The intermediate volcanic sequence hosting the Que River and Hellyer mines provides an excellent environment for electromagnetics in that the only two strong conductors ever found in them have been developed into mines. Now that the ground has been thoroughly explored by surface EM and the search is by necessity becoming deeper, downhole EM has become an extremely important aspect of the exploration programme. However, even in this ideal environment for EM, there are factors that cause interpretation headaches, although all can be overcome with care and experience. These problems include the overlying moderately conductive black shales, instrumentation responses from the Sirotem unit, responses from culture, and the effect of strong conductors such as the known ore bodies close to the target.
The Cole‐Cole dispersion approximates the behavior of inductive coupling over only a part of the frequency range. We show that the interaction between the induced polarization (IP) and inductive coupling (IC) effects will, in general, be more complicated than a multiplication of two Cole‐Cole dispersions representing the separate IP and IC effects. The inversion of published data shows that the time constant [Formula: see text] of the IP effect is often a poorly defined parameter. Hence, small changes in the parameters used to approximate inductive coupling by a Cole‐Cole dispersion can produce very large changes in the calculated value of [Formula: see text]. From these considerations, guidelines are developed to show when the Cole‐Cole dispersion may be successfully used to approximate inductive coupling and define [Formula: see text].
In the Buffalo Head Hills diamond province of Alberta, Canada, kimberlites have intruded a thick sequence of sedimentary rock units with thickness in excess of 300-500 m and resistivities of 5-10 ohm-m. In contrast to the conductive sedimentary rock the kimberlite intrusion is invariably characterised by a much higher electrical resistivities.These "resistive" kimberlites can be detected by both airborne and ground time domain EM methods. Because of the host sedimentary rock‖s very low resistivity, the resistive kimberlite response in many cases appears counterintuitive to the expectations based on the simpler analysis of the problem which ignores the EM interactions between a 3D body and a conductive host. For similar reasons, successful detection of kimberlites in the Buffalo Head Hills province also required developments of algorithms which facilitate correction of airborne TDEM data for variations in aircraft altitude and pitch. "Anomaly hunting" analysis which decompose the spatial and temporal characteristics of the EM response into a number of components and innovations in the inversion and transformations of ground TDEM data sets was also required. Application of standard Conductivity-Depth-Image (CDI) techniques was not appropriate to the solution to the problem. A new pseudo ID-inversion algorithm was developed to partially assist in the assessment of the data.A number of areas previously covered by detailed airborne magnetic surveys were re-surveyed with the Geotem airborne TDEM system. Use of the developed concepts and insights has resulted in a number of new diamonds-bearing non-magnetic kimberlite discoveries. New discoveries, for example, include kimberlites K296 (with a surface area of some 500 by 500 m), and K252 (with an estimated mini-bulk sample diamond content of 55.0 cpht), the highest estimated diamond content of all Alberta kimberlites to date.
The advantages of 2.5D (2D geology, 3D source) airborne electromagnetic inversion in 3D geological mapping applications and the identification of conductive drilling targets compared to the more commonly used CDI transforms or simple 1D inversions are demonstrated using examples from different geological settings.The 2.5D inversion application used in this work and described in Silic et al, 2015 is a substantially changed version of ArjunAir, Wilson et al., 2006, a product of CSIRO/AMIRA project P223F. The changes include a new forward model algorithm and a new inversion solver. The application enables the accurate simulation of 3D source excitation for full domain models inclusive of topography, non-conforming boundaries and very high resistivity contrasts. Solution is accurate for a geoelectrical cross-section which is relatively constant along a strike length that exceeds the AEM system footprint.The major innovation includes a new inversion solver with adaptive regularisation which allows the incorporation of a misfit to the reference model and the model smoothness function. The regularisation parameter is chosen automatically and changed adaptively at each iteration, as the model, the sensitivity and the roughness matrices are changing, Silic et al, 2015.Memory usage has been dramatically reduced and provides a usage estimate prior to execution. For speed the software has been parallelised using Intel MPI and can be used on standard computing hardware or computing clusters. Data from survey lines with lengths exceeding 30 kilometres can be inverted on high end laptop computers. The integrated software design allows the user to prepare a full survey inversion then execute this simply in a batch process. The user can visualise inversion progress at any time during process execution.We allow flexibility in the selection of components and in the estimation of noise. A non-specialist can obtain a high value result from our 2.5D AEM inversion in terms of it achieving a more realistic geological section.We show inversion examples from groundwater, minerals (VMS) and geological mapping AEM surveys projects and compare the results with known geology and drilling. We demonstrate the much improved mapping and target definition delivered by this inversion method when compared with the other more common transforms or inversion methods used on these projects.
SummaryApplication of Integral Equation Method to calculate the electromagnetic induction in multiply folded sheet conductors (many folds) is simplified by replacing the conductor with trial source currents (two dimensional polynomials) of unknown amplitude. Using the Galerkin method to solve the integral equation reduces the problem to inverting for the amplitudes of the current basis (trial) functions .This results in calculation of two matrices, one the resistance matrix and only a function of the sheets dimension and conductivity, the inductance matrix related to the self and mutual inductance of the trial currents, and only function of sheet’s geometry,and a vector describing the interaction of the primary magnetic field with each trial function . In comparison to the solution for a flat (not folded) sheet conductor, the folded conductor solution involves changes to the inductance matrix . Using these solutions, computing the EM induction (forward model) requires less than one second of CPU time using current computing units. Including this forward model solution in an inversion scheme to produce parameters of multiply folded and plunging sheet conductors is easy to apply and results is inversion solutions requiring (typically) less that one minute of CPU time using a 2 GHz processor . This is expected to be an orders of magnitude improvement on any inversion scheme using for example smooth model voxel (cells) or finite element inversion algorithms .By using approximate solutions to show that at appropriate sampled times or frequencies, EM response of multiply folded sheet conductors in a layered medium, could be largely controlled by the changes of the primary magnetic field at the conductor, similar quick forward models and inversion algorithms can be applied to sheet conductors in conductive layered earth . A number of forward models and practical inversions of field data are used to demonstrate the effectiveness of the developed forward modelling and inversion algorithms.
