 10 Optimized stack method 11 First arrival selection approach 12 Cross-dip analysis and corrections 13 Residual statics, maximum power autostatics 14 Stack
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velocities and using the velocities that produced the best image at different times. The velocity function used for the NMO correction is given in Table 2. 4.2. Optimized stack method Due to the long offset between profiles and relatively small charge size used, the signal-to-noise ratio of the cross-profile data is low compared to the in-line data. Thus, the main goal of the processing was to minimize the noise and enhance the signal as much as possible. To achieve this, a processing sequence similar to the optimized stack method described by Mayrand and Milkereit (1988) was applied. This method tries to maximize S/N ratio as expressed by: qn ¼
mS n X
!1=2
ð1Þ
r2i
i¼1
where ρn is the S/N ratio of a simple straight-line stack of n traces, S is the signal assumed to be constant and coincident on m traces, and σi2 is the estimated variance per trace. It is assumed that m out of n traces contribute to the signal in a CDP gather and that the remaining (n − m) traces are mostly noise. A function D(l) is defined for every CDP as !1=2 l X 2 DðlÞ ¼ ri =l ð2Þ i¼1
where the lowest possible noise in a CDP is obtained by finding the optimum value of l that minimizes the function D(l). The signal amplitudes in the window containing the first arrivals and the picked noise amplitudes were calculated by scanning the traces in a window between 0–500 ms before the first arrivals. The variance of the receivers was estimated and used for calculating the function D(l) and the optimum value of l for each CDP gather. By applying this method, 37% of the data were excluded from the stack. After editing the data using the optimized stack method, a new analysis for the first arrivals was done. Most of the noisy traces were successfully removed from the gathers. However, there were still several traces where first arrivals could not be clearly observed. Thus, in a second step all traces were excluded where first arrivals could not be identified. 67% of the data were now omitted as result of the combined editing due to the optimized stack method and first arrival existence criteria. The remaining signal is about 30 dB above the noise, compared to about 15 dB on average before the removal of noisy
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Fig. 3. Schematic plot showing the main components in the cross-dip analysis calculation. Stars are midpoint locations, and Yij is the distance of a CDP point to the CDP line. Traditionally all dip of reflector plane underneath a medium of velocity vi is assumed to be in the line of the profile, but if the plane dips an angle ϕi perpendicular to the line it will not stack coherently unless corrected for as in Eq. (3).
traces. This is still low compared to the inline data, where the signal is about 50 dB and 40 dB above the noise for Profile 1 and 5, respectively.
this distance in order for standard CDP stacking to function properly, which is highly unlikely for this area. Therefore, we applied a pseudo-3D data processing technique for cross-dip analysis on straight stacking lines (Wu et al., 1995) to determine the cross-dip component of some of the more clear reflections. Crossdip is defined as the component of reflector dip in the vertical plane perpendicular to the seismic profile (Larner et al., 1979; Wu et al., 1995; O'Dowd et al., 2004). Given constant crossdip and medium velocity, the reflection times in the seismic traces within a CDP gather will vary according to the distance between the midpoint and the effective stacking line (Wu et al., 1995). These delays are neither surface consistent nor hyperbolic, hence, they cannot be corrected for by standard residual statics and reflection energy will not stack in phase after conventional NMO corrections (Larner et al., 1979; O'Dowd et al., 2004). Fig. 3 shows a schematic three-dimensional diagram illustrating the geometry of a reflector having a significant cross-dip component relative to the survey and stacking line. Using Fig. 3 as a reference, the crossdip correction, Δtij, is given by:
4.3. Cross-dip analysis and corrections Dtij ¼ CDP bins have a width of about 1.5 km perpendicular to the profile. This implies that there should be neither lateral velocity variations nor geological structure over
2sinui Yij Vi
ð3Þ
where ϕi is the cross-dip angle at the ith common depth point, Vi is the velocity above the shallowest dipping
Fig. 4. Velocity and cross-dip analysis for window ranging from CDP 1160 to 1240 and 2.4 to 3.0 s TWT. Top panels show constant velocities in m/s, and the lower panels shows the crossdip using a constant velocity of 6200 m/s. Positive number means a dip to the west, whereas negative numbers a dip to the east. The angle is sinus of the number in the window, e.g. the optimal number of 0.1 corresponds to an angle of 6° west.
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layer, Yij is the transverse offset between the midpoint and the stacking line and j is the trace number within a CDP gather (Larner et al., 1979). By stacking data with
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different cross-dip corrections at a given stacking or NMO velocity, an estimate of the cross-dip component can be made. If the strike of the reflector is not parallel to
Fig. 5. Stacked section of the cross-profile in a) without optimized stack and cross-dip analysis and in b) after the full processing sequence. W1 indicates north-dipping reflectivity that can be correlated on the three data sets discussed in this paper.
