ASEG Extended Abstracts - ASEG2009 - 20th Geophysical Conference, 2009

The location and identification of unexploded ordnance (UXO) is a major challenge for environmental rehabilitation of former military firing ranges and bombing target areas. EM methods are in widespread use for the location of metal objects, however the presence of large quantities of scrap metal from successful detonation of munitions makes discrimination between munitions and scrap and munitions of various sizes a necessity in order for efficient location, digging and removal of UXOs to proceed. Several recent papers show that detailed three- component EM measurements followed by inversion to dipole moments of an EM target is effective in characterising a target, however such techniques require precise data, usually from stationary data acquisition.

EM data acquired from a moving ground platform for UXO detection is typically high in motion-induced noise which limits the usefulness of decay-curve analysis in target characterization. We use a data set from the Australian Air Force Newholme UXO Test Range, Armidale, NSW, and show that

a) images of time-window data are unsuccessful in discriminating between different types of munitions,

b) adaptive decay index methods are ineffective due to high noise levels on the observed decay curves, and

c) principal-component transforms of the data are successful in differentiating between different types of munitions.

The method provides a tool for initial classification and prioritization of anomalies from a surveyed area, thus facilitating preparation of an efficient program of follow-up surveys and site clean-up.

Researchers involved in induced polarization studies are well familiar with Seigel’s (1959) definition of the chargeability parameter m as the ratio of the secondary potential drop immediately after an infinitely long injected current is turned off, to the primary potential drop that builds up at the end of the current pulse. A major advantage of Seigel’s formulation is that it allows to recover the intrinsic chargeability of the subsurface applying a simple perturbation to the sensitivity matrix of the background resistivity (i.e. not affected by IP effects) model. In fact he proved that the apparent chargeability above an heterogeneous earth is simply

where mi and ρi represent the intrinsic chargeability and background resistivity of the ρa media (for a layered earth, layers) that compose the subsurface, and pa the apparent background resistivity. This important result implies that the chargeability model can be readily obtained after the resistivity model has been recovered, and forms the basis of well established time domain IP inversion techniques (Li and Oldenburg, 2000a; Loke, 1999; Oldenburg and Li, 1994; Sogade et al., 2006). This manuscript aims at showing a fundamental discrepancy between Seigel’s fundamental theory and many different well accepted IP models. While contradicting in practice Seigel’s model, these other models do make use of important mathematical formulation that Seigel derived from his model.

In this paper we present and analyse DC resistivity sensitivity patterns for uniform anisotropic media. The sensitivity functions (or Fréchet derivatives) give the responsive change in measured electric potential for a perturbation in a model parameter at a particular point in the subsurface for a specific electrode configuration. The anisotropic model investigated is the common tilted transversely isotropic medium (TTI) which is defined by four model parameters. We examine the changes in the Fréchet derivatives of the Green’s functions with respect to both the longitudinal and transverse conductivity and the dip and azimuth angle of the symmetry axis (dG/dσ1, dG/dσt, dG/dθ0, dG/dϕ0) for varying model parameters.

Secondly, we wish to illustrate the differences that exist between the sensitivities calculated using an isotropic assumption and those computed with the correct anisotropic formulation. It is shown that in certain cases gross errors in inversion may occur if isotropic Fréchet derivatives are mistakenly used. Here we work with two special forms of the derivatives -one taken with respect to the mean conductivity and the other with respect to the magnitude of the anisotropy- and investigate a range of possible cases.

A fast approximate three dimensional inversion scheme for interpreting ground transient electromagnetic (TEAT) data is presented. The scheme relies on linear superposition of magnetic moments. The moment transform of TEAT data is a time-weighted integral of the impulse response.

In effect, the moment transformation converts the 3-D TEM inversion problem into a 3-D magnetic inversion problem, with accuracy traded for speed. A starting model is generated from conductivity-depth sections, and the inversion is conditioned using standard potential field inversion devices such as depth weighting.

