Joint inversion of receiver functions and apparent incidence angles to investigate the crustal structure of Mars

2021 ◽  
Author(s):  
Rakshit Joshi ◽  
Brigitte Knapmeyer-Endrun ◽  
Klaus Mosegaard ◽  
Felix Bissig ◽  
Amir Khan ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Crustal Structure ◽  
Joint Inversion ◽  
Landing Site ◽  
Crustal Thickness ◽  
Receiver Functions ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Insight Mission

<p>Since InSight (the Interior Exploration using Geodesy and Heat Transport) landed 26 months ago and deployed an ultra sensitive broadband seismometer(SEIS) on the surface of Mars, around 500 seismic events of diverse variety have been detected, making it possible to directly analyze the subsurface properties of Mars for the very first time. One of the primary goals of the mission is to retrieve the crustal structure below the landing site. Current estimates differ by more than 100% for the average crustal thickness. Since data from orbital gravity measurementsprovide information on relative variations of crustal thickness but not absolute values, this landing site measurement could serve as a tie point to retrieve global crustal structure models. To do so, we propose using a joint inversion of receiver functions and apparent incidence angles, which contain information on absolute S-wave velocities of the subsurface. Since receiver function inversions suffer from a velocity depth trade-off, we in addition exploit a simple relation which defines apparent S-wave velocity as a function of observed apparent P-wave incidence angles to constrain the parameter space. Finally we use the Neighbourhood Algorithm for the inversion of a suitable joint objective function. The resulting ensemble of models is then used to derive the full uncertainty estimates for each model parameter. Before its application on data from InSight mission, we successfully tested the method on Mars synthetics and terrestrial data from various geological settings using both single and multiple events. Using the same method, we have previously been able to constrain the S-wave velocity and depth for the first inter-crustal layer of Mars between 1.7 to 2.1 km/s and 8 to 11 km, respectively. Here we present the results of applying this technique on our selected data set from the InSight mission. Results show that the data can be explained equally well by models with 2 or 3 crustal layers with constant velocities. Due to the limited data set it is difficult to resolve the ambiguity of this bi-modal solution. We therefore investigate information theoretic statistical tests as a model selection criteria and discuss their relevance and implications in seismological framework.</p><div></div><div></div><div></div>

Mapping crustal structure of the Nechako–Chilcotin plateau using teleseismic receiver function analysis,

2014 ◽  
Vol 51 (4) ◽  
pp. 407-417 ◽  
Author(s):  
H.S. Kim ◽  
J.F. Cassidy ◽  
S.E. Dosso ◽  
H. Kao
Keyword(s):  
Wave Velocity ◽  
Crustal Structure ◽  
Velocity Structure ◽  
Receiver Function ◽  
Function Analysis ◽  
Crustal Thickness ◽  
Receiver Functions ◽  
S Wave ◽  
Low Velocity ◽  
Velocity Models

This paper presents results of a passive-source seismic mapping study in the Nechako–Chilcotin plateau of central British Columbia, with the ultimate goal of contributing to assessments of hydrocarbon and mineral potential of the region. For the present study, an array of nine seismic stations was deployed in 2006–2007 to sample a wide area of the Nechako–Chilcotin plateau. The specific goal was to map the thickness of the sediments and volcanic cover, and the overall crustal thickness and structural geometry beneath the study area. This study utilizes recordings of about 40 distant earthquakes from 2006 to 2008 to calculate receiver functions, and constructs S-wave velocity models for each station using the Neighbourhood Algorithm inversion. The surface sediments are found to range in thickness from about 0.8 to 2.7 km, and the underlying volcanic layer from 1.8 to 4.7 km. Both sediments and volcanic cover are thickest in the central portion of the study area. The crustal thickness ranges from 22 to 36 km, with an average crustal thickness of about 30–34 km. A consistent feature observed in this study is a low-velocity zone at the base of the crust. This study complements other recent studies in this area, including active-source seismic studies and magnetotelluric measurements, by providing site-specific images of the crustal structure down to the Moho and detailed constraints on the S-wave velocity structure.

