1. |
- Veisi, Mohammad, et al.
(author)
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jrfapp: A Python Package for Joint Inversion of Apparent S-Wave Velocity and Receiver Function Time Series
- 2024
-
In: Pure and Applied Geophysics. - 0033-4553 .- 1420-9136. ; 181:1, s. 65-86
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Journal article (peer-reviewed)abstract
- Receiver function (RF) inversion is a well-established method to quantify a horizontally layered approximation of the S-wave velocity structure beneath a seismic station. It is well-known that the RF inverse problem is highly non-unique, and various tools such as joint inversion with other seismological observations exist that may overcome this problem. We present a joint inversion framework along with a Python package that implements the joint inversion of RF and the apparent S-wave velocity (VS,app). Our implementation includes a pseudo-initial model estimation, which helps address the inherent non-uniqueness of the joint inversion of RFs and VS,app. This implementation enhances the resolving power, enabling estimation of S-wave velocities with resolution approaching that of deep controlled source seismic methods. As an illustration, we showcase an example from a permanent station in the Makran subduction zone southeast of the Iranian Plateau and two other stations in the supplementary material. We compare our joint inversion results with several S-wave velocity models obtained through a deep seismic sounding profile and joint inversion of surface wave dispersion and RFs. This comparison shows that although we note a slightly lower sensitivity of our proposed method at greater depths (beyond 50 km), the method yields much better results for shallow structures. Our inversion code provides a powerful, accessible software package that has superior resolving power at shallow depth compared to RFs-surface wave inversion codes. Furthermore, the fact that only one data-derivative is used, makes this inversion code extremely easy to use, without the need for complementary datasets.
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2. |
- Veisi, Mohammad, et al.
(author)
-
jrfapp: A Python Package for Joint Inversion of Apparent S-Wave Velocity and ReceiverFunction Time Series
- 2024
-
In: Pure and Applied Geophysics. - 0033-4553 .- 1420-9136.
-
Journal article (peer-reviewed)abstract
- Receiver function (RF) inversion is a well-estab-lished method to quantify a horizontally layered approximation ofthe S-wave velocity structure beneath a seismic station. It is well-known that the RF inverse problem is highly non-unique, andvarious tools such as joint inversion with other seismologicalobservations exist that may overcome this problem. We present ajoint inversion framework along with a Python package thatimplements the joint inversion of RF and the apparent S-wavevelocity (VS,app). Our implementation includes a pseudo-initialmodel estimation, which helps address the inherent non-uniquenessof the joint inversion of RFs and VS,app. This implementationenhances the resolving power, enabling estimation of S-wavevelocities with resolution approaching that of deep controlledsource seismic methods. As an illustration, we showcase anexample from a permanent station in the Makran subduction zonesoutheast of the Iranian Plateau and two other stations in the sup-plementary material. We compare our joint inversion results withseveral S-wave velocity models obtained through a deep seismicsounding profile and joint inversion of surface wave dispersion andRFs. This comparison shows that although we note a slightly lowersensitivity of our proposed method at greater depths (beyond50 km), the method yields much better results for shallow struc-tures. Our inversion code provides a powerful, accessible softwarepackage that has superior resolving power at shallow depth com-pared to RFs-surface wave inversion codes. Furthermore, the factthat only one data-derivative is used, makes this inversion codeextremely easy to use, without the need for complementarydatasets.
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