It has been shown that the spectral method (Trefethen 2000) and the spectral element method (Komatitsch and Tromp 1999) have more attractive features than the traditional finite difference (FD) and the finite element (FE) numerical methods used in resistivity modelling. The main advantages lie in the capability to simulate complex physical models and the exponential power convergence. They have been successfully applied to fluid flow dynamic modelling (Boyd 1989), seismic wave simulations (Komatitsch and Tromp 1999) and electromagnetic computations (Martinec 1999).

The spectral method uses some global series of orthogonal functions to represent the unknown solution at the irregular collocation points, subject to boundary conditions. The resulting linear system matrix is full. The spectral element method combines the spectral method and the finite element method, and it possesses the main advantages of each. This includes the capability to handle various model shapes, the sparse matrix format of the FEM and the exponential power convergence of the spectral method.

In a recent paper (Zhou et al., 2008) we presented the theory for a new resistivity modelling method based on Gaussian Quadrature Grids (GQG). It readily enables calculation of the electric potential in 2.5-D/3-D heterogeneous, anisotropic models having arbitrary surface topography. The method co-operatively combines the solution of the Variational Principle of the partial differential equation, Gaussian quadrature abscissae and local cardinal functions so that it transforms the 2.5-D/3-D resistivity modelling problem into a sparse and symmetric linear equation system, which can be solved by an iterative or matrix inversion method.

The GQG method was inspired by the spectral element approach, but does not require a constant element mesh matching the surface topography (avoiding the 2-D/3-D mesh generator), or the resistivity tensor to be constant within the element integrations. This makes it particularly well suited for handling arbitrary surface topography and easily accommodates general anisotropy of the medium. This new method makes complex forward modelling much easier with the bonus of a deterministic mesh for resisitivity inversion techniques.

Comparison with analytic solutions for homogeneous isotropic and anisotropic models with no topography shows that the error depends on the Gaussian quadrature order (abscissae number) and the sub-domain size. The higher the quadrature order or smaller the subdomain size employed, the more accurate the solution. Several other synthetic examples, both homogeneous and inhomogeneous, incorporating sloping, undulating and severe topography are presented and found to yield results comparable to finite element solutions involving a dense mesh.

Major metal resources, predominantly gold and base metals, are hosted in the Cobar region, in the Central Lachlan Orogen of NSW, (Figure 1). The Predictive Mineral Discovery Cooperative Research Centre (pmd*CRC) Til Cobar project was a two-year, one-on-one project between the pmd*CRC NSW DPI and five mining companies in the Cobar region: CBH Resources Ltd., Cobar Management Pty Ltd., Peak Gold Mines, Triako Resources Ltd. and Tritton Resources Ltd.

The future of greenfields mineral exploration will be driven towards covered terranes with little or no outcrop. Consequently, the inherent risk and costs of such exploration will rise. The exploration focus will be pushed towards inexpensive methods and more importantly obtaining the most value from them. Potential field geophysics provide a solution to this impending issue with regional datasets often available in the public domain and higher resolution data being relatively inexpensive to acquire. Constrained potential field inversion represents a method for adding or maximising the value from the associated datasets.

Many greenfields environments have an apparent absence of a priori data to constrain the first pass inversion. This paper suggests that although this absence may exist, meaningful "soft" constraints will still be present which when included in the model objective function, improve and add value to the inversion process. Additionally the same constraints can be used to test whether a proposed geological hypothesis is a viable model.

Using gravity data over covered IOCG prospects within the Gawler Craton, this paper demonstrates how "soft" constraints can be employed to enhance the inversion process. Simplified layered geological models representing cover and basement have been discretised, using realistic petrophysical bounds that when incorporated into the model objective function yield more accurate results. Furthermore, the potential of a prospect to host IOCG mineralisation can be simply tested in a similar fashion. When inversion results describe bodies that are geologically unrealistic, the target can be downgraded saving a potentially expensive drillhole.