Shear‐wave velocity and density estimation from PS-wave AVO analysis: Application to an OBS dataset from the North Sea

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1446-1454 ◽  
Author(s):  
Side Jin ◽  
G. Cambois ◽  
C. Vuillermoz
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Random Noise ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Avo Analysis ◽  
The North ◽  
Avo Inversion ◽  
The North Sea

S-wave velocity and density information is crucial for hydrocarbon detection, because they help in the discrimination of pore filling fluids. Unfortunately, these two parameters cannot be accurately resolved from conventional P-wave marine data. Recent developments in ocean‐bottom seismic (OBS) technology make it possible to acquire high quality S-wave data in marine environments. The use of (S)-waves for amplitude variation with offset (AVO) analysis can give better estimates of S-wave velocity and density contrasts. Like P-wave AVO, S-wave AVO is sensitive to various types of noise. We investigate numerically and analytically the sensitivity of AVO inversion to random noise and errors in angles of incidence. Synthetic examples show that random noise and angle errors can strongly bias the parameter estimation. The use of singular value decomposition offers a simple stabilization scheme to solve for the elastic parameters. The AVO inversion is applied to an OBS data set from the North Sea. Special prestack processing techniques are required for the success of S-wave AVO inversion. The derived S-wave velocity and density contrasts help in detecting the fluid contacts and delineating the extent of the reservoir sand.

Inversion of reflection traveltimes for transverse isotropy

Geophysics ◽  
1995 ◽  
Vol 60 (4) ◽  
pp. 1095-1107 ◽  
Author(s):  
Ilya Tsvankin ◽  
Leon Thomsen
Keyword(s):  
Wave Velocity ◽  
Vertical Velocity ◽  
Joint Inversion ◽  
Transverse Isotropy ◽  
Taylor Series Expansion ◽  
High Sensitivity ◽  
Transversely Isotropic ◽  
P Wave ◽  
S Wave ◽  
Quartic Term

In anisotropic media, the short‐spread stacking velocity is generally different from the root‐mean‐square vertical velocity. The influence of anisotropy makes it impossible to recover the vertical velocity (or the reflector depth) using hyperbolic moveout analysis on short‐spread, common‐midpoint (CMP) gathers, even if both P‐ and S‐waves are recorded. Hence, we examine the feasibility of inverting long‐spread (nonhyperbolic) reflection moveouts for parameters of transversely isotropic media with a vertical symmetry axis. One possible solution is to recover the quartic term of the Taylor series expansion for [Formula: see text] curves for P‐ and SV‐waves, and to use it to determine the anisotropy. However, this procedure turns out to be unstable because of the ambiguity in the joint inversion of intermediate‐spread (i.e., spreads of about 1.5 times the reflector depth) P and SV moveouts. The nonuniqueness cannot be overcome by using long spreads (twice as large as the reflector depth) if only P‐wave data are included. A general analysis of the P‐wave inverse problem proves the existence of a broad set of models with different vertical velocities, all of which provide a satisfactory fit to the exact traveltimes. This strong ambiguity is explained by a trade‐off between vertical velocity and the parameters of anisotropy on gathers with a limited angle coverage. The accuracy of the inversion procedure may be significantly increased by combining both long‐spread P and SV moveouts. The high sensitivity of the long‐spread SV moveout to the reflector depth permits a less ambiguous inversion. In some cases, the SV moveout alone may be used to recover the vertical S‐wave velocity, and hence the depth. Success of this inversion depends on the spreadlength and degree of SV‐wave velocity anisotropy, as well as on the constraints on the P‐wave vertical velocity.

scholarly journals First seismic constraints on the Martian crust – receiver functions for InSight

2020 ◽  
Author(s):  
Brigitte Knapmeyer-Endrun ◽  
Felix Bissig ◽  
Nicolas Compaire ◽  
Raphael Garcia ◽  
Rakshit Joshi ◽  
...  
Keyword(s):  
Thermal Evolution ◽  
Broad Band ◽  
Landing Site ◽  
Crustal Thickness ◽  
Receiver Functions ◽  
Apparent Velocity ◽  
S Waves ◽  
Complementary Method ◽  
3D Effects ◽  
Insight Mission

