Optimal resolution seismic tomography: Lithospheric thinning beneath the British Tertiary Igneous Province and other new observations

2020 ◽  
Author(s):  
Raffaele Bonadio ◽  
Sergei Lebedev ◽  
Pierre Arroucau ◽  
Andrew Schaeffer ◽  
Andrea Licciardi ◽  
...  
Keyword(s):  
Phase Velocity ◽  
Structural Information ◽  
Shear Velocity ◽  
Velocity Curve ◽  
Lateral Resolution ◽  
Data Sampling ◽  
Optimal Resolution ◽  
Igneous Province ◽  
Recording Station ◽  
Data Adaptive

<p>The maximum achievable resolution of a tomographic model varies spatially and depends on the data sampling and errors in the data. Adaptive parameterization schemes match the spatial variations in data sampling but do not address the effects of the errors. The propagation of systematic errors, however, is resistant to data redundancy and results in models dominated by noise if the target resolution is too high. This forces us to look for smoother models and thus limits the imaging resolution.<br><br>We develop a surface-wave tomography method that finds optimal lateral resolution at every point by means of error tracking. We first measure inter-station phase-velocities at simultaneously recording station pairs and compute phase-velocity maps at densely, logarithmically spaced periods. Unlike in the classical approach, multiple versions of the maps with varying smoothness constraints are computed, so that the maps range from very rough to very smooth. Phase-velocity curves extracted from the maps at every point can then be inverted for shear-velocity (V<sub>s</sub>) profiles. As we show, errors in these phase-velocity curves increase nearly monotonically with the map roughness. Very smooth V<sub>s</sub> models computed from very smooth phase-velocity maps will be the most robust, but at a cost of a loss of most structural information. At the other extreme, models that are too rough will be dominated by noise. We define the optimal resolution at a point such that the error of the local phase-velocity curve is below an empirical threshold. The error is estimated by isolating the roughness of the phase-velocity curve that cannot be explained by any Earth structure. A 3D V<sub>s</sub> model is then computed by the inversion of the phase-velocity maps with the optimal resolution at every point. The estimated optimal resolution shows smooth lateral variations, confirming the robustness of the procedure. Importantly, optimal resolution does not scale with the density of the data coverage: some of the best-sampled locations require relatively low lateral resolution, probably due to systematic data errors. We apply the method to image the Ireland’s and Britain’s upper mantle, using our large, new regional dataset. We report a pronounced thinning of the lithosphere beneath the British Tertiary Igneous Province, with important implications for the Paleogene uplift and volcanism in the region.</p>

Optimal resolution seismic tomography with error tracking: imaging the upper mantle beneath Ireland and Britain

2021 ◽  
Author(s):  
Raffaele Bonadio ◽  
Sergei Lebedev ◽  
Thomas Meier ◽  
Pierre Arroucau ◽  
Andrew Schaeffer ◽  
...  
Keyword(s):  
Phase Velocity ◽  
Seismic Tomography ◽  
Structural Information ◽  
Systematic Errors ◽  
Velocity Curve ◽  
Lateral Resolution ◽  
Data Sampling ◽  
Lithospheric Thickness ◽  
Optimal Resolution ◽  
Data Coverage

