The upper crustal 3-D resistivity structure of the Kristineberg area, Skellefte district, northern Sweden revealed by magnetotelluric data

Hübert, Juliane; Juanatey, María de los Ángeles García; Malehmir, Alireza; Tryggvason, Ari; Pedersen, Laust B.

doi:10.1093/gji/ggs044

Cited by 18 publications

(18 citation statements)

References 33 publications

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“…Hence, models = * + △ that fulfil the condition are added to the equivalent model domain, where Q * d is a threshold value for data misfit deemed acceptable. Compared to other uncertainty analysis tools, this tool may be the most economical tool as only several forward modelling computations are needed to evaluate the model variations (Nolasco et al 1998;Hübert et al 2009;Hübert et al 2013). More advanced versions of this approach account for the fact that model parameters outside a given region of interest need to be adjusted to generate forward responses with sufficiently low misfit.…”

Section: Deterministic Methodsmentioning

confidence: 99%

Uncertainty and Resolution Analysis of 2D and 3D Inversion Models Computed from Geophysical Electromagnetic Data

Ren

Kalscheuer

2019

Surv Geophys

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A meaningful solution to an inversion problem should be composed of the preferred inversion model and its uncertainty and resolution estimates. The model uncertainty estimate describes an equivalent model domain in which each model generates responses which fit the observed data to within a threshold value. The model resolution matrix measures to what extent the unknown true solution maps into the preferred solution. However, most current geophysical electromagnetic (also gravity, magnetic and seismic) inversion studies only offer the preferred inversion model and ignore model uncertainty and resolution estimates, which makes the reliability of the preferred inversion model questionable. This may be caused by the fact that the computation and analysis of an inversion model depend on multiple factors, such as the misfit or objective function, the accuracy of the forward solvers, data coverage and noise, values of trade-off parameters, the initial model, the reference model and the model constraints. Depending on the particular method selected, large computational costs ensue. In this review, we first try to cover linearised model analysis tools such as the sensitivity matrix, the model resolution matrix and the model covariance matrix also providing a partially nonlinear description of the equivalent model domain based on pseudo-hyperellipsoids. Linearised model analysis tools can offer quantitative measures. In particular, the model resolution and covariance matrices measure how far the preferred inversion model is from the true model and how uncertainty in the measurements maps into model uncertainty. We also cover nonlinear model analysis tools including changes to the preferred inversion model (nonlinear sensitivity tests), modifications of the data set (using bootstrap re-sampling and generalised cross-validation), modifications of data uncertainty, variations of model constraints (including changes to the trade-off parameter, reference model and matrix regularisation operator), the edgehog method, mostsquares inversion and global searching algorithms. These nonlinear model analysis tools try to explore larger parts of the model domain than linearised model analysis and, hence, may assemble a more comprehensive equivalent model domain. Then, to overcome the bottleneck of computational cost in model analysis, we present several practical algorithms to accelerate the computation. Here, we emphasise linearised model analysis, as efficient computation of nonlinear model uncertainty and resolution estimates is mainly determined by fast forward and inversion solvers. In the last part of our review, we present applications of model analysis to models computed from individual and joint inversions of electromagnetic data; we also describe optimal survey design and inversion grid design as important Extended author information available on the last page of the article applications of model analysis. The currently available model uncertainty and resolution analyses are mainly for 1D and 2D problems due to the limitation...

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Section: Deterministic Methodsmentioning

confidence: 99%

Uncertainty and Resolution Analysis of 2D and 3D Inversion Models Computed from Geophysical Electromagnetic Data

Ren

Kalscheuer

2019

Surv Geophys

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“…It was first described in the regional MT study along the FENNOLORA profile (Rasmussen et al, 1987), as a crustal conductive anomaly below the Skellefte District, dipping to the northeast and spanning 5-32-km depth over a span of 100 km. This anomaly was later confirmed by local MT studies in the Kristineberg area (Hübert et al, 2009;Hübert et al, 2012;García Juanatey et al, 2012). It is worth noting that Hübert et al (2009) found the top of the deep conductor at 11 km depth in the northern side of Profile 5 in the Kristineberg area , coinciding almost seamlessly with our MT model (see Figure 13).…”

Section: Deep Conductormentioning

confidence: 69%

“…Geologic map of western Skellefte District showing the main lithological units, closed and current mines, and acquired seismic surveys and MT stations. Lines and sites in red are part of the pilot study Hübert et al, 2009), in blue and green is the follow-up within the VINNOVA project García Juanatey et al, 2012;Hübert et al, 2012), and in orange is the extension funded by SGU and treated in this paper. SG: Skellefte Group, VG: Vargfors Group, TF: Tjamstan Formation.…”

Section: Geologic Settingmentioning

confidence: 99%

“…Given the success of this study, the project VINNOVA 4D modeling of the Skellefte District was launched, and more localized seismic and MT data were acquired in the area García Juanatey et al, 2012;Hübert et al, 2012). In the framework of this project, the Geological Survey of Sweden (SGU) funded the extension of the area of investigation to the north, towards the Adak mineralizations.…”

