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Towards Hourly 4-D Subsurface Monitoring using Seismic Ambient Noise
  • Peng Guo,
  • Erdinc Saygin
Peng Guo
CSIRO

Corresponding Author:[email protected]

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Erdinc Saygin
CSIRO
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Abstract

We use seismic ambient noise recorded by ocean bottom nodes (OBNs) in the Gorgon gas field, Western Australia to compute time-lapse seafloor models. The extracted hourly cross-correlation (CC) functions of 0.1 – 1 Hz contain mainly Scholte waves with very high signal to noise ratio. The conventional time-lapse analysis suggests relative velocity variations (dv/v) up to 1% assuming a spatially homogeneous dv/v, with a likely 24-hour cycling pattern. With high-resolution baseline models from full waveform inversion of Scholte waves, we propose a double-difference waveform inversion (DD-WI) method using travel time differences for localizing the time-lapse dv/v in the heterogeneous subsurface in depth. The time-lapse velocity models show velocity increase/decrease patterns in agreement with that from conventional analysis, with more notable changes at the shallower depths. We demonstrate the feasibility of using ambient noise for quantitative monitoring of subsurface property changes in the horizontal and depth domain at an hourly basis.