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    ๋ฏธ๊ตญ ์บ˜๋ฆฌํฌ๋‹ˆ์•„ ์ง€์—ญ์˜ CCSE ๊ด€์ธก๋ง์—์„œ์˜ LgํŒŒ ๊ฐ์‡ ํ˜„์ƒ์˜ ๊ณต๊ฐ„์  ๋ณ€ํ™” ๋ฐ ๋ถ€์ง€ ์‘๋‹ต ๋ณด์ •, ๊ทธ๋ฆฌ๊ณ  ์ฃผํŒŒ์ˆ˜ ์˜์กด์„ฑ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ์ง€๊ตฌํ™˜๊ฒฝ๊ณผํ•™๋ถ€, 2021. 2. ๊น€์˜ํฌ.We estimate lateral variation of the Lg Q at four center frequencies, 0.75 Hz, 1 Hz, 2 Hz and 2.75 Hz, based on the two-station method (TSM) along a great circle profile (Aโ€“Aโ€™) passing the Central California Seismic Experiment (CCSE) array. Relative site responses at each station are also obtained using the reverse two-station method. Positive site responses are obtained from 34 stations out of total 46 stations examined, and their responses are mostly correlated with geological features (i.e. sedimentary rocks) along the profile. Surficial lithology is likely to have a significant impact on the site response, rather than the thickness of sediments. The site responses also exhibit strong negative correlation to the Vs30 data. We then correct the Lg Q estimates for the site responses. The correction is effective in eliminating surficial properties, resulting in a shift of the peak locations, being more remarkable at lower frequencies (0.75 Hz and 1 Hz) than at higher frequencies (2 Hz and 2.75 Hz). With the site-response-corrected Q values, a power-law frequency dependence of Q(f)=(81ยฑ8)f^((0.62ยฑ0.11)) is obtained, reflecting the active tectonic setting and the presence of fluids in the region. We also compared the corrected Lg Q variation with several geologic properties. The effect of sediments becomes trivial after the correction, particularly at lower frequencies. Comparison