ABSTRACT
Processing and interpretation of magnetic data, such as reduction to the pole (RTP), forward and inverse modelling, etc., usually require knowledge of the total magnetisation direction. Magnetisation of subsurface sources is often oblique to the geomagnetic field direction, due to remanent magnetisation, anisotropic induced magnetisation or, for sources with high susceptibility, self-demagnetisation. In order to re-place the magnetic anomalies above their causative sources, a mathematical transformation called RTP is required. RTP processing is usually performed without considering the impact of remanent magnetisation and directly uses the induced magnetisation direction (or geomagnetic field direction) as the total magnetisation direction, resulting in possible misinterpretation of the actual geology. Because the total gradient of the RTP data defines the envelope for the vertical gradient, the two gradients should achieve maximum symmetry after RTP processing that uses the correct total magnetisation direction. The RTP processed anomaly then corresponds to the vertical field anomaly for a vertically magnetised source. Based on this consideration, the total magnetisation direction of the magnetised body is estimated by calculating the cross-correlation between the two gradients. Introducing total magnetisation factors into the RTP operator in the frequency domain and using the Taylor formula, both of which have been proven to be practical by previous studies, we propose a modified reduction to the pole (MRTP) method taking the total magnetisation direction and variable geomagnetic inclination into consideration. Model computations and the practical applications to the Sichuan Basin indicate that this method can characterise oblique magnetisation, which is due to strong remanent magnetisation of igneous rocks, and improve the accuracy of magnetic data processing and geological interpretation.
Acknowledgments
This work was sponsored by the Special Projects of Geologic Surveys of Ministry of National Lands and Resources of China (GZH200900504-207), the National Natural Science Foundation of China (Grant Nos. 41476033, 91858212, and U1505232), the Special International Cooperation Program of “Global Change and Ocean–Atmosphere Interaction” (grant number GASI-GEOGE-01), the National Key Research and Development Program of China (Grant Nos. 2016YFC0601102 and 2016YFC0601104), and the National Science and Technology Major Project of China (grant number 2016ZX05004003).
Disclosure statement
No potential conflict of interest was reported by the authors.