Current gathering in fixed loop electromagnetic data often dominates responses from large high-grade ore bodies as well as responses from less desirable features such as fault zones, weathering troughs and regional conductors. Through decay curve analysis, current gathering can now be unambiguously recognised.Many widely used EM interpretation techniques are not applicable to current gathering (channelling) responses. An effective method of deriving the location and shape of the causative source is to study the second spatial derivative, as is shown in several examples.
Magnetic sensors are being used to measure magnetic fields associated with galvanic current flow in a number of countries because of claims that they can detect conductive features beneath conductive overburden.An experimental magnetometric resistivity (MMR) survey was conducted in an area of deep weathering around the Elura lead-zinc deposit near Cobar, Australia. The survey did not appear to detect the Elura deposit. However, anomalies related to shallow conductive features and possible bedrock boundaries were observed.It is shown that the optimum array size for locating a conductive body under conductive overburden, is a compromise between trying to inject more current into the bedrock and not making the array too large to resolve the body being sought. The results from Elura, supported by theoretical calculations, indicate that this compromise will not be met easily with the weathering conditions in Australia, where the thickness and the conductivity of the overburden will frequently attenuate the maximum possible MMR anomaly by about 85 percent.By extending the accepted formulation for magnetic induced polarisation (MIP) response, it is shown that the ability of the MIP method to detect a polarisable body can be predicted from the results of MMR measurements if the body has a conductivity and polarisability contrast with the surrounding medium. This concept indicates that the absence of an MMR anomaly over Elura precludes the MIP method being a successful exploration method for Elura type deposits in this area.However, the results do indicate that MMR can be used as a mapping tool and that it is possible to discriminate between long striking conductors and localised ones by setting up electrode arrays at right angles to the supposed strike of the feature.
Summary2.5D (2D geology, 3D source) inversion of airborne electromagnetic (AEM) data has evolved into a routine and established practice on datasets from an array of applications. Large datasets may be inverted in days using conventional PC’s, or cloud computing for faster results.The 2.5D inversions in this study were carried out using a highly modified adaptation of the ArjunAir program originally developed by the CSIRO and subsequently by AMIRA project P223F. The new program is called Moksha.Results are presented from a continental scale AEM regional mapping survey carried out by Geoscience Australia. 2.5D inversions performed in a study area in the Mammoth Mines mineral district of Queensland defined discrete conductivity anomalies on a line over the Mount Gordon Fault Zone, and imaged a series of steeply-dipping conductors on a nearby regional traverse.The study demonstrated the ability of 2.5D inversions to image steeply-dipping and folded geology, and present possible exploration targets, in a mineralised deformed terrane.
The advantages of 2.5D airborne electromagnetic inversion in 3D geological mapping applications compared to the more commonly used CDI transforms or simple 1D inversions are described using an example from the Bryah Basin in Western Australia. We demonstrate this using a substantially rewritten version of ArjunAir (Wilson et al., 2006), a product of the CSIRO/AMIRA consortia (project P223F). The ArjunAir inversion solver has been replaced with a new GSVD (Paige, C. C. et al, 1981) solver, with adaptive regularisation which also incorporates a misfit to the reference model and a model smoothness function. The ArjunAir forward modelling code has been revised to fix two errors which manifest at late times around high resistivity discontinuities and in steep topography. The software has been parallelised using Intel MPI. We allow the use of a starting or reference geology/ resistivity model to influence the inversion. The software is implemented in a 3D geological modelling package (McInerney et al, 2005) with an intelligent graphical user interface for inversion setup, for introduction of geological reference models and for visualising results. Apparent Resistivity, 2.5D Forward and 1D and 2.5D Inversion methods are integrated in one 3D geological and potential field gravity and magnetics inversion environment.
The southern McArthur Basin in Australia’s Northern Territory is host to some Tier-1 sediment-hosted base metal mineral deposits including the McArthur River Zn-Pb-Ag mine. Airborne electromagnetic (AEM) data sets have been employed as a key exploration technology in the search for these mineral systems. A geological interpretation of results arising from the use of different inversion techniques, including a 1, 2.5 and 3D methods, was undertaken on a helicopter EM data set acquired over a structurally complex sediment package in the Batten Fault Zone north of the McArthur River Mine. The exploration targets were conductive, mineralised units (HYC pyritic shale member) associated with the Barney Creek Formation. Results from this study suggested that although the model fits were good, the derived conductivity models for the 2.5D and 3D inversions appeared to be smooth representations of geological reality, particularly when compared with data from drilling and surface geological mapping. Superficially, the 1D smooth model layered Earth inversions appear to map geological variability and structural complexity in greater detail even though the structures are more 3D in nature. IP effects are observed in the data and influence the modelled structure, but can be accounted for and complement the non IP 1D inversion results. The outcome of this study also indicates that when employing higher order inversion methods in the interpretation of AEM data sets, there may be significant benefit in asking a contractor/consultant for 1D inversion results as well. In the resulting interpretations if conductors appear in one but not the other, it is worth asking the question why?
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