Mineral exploration produces a large amount of diverse geological and geophysical data, yet it can be difficult to combine all of this information into integrated models of subsurface geology. Gravity and magnetic data are the two most common geophysical datasets used in mineral exploration. They are commonly interpreted by developing 2D or 3D geological models, forward modelling the geophysical response, and modifying the models until they explain the observed data. Inversion techniques have also been developed to calculate 2D or 3D physical property models that explain observed geophysical responses. However, inversion of potential field data is hindered by the non-uniqueness of solutions.

Application of default, geologically-unconstrained inversions to obtain estimated subsurface physical property models from gravity and aeromagnetic datasets is a common step in many exploration programs. Although the recovered models can help target anomalous features in the subsurface, a reliable model, consistent with all observed geological and geophysical information, can only be recovered by including geology-based constraints with the standard mathematical constraints.

The University of British Columbia - Geophysical Inversion Facility’s (UBC-GIF) GRAV3D and MAG3D gravity and magnetic inversion packages (Li and Oldenburg, 1996, 1998) are particularly well suited to early stages of exploration where prior geological knowledge is limited.

Terracing (Cordell and McCafferty, 1989, Philips, 1992) is an operator that is applied to potential field data to produce regions of constant field amplitude that are separated by sharp boundaries. Magnetic data are usually transformed into pseudogravity data (Baranov, 1957) prior to the application of terracing. The objective of terracing is ‘to recast potential field maps into a geologic map like format’ (Cordell and McCafferty, 1989). Terracing is performed by moving a window through the data and computing the curvature at each point. The curvature of the field f is calculated using a three coefficient numerical approximation to the Laplacian derivative operator, which for profile data are given by;

Lamproites are peralkaline, typically ultrapotassic (6 to 8% K2O) and magnesia-rich lamprophyric rocks of volcanic or hypabyssal origin and are now considered to crystallize from a distinct type of magma. Most lamproites occur in irregular, asymmetric craters that are generally rather shallow, usually less than 300 metres in depth, often in the shape of a champagne glass with crater diameters ranging from a few hundred metres to 1500 metres. An unusual feature is that volcaniclastic rocks in many lamproite craters are intruded by a magmatic phase that forms lava lakes or domes. Lamproite forms from a very explosive volatile-rich magma that forms deep down within the Earth (greater than 150 km) and rises rapidly to the surface because of the high fluid pressure. As it rises, it fractures the surrounding rock explosively and most lamproites contain numerous xenoliths from all levels of the mantle and crust that the lamproite has passed through on its way to the surface. The initial explosive phreatomagmatic stage of the eruption, powered by gases or boiling ground water, corrodes the hosting rock to form the champagne-glass shape. Particles of ash, lapilli, and pumice partially fill the crater and form a tuff ring and finally the crater fills with a lava pond from the degassed lamproite magma. These are typical maar-type diatremes, formed by an explosive reaction induced when hot, rising magma came into contact with subterranean water.

Lamproites are small-volume magmas and there are relatively few lamproites known world wide, with less than 20 geological provinces, of which only seven are diamondiferous. Only olivine lamproites are diamondiferous, other varieties such as leucite lamproites presumably did not originate deep enough in the mantle to contain significant diamond content. Olivine lamproite pyroclastic rocks and dikes are the usual source of diamonds whereas diamonds are rarely found in the magmatic equivalents. Diamonds do not crystallize from the lamproite magma but are brought to the surface as the magma ascends rapidly to the surface, collecting fragments of the mantle and crust en route. The Kimberley region of Western Australia contains the only two lamproite-hosted diamond mines in the world (the Argvle Diamond Mine in the East Kimberley and Kimberley Diamond Company’s Ellendale 9, in the West Kimberley).

Most magnetic field interpretation is based on the assumption that magnetization is in the same direction as the ambient geomagnetic field, and there is a widely held suspicion that anomalies cannot be inverted without this assumption. In this paper we aim to establish that the problems of uncertain magnetization direction can be largely overcome utilising both staged inversion and magnetic moment analysis (MMA).

