the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Sep 2024
Passive seismic imaging of ore deposits using coda wave interferometry: a case study of Akanvaara V-Cr-PGE deposit in Northern Finland
Abstract. In this study, we present an innovative method to image the inner structure of orthomagmatic ore deposits using P-wave coda of regional seismic events. We combine data processing and interpretation schemes from conventional passive seismic interferometry and teleseismic receiver function (RF) method. We hypothesize that correlation of P-wave coda recorded by three-component sensors can be used to evaluate body wave part of empirical Green's tensor, from which arrivals of reflected and converted waves could be extracted. To test our hypothesis, we installed a high-resolution seismic array (profile) with 606 seismic instruments on the Akanvaara V-Cr-PGE deposit in Northern Finland above the inclined zones of V-Cr mineralization, placed inside ultramafic intrusion. From the regional seismic catalogue, provided by the Institute of Seismology, University of Helsinki, we selected the P-wave coda of 363 regional seismic events to evaluate body wave part of empirical Green's tensor by passive seismic interferometry. Further interpretation of the tensor allowed us to identify arrivals of PS and SP waves, converted at Cr and V mineralization zones. We conducted numerical simulation of plane wave interaction with the synthetic Akanvaara deposit model compiled from geological and drilling data and found that Green's tensors evaluated from synthetic seismograms and from seismic data contain similar converted PS and SP arrivals. To calculate depths to the conversion boundaries, we obtained S-wave velocity model using MASW method. According to calculated depths and geological model compiled from drilling data we suggest that the converted arrivals correspond to continuation of the Cr and V mineralized zones. Therefore, using the empirical Green's tensor, evaluated from P-wave coda of regional seismic events can be an effective tool for orthomagmatic ore deposits exploration in both greenfield and brownfield cases. In this paper we are describing details of the passive seismic experiment, numerical simulation, data processing and interpretation.
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RC1: 'Comment on egusphere-2024-2637', Mariusz Majdanski, 09 Oct 2024
Review of the manuscript Passive seismic imaging of ore deposits using coda wave interferometry: a case study of Akanvaara V-Cr-PGE deposit in Northern Finland by Afonin et al. submitted to Solid Earth journal.
General comment
The manuscript is an extensive and detailed case study of the use of coda waves combined with the MASW technique to recognise mineral deposits in a hard rock environment. The presented technique is innovative and uses high-resolution 3C seismic and correlation of components to image inclined boundaries. The study explains the method using a synthetic example and follows with a field data case. The manuscript is rather long but has a logical structure. It is written in understandable English, and the figure's quality meets the research article criteria.
Main problems to fix
1) the synthetic example is very detailed and tries to mirror the study site geometry. Still, the results, especially in Figure 14, are difficult to follow. If, in such idealised cases, these results are not very convincing, how will this method work with real data?
2) There are some significant differences in processing synthetic and field data. The filtering is very different. For the field data 2-20 Hz, for synthetics 10-15 Hz. I would expect the synthetic case should be as close to real case thus the processing parameters should be the same. Please explain those differences.
3) The final results (Figure 20) are not convincing. How the results look like without interpretation. I cannot see any arrivals as they are marked with interpretation lines.
Small suggestions
Figure 2b to small fonts, it is hard to read any information
Figure 4. caption - add N and E for latitude and longitude for clarity
Figure 4 quality of these plots are horrible, I would like to see some waveforms. Maybe it would be better do decimate the number of traces and show some useful signal. The horizontal scale is not described.
Figure 5 I am guessing those are Z, N and E components. Please mark them, and add event info (date?) too, for clarity
Something is wrong with table 1 – there are P and S rows, but velocity is defined for both. So what for the separate rows with sub-tasks exist? This is explained in the text (page 9) and is not needed in the table.
Page 9, line 200: we select the frequency equal to 10 Hz was used for these waves -> we select the frequency equal to 10 Hz for these waves
Figure 12 these results indeed show some weak signals, but this is a synthetic case when we know exactly what we are looking for. How will it work for field data?
