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Advanced 3-D Vs Inversion at Mendocino Triple Junction Using Innovative Analysis Techniques

Kaijian Liu, a 5th-year graduate student at Rice University, is currently conducting research on 3-D Vs inversion in the Mendocino Triple Junction (MTJ). This project involves a joint analysis of surface wave, ambient noise, and receiver function data to develop high-resolution shear velocity models. Key methodologies include Rayleigh wave tomography using the two-plane wave method and the use of data from the Flexible Array Mendocino Experiment (FAME) to enhance the accuracy of the Vs models in this geologically complex region.

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Advanced 3-D Vs Inversion at Mendocino Triple Junction Using Innovative Analysis Techniques

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Presentation Transcript

  1. Basic info • Kaijian Liu • Rice University • 5th year graduate student • Current research project: • 3-D Vs inversion in the Mendocino Triple Junction (MTJ) from joint analysis of surface wave, ambient noise and PdS receiver functions

  2. Data flow and tools • Rayleigh wave tomography from two-plane wave method • Joint inversion of surface wave, ambient noise, and receiver functions for high-resolution shear velocity model • Vs model in Mendocino Triple Junction region using Flexible Array Mendocino Experiment (FAME) data

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