Induced magnetization has a single, known direction. Not only may a remanent magnetization direction be unknown, but it may also be variable across a wide range of scales. Palaeomagnetic studies address this variability with collection of multiple samples from multiple sites (generally outcrops, quarries or road-cuts) for hierarchical statistical analysis. For rapidly cooled volcanic or sub-volcanic bodies, magnetization directions may vary due to short-term changes in the geomagnetic field. For deeper, more slowly cooled bodies, or for bodies formed by multi-phase intrusions, magnetization direction may vary due to apparent polar wander. Furthermore, remanent magnetization of rocks with a complex thermal history may include over-prints of components of different direction acquired at different times, with variable contributions to the overall magnetization in different samples. Magnetization directions may also vary due to any post-acquisition tectonic rotations. The magnetic field generated by a body depends on the resultant of induced and remanent magnetizations, determined by the Koenigsberger (or “Q”) ratio, which generally is also highly variable across a wide range of scales. To properly incorporate remanent magnetizations in a magnetic field interpretation we can not expect to just replace the geomagnetic field direction of an induced magnetization with a predetermined remanent magnetization direction. Rather, the interpretation of anomalies caused in substantial part by remanent magnetization requires flexible and adaptive methods.

In this paper we firstly review the derivation of magnetization direction by MMA of vector components and the gradient tensor of the magnetic field. Then we investigate the combination of inversion and MMA in a study of the Newcastle Range Volcanics in north-west Queensland. This volcanic province has bodies with a wide range of shapes, sizes, complexities and settings, many with magnetizations dominated by remanence. Each anomaly presents an opportunity to determine magnetization direction with its own particular challenges. A palaeomagnetic study of the same rocks by Anderson et al (2003) provides data with which to validate and classify magnetization directions derived from the magnetic field interpretation.

Seismic and electromagnetic wave fields in the accessible (drillable) earth both respond to changes in rock properties and structure, yet are not usually combined into a single subsurface map that reflect these common changes. Variations in layer thicknesses, folds, faults, fault-related offsets, porosity, fluids, and saturation create anomalies in both fields. The presence of oriented fractures and fabric adds anisotropic responses to both as well. Ideally, both fields would be used to create a map that combines their responses to a sought after property, say porosity, in a single “joint geophysical image”. The members of the Institute of Earth Science and Engineering are working toward such JGI maps, progress in which is reported on in this presentation.

A simple example of JGI is the inversion of high-resolution seismic refraction and magnetotelluric data collected over a simple layer-over-basement structure. Here the common factor is the layer thickness, the value of which is most accurately found forcing the seismic velocity and apparent resistivity models to give the same number. A less simple example is the combined use of seismic travel times and MT resistivity converted to seismic velocity to locate microearthquakes. An even more complicated example is the inversion of shared S-wave-splitting and MT-polarization effects from zones of oriented and fluid-filled fractures.

Some of theoretical and practical aspects of these three cases will be discussed, including: (a) data gathering techniques, (b) physical models of the shared properties, especially in the case of fractures and anisotropy, and (c) quantitative methods for combining measurements.

PRESENTER PROFILE

PETER MALIN is a geophysicist interested in the properties and dynamics of the crust, specializing in seismology in energy-reservoir exploration and characterization. He is involved in 3 borehole seismology projects in Australia - Cooper Basin, Latrobe Valley, and Paralana. These projects combined different methods to locate and characterize fracture systems. He received BSc and MSc degrees from Stanford in Exploration Geophysics, and a PhD from Princeton for work on surface wave scattering in weathering layers. After 17 years at Duke University in the US, he is now Director of the Institute of Earth Science and Engineering at University of Auckland, New Zealand.

[email protected]

Hot Rocks have potential to fuel competitive, emission free and renewable electricity for centuries to come. This potential is stimulating Enhanced (Engineered) Geothermal Systems projects worldwide, calling upon integrated expertise from the petroleum, minerals and power industries.

