A new technique for low magnetic latitude transformation: synthetic model results & examples
Z Shi, M den Hartog, L Pryer, Y Poudjom Djomani and K Connors
ASEG Extended Abstracts
2013(1) 1 - 4
Published: 12 August 2013
Abstract
Traditional methods for processing low magnetic latitude data below ±25° magnetic latitude are notoriously unstable. Existing methods such as Reduction to the Pole (RTP), and Equator (RTE), and Analytical Signal (AS), do not fully resolve anomaly location and may distort the anomaly shape leading to misinterpretation of the data, as well as loss of certain directional anomalies. These methods contain some limitations such that satisfactory results are not always achievable, and interpretation of geology from magnetic data can be difficult. The main difficulties are to do with anomaly shape and location, negative anomalies over induced magnetised source bodies, elongated anomalies perpendicular to the declination direction and weak or barely detectable anomalies for source bodies with a strike parallel to the declination direction. Combined, these difficulties lead to unsatisfactory processing, enhancement and interpretation of low magnetic latitude data. We have developed a new filter, Modulus of Total Component at Low Magnetic Latitude (MTC-LML Filter) based on the calculation of the Modulus of three magnetic components of the main field (one vertical and two orthogonal horizontal). The filter is designed to better position anomalies, reduce anomaly distortion and provide good anomaly shape. Positive anomalies are derived from both induced and remanently magnetised bodies and structures parallel to the declination direction are better recovered. We present the results of the MTC-LML Filter for synthetic models, composed of complicated bodies each with different strike directions and depths. We then present applications of the Filter to survey datasets from Peru and Niger, and compare the results with traditional low magnetic latitude transformation methods. Preliminary results show strong spatial correlation of geologic features between the MTC-LML Filter, radiometric (showing surface geology) and DEM datasets providing confidence that this technique can be used for geological interpretation.https://doi.org/10.1071/ASEG2013ab241
© ASEG 2013