Many geophysical models are created without satisfactory uncertainty analysis. Most geophysicists are aware of their model’s limitations, but if the model is passed on to a third party, this information is lost and the risk of misinterpretation arises.This project develops multi-solution inversion techniques to improve inversion and joint inversion modelling of geophysical data in mineral exploration. The main focus is the advancement of the probability and uncertainty analysis of inversion models to increase their reliability. To create solution ensembles, a bootstrapping resampling approach is taken, which produces reduced data sets from a base data set by random omission of data points. Each of these new data sets is run through a conventional inversion process to produce a variety of solutions with minor variations.In the appraisal stage the solution ensemble is statistically analysed to infer model uncertainties, which are then visualised to allow easy communication of the results. The process yields a clear and easy to interpret uncertainty map for the connected model and we demonstrate its effectiveness with several case studies.Furthermore, we are currently investigating swarm intelligence based global search algorithms as a second approach to solution ensemble creation.
AbstractA method of joint inversion of Magnetotelluric, seismic refraction and seismic reflection (JIMRR) is developed especially for typical hydrocarbon or hard-rock mineral exploration. JIMRR includes two parts: jointed seismic refraction and seismic reflection; and its combination with Magnetotelluric (MT) method. The objective of the research is to enhance spatial resolution of the three model parameters: electrical resistivity, seismic velocity and reflector depth. Since horizontal coordinates of reflector are not treated as model parameters in existing travel time inversion algorithm, seismic forward modelling may loss the true reflection point locations at the side edges of reflector with limited extension. We developed the technology of extensible reflector to overcome this problem. JIMRR is completed by employing the cross-gradient function as constraints which enforces the structural similarity between the resistivity and the seismic velocities, so as to reduce velocity-depth ambiguity. The cross-gradient constraints are incorporated into the solution through least squares and Lagrange multiplier method. This method results in integrated symmetric square linear matrix that is solved by bi-conjugate gradient method (BiCG). Two example synthetic models show that our joint inversion can significantly enhance the spatial resolution of inversion; and also the velocity-depth ambiguity caused by reflection travel time inversion can be notably reduced by constraints from shallow lithologies.Keywordsinversionmagnetotelluricsrefraction and reflection seismology. AcknowledgmentsWe would like to appreciate the Deep Exploration Technologies Cooperative Research Centre (DET CRC) and ARC discovery project (DP1093110) for the sponsorship on this project.
A long period magnetotelluric (MT) survey, comprising 39 sites over an area of 270 by 150 km, has identified partial melt within the thinned lithosphere of Quaternary Newer Volcanics Province (NVP) in southeast Australia. MT inversion models reveal several important tectonic features and unravel critical information about the tectonics of the area. The models have imaged a conductive anomaly beneath the NVP at -40-80 km depth, which is consistent with the presence of 1.5-4% partial-melt in the lithosphere. The conductive zone is located within thin juvenile oceanic lithospheric mantle, which was accreted onto thicker Proterozoic continental lithospheric mantle, suggesting that the NVP origin is due to decompression melting within the asthenosphere, promoted by lithospheric thickness variations in conjunction with rapid shear. In addition, inversion modelling shows that there is a conductivity contrast across the Moyston Fault that suggests the transition from Proterozoic continental lithospheric mantle under the Delamerian Orogen to the Phanerozoic lithospheric mantle under the Lachlan Orogen.
Abstract. The closure of the Mongo-Okhotsk ocean has a strong influence on the tectonic evolution of Northeast China. However, the dynamic mechanism in the Mongol-Okhotsk suture area is controversial. This paper intends to obtain the deep structure of beneath Northeast China based on geomagnetic depth sounding, and constrain the subduction of Mongol-Okhotsk Ocean from the perspective of electrical properties. This paper collects and processes the data of geomagnetic stations in China and adjacent areas, and obtains stable C-response data. The staggered grid finite difference method is used for forward modeling, and the finite memory quasi Newton method based on L1-norm is used for inversion. The three-dimensional inversion of geomagnetic data is carried out in spherical coordinates. The intensive model testing stations can obtain high-resolution underground electrical structures. The measured data show that there are obvious high conductivity anomalies in the mantle transition zone in Northeast China, especially in the west of the Great Xing’an Range, showing an area of high conductivity anomalies. Combined with the regional tectonic background of the region, we speculate that the high conductivity anomaly body is related to the southward subduction of the Mongol-Okhotsk Ocean. The Mongol-Okhotsk Ocean subducted under the Eurasian plate at a small angle in the southward direction. With the closing of the Okhotsk Ocean and the extension environment after the termination of subduction, the subducted oceanic crust plate has been faulted and depressed and partially stopped in the mantle transition zone.
Realization of enhanced geothermal systems (EGS) prescribes the need for novel methods to monitor fluid inclusion and connectivity at depth. Magnetotellurics (MT) is a passive electromagnetic method sensitive to electrical conductivity contrasts as a function of depth. The goal here is to use MT as a monitoring tool to estimate areal extent of an EGS reservoir by collecting measurements before, during and after fluids are injected. 3D forward modeling suggests changes in the MT response will be small, on the order of a few percent. Repeatability of the MT response is important and it is shown that most stations are within a few percent. Results from a test case at Paralana, South Australia are presented supporting the idea that MT can be used as a monitoring tool by showing changes due to fluids input into the system.
Electrical anisotropy, defined as the directional dependence of electrical conductivity within a medium, is an important property to consider when interpreting magnetotelluric (MT) data. We propose the use of anisotropic forward modelling to model fluid flow within a geothermal setting.Forward models provide synthetic MT responses for hypothetical structures which are compared with measured data to obtain knowledge about the subsurface geology of a region.Comparisons between synthetic and measured data shows anisotropic fluid volumes are acceptable approximations of fluid injected into the crust. As a result, we support the use of anisotropic forward modelling as a means of modelling fluid motion at depth within a fractured geothermal system.
Summary A number of tools have been developed to help understand the processes of salinisation at work along the Murray River in Southern Australia. Four techniques that have been used to help investigators either directly measure the salt load entering the river, or to image the distribution of conductivities under the river are examined here. They include Run-of-River surveys (ROR), in-stream towed NanoTEM, in-stream towed Resistivity, and Helicopter EM (specifically using the RESOLVE FDHEM system). Each technique has strengths and weaknesses related to its mode of operation and the approach adopted in field data collection. Runof-River samples the water salinity directly and then attempts to estimate river salt load and source location. It provides a direct measure of the salt entering the river but a) only provides salt load information and b) generally only provides information on a kilometre scale. The other three techniques are all geophysical techniques that do not directly inform the investigator about salt loads in the river, but provide information about conductivity distributions in the sediments under the river, which then may be related to salt loads. Each of the geophysical techniques sample the instream environment at three to 20 metre intervals, and provide information from near the river surface to depths of between 10 and 40 metres below the surface. Data may be displayed as depth sections, or as contoured depth slices prepared to examine different levels beneath the river bottom.
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