New data processing algorithm for marine heat flow and thermal modeling for Tsan-Yao mud volcano offshore SW Taiwan
Date Issued
2016
Date
2016
Author(s)
Wu, Jyun-Nai
Abstract
Marine heat flow surveys typically utilize Lister-type heat probes, which allow multi-penetrations to measure both temperature and thermal conductivity in situ. Over the past decade, the data processing technique of the heat probes usually use a two stages procedure with empirical constrain to overcome the shortcomings of convergent. However, the empirical constrain had never been validated by experimental data and will certainly vary with sediment type. In this study we attempt to simplify the procedure and remove the empirical part with an advantageous inversion scheme. Our algorithm has been tested on both synthetic and field data and the results show a good agreement with previous algorithm. In our study area, the Tsan-Yao mud volcano, we observed high heat flow value on the top of mud volcano by both previous and our data processing algorithm. To understand the mechanism of heat transfer in this area, we construct a 2D thermal model across the mud volcano. The model shows that there is an advection under the mud volcano and causes the high heat flow measurement; we suggest that advection should be caused by the fluid migration beneath the mud volcano. Base on some assumptions, we found that the fluid migration rate beneath the mud volcano should be 13 cm/yr upward to satisfy our heat flow measurement.
Subjects
Lister-type heat probe
heat flow
mud volcano
thermal model
inverse algorithm
SDGs
Type
thesis
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