<p>Spatial resolution, as the ability to distinguish different features that are close together, is a fundamental concept in seismic tomography and other imaging fields. In contrast with microscopy or telescopy, seismic tomography’s images are computed, and their resolution has a complex, non-linear dependence on the data sampling and errors. Linear inverse theory provides a useful resolution-analysis approach, defining resolution in terms of the closeness of the resolution matrix to the identity matrix. This definition is similar to the universal, multi-disciplinary one in some contexts but diverges from it markedly in others. In this work, we adopt the universal definition of resolution (the minimum distance at which two spike anomalies can be resolved). The highest achievable resolution of a tomographic model then varies spatially and depends on the data sampling and errors in the data. We show that the propagation of systematic errors is resistant to data redundancy and results in models dominated by noise if the target resolution is too high. This forces one to look for smoother models and effectively limits the resolution. Here, we develop a surface-wave tomography method that finds optimal lateral resolution at every point by means of error tracking.<br>We first measure interstation phase velocities at simultaneously recording station pairs and compute phase-velocity maps at densely, logarithmically spaced periods. Multiple versions of the maps with varying smoothness are computed, ranging from very rough to very smooth. Phase-velocity curves extracted from the maps at every point are then inverted for shear-velocity (V<sub>S</sub>) profiles. As we show, errors in these phase-velocity curves increase nearly monotonically with the map roughness. Very smooth V<sub>S</sub> models computed from very smooth phase-velocity maps will be the most accurate, but at a cost of a loss of most structural information. At the other extreme, models that are too rough will be dominated by noise. We define the optimal resolution at a point such that the error of the local phase-velocity curve is below an empirical threshold. The error is estimated by isolating the roughness of the phase-velocity curve that cannot be explained by any Earth structure.<br>A 3D V<sub>S</sub> model is then computed by the inversion of the phase-velocity maps with the optimal resolution at every point. The estimated optimal resolution shows smooth lateral variations, confirming the robustness of the procedure. Importantly, optimal resolution does not scale with the density of the data coverage: some of the best-sampled locations require relatively low lateral resolution, probably due to systematic errors in the data.<br>We apply the method to image the lithosphere and underlying mantle beneath Ireland and Britain, using 11238 newly measured, broadband, inter-station dispersion curves. The lateral resolution of the 3D model is computed explicitly and varies from 39 km in central Ireland to over 800 km at the region boundaries, where the data coverage declines. Our tomography reveals pronounced, previously unknown variations in the lithospheric thickness beneath the region, with implications for the Caledonian assembly of the islands’ landmass and the mechanism of the magmatism of the British Tertiary Igneous Province.</p>

Optimal resolution tomography with error tracking and the structure of the crust and upper mantle beneath Ireland and Britain

2021 ◽  
Author(s):  
Raffaele Bonadio ◽  
Sergei Lebedev ◽  
Thomas Meier ◽  
Pierre Arroucau ◽  
Andrew J Schaeffer ◽  
...  
Keyword(s):  
Phase Velocity ◽  
Systematic Errors ◽  
Model Error ◽  
Velocity Curve ◽  
Lateral Resolution ◽  
Earth Structure ◽  
Data Redundancy ◽  
Optimal Resolution ◽  
Data Coverage ◽  
The Impact

Summary The classical Backus-Gilbert method seeks localized Earth-structure averages at the shortest length scales possible, given a dataset, data errors, and a threshold for acceptable model errors. The resolving length at a point is the width of the local averaging kernel, and the optimal averaging kernel is the narrowest one such that the model error is below a specified level. This approach is well suited for seismic tomography, which maps three-dimensional Earth structure using large sets of seismic measurements. The continual measurement-error decreases and data-redundancy increases have reduced the impact of random errors on tomographic models. Systematic errors, however, are resistant to data redundancy and their effect on the model is difficult to predict. Here, we develop a method for finding the optimal resolving length at every point, implementing it for surface-wave tomography. As in the Backus-Gilbert method, every solution at a point results from an entire-system inversion, and the model error is reduced by increasing the model-parameter averaging. The key advantage of our method stems from its direct, empirical evaluation of the posterior model error at a point. We first measure inter-station phase velocities at simultaneously recording station pairs and compute phase-velocity maps at densely, logarithmically spaced periods. Numerous versions of the maps with varying smoothness are then computed, ranging from very rough to very smooth. Phase-velocity curves extracted from the maps at every point can be inverted for shear-velocity (VS) profiles. As we show, errors in these phase-velocity curves increase nearly monotonically with the map roughness. We evaluate the error by isolating the roughness of the phase-velocity curve that cannot be explained by any Earth structure and determine the optimal resolving length at a point such that the error of the local phase-velocity curve is below a threshold. A 3D VS model is then computed by the inversion of the composite phase-velocity maps with an optimal resolution at every point. The estimated optimal resolution shows smooth lateral variations, confirming the robustness of the procedure. Importantly, the optimal resolving length does not scale with the density of the data coverage: some of the best-sampled locations display relatively low lateral resolution, probably due to systematic errors in the data. We apply the method to image the lithosphere and underlying mantle beneath Ireland and Britain. Our very large dataset was created using new data from Ireland Array, the Irish National Seismic Network, the UK Seismograph Network, and other deployments. A total of 11238 inter-station dispersion curves, spanning a very broad total period range (4–500 s), yield unprecedented data coverage of the area and provide fine regional resolution from the crust to the deep asthenosphere. The lateral resolution of the 3D model is computed explicitly and varies from 39 km in central Ireland to over 800 km at the edges of the area, where the data coverage declines. Our tomography reveals pronounced, previously unknown variations in the lithospheric thickness beneath Ireland and Britain, with implications for their Caledonian assembly and for the mechanisms of the British Tertiary Igneous Province magmatism.

