Comparative study of estimating the Curie point depth and heat flow using potential magnetic data

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Abstract

The estimation of the Curie point depth (CPD) and heat flow (HF) from magnetic data is useful for geothermal and tectonic studies. However, the methodology of estimating these values is still controversial as numerous studies have used different types of transformed magnetic data. Most studies utilize the total magnetic intensity (TMI) or the reduced to the pole (RTP) data, and since shallow magnetic bodies may affect the final CPD values, low-pass (LP) wavelength filtering has also been used to estimate the CPD. In this study, the two-dimensional radially averaged spectral analysis was applied to the land-based magnetic data from the Sinai Peninsula. TMI and RTP data were both analyzed, using different LP filtered wavelengths, and the final CPD and HF values were compared. The cut-off wavelength parameter was selected in terms of the geologic complexity. The results show that the estimated CPD values are well correlated regardless of whether the magnetic data were either TMI or RTP. The RTP data produced a spatial shift in the CPD smaller than the window size being used. Additionally, the centroid method is primarily dependent on the wavenumber, which varied slightly on applying the RTP. There were slight differences in the estimated CPDs when a short LP filter (e.g., 20 km) was applied, whereas increasing the wavelength (e.g., 40 km) caused the CPD values to increase exceeding the plausible depth limits, and the associated spatial trends varied when compared to the other methods. In areas where the basement rocks were shallow or exposed, a LP filter can be applied with short cut-off wavelength. The estimated CPDs were discussed in the context of seismicity data, gravity-based Moho depths, and HF measurements.

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Ibrahim, A., Saada, S. A., Mickus, K., Abdelrahman, K., & Khedr, F. I. (2022). Comparative study of estimating the Curie point depth and heat flow using potential magnetic data. Open Geosciences, 14(1), 462–480. https://doi.org/10.1515/geo-2022-0378

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