Converting just 1% of Australia’s estimated Hot Rock crustal energy to electricity, from temperatures above 150°C and depths below 5 km (190 million PJ) would supply 26,000 years of Australia’s primary power use, and that neither takes into account the renewable characteristics of hot rocks, nor resources below 5,000m.

Factors that distinguish Australian Hot Rock resources are: (1) Very radioactive granites are abundant, as in South Australia where the mean heat flow is 92μWm-2 compared to a global continental average of 51μWm-2¹; and (2) Australia is converging with Indonesia on a plate scale – giving rise to common, naturally occurring sub-horizontally fractured basement rocks that are susceptible to hydraulic fracture stimulation.

Australia’s geothermal projects are focused on both Hot Rocks to develop Enhanced (Engineered) Geothermal Systems and associated Hot Sedimentary Aquifer plays to fuel binary power plants. In addition to meeting demand for base load power, mining, desalinisation and diying processes are also markets for geothermal energy.

In the term January 2000 through December 2008, companies have applied for 385 licence areas (covering 359,723 km²) to progress proof-of-concept amagmatic Hot Rock and Hot Sedimentary Aquifer projects in Australia. In the term 2002 through 2008, more than Aus$325 million (US$228 million) has been spent on studies, geophysical surveys, drilling, reservoir stimulation and flow tests that comprise the work programs required to sustain tenure in geothermal licences areas. In the term 2002-2013, investment for Australian proof-of-concept geothermal projects is expected to exceed Aus$ 1,523 million (US$1,066 million).

This rapidly rising level of investment is driving sector-wide cooperation to support high priority and complementary research that can speed the pace and lower the cost of commercialising Australia’s vast Hot Rock (HR) and Hot Sedimentary Aquifer (HSA) geothermal plays. That cooperation is underpinned with more than Aus$110 million (US$77 million) in Australian Federal and State government grants to meet up to half of the cost of the private sector’s field efforts. This includes Aus$60 million (US$42 million) available to support new deep drilling for the proof-of-concept HR and HSA projects, but excludes Aus$507 million (US$355 million) for all forms of meritorious, commercial-scale demonstration of renewable energy technologies, including geothermal projects.

This paper summarises: (1) proof-of-concept amagmatic HR and HSA geothermal projects co-funded by investors and governments in Australia; (2) policies, programs and alliances put in place to support the development of geothermal plays; (3) research priorities and studies undertaken in support of geothermal projects and (4) emerging protocols to build trust with stakeholders, including a reporting code for geothermal resource and reserve estimates and best practice procedures for the management of potential risks associated with induced seismicity.

These collateral efforts are all directed at having at least 10 successful research and proof-of-concept geothermal projects by YE 2012/13, and at least 3 power generation demonstration projects in distinctly different geologic settings by 2012/13, with the results providing compelling evidence to justify investment in the development of Australia’s vast Hot Rock and Hot Sedimentary Aquifer plays.

Success in Australia will have positive implications for similar projects elsewhere.

The Cooper Basin region straddles the Queensland/South Australia (SA) border (Figure 1) and is coincident with a prominent geothermal anomaly (Cull & Denham, 1979; Cull & Conley, 1983; Somerville et al., 1994) (Figure 2). The region forms part of a broad area of anomalously high heat flow which is attributed to Proterozoic basement enriched in radiogenic elements (Sass & Lachenbruch, 1979; McLaren et al., 2003). Thick sedimentary sequences in the Cooper and overlying Eromanga Basins provide a thermal blanketing effect resulting in temperatures as high as 230° C at depths <5 km (Holgate, 2005).

A regional seismic survey in north Queensland, with acquisition parameters set for deep crustal imaging, shows a potential geothermal target beneath about 2 km of sediments. Beneath the sedimentary structure there appears to be an area of low seismic reflection signal from about 1 s to 4 s. Combined with die relatively low gravity signature over this location, this area of low seismic reflection signal could be interpreted as a large granite body, overlain by sediments. This body lies near an area of high crustal temperature and suggests a potential geothermal energy target.