to the Vs and Moho temperature showed that each frequency is capable of imaging distinct depth range. Finally, we compare the result to that of the Sacramento Valley. An analogous behavior at the sedimentary basin is obtained at both regions. However, the conflicting result in Sierra Nevada emphasizes a necessity of further investigation in the region with denser seismic networks.๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” TSM(Two-Station Method) ๋ฐฉ๋ฒ•์„ ํ™œ์šฉํ•˜์—ฌ CCSE(Central California Seismic Experiment)๊ด€์ธก๋ง์„ ํ†ต๊ณผํ•˜๋Š” ๋Œ€์›์ƒ์˜ ๋‹จ๋ฉด(A-Aโ€™)์„ ๋”ฐ๋ผ Lg Q๊ฐ’์ด ๊ณต๊ฐ„์ ์œผ๋กœ ๋ณ€ํ™”ํ•˜๋Š” ์–‘์ƒ์„ ๋„ค ๊ฐœ์˜ ์ค‘์‹ฌ ์ฃผํŒŒ์ˆ˜ 0.75 Hz, 1 Hz, 2 Hz, ๊ทธ๋ฆฌ๊ณ  2.75 Hz๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ์ถ”์ •ํ•˜์˜€๋‹ค. ๊ฐ ๊ด€์ธก์†Œ์—์„œ์˜ ์ƒ๋Œ€์ ์ธ ๋ถ€์ง€ ์‘๋‹ต ์—ญ์‹œ RTSM(Reverse Two-Station Method) ๋ฐฉ๋ฒ•์„ ํ™œ์šฉํ•˜์—ฌ ๊ตฌํ•˜์˜€๋‹ค. ๋ถ„์„์— ์‚ฌ์šฉ๋œ 46๊ฐœ ๊ด€์ธก์†Œ๋“ค ์ค‘ 34๊ฐœ์˜ ๊ด€์ธก์†Œ๋กœ๋ถ€ํ„ฐ ์–‘์˜ ๋ถ€์ง€ ์‘๋‹ต ๊ฐ’์ด ์–ป์–ด์กŒ๊ณ , ์ด๋Š” ์ฃผ๋กœ ํ‡ด์ ์•”์˜ ์กด์žฌ์™€ ๊ฐ™์€ ์ด ์ง€์—ญ์˜ ์ง€์งˆํ•™์  ํŠน์„ฑ๊ณผ ๊ด€๋ จ๋˜์–ด์žˆ๋‹ค. ๋ถ€์ง€ ์‘๋‹ต ์ถ”์ •์— ์žˆ์–ด ํ‡ด์ ๋ฌผ์˜ ๋‘๊ป˜๋ณด๋‹ค๋Š” ํ‘œ์ธต์˜ ์•”์ƒ์ด ๋” ์ฃผ์š”ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ๋˜ํ•œ ๋ถ€์ง€ ์‘๋‹ต ๊ฐ’์€ Vs30๊ฐ’ ๋ถ„ํฌ์™€ ๊ฐ•ํ•œ ์Œ์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ์ด๋ ‡๊ฒŒ ์ธก์ •๋œ ๋ถ€์ง€ ์‘๋‹ต ๊ฐ’์„ ์ด์šฉํ•˜์—ฌ Lg Q๊ฐ’ ์ถ”์ •์น˜๋ฅผ ๋ณด์ •ํ–ˆ๋‹ค. ๋ณด์ • ๊ฒฐ๊ณผ ํ”ผํฌ ๊ฐ’์ด ๋‚˜ํƒ€๋‚˜๋Š” ์œ„์น˜๊ฐ€ ๋ณ€ํ™”ํ•˜์˜€๋Š”๋ฐ, ์ด๋Š” ๋ณด์ • ๊ณผ์ •์ด ํ‘œ์ธต์˜ ํŠน์„ฑ์„ ํšจ๊ณผ์ ์œผ๋กœ ์ œ๊ฑฐํ•˜๊ธฐ ๋•Œ๋ฌธ์œผ๋กœ ๋ณด์ธ๋‹ค. ํ”ผํฌ ์œ„์น˜์˜ ๋ณ€๋™์€ ๋†’์€ ์ฃผํŒŒ์ˆ˜(2 Hz & 2.75 Hz)์—์„œ๋ณด๋‹ค ๋‚ฎ์€ ์ฃผํŒŒ์ˆ˜(0.75 Hz & 1 Hz)์—์„œ ๋” ๋‘๋“œ๋Ÿฌ์กŒ๋‹ค. ๋ถ€์ง€ ์‘๋‹ต์— ๋Œ€ํ•ด ๋ณด์ •๋œ Q๊ฐ’์œผ๋กœ๋ถ€ํ„ฐ Q(f)=(81ยฑ8)f^((0.62ยฑ0.11)) ์ด๋ผ๋Š” ์ฃผํŒŒ์ˆ˜ ์˜์กด์„ฑ์„ ์–ป์„ ์ˆ˜ ์žˆ์—ˆ๊ณ , ์ด๋Š” ์ง€๊ตฌ์กฐ์ ์œผ๋กœ ํ™œ๋ฐœํ•œ ์ง€์—ญ์  ํŠน์„ฑ๊ณผ ์œ ์ฒด์˜ ์กด์žฌ์„ฑ์„ ๋ฐ˜์˜ํ•œ๋‹ค. ๋˜ํ•œ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ณด์ •๋œ Lg Q๊ฐ’์˜ ๋ณ€ํ™”๋ฅผ ๋‹ค์–‘ํ•œ ์ง€์งˆํ•™์  ํŠน์„ฑ๋“ค๊ณผ ๋น„๊ตํ•ด๋ณด์•˜๋‹ค. ๋ณด์ •์„ ๊ฑฐ์น˜๋ฉด ํ‡ด์ ๋ฌผ์˜ ์˜ํ–ฅ์€ ์ค„์–ด๋“œ๋Š” ๋ชจ์Šต์„ ๋ณด์˜€๊ณ , ์ด๋Š” ํŠนํžˆ ๋‚ฎ์€ ์ฃผํŒŒ์ˆ˜์—์„œ ๋‘๋“œ๋Ÿฌ์ง€๊ฒŒ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. SํŒŒ ์†๋„ ๋ฐ ๋ชจํ˜ธ๋ฉด ์˜จ๋„ ๋ถ„ํฌ์™€์˜ ๋น„๊ต๋ฅผ ํ†ตํ•ด ๊ฐ๊ฐ์˜ ์ฃผํŒŒ์ˆ˜๋“ค์ด ๋‹ค์–‘ํ•œ ๊นŠ์ด ์˜์—ญ์„ ๋‚˜ํƒ€๋‚ผ ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ์ด ์ง€์—ญ์—์„œ์˜ ๊ฒฐ๊ณผ๋ฅผ ์‚ฌํฌ๋ผ๋ฉ˜ํ†  ๋ถ„์ง€ ์ง€์—ญ์—์„œ์˜ ๊ฒฐ๊ณผ์™€ ๋น„๊ตํ–ˆ๋‹ค. ํ‡ด์  ๋ถ„์ง€์—์„œ๋Š” ๋‘ ์ง€์—ญ์—์„œ ์œ ์‚ฌํ•œ ๊ฑฐ๋™์ด ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹œ์—๋ผ ๋„ค๋ฐ”๋‹ค ์‚ฐ๋งฅ ์ธ๊ทผ์—์„œ๋Š” ๋‘ ์ง€์—ญ์—์„œ ์ƒ๋ฐ˜๋˜๋Š” ๊ฒฐ๊ณผ๋ฅผ ๋ณด์˜€๊ธฐ ๋•Œ๋ฌธ์— ์ถ”ํ›„์— ๋” ์ด˜์ด˜ํ•œ ๊ด€์ธก๋ง์„ ์ด์šฉํ•œ ์ถ”๊ฐ€์ ์ธ ์—ฐ๊ตฌ๊ฐ€ ์ด๋ฃจ์–ด์งˆ ํ•„์š”๊ฐ€ ์žˆ๋‹ค.Abstract โ…ฐ Chapter 1 Introduction 1 Chapter 2 Geological Setting 7 Chapter 3 Data Processing 11 Chapter 4 Methods 19 4.1. Two-Station Method (TSM) 20 4.2. Reverse Two-Station Method (RTSM) 23 Chapter 5 Results 30 5.1. 1-D Checker-board Resolution Test 30 5.2. Relative Site Response Result 31 5.3. Lateral Variation of Lg Q 33 5.3.1. TSM results 33 5.3.2. Passband Effect 34 Chapter 6 Discussion 46 6.1. Site Response 46 6.2. Frequency Dependence of Lg Q 47 6.3. Relation to the Regional Geology 48 6.4. Comparison to the Sacramento Valley Region 51 Chapter 7 Conclusions 62 References 64 ์ดˆ๋ก 74Maste