<p>NASA’s InSight mission arrived on Mars in November 2018 and deployed the first very broad-band seismometer, SEIS, on the planet’s surface. SEIS has been collecting data continuously since early February 2019, by now recording more than 400 events of different types. InSight aims at enhancing our understanding of the internal structure and dynamics of Mars, including better constraints on its crustal thickness. Various models based on topography and gravity observed from the orbit currently vary in average crustal thickness from 30 km to more than 100 km, with important implications for Mars’ thermal evolution, and the partitioning of silicates and heat-producing elements between different layers of Mars.</p><p>We present P-to-S and S-to-P receiver functions, which are available for 4 and 3 marsquakes, respectively, up to now. Out of all of the marsquakes recorded to date, these are the only ones with clear enough P- or S-arrivals not dominated by scattering to make them suitable for the analysis. All of the quakes are located at comparatively small epicentral distances, between 25° and 40°. We observe three consistent phases within the first 10 seconds of the P-to-S receiver functions. The S-to-P receiver functions also show a consistent first phase. Later arrivals are harder to pinpoint, which could be due to the comparatively shallow incidence of the S-waves at the considered distances, which prevents the generation of converted waves. Identification of later multiple phases in the P-to-S receiver functions likewise remains inconclusive. To obtain better constraints on velocity, we also calculated apparent velocity curves from the P-to-S receiver functions, but these provide meaningful results for only one event so far, implying a large uncertainty. Due to difficulties in clearly identifying multiples, the receiver functions can currently be explained by either two crustal layers and a thin (25-30 km) crust or three crustal layers and a thicker (40-45 km) crust at the landing site. This model range already improves the present constraints by providing a new maximum value of less than 70 km for the average crustal thickness. Information from noise autocorrelations as a complementary method, identification of P-reverberations and S-precursors in the event recordings, and more extensive modeling, ultimately including 3D-effects, are considered to further our understanding of the waveforms and tighten the constraints on the crust.</p>

Full-waveform matching of VP and VS models from surface waves

2019 ◽  
Vol 218 (3) ◽  
pp. 1873-1891 ◽  
Author(s):  
Farbod Khosro Anjom ◽  
Daniela Teodor ◽  
Cesare Comina ◽  
Romain Brossier ◽  
Jean Virieux ◽  
...  
Keyword(s):  
Surface Waves ◽  
Wave Velocity ◽  
Real Data ◽  
Test Site ◽  
P Wave ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Data Set ◽  
Near Surface ◽  
Velocity Models

SUMMARY The analysis of surface wave dispersion curves (DCs) is widely used for near-surface S-wave velocity (VS) reconstruction. However, a comprehensive characterization of the near-surface requires also the estimation of P-wave velocity (VP). We focus on the estimation of both VS and VP models from surface waves using a direct data transform approach. We estimate a relationship between the wavelength of the fundamental mode of surface waves and the investigation depth and we use it to directly transform the DCs into VS and VP models in laterally varying sites. We apply the workflow to a real data set acquired on a known test site. The accuracy of such reconstruction is validated by a waveform comparison between field data and synthetic data obtained by performing elastic numerical simulations on the estimated VP and VS models. The uncertainties on the estimated velocity models are also computed.

Advances in surface-wave tomography for near-surface applications

2021 ◽  
Vol 40 (8) ◽  
pp. 567-575
Author(s):  
Myrto Papadopoulou ◽  
Farbod Khosro Anjom ◽  
Mohammad Karim Karimpour ◽  
Valentina Laura Socco
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
P Wave ◽  
Seismic Exploration ◽  
S Wave ◽  
Data Set ◽  
Near Surface ◽  
Processing Times ◽  
Spatial Coverage ◽  
Wave Tomography

Surface-wave (SW) tomography is a technique that has been widely used in the field of seismology. It can provide higher resolution relative to the classical multichannel SW processing and inversion schemes that are usually adopted for near-surface applications. Nevertheless, the method is rarely used in this context, mainly due to the long processing times needed to pick the dispersion curves as well as the inability of the two-station processing to discriminate between higher SW modes. To make it efficient and to retrieve pseudo-2D/3D S-wave velocity (VS) and P-wave velocity (VP) models in a fast and convenient way, we develop a fully data-driven two-station dispersion curve estimation, which achieves dense spatial coverage without the involvement of an operator. To handle higher SW modes, we apply a dedicated time-windowing algorithm to isolate and pick the different modes. A multimodal tomographic inversion is applied to estimate a VS model. The VS model is then converted to a VP model with the Poisson's ratio estimated through the wavelength-depth method. We apply the method to a 2D seismic exploration data set acquired at a mining site, where strong lateral heterogeneity is expected, and to a 3D pilot data set, recorded with state-of-the-art acquisition technology. We compare the results with the ones retrieved from classical multichannel analysis.