Collaborative work is under way to develop an accessible method for rapid calculation of the spatial variation of temperature directly from a 3D geology model. The need for a tool of this nature stems from Australia’s emerging geothermal energy exploration and production industry. The prohibitive cost and huge task involved in acquiring comprehensive sets of heat flow data, means that the ability to accurately model heat flow at surface, and/or predict 3D temperature distribution for a modelled part of the crust will be key to supporting this industry and possibly others. Here we explain the approach we have taken. The Mount Painter region in South Australia is used as a case study to showcase the developments.

With the increasing pressure on the world’s hydrocarbon resources, alternative sources of energy are being investigated and established. At the forefront is wind power and more specifically offshore wind.

Many developers investing in this new technology have turned to the oil sector for advice on offshore construction, resulting in not only a transfer of technology but an acceptance of alternatives which also embraces the realms of geophysics. As the offshore wind industry evolves, developers are being faced with more stringent requirements to obtain consents, specifically those of an environmental and archaeological nature.

These demands have to be taken into consideration when designing a site investigation survey and innovative methodologies have to be applied. The following presents data from the United Kingdom Round 1 and 2 wind farm sites and provides a brief overview of the European offshore wind industry and how well designed geophysical surveys, utilizing the latest technology is aiding the developers.

Through the mid to late 1980’s, the application of airborne electromagnetics for environmental management was limited to small surveys, and in Australia their primary purpose was aimed at encouraging the wide take-up of the technology by the natural resource management (NRM) community. This technology-led push fed off a growing national awareness of the threat of land salinisation, and AEM was principally marketed as the panacea to this threat. Unfortunately the early promises did not live up to expectations, in part reflecting the limitations of the technology at that time, particularly the inability to map conductivity reliably in the top 5 m of the land surface. Throughout the 90’s, applications continued on a piecemeal basis with small surveys being the norm. In the early 2000’s, Federal Government-led initiatives, particularly the National Action Plan for Salinity and Water Quality, constrained by State representation, prompted a more considered, targeted approach for AEM applications. Projects in South Australia and Queensland revolutionised the way these technologies were used. Helping achieve this were significant developments in AEM system technologies, including the definition of system geometry and calibration, all contributing to the better definition of near surface conductivity. Coupled with advances in in data processing and inversion, the derived information has become much more relevant. Under the NAP some of the largest surveys ever flown in Australia have now been completed. Delivery of relevant products, not just maps of conductivity, which can be incorporated into predictive tools represent the way forward for AEM in environmental management.

PRESENTER PROFILE

Tim Munday is a Principal Research Scientist with CSIRO. He is currently working in the CSIRO-led Water for a Healthy Country Program and is concerned with the application of geophysical technologies in groundwater characterisation.

Email:[email protected]

Along the floodplains of the Murray River in south eastern Australia, where the saline groundwater system is particularly close to the surface, evapotranspiration concentrates salt resulting in extensive salinisation, vegetation dieback or health decline. In many floodplain areas, ecologically important woodland species that inhabit the floodplain are dying from soil water salt concentrations that often exceed those of seawater. To better manage this problem and to protect the ecology and biodiversity on the floodplains along the river, a range of management strategies are being employed. Modelling tools are integral to their development, but key to their effectiveness is the availability of detailed biophysical data. In a study focussed on the Chowilla Floodplain in South Australia, WINDS, a spatial model that examines soil water availability was employed to show the possible effects of manipulating flow regimes and groundwater lowering options across the whole of the floodplain. We examined the value of using biophysical parameters derived from the helicopter electromagnetic (HEM) data, specifically groundwater conductivity and salt storage for specific zones in the saturated, capillary and unsaturated parts of the floodplain, as a basis for making vegetation health assessments or predictions at any particular time. The procedure for deriving this information in 3D is discussed.