Figure 17 shows application of very narrow filter 17-18 Hz. Is this correct?
My recommendation
I am convinced this manuscript presents an interesting approach to study hard rock environment. The results are not very convincing, but it is still an innovative method. I recommend publishing it after fixing some minor problems and explaining the mentioned issues.
Citation: https://doi.org/10.5194/egusphere-2024-2637-RC1 -
RC2: 'Comment on egusphere-2024-2637', Anonymous Referee #2, 24 Oct 2024
General Comments
I enjoyed reading this study. It aims to tackle the important challenge of mineral exploration using passive seismic techniques in a novel and potentially exciting way. The study includes a geological background to the Akanvaara deposit, an overview of the methods, a set of synthetic models, and then processing and interpretation of results from a month-long deployment around the Akanvaara deposit. The introduced method is innovative for mineral exploration, but unfortunately I am not convinced by the results and there are a number of questions I have regarding the validity of the method in this case study. Whilst I would not recommend publishing this exact manuscript, the study could be re-written to clarify/better support the method and improve the quality of the results. Alternatively, perhaps a renewed focus on synthetic case studies from a variety of deposit types with more realistic crustal structures would enable this study to better showcase the suitability of the method for exploration.
Specific Comments
I have given detailed comments below, separated into each section of the manuscript. However, my main questions can be summarised as follows:
P-wave coda
P-wave coda for regional earthquakes are likely dominated by conversions at the Moho, as well as other major crustal reflectors and reverberations in cover lithologies (e.g., Wang et al., 2020). The synthetic models (e.g., Fig. 7) do not contain lower crustal boundary layers and therefore it is difficult to assess the impact these large-scale structures might be having on the results. The geological cross-section only goes down to 100m so it is difficult to assess the impact major upper crustal interfaces, like the basement-cover contact, may have on the case study example. Without addressing these potential issues, I worry whether the method is actually able to reliably resolve shallow structures with thicknesses of only metres to 100s metres.Phases of interest
The study uses SP and SS phase arrivals, among others. I do not understand how it is possible to calculate accurate time delays for SP and SS waves using P-wave coda. The SP and SS waves originate from the initial S-wave, and therefore must be compared relative to the S-wave arrival rather than the P-wave. In the synthetic example, an initial S-wave is used (e.g., Fig. 11), but the S-wave coda is not used in the real case-study data.Depth conversion for Figure 20
The depth conversion of Figure 20 relies on the knowledge of S-wave and P-wave velocities, as mentioned in the study. It is unclear where the required P-wave velocities came from. Additionally, the surface wave analysis of Fig. 19 constrains the S-wave structure to a maximum of 550m, yet Figure 20 contains depths in excess of 5 km. It is unclear where these additional velocity constraints came from, and how the depth conversion is performed.Interpretation of Figure 20
Without referring to the geological cross-section provided in Figure 2, I think it would be difficult to persuasively arrive at the interpretation of the seismic data presented in Figure 20. The geophysics depth conversion, as well as the significant difference in depth of the geophysical cross-section (>5 km in Figure 20) vs. the geological cross-section (~100m in Fig. 2) also raises some questions.Technical Comments
Introduction
- The introduction could do with a few more details on the deposit itself. For example, Lines 66-69 are too sparse in detail (layer thicknesses, rheological contrasts between layers) to allow me to assess whether the method is reasonable to start with.
Geological characteristics etc.
- More references required in the geological background section (e.g., Line 74).
- Figure 1: Can you please show where (b) is on (a), perhaps by highlighting Akanvaara label on (a). Also, does ‘m’ mean metres on (b)? The scale isn’t particularly clear as I am not familiar with the co-ordinate system.
- Perhaps make it clearer that the Akaanvaara intrusion belongs to the 2.44–2.5 Ga suite of layered mafic intrusions.
- Please state the aim more clearly: do you aim to resolve the mineralised layers within the Lower and Middle Zone (thickness of ~cm. to several metres), the magnetite gabbro of the Upper Zone (thickness of 100s metres), or just the general dipping structure of the area? This is important for deciding where the tool would be useful for exploration.