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Fig. 6. a) Line drawing of the cross profile based on coherent reflectivity, and b) a geometric migration of the line drawings. W1 marks a north-dipping feature separating more reflective crust below from less reflective crust above it.
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the CDP stacking line then the cross-dip correction also depends upon its dip (Nedimovic and West, 2003). Therefore, the cross-dip angle obtained should be considered with caution, but is reasonably accurate for gently dipping reflections at all strikes. This simplified correction enables a quick and efficient analysis of outof-the-plane reflections. Cross-dip analysis was applied to normal moveoutcorrected CDP gathers. Fig. 4 shows a velocity analysis (top panels) from CDP 1160 to 1240, and a cross-dip analysis (bottom panels) over the same CDP range using a velocity of 6200 m/s. A constant velocity of 6200 m/s and crossdip of 0.1 (6° to the west) are best for this section. As the CDP line consists of four straight line segments, it is expected that different angles would be needed to achieve the most coherent section for a given subsurface crossdip along each segment. This was not done due to the approximate nature of the analysis when the S/N ratio is low. Fig. 5a shows the stacked section resulting from the processing sequence up to step 10 in Table 2 (i. e. without optimized stack and cross-dip corrections), and Fig. 5b shows the stack obtained after the full processing sequence was performed. 5. Results By comparing Fig. 5a and b, it is clear that the processing including optimized stack and cross-dip corrections successfully enhanced the signal-to-noise ratio and produced a more coherent image. Fig. 5b shows a north-dipping reflectivity pattern, clearly observed between CDPs ∼ 900 to 1500. This pattern can also be identified, although not as clearly, between CDPs 600 to 800 at earlier times (1.75–2.25 s). Further interpretation is difficult, but presented as line drawings from an automatic event-picking algorithm based on coherent reflectivity, several features of the stacked data is accentuated in Fig. 6a. Below 3 s the observed reflectivity is almost horizontal. From about 1.5 s TWT at CDP 800 a band of south-dipping reflectivity is observed crossing the north-dipping reflectivity. Southdipping reflectivity is also observed at 1.5 s at CDP 1400. Geometric migration of the linedrawings proved difficult due to the sparseness of the reflectivity and the Table 3 Velocity profile used for the line drawing migration t (ms)
V (m/s)
0 2000 14,000
5000 5500 6500
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acquisition geometry, and was done without taking the bends of the CDP line into account. The 1D velocity function shown in Table 3 (similar to the velocity functions used for migration of the inline data) was used for the migration shown in Fig. 6b. The reflectivity at 1.5 s at CDP 1400 is focused after migration. Similarly, the south-dipping reflectivity at CDP 800 is focused above the W1 reflectivity and does not cross it now. 6. Interpretation Though the S/N ratio of the cross-profile is lower than in the inline profiles, the main features of the images in Fig. 6 agree well with what is observed along Profile 1 and Profile 5 (Tryggvason et al., 2006). Similar to what has been observed on these profiles, the reflectivity south and underneath the W1 horizon in Fig. 6 appears different than the reflectivity observed above it. The W1 horizon was interpreted by Tryggvason et al. (2006) as representing the contact between the Bothnian Basin and the Skellefte Group, an interpretation further supported by potential field modeling (Malehmir et al., 2006) and geologic modeling (Malehmir et al., submitted for publication). In Fig. 7 the migrated line drawings of all the three profiles are shown together in a 3D view. The red stippled line marks the north dipping W1 reflectivity band observed in all three profiles. Estimating the dip of the W1 horizon from the three profiles gives a dip of about 9° to the west, which is in good agreement with the 6° estimated from the cross-dip analysis. Our processing of the cross-profile, thus, supports the interpretation that the change in reflectivity pattern across the W1 horizon observed on all three profiles originates from the same feature. The 3D view of the three profiles in Fig. 7 allows for further correlation of the main reflectivity packages between the profiles. The strong near surface reflectivity observed along Profile 5 at about km 7220N has been interpreted as resulting from mafic dykes. Similar reflectivity is not observed along Profile 1, which was interpreted as due to that these dykes are positioned in a stratigraphic level that may have been eroded away along Profile 1 (Tryggvason et al., 2006). This reflectivity is also not observed along the cross profile, most likely due to that nothing is imaged above 1.2 s TWT or 3.5 km depth there. It was hypothesized that the bright spot reflectivity observed at about km 7225N along Profile 5 could possibly be related to the Kristineberg sulfide mineralization in the top 1.5 km of the crust along Profile 1 at about km 7220N. However, no similar bright spot reflectivity as on Profile