    P And S Wave Velocity Determination

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    There are three general methods that can be used to determine formation velocities from full waveform logs. The first approach is to make use of the data from the entire waveform. This type of velocity analysis is performed either in the frequency domain (i.e. f-k analysis or the two station method) or in the time domain (I.e. velocity spectral analysis). The second approach is to identify the P wave pulses on individual traces and to determine delay times between traces. In conventional acoustic logging this technique has been used successfully to determine the compressional wave velocities. The third approach' is to use the phase velocity of the gUided waves (Pseudo-Rayleigh) to determine the shear velocity. Each of these approaches have certain advantages and limitations depending on the tool characteristics (number of records, frequency response), formation properties (high or low shear velocity), and computation times required. The effect of these parameters upon each method of velocity determination is presented

    High resolution regional seismic attenuation tomography in eastern Tibetan Plateau and adjacent regions

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    The Q of regional seismic phases Lg and Pg within the crust is assumed as a proxy for crustal Qฮฒ and Qฮฑ, which is used as a constraint of crustal rheology. We measure regionalโ€phase Q of the eastern Tibetan Plateau and adjacent areas. This method eliminates contributions from source and site responses and is an improvement on the Twoโ€Station Method (TSM). We have generated tomographic images of crustal attenuation anomalies with resolution as high as 1ยฐ. In general we observe low Q in the northernmost portions of the Tibetan Plateau and high Q in the more tectonically stable regions such as the interior of the Qaidam basin. The calculated site responses appear to correlate with topography or sediment thickness. Furthermore the relationship between earthquake magnitudes and calculated source terms suggest that the RTM method effectively removes the source response and may be used as an alternative to source magnitude

    Seismic anisotropy of Precambrian lithosphere : Insights from Rayleigh wave tomography of the eastern Superior Craton

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    The seismic data used in this study are freely available from the CNDC (Canadian National Data Centre for Earthquake Seismology and Nuclear Explosion Monitoring) and IRIS DMC (Data Management Center) via their data request tools. The Leverhulme Trust (grant RPG-2013-332) and National Science Foundation are acknowledged for financial support. L.P. is supported by Janet Watson Imperial College Department Scholarship and the Romanian Government Research Grant NUCLEU. F.D. is supported by NSERC through the Discovery Grants and Canada Research Chairs program. We also thank two anonymous reviewers and the Associate Editor for insightful comments that helped improve the manuscript.Peer reviewedPublisher PD

    Application of surface-wave tomography to mineral exploration : a case study from Siilinjarvi, Finland

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    In order to assess the feasibility and validity of surface-wave tomography as a tool for mineral exploration, we present an active seismic three-dimensional case study from the Siilinjarvi mine in Eastern Finland. The aim of the survey is to identify the formation carrying the mineralization in an area south of the main pit, which will be mined in the future. Before acquiring the data, we performed an accurate survey design to maximize data coverage and minimize the time for deployment and recollection of the equipment. We extract path-averaged Rayleigh-wave phase-velocity dispersion curves by means of a two-station method. We invert them using a computationally efficient tomographic code which does not require the computation of phase-velocity maps and inverts directly for one-dimensional S-wave velocity models. The retrieved velocities are in good agreement with the data from a borehole in the vicinity, and the pseudo three-dimensional S-wave velocity volume allows us to identify the geological contact between the formation hosting most of the mineralization and the surrounding rock. We conclude that the proposed method is a valid tool, given the small amount of equipment used and the acceptable amount of time required to process the data.Peer reviewe

    Surface-wave tomography for mineral exploration : a successful combination of passive and active data (Siilinjรคrvi phosphorus mine, Finland)

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    Surface wave (SW) methods offer promising options for an effective and sustainable development of seismic exploration, but they still remain under-exploited in hard rock sites. We present a successful application of active and passive surface wave tomography for the characterization of the southern continuation of the Siilinjarvi phosphate deposit (Finland). A semi-automatic workflow for the extraction of the path-average dispersion curves (DCs) from ambient seismic noise data is proposed, including identification of time windows with strong coherent SW signal, azimuth analysis and two-station method for DC picking. DCs retrieved from passive data are compared with active SW tomography results recently obtained at the site. Passive data are found to carry information at longer wavelengths, thus extending the investigation depth. Active and passive DCs are consequently inverted together to retrieve a deep pseudo-3D shearwave velocity model for the site, with improved resolution. The southern continuation of the mineralization, its contacts with the host rocks and different sets of cross-cutting diabase dikes are well imaged in the final velocity model. The seismic results are compared with the latest available geological models to both validate the proposed workflow and improve the interpretation of the geometry and extent of the mineralization. Important large-scale geological boundaries and structural discontinuities are recognized from the results, demonstrating the effectiveness and advantages of the methods for mineral exploration perspectives.Peer reviewe

    Metabolism Modeling in Rivers With Unsteady Flow Conditions and Transient Storage Zones