- Fig 2b: is this cross-section in line with the drill-holes or is it a cross-section along the seismic profile onto which you have projected the drill-holes?
- It is unclear in Line 134 as to how the events were selected. Did you use the whole catalogue of 363 events or filter that down to a smaller sample-set?
- How local are the “local” earthquakes and will they still satisfy the vertical incidence assumption (Line 139)?
- Fig 4 and Fig 5: These figures are unclear. Please show some seismograms and perhaps PSD plots through time for individual events.
- Line 160: a few reference examples would be useful here.
Method:
- Line 176: Presumably a significant part of the P-wave coda The Ps will arrive after the P.
- It would be good to link the method description with Figure 6 more clearly.
- Line 189: Surely the SP arrival cannot be compared with the P-wave arrival, as it is a conversion from an original S wave with a different original travel time.
- 7: perhaps make it clearer that Y is equal to depth, and panel 2 represents a bird’s-eye view.
- More detail on the method used by SOF13D would be helpful here.
- Line 217: What is the third dimension?
- Line 224: What does “done with MATLAB scripts” mean?
- 8: A plot of individual seismograms would be useful here, with labelled phases.
- Line 227: Please make it clearer that you subtracted the seismograms from the homogenous model from the seismograms from the heterogenous model.
Data Processing:
- How long was each P-wave coda record? How did you define the start and end?
- I assume this was an autocorrelation, in which each station was correlated with itself. If so, please make this clearer.
- What was the signal-to-noise of the stacked cross-correlations? Were low SNR records removed prior to analysis?
- Surely SP and SS arrivals need to be correlated relative to the original S-wave arrival time. I do not think they can be easily related directly to the original P-wave arrival.
- Line 299: Please give details of these 37 seismic events, and their azimuth.
- Fig 16: (A) I am not sure why the moveout is not reflected about the 0s time. Normally, moveout should be symmetrical about the 0s highlighting anti-causal and causal signals. Please explain why your results are different. (B) The phase velocities seem too high, suggesting either azimuthal biases or perhaps a processing error.
- Fig 17: (A) Please make this figure clearer – the definition is too low. (B) I am not entirely sure what this figure means. I am unsure why there are three 200m distance values. Moveout plots are standardly plotted showing an increasing distance on the y-axis against time on the x-axis, symmetrical around 0s.
- Line 324: please be specific as to the frequency range. Presumably these are surface-wave phase velocities, not S-wave velocities. No phase velocity to S-wave velocity has been performed yet.
- Please plot the 5 dispersion curves, and show where they come from along the profile.
- How does Geopsy calculate the theoretical dispersion curves?
- Did you set the Vp/Vs ratio in the Monte-Carlo models?
- Which misfit function did you use?
- Fig 19: in Line 327, it is mentioned that dispersion curves could not be obtained for two parts of the profile. Where are those parts on Fig. 19? Also, why have the results from 20m–150m been removed if they are included within the 1D inversions?
- Please include some sensitivity kernel plots to demonstrate that the surface waves are indeed sensitive to geological structure at these depths.
Results:
- How did you perform the depth conversion? Did you use the S-wave 2D velocity profile or select a 1D average? What P-wave velocity did you use? The depths go down to 5.4 km, yet the S-wave velocity model only extends to 500m.
- Line 378: Could this be more quantitative. There are numerous boundaries into Fig. 20, 19 and 18. Which boundaries correspond to the 0.15s arrival time?
Citation: https://doi.org/10.5194/egusphere-2024-2637-RC2 -
EC1: 'Comment on egusphere-2024-2637', Irene Bianchi, 05 Nov 2024
Dear Authors,
please proceed with your responses to the reviewer's comments.
I would also like to add to please extend your discussions and conclusions section. At the moment the latter is unbalanced with respect to the other sections of the manuscript, and a comprehensive discussion on the implication of your work is lacking.
Thank you very much, and looking forward to read the revised version of the manuscript.
Kind regards,
Irene Bianchi
Citation: https://doi.org/10.5194/egusphere-2024-2637-EC1
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