scholarly journals Mantle Rayleigh waves from the Kamchatka earthquake of November 4, 1952*

1954 ◽  
Vol 44 (3) ◽  
pp. 471-479
Author(s):  
Maurice Ewing ◽  
Frank Press
Keyword(s):  
Internal Friction ◽  
Rayleigh Waves ◽  
Shear Velocity ◽  
Velocity Curve ◽  
The Core ◽  
Long Period ◽  
A Value ◽  
The Earth ◽  
Dispersion Data ◽  
Kamchatka Earthquake

Abstract Mantle Rayleigh waves from the Kamchatka earthquake of November 4, 1952, are analyzed. The new Palisades long-period vertical seismograph recorded orders R6–R15, the corresponding paths involving up to seven complete passages around the earth. The dispersion data for periods below 400 sec. are in excellent agreement with earlier results and can be explained in terms of the known increase of shear velocity with depth in the mantle. Data for periods 400-480 sec. indicate a tendency for the group velocity curve to level off, suggesting that these long waves are influenced by a low or vanishing shear velocity in the core. Deduction of internal friction in the mantle from wave absorption gives a value 1/Q = 370 × 10−5 for periods 250-350 sec. This is a little over half the value reported earlier for periods 140-215 sec.

scholarly journals High-resolution 3D shallow crustal structure in Long Beach, California: Application of ambient noise tomography on a dense seismic array

Geophysics ◽  
2013 ◽  
Vol 78 (4) ◽  
pp. Q45-Q56 ◽  
Author(s):  
Fan-Chi Lin ◽  
Dunzhu Li ◽  
Robert W. Clayton ◽  
Dan Hollis
Keyword(s):  
Phase Velocity ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Shear Velocity ◽  
Seismic Array ◽  
Clear Correlation ◽  
Long Beach ◽  
Ambient Noise Tomography ◽  
Station Pair ◽  
Dense Seismic Array

Ambient noise tomography has proven to be effective in resolving shallow earth structure. We applied ambient noise tomography on a dense seismic array in Long Beach, California. The array was composed of more than 5200 stations with an average spacing close to 100 m. Three weeks of passive ambient noise were crosscorrelated between each station pair, which resulted in more than 13.5 million crosscorrelations within the area. Clear fundamental-mode Rayleigh waves were observed between 0.5 and 4 Hz, which were most sensitive to structure above 1-km depth. For each station pair, we applied frequency-time analysis to determine the phase traveltime dispersion, and, for each frequency, we applied eikonal tomography to determine the Rayleigh wave phase velocity map. The eikonal tomography accounted for ray bending by tracking the wavefront and allowed uncertainties to be estimated through statistical analysis. The compilation of phase velocity maps was then used to invert for 3D shear velocity structure. The inverted model showed clear correlation with the known geologic features such as the shallow south–north velocity dichotomy and a deeper fast anomaly associated with the Newport-Inglewood fault zone. Our results can potentially be used to complement traditional active source studies.

Rayleigh wave dispersion in the Pacific Ocean for the period range 20 to 140 seconds

1962 ◽  
Vol 52 (2) ◽  
pp. 333-357 ◽  
Author(s):  
John Kuo ◽  
James Brune ◽  
Maurice Major
Keyword(s):  
Phase Velocity ◽  
Rayleigh Wave ◽  
Rayleigh Waves ◽  
Initial Phase ◽  
Velocity Curve ◽  
Period Range ◽  
Long Period ◽  
Phase Velocities ◽  
The Pacific ◽  
Group Velocities