Crustal structure of the Iceland region from dispersion of surface waves

1962 ◽  
Vol 52 (2) ◽  
pp. 359-388
Author(s):  
Eysteinn Tryggvason
Keyword(s):  
Surface Layer ◽  
Surface Wave ◽  
Surface Waves ◽  
Wave Velocity ◽  
Crustal Structure ◽  
Wave Dispersion ◽  
P Wave ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Mid Atlantic Ridge

ABSTRACT A number of Icelandic records of earthquakes originating in the Mid-Atlantic Seismic Belt between 52° and 70° N. lat. have been investigated. The surface waves on these records are chiefly in the period interval 3–10 sec, and are first mode Love-waves and Rayleigh-waves. The surface wave dispersion can be explained by a three-layered crustal structure as follows. A surface layer of S-wave velocity about 2.7 km/sec covering the whole region studied, a second layer of S-wave velocity about 3.6 km/sec covering Iceland and extending several hundred kilometers off the coasts and a third layer of S-wave velocity about 4.3 km/sec and P-wave velocity about 7.4 km/sec underlying the whole region. The thickness of the surface layer appears to be about 4 km on the Mid-Atlantic Ridge south of Iceland and in western Iceland, 3 km in central Iceland and 7 km northwest of Iceland. The second layer is apparently of similar thickness than the surface layer, while the third layer is thick; and the surface wave dispersion does not indicate any layer of higher wave velocity. This 7.4-layer is supposed to belong to the mantle, although its wave velocity is significantly lower than usually found in the upper mantle

Simultaneous inversion of PP and PS seismic data

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. R1-R10 ◽  
Author(s):  
Helene Hafslund Veire ◽  
Martin Landrø
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Model Building ◽  
Joint Inversion ◽  
P Wave ◽  
Inversion Method ◽  
System Of Equations ◽  
S Wave ◽  
Data Set ◽  
Simultaneous Inversion

Elastic parameters derived from seismic data are valuable input for reservoir characterization because they can be related to lithology and fluid content of the reservoir through empirical relationships. The relationship between physical properties of rocks and fluids and P-wave seismic data is nonunique. This leads to large uncertainties in reservoir models derived from P-wave seismic data. Because S- waves do not propagate through fluids, the combined use of P-and S-wave seismic data might increase our ability to derive fluid and lithology effects from seismic data, reducing the uncertainty in reservoir characterization and thereby improving 3D reservoir model-building. We present a joint inversion method for PP and PS seismic data by solving approximated linear expressions of PP and PS reflection coefficients simultaneously using a least-squares estimation algorithm. The resulting system of equations is solved by singular-value decomposition (SVD). By combining the two independent measurements (PP and PS seismic data), we stabilize the system of equations for PP and PS seismic data separately, leading to more robust parameter estimation. The method does not require any knowledge of PP and PS wavelets. We tested the stability of this joint inversion method on a 1D synthetic data set. We also applied the methodology to North Sea multicomponent field data to identify sand layers in a shallow formation. The identified sand layers from our inverted sections are consistent with observations from nearby well logs.

Constraining crustal structure in the presence of sediment: a multiple converted wave approach

2019 ◽  
Vol 219 (1) ◽  
pp. 313-327 ◽  
Author(s):  
Erin Cunningham ◽  
Vedran Lekic
Keyword(s):  
Wave Velocity ◽  
Seismic Velocity ◽  
Seismic Station ◽  
Sedimentary Basins ◽  
Crustal Thickness ◽  
Receiver Functions ◽  
P Wave ◽  
Converted Wave ◽  
P Wave Velocity ◽  
Multiple Data Sets

SUMMARY Receiver functions are sensitive to sharp seismic velocity variations with depth and are commonly used to constrain crustal thickness. The H–κ stacking method of Zhu & Kanamori is often used to constrain both the crustal thickness (H) and ${V_P}$/${V_S}$ ratio ($\kappa $) beneath a seismic station using P-to-s converted waves (Ps). However, traditional H–κ stacks require an assumption of average crustal velocity (usually ${V_P}$). Additionally, large amplitude reverberations from low velocity shallow layers, such as sedimentary basins, can overprint sought-after crustal signals, rendering traditional H–$\ \kappa $ stacking uninterpretable. We overcome these difficulties in two ways. When S-wave reverberations from sediment are present, they are removed by applying a resonance removal filter allowing crustal signals to be clarified and interpreted. We also combine complementary Ps receiver functions, Sp receiver functions, and the post-critical P-wave reflection from the Moho (SPmp) to remove the dependence on an assumed average crustal ${V_P}$. By correcting for sediment and combining multiple data sets, the crustal thickness, average crustal P-wave velocity and crustal ${V_P}$/${V_S}$ ratio is constrained in geological regions where traditional H–$\ \kappa $ stacking fails, without making an initial P-wave velocity assumption or suffering from contamination by sedimentary reverberations.

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