Open AccessResistivity studies over the Flinders conductivity anomaly, South Australia
Author(s) -
Constable S. C.
Publication year - 1985
Publication title -
geophysical journal of the royal astronomical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0016-8009
DOI - 10.1111/j.1365-246x.1985.tb04337.x
Subject(s) - geology , electrical resistivity and conductivity , depth sounding , anomaly (physics) , electrical conductor , geophysics , magnetometer , signal (programming language) , stacking , sediment , current (fluid) , conductivity , noise (video) , mineralogy , seismology , geomorphology , magnetic field , oceanography , electrical engineering , materials science , physics , condensed matter physics , nuclear magnetic resonance , composite material , quantum mechanics , image (mathematics) , engineering , artificial intelligence , computer science , programming language
Summary. Seven Schlumberger resistivity soundings with maximum current electrode spacings of 20 km have been conducted south of Lake Frome in South Australia. These experiments were done partly to test new electrical sounding equipment and partly to investigate a large conductivity anomaly previously delineated by other workers using magnetometer array and MT methods (the ‘Flinders’anomaly). These previous studies left some doubt as to the depth to the conductive region responsible for the anomaly. The electrical soundings did not detect a buried conductive zone, which constrains it to lie deeper than 5–7 km. However, the study did show the surface sediments of the region to be very conductive; resistivities of 2–9 μm were measured over thicknesses of 50–400 m, with sediment thickness inferred to be up to 2 km to the north of the studied area. This raises the question of whether current channelling in the surface sediments could have been responsible for the earlier results. Simple modelling and application of the criteria given by Jones suggest this may be so. The equipment used for this study is a low power (200 W), computer controlled system which employs synchronous stacking and other signal processing to achieve signal to noise improvement ratios of up to 1000.