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    Whole-stream metabolism characterizes energy and carbon transformations, thus providing an estimate of the food base and CO2 emission sources from streams and rivers. Metabolism models are generally implemented with a steady flow assumption that does not hold true for many systems with sub-daily flow variation, such as river sections downstream of dams. The steady flow assumption has confined metabolism estimation to a limited range of river environments, thus limiting our understanding about the influence of hydrology on biological production in rivers. Therefore, we couple a flow routing model with the two-station stream metabolism model to estimate metabolism under unsteady flow conditions in rivers. The model's applicability is further extended by including advection-dispersion processes to facilitate metabolism estimation in transient storage zones. Metabolism is estimated using two approaches: (a) an accounting approach similar to the conventional two-station method and (b) an inverse approach that estimates metabolism parameters using least squares minimization method. Both approaches are complementary since we use outputs of the accounting approach to constrain the inverse model parameters. The model application is demonstrated using a case study of an 11 km long stretch downstream of a hydropower plant in the River Otra in southern Norway. We present and test different formulations of the model to show that users can make an appropriate selection that best represents hydrology and solute transport mechanism in the river system of interest. The inclusion of unsteady flows and transient storage zones in the model unlocks new possibilities for studying metabolism controls in altered river ecosystems.publishedVersio

    Exploiting seismic signal and noise in an intracratonic environment to constrain crustal structure and source parameters of infrequent earthquakes

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    In many regions of the world characterized by a relatively low rate of seismicity, the determination of local and regional seismic source parameters is often restricted to an analysis of the first onsets of P waves (or first motion analysis) due to incomplete information about Earth structure and the small size of the events. When rare large earthquakes occur in these regions, their waveforms can be used to model Earth structure. This, however, makes the nature of the earthquake source determination problem circular, as source information is mapped as structure. Presented here is one possible remedy to this situation, where through a two-step approach we first constrain Earth structure using data independent of the earthquake of interest. In this study, we focus on a region in Western Australia with low seismicity and minimal instrument coverage and use the CAPRA/LP temporary deployment to demonstrate that reliable structural models of the upper lithosphere can be obtained from an independent collection of teleseismic and ambient noise datasets. Apart from teleseismic receiver functions (RFs), we obtain group velocities from the cross-correlation of ambient noise and phase velocities from the traditional two-station method using carefully selected teleseismic earthquakes and station pairs. Crustal models are then developed through the joint inversion of dispersion data and RFs, and structural Green's functions are computed from a layered composite model. In the second step of this comprehensive approach, we apply full waveform inversion (three-component body and surface waves) to the 2007 M L= 5.3 Shark Bay, Western Australia, earthquake to estimate its source parameters (seismic moment, focal mechanism, and depth). We conclude that the full waveform inversion analysis provides constraints on the orientation of fault planes superior to a first motion interpretation

    Multimodal surface-wave tomography to obtain S- and P-wave velocities applied to the recordings of unmanned aerial vehicle deployed sensors

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    Exploration seismic surveys in hard-to-access areas such as foothills and forests are extremely challenging. The Multiphysics Exploration Technologies Integrated System (METIS) research project was initiated to design an exploration system, facilitating the acquisition in these areas by delivering the receivers from the sky using unmanned aerial vehicles. Air dropping of the sensors in vegetated areas results in an irregular geometry for the acquisition. This irregularity can limit the application of conventional surface wave methods. We have developed a surface wave workflow for estimating the S-wave velocity (VS) and P-wave velocity (VP) models and that supports the irregular geometry of the deployed sources and receivers. The method consists of a multimodal surface-wave tomography (SWT) technique to compute the VS model and a data transform method (the wavelength/depth [W/D] method) to determine the Poisson's ratio and VP model. We applied the method to the METIS's first pilot records, which were acquired in the forest of Papua New Guinea. Application of SWT to the data resulted in the first 90 m of the VS model. The W/D method provided the Poisson's ratio averaged over the area and the VP model between 10 and 70 m from the surface. The impact of the acquisition scale and layout on the resolution of the estimated model and the advantages of including the higher modes of surface waves in the tomographic inversion are assessed in detail. The presence of shots from diverse site locations significantly improves the resolution of the obtained model. Including the higher modes enhances the data coverage and increases the investigation depth
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