ABSTRACT Rayleigh wave data obtained from Columbia long-period seismographs installed during the International Geophysical Year (I.G.Y.) at Honolulu, Hawaii; Suva, Fiji; and Mt. Tsukuba, Japan, are analyzed to determine group and phase velocities in the Pacific for the period range 20 to 140 seconds. Group velocities are determined by usual techniques (Ewing and Press, 1952, p. 377). Phase velocities are determined by assuming the initial phase to be independent of period and choosing the initial phase so that the phase velocity curve agrees in the long period range with the phase velocity curve of the mantle Rayleigh wave given by Brune (1961). Correlations of wave trains between the stations Honolulu and Mt. Tsukuba are used to obtain phase velocity values independent of initial phase. The group velocity rises from 3.5 km/sec at a period of about 20 see to a maximum of 4.0 km/sec at a period of about 40 sec and then decreases to 3.65 km/sec at a period of about 140 sec. Phase velocity is nearly constant in the period range 30–75 sec with a value slightly greater than 4.0 km/sec. Most of the phase velocity curves indicate a maximum and a minimum at periods of approximately 30 and 50 sec respectively. At longer periods the phase velocities increase to 4.18 km/sec at a period of 120 sec. Except across the Melanesian-New Zealand region, dispersion curves for paths of Rayleigh waves throughout the Pacific basin proper are rather uniform and agree fairly well with theoretical dispersion curves for models with a normal oceanic crust and a low velocity channel. Both phase and group velocities are comparatively lower for the paths of Rayleigh waves across the Melanesian-New Zealand region, suggesting a thicker crustal layer and/or lower crustal velocities in this region.

Azimuthally anisotropic ambient-noise tomography using the AlpArray seismic network

2020 ◽  
Author(s):  
Emanuel Kästle ◽  
Irene Molinari ◽  
Lapo Boschi ◽  
AlpArray Working Group
Keyword(s):  
Phase Velocity ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Sedimentary Basins ◽  
Shear Velocity ◽  
Velocity Model ◽  
Azimuthal Anisotropy ◽  
Seismic Network ◽  
Fast Axis ◽  
Noise Field

<p>We make use of the AlpArray Seismic Network to study the properties of the ambient-noise field and create a new 3D shear-velocity model of the Alpine crust. The latter will be used to improve our understanding of the tectonic processes that formed the Alps.</p><p>From two years of data, more than 150,000 station-station cross-correlations are extracted and used to evaluate strength and directivity of the noise field and its seasonal variations. Phase-velocity measurements for both Love and Rayleigh waves are obtained and the anisotropic phase-velocity structure is imaged. At mid-crustal levels, the strongest azimuthal anisotropy is found underneath the northern Italian Po plain and in the northern Dinarides, with strengths of 10-20% and a fast axis direction pointing NNE in Italy and NE in the Dinarides. In the western and central Alps we find an approximately NE direction and a strength of 5%; the eastern Alpine fast axis point toward the north with strengths of 2-5%.</p><p>We apply a probabilistic inversion to resolve the 3D shear-velocity structure of the crust. The homogeneous and dense station setup results in a shear-velocity model of unprecedented resolution for the uppermost 60 km of the crust underneath the entire orogen. By using data in the period range between 2 and 100s, we are able to better constrain shallow structures, such as the sedimentary basins, and to link surface-geological features to velocity variations observed at depth.</p>

Upper mantle shear velocity structure beneath the equatorial East Pacific Rise from array-based teleseismic surface-wave dispersion analysis

2019 ◽  
Author(s):  
Qiushi Zhai ◽  
Huajian Yao ◽  
Zhigang Peng
Keyword(s):  
Phase Velocity ◽  
Rayleigh Wave ◽  
Upper Mantle ◽  
Velocity Dispersion ◽  
Velocity Structure ◽  
Shear Velocity ◽  
Wave Phase ◽  
Phase Velocity Dispersion ◽  
Wave Phase Velocity ◽  
Rayleigh Wave Phase Velocity