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Fig. 7. 3D view from the east of migrated line-drawings of the cross profile and the inline Profile 1 and 5 (cf. Tryggvason et al., 2006). The red stippled line marks the W1 horizon. Scale is in km. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
5 is observed on the cross-profile, suggesting that the two regions are not connected. Along Profile 1 a weak reflectivity package is observed at km 7230N. This is similar to the reflectivity observed along the crossprofile that focuses at 4 km after migration at CDP 1600–1700 (cf. Fig. 6b). Little is known about the stratigraphic orientation of the Skellefte Group volcanics in this region as they are covered by a thin layer of Revsund granites (Malehmir et al., 2006), but it is possible that the observed southwesterly plunge of about 30° continues underneath the Revsund granites. If there is a connection between the reflectivity observed at km 7230N along Profile 1 and the cross-profile, then this reflectivity is not originating from the same stratigraphic level. It has been hypothesized that the Skellefte Shear Zone (separating two major metamorphic phases in the region) may be crossed by the profiles at this location (Bergman Weihed, 2001), thus, the observed reflectivity may provide some very speculative support for this idea. 7. Discussion Due to the long offset between the profiles (6500– 12000 m), the first arrivals recorded for the cross-profile data are first observed at approximately 1.2 s on the shot
gathers. This implies that the cross-profile does not image the upper 3–4 km of crust in the area, where the stacks from Profile 1 and Profile 5 show most of the reflectivity (Fig. 7). The lack of near-offset data is the main reason for the low S/N ratio of the cross-profile compared to the inline profiles, despite the fold being that of the two inline profiles combined. This emphasizes the importance of efficient processing of nearoffset data (often contaminated by source-generated noise) in conventional reflection seismic processing. In order to increase the S/N ratio the optimized stack method (Mayrand and Milkereit, 1988) was not sufficient in reducing noise, but had to be complemented by a removal of traces where first arrivals could not be clearly identified. Other complicating factors in the data processing include the different frequency contents caused by the differences in instrumentation used on the two profiles. This was largely compensated for by the use of spectral whitening in the processing, that is using overlapping windows to equalize the frequency contents of the data. Though a CDP point in this case only extends 12.5 m along the profile, it collects data with true midpoints spread out over several km laterally. Therefore, our acquisition geometry of two closely separated parallel profiles allows comparing the result of the cross-dip analysis method of Wu et al. (1995) with
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geometrical estimates from the adjacent profiles. Despite the low S/N ratio of the cross-profile, the different dip-estimates agree well with one another, showing the robustness of the cross-dip method. 8. Conclusions Seismic reflection data acquired in the fall 2003 in the Skellefte Ore district, northern Sweden, along two parallel profiles also involved the recording of shots from one profile into the other. This resulted in a nonstandard third profile with CDP points halfway between the two seismic profiles. Despite a fold of about twice that of the individual profiles, the S/N ratio of this cross-profile is rather low. The optimized stack method (Mayrand and Milkereit, 1988) in combination with criteria for removing traces where first arrivals cannot be properly picked gave the best results in enhancing the S/N ratio. Cross-dip analysis of a north-dipping reflectivity package similarly observed on the two inline profiles gave a dip of about 6° west, which is similar to the 9° obtained from geometrical estimates from all three profiles. This observation further supports that this reflectivity constitutes an important structure in the region, and has been interpreted as evidence for a structural basement for the Skellefte Volcanics. The bright-spot reflectivity observed on the reflection profile 3 km to the west is not observed on the cross-profile, thus there is no evidence for a connection to the sulfide mineralizations mined at Kristineberg further east. Despite that the cross-profile does not image the upper 1.2 s of crust, our results show that cross-profile acquisition geometries and cross-dip analysis can maximize the amount of information that can be obtained from an area when small budgets and equipment limitations do not allow for 3D seismic. Acknowledgements The data acquisition was funded by the GEORANGE consortium. We also thank Boliden Mineral AB for support in the field. This manuscript was conscientiously reviewed by three anonymous reviewers. We thank them for their constructive suggestions and criticism. References Allen, R.L., Weihed, P., Svensson, S., 1996. Setting of Zn–Cu–Au– Ag massive sulphide deposits in the evolution and facies architecture of a 1.9 Ga marine volcanic arc, Skellefte District, Sweden. Economic Geology 91, 1022–1053.
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