Simultaneous modelling of the phase and amplitude components of downhole magnetometric resistivity data (original) (raw)

Finding sphalerite at Broken Hill with drillhole magnetometric resistivity

Exploration Geophysics, 1997

Lode horizons north and south of the Broken Hill, New South Wales orebody contain a number of zones rich in sphalerite and poor in galena. One example is Pasminco Mining's new opencut Potosi Mine, which averages 8.5% Zn and 2% Pb with little other sulphide. The mineralisation at the Potosi Mine has been well defined by applied potential and induced polarisation (IP) surveys, but different techniques are required for deeper, downplunge exploration. Drillhole electromagnetics (DHEM) is routinely used but may miss those zones where sphalerite is almost the only sulphide. It was therefore decided to try a series of drillhole magnetometric resistivity (DHMMR) surveys, since this method responds to contrasting, rather than absolute, conductivity. The results were very successful with the known sulphides (and some previously unsuspected zones) responding at downhole depths of more than 600 m. The method has detected mineralisation at distances greater than 150 m from the drillhole and ...

Joint Inversion of Apparent Conductivity and Magnetic Susceptibility to Characterize Buried Targets

— A good knowledge of the underground space is needed in urban planning. The main objects found buried are water and sewage pipes, cables, and contaminants storage tanks. Through the inversion of inductive electromagnetic data, we can obtain parameters like depth, position, and radius of these targets. Here, we show a joint inversion approach of apparent conductivity and magnetic susceptibility using data collected at the IAG/USP test site. The model employed assumes three coils (transmitter, receiver, and target/conductor) and relates the electromotive force, through the mutual inductance that occurs between the pairs of transmitter–receiver and conductor– receiver coils, to the acquired conductivity and susceptibility data. The achieved adjustment between field and calculated data indicates that, despite the simplicity of the model, it is a good representation of the conductors, increasing the results of the inversion process. The inversion algorithm is based on the controlled random search algorithm, which presented to be quite stable with electromagnetic data. The main advantage of the proposed approach is the relatively fast inversion process that showed better results than the traditional qualitative interpretation usually applied to this kind of investigation, being promising for noninvasive target characterization and having application in geotechnical studies.