Summary The Discovery/Gofar transform faults system is associated with a fast-spreading center on the equatorial East Pacific Rise. Most previous studies focus on its regular seismic cycle and crustal fault zone structure, but the characteristics of the upper mantle structure beneath this mid-ocean ridge system are not well known. Here we invert upper mantle shear velocity structure in this region using both teleseismic surface waves and ambient seismic noise from 24 ocean bottom seismometers (OBSs) deployed in this region in 2008. We develop an array analysis method with multi-dimensional stacking and tracing to determine the average fundamental mode Rayleigh wave phase-velocity dispersion curve (period band 20–100 s) for 94 teleseismic events distributed along the E-W array direction. Then, we combine with the previously measured Rayleigh wave phase-velocity dispersion (period band 2–25 s) from ambient seismic noise to obtain the average fundamental mode (period band 2–100 s) and the first-higher mode (period band 3–7 s) Rayleigh wave phase-velocity dispersion. The average dispersion data are inverted for the 1-D average shear wave velocity (Vs) structure from crust to 200-km depth in the upper mantle beneath our study region. The average Vs between the Moho and 200-km depth of the final model is about 4.18 km/s. There exists an ∼5-km thickness high-velocity lid (LID) beneath the Moho with the maximum Vs of 4.37 km/s. Below the LID, the Vs of a pronounced low-velocity zone (LVZ) in the uppermost mantle (15–60 km depth) is 4.03–4.23 km/s (∼10 per cent lower than the global average). This pronounced LVZ is thinner and shallower than the LVZs beneath other oceanic areas with older lithospheric ages. We infer that partial melting (0.5–5 per cent) mainly occurs in the shallow upper mantle zone beneath this young (0–2 Myr) oceanic region. In the deeper portion (60–200 km depth), the Vs of a weak LVZ is 4.15–4.27 km/s (∼5 per cent lower than the global average). Furthermore, the inferred lithosphere-asthenosphere boundary (LAB) with ∼15-km thickness can fit well with the conductive cooling model. These results are useful for understanding the depth distribution and melting characteristics of the upper mantle lithosphere and asthenosphere in this active ridge-transform fault region.

scholarly journals A general interactive framework for false discovery rate control under structural constraints

Biometrika ◽  
2020 ◽  
Author(s):  
Lihua Lei ◽  
Aaditya Ramdas ◽  
William Fithian
Keyword(s):  
False Discovery Rate ◽  
Rate Control ◽  
Multiple Testing ◽  
Structural Information ◽  
Directed Acyclic Graphs ◽  
Structural Constraints ◽  
False Discovery Rate Control ◽  
Region Detection ◽  
False Discovery ◽  
Data Adaptive

Summary We propose a general framework based on selectively traversed accumulation rules for interactive multiple testing with generic structural constraints on the rejection set. It combines accumulation tests from ordered multiple testing with data-carving ideas from post-selection inference, allowing highly flexible adaptation to generic structural information. Our procedure defines an interactive protocol for gradually pruning a candidate rejection set, beginning with the set of all hypotheses and shrinking the set with each step. By restricting the information at each step via a technique we call masking, our protocol enables interaction while controlling the false discovery rate in finite samples for any data-adaptive update rule that the analyst may choose. We suggest update rules for a variety of applications with complex structural constraints, demonstrate that selectively traversed accumulation rules perform well in problems ranging from convex region detection to false discovery rate control on directed acyclic graphs, and show how to extend the framework to regression problems where knockoff statistics are available in lieu of $p$-values.

Imaging the Deep Structures of Los Humeros Geothermal Field, Mexico, Using Three-Component Seismic Noise Beamforming

2020 ◽  
Vol 91 (6) ◽  
pp. 3269-3277 ◽  
Author(s):  
Katrin Löer ◽  
Tania Toledo ◽  
Gianluca Norini ◽  
Xin Zhang ◽  
Andrew Curtis ◽  
...  
Keyword(s):  
Seismic Noise ◽  
Structural Information ◽  
Shear Velocity ◽  
Velocity Model ◽  
Geothermal Field ◽  
Well Logs ◽  
Ambient Seismic Noise ◽  
Geothermal Systems ◽  
Near Surface ◽  
Brittle Ductile Transition

Abstract We present a 1D shear-velocity model for Los Humeros geothermal field (Mexico) obtained from three-component beamforming of ambient seismic noise, imaging for the first time the bottom of the sedimentary basement ∼5  km below the volcanic caldera, as well as the brittle-ductile transition at ∼10  km depth. Rayleigh-wave dispersion curves are extracted from ambient seismic noise measurements and inverted using a Markov chain Monte Carlo scheme. The resulting probability density function provides the shear-velocity distribution down to 15 km depth, hence, much deeper than other techniques applied in the area. In the upper 4 km, our model conforms to a profile from local seismicity analysis and matches geological structure inferred from well logs, which validates the methodology. Complementing information from well logs and outcrops at the near surface, discontinuities in the seismic profile can be linked to geological transitions allowing us to infer structural information of the deeper subsurface. By constraining the extent of rocks with brittle behavior and permeability conditions at greater depths, our results are of paramount importance for the future exploitation of the reservoir and provide a basis for the geological and thermodynamic modeling of active superhot geothermal systems, in general.

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