Exploration Geophysics - Volume 39, Issue 3, 2008

We have modified the minimum curvature gridding method to cope with various flight line gaps, by employing a line spacing compression technique. The line spacing compression method was applied to magnetic data from a survey in northern Canada and was able to smoothly interpolate across the unevenly spaced lines without creating false anomalies. We have also derived a new, longer minimum curvature operator to handle flight lines of various lengths. The longer operator was applied to South Australia Salinity Project data and it removed the artificial boundaries at changes in flight line spacing and smoothly interpolated anomalies even over wider flight line gaps.

We have developed a new least-squares inversion approach to determine successively the depth (z), polarization angle, and electric dipole moment of a buried structure from the self-potential (SP) anomaly data measured along a profile. This inverse algorithm makes it possible to use all the observed data when determining each of these three parameters. The problem of the depth determination has been parameterised from the forward modelling operator, and transformed into a nonlinear equation in the form ξ(z) = 0 by minimising an objective functional in the least-squares sense. Using the estimated depth and applying the least-squares method, the polarization angle is then determined from the entire observed data by a linear formula. Finally, knowing the depth and polarization angle, the dipole moment is expressed by a linear equation and is computed using the whole measured data. This technique is applicable for a class of geometrically simple anomalous bodies, including the semi-infinite vertical cylinder, the infinitely long horizontal cylinder, and the sphere. The method is tested and verified on numerical examples with and without random noise. It is also successfully applied to two real datasets from mineral exploration in Germany and Turkey, and we have found that the estimated depths and the other SP model parameters are in good agreement with the known actual values.

We propose a rapid and efficient methodology for the detection and interpretation of airborne time-domain electromagnetic anomalies generated by thin sheet-like volcanogenic massive sulphides (VMS) deposits in a resistive environment, which are representative of VMS deposits in the Canadian Shield.

In the first step of the approach, we use high-order statistics for the detection and the recognition of a MEGATEM anomaly as indicating a thin sheet-like VMS deposit with respect to three criteria of detection: the minimum level of detection, the length of detection, and the coherence of detection over time. We adapt these criteria in order to optimise the detection of thin sheet-like VMS deposits against geological noise models. Once the anomaly is detected and recognised as the response to a thin sheet conductor, we interpret the model geometry and physical property using attributes calculated from the MEGATEM anomaly. We develop a system of weighted multi-linear regression to find the most significant attributes to estimate the dip, depth, conductance, and dimensions of a thin sheet-like VMS deposit. Stepwise regression suggests that shape attributes are most significant to estimate dip while depth is most strongly estimated by size attributes. The most significant attribute to estimate the conductance is the time constant. The size is best estimated by attributes related to the size of the anomaly. We test the regression system on thin sheet models with excellent performance. Most of the parameters of the thin sheet models were estimated within an interval of confidence about the initial property. We further test the system by estimating properties of three VMS deposits in the Abitibi Greenstone Belt, Québec, Canada, for which the geometries and geological properties are known. Most parameters are estimated within the interval of confidence for ISO, a thin sheet body, while the estimates for New-Insco and Gallen show more variability caused by departure from the reference thin sheet model.

A GEOTEK multi-sensor core logger (MSCL), originally developed to log soft-sediment cores, has been adapted to allow simultaneous measurement of a range of petrophysical parameters on diamond drill core. The system can measure the density, P-wave velocity, electrical conductivity, and magnetic susceptibility of either whole or half core. It also acquires high-resolution digital colour imagery of the core. System operation, sensor modification, sensor calibration, data accuracy, and repeatability are described in this paper. With careful calibration and close adherence to logging protocols, accuracy and precision of a few percent can be achieved with the MSCL in routine operation. The system is currently being used to record detailed petrophysical data on archival drill core from metalliferous mines for correlation with metallurgical parameters, but it has significant potential in mineral exploration and environmental applications as well.