This article has been peer reviewed and accepted for publication. It is in production and has not been edited, so may differ from the final published form.
SYNTHETIC MODELLING AND ANALYSIS OF CSEM FULL-FIELD APPARENT RESISTIVITY RESPONSE COMBINING EM INDUCTION AND IP EFFECT FOR 1D MEDIUM
In order to reduce the distortion of cagniard apparent resistivity in near-field and transition-field in controlled source electromagnetic method (CSEM) exploration and analyse the influence of induced polarization (IP) effect on sounding curve, The full-field apparent resistivity responses combining electromagnetic (EM) induction and IP effect for 1D medium were modelled. Complex resistivity of the rocks and ore were calculated using the Cole-Cole model, and this complex resistivity was used to replace the real resistivity without IP effect in CSEM forwarding. Additionally, full-field apparent resistivity was calculated using electric field component by Newton iterative algorithm, which is suitable for the whole field zone. Sounding curves of full-field apparent resistivity and cagniard apparent resistivity were compared. Full-field apparent resistivity responses with and without IP effect were analysed. Influence of varying time constant and frequency dependent coefficient on the responses, influence of noise levels on the responses and influence of the IP effect on the inversion were also evaluated. The results show that the distortions in near-field and transition-field are removed in full-field apparent resistivity sounding curves. IP effect has a significant impact on full-field apparent resistivity response. For multi-layer medium, the influence of IP effect on sounding curve is dependent of the burial depth of polarization layer and the curve type of layered medium. The influence of chargeability is greater than that of other two parameters, time constant and frequency dependent coefficient. Resistivity and thickness of the layered model were distorted seriously by using the inversion algorithm ignoring IP effect.
EG17049 Accepted 22 September 2017
© ASEG 2017