The Central Asian Orogenic Belt (CAOB) is a typical accretionary orogen divided into numerous lithostratigraphic terranes. In theory, these terranes should be characterized by contrasting magnetic and gravity signatures owing to their dissimilar petrophysical properties. To test this hypothesis, the extent of tectonostratigraphic terranes in southern Mongolia was compared with the potential field data. The analysis reveals that the terrane boundaries are not systematically defined by strong gravity and magnetic gradients. The correlation of the magnetic signal with the geology reveals that the magnetic highs coincide with Late Carboniferous to Early Permian volcanic-plutonic belts. The matched filtering shows a good continuity of signal along the boundaries of these high magnetic anomalies toward the deeper crustal levels which may indicate the presence of deeply rooted tectonomagmatic zones. The axes of high-density bodies in the western and central parts of the study area are characterized by periodic alternations of NW-SE trending gravity anomalies corresponding to up to 20 km wide cleavage fronts of Permo-Triassic age. The matched filtering analysis shows good continuity of signal to the depth of these gravity highs which may indicate presence of deeply rooted high-strain zones. The magnetic signal is interpreted to be as the result of a giant Permo-Triassic magmatic event associated with lithosphere-scale deformation, whereas the gravity pattern is related to the postaccretionary shortening of the CAOB between the North China and Siberia cratons.

Uranium exploration in the Athabasca Basin, Canada, relies heavily on ground-based transient electromagnetic (TEM) surveys to target thin, steeply dipping graphitic conductors that are often closely related to the uranium ore deposits. The interpretation of TEM data is important in identifying the locations and trends of conductors in order to guide subsequent drilling campaigns. We present a trial-and-error modeling approach and its application to the interpretation of a data set acquired at Close Lake in the Athabasca Basin. The modeling process has two key tasks: building geo-electric models and computing their TEM responses. The modeling process is repeated with the geo-electric model being iteratively refined based on the match between three-component calculated and measured data from early to late times. To create geo-electric models, we first build a realistic geological model and discretize it using an unstructured tetrahedral mesh, with each mesh cell populated with appropriate resistivities. To calculate the TEM responses of the geo-electric model, we use a 3D finite-volume time-domain (FVTD) algorithm. We construct our initial model based on existing geologic information and drilling data. We show that this modeling process is flexible and can easily handle thin, steeply dipping conductive graphitic fault models with variable resistivities in the fault and background, and with topography. Our interpretation of the Close Lake data matches well with the trend and location of the main conductor as revealed by drilling data, and also confirms the existence of a smaller conductor which only caused noticeable anomalous responses in early-time horizontal-component data. The smaller conductor was suggested by previous electromagnetic data but was missed in a recent interpretation based on the modeling of only late-time vertical component data with plate-based approximate modeling methods.

2D electrical Imaging of a brine filled cavity A bstractWithin the domain of mining problems linked to salt exploitation and abandoned cavities, BRGM has carried out a geophysical study for GEODERIS in the Art-sur-Meurthe brine field which belongs to NOVACARB company. The objective is to test the potential of 2D electrical imaging so as to focus on salt brine filled cavities. The LR45 cavity, having a circular shape with a 90m diameter and a 7m thickness, is situated at a depth of 115m. Preliminary trial runs have given validity to the concept. Resistivity measurements have shed light on a low resistivity structure, of which the characteristics coincide with the established geometry of the cavity. IP measurements detected polarising levels whose origin remains to be determined.

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Electromagnetic (EM) methods are important geophysical tools for mineral exploration. Forward and inverse computer modeling are commonly used to interpret EM data. Real-life geology can be complex, and our computer modeling tools need to faithfully represent subsurface features to achieve accurate data interpretation. Traditional rectilinear meshes are less flexible and have difficulty conforming to the complex geometries of realistic geologic models, resulting in large numbers of mesh cells. In contrast, unstructured grids can represent complex geologic structures efficiently and accurately. However, building realistic geologic models and discretizing these models with unstructured grids suitable for EM modeling can be difficult and requires significant effort and specialized computer software tools. Therefore, it is important to develop workflows that can be used to facilitate model building and mesh generation. We have developed a procedure that can be used to build arbitrarily complex geologic models with topography using unstructured grids and a finite-volume time-domain code to calculate EM responses. We present an example of a trial-and-error modeling approach applied to a real data set collected at a uranium exploration project in the Athabasca Basin in Canada. The uranium mineralization is closely related to graphitic fault conductors in the basement. The deep burial depth and small thickness of the graphitic fault conductors demand accurate data interpretation results to guide subsequent drill testing. Our trial-and-error modeling approach builds initial realistic geologic models based on known geology and downhole data and creates initial geoelectrical models based on physical property measurements. Then, the initial model is iteratively refined based on the match between modeled and real data. We show that the modeling method can obtain 3D geoelectrical models that conform to known geology while achieving a good match between modeled and real data. The method can also provide guidance of where future drill holes should be directed.