Section: Introductionmentioning

confidence: 99%

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MT and reflection seismics in northwestern Skellefte Ore District, Sweden

et al. 2013

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A seismic reflection and MT survey was carried out along a 27-km long transect in northwestern Skellefte District, as part of a bigger 3D modeling project. The main motivation for the data acquisition is to elucidate the geologic relationship between the known mineralizations in the Adak mining camp to the north and in the well studied Kristineberg area south of the transect. The seismic reflection data were acquired with a VIBSIST system, and show reflectivity down to 3 s. Apart from the conventional processing for crystalline environments, the seismic data was also subject to an azimuthal binning procedure and crossdip analysis, allowing the orientation of planar reflectors in 3D. Regarding the MT data, it is primarily of good quality along the 17 installed sites. The inversion of the determinant of the impedance tensor yielded a stable 2D resistivity model, dominated by resistors corresponding to the postorogenic intrusions along the transect. Adding the location of the analyzed seismic reflectors in the MT inversion rendered an integrated model that facilitated a preliminary joint interpretation of the data sets. Overall, the results are in good agreement with surface observations and reveal a crude configuration of the geologic units below the transect. The most prominent outcomes are the lateral and depth extent of the large postorogenic intrusions in the area reaching to 5-or 6-km depth, the dimensions of the nearly vertical Brännäs gabbro extending to 6-km depth, and the presence of enhanced conductivities along the transect at about 10 km depth. The latter is probably related to the deep conductor previously identified in the district.

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“…Where AMT signal levels are low, e.g., in the dead band at $ 800-3000 Hz (Garcia and Jones 2002), the controlled-source audiomagnetotelluric method (CSAMT, f = 1-10000 Hz, Zonge and Hughes 1991) is routinely applied. Consequently, MT methods have a long-standing history in the investigation of mineral deposits (Strangway et al 1973;Meju 2002;Jones 2017) with field cases reported from, for instance, copper, gold, lead, silver and zinc deposits (Kellett et al 1993;Garcia Juanatey et al 2013a, b;Hübert et al 2013;Hu et al 2013), copper, gold and iron deposits (Heinson et al 2006), copper and iron deposits (Chouteau et al 1997;Jones and Garcia 2003), copper, iron and zinc deposits (Basokur et al 1997), copper, lead and zinc deposits (Sasaki et al 1992;Bastani et al 2009), copper and nickel deposits (Lakanen 1986;Livelybrooks et al 1996;Jones et al 1997;Balch et al 1998;Stevens and McNeice 1998;Zhang et al 1998;Watts and Balch 2000;King 2007;Xiao et al 2011;Varentsov et al 2013; Le et al 2016a), copper, silver and zinc deposits (Gordon 2007), gold deposits (Jones et al 1997;Liu et al 2006;Howe et al 2014;Takam Takougang et al 2015;Hübert et al 2016;Le et al 2016b), and uranium deposits (Leppin and Goldak 2005;Tuncer et al 2006;Farquharson and Craven 2009;Goldak et al 2010;…”

Section: Mt Methods In Exploring Deep Ore Depositsmentioning

confidence: 99%

Two-Dimensional Magnetotelluric Modelling of Ore Deposits: Improvements in Model Constraints by Inclusion of Borehole Measurements

Kalscheuer

Juhojuntti

Vaittinen³

2017

Surv Geophys

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A combination of magnetotelluric (MT) measurements on the surface and in boreholes (without metal casing) can be expected to enhance resolution and reduce the ambiguity in models of electrical resistivity derived from MT surface measurements alone. In order to quantify potential improvement in inversion models and to aid design of electromagnetic (EM) borehole sensors, we considered two synthetic 2D models containing ore bodies down to 3000 m depth (the first with two dipping conductors in resistive crystalline host rock and the second with three mineralisation zones in a sedimentary succession exhibiting only moderate resistivity contrasts). We computed 2D inversion models from the forward responses based on combinations of surface impedance measurements and borehole measurements such as (1) skin-effect transfer functions relating horizontal magnetic fields at depth to those on the surface, (2) vertical magnetic transfer functions relating vertical magnetic fields at depth to horizontal magnetic fields on the surface and (3) vertical electric transfer functions relating vertical electric fields at depth to horizontal magnetic fields on the surface. Whereas skin-effect transfer functions are sensitive to the resistivity of the background medium and 2D anomalies, the vertical magnetic and electric field transfer functions have the disadvantage that they are comparatively insensitive to the resistivity of the layered background medium. This insensitivity introduces convergence problems in the inversion of data from structures with strong 2D resistivity contrasts. Hence, we adjusted the inversion approach to a three-step procedure, where (1) (2) this inversion model from surface impedances is used as the initial model for a joint inversion of surface impedances and skin-effect transfer functions and (3) the joint inversion model derived from the surface impedances and skin-effect transfer functions is used as the initial model for the inversion of the surface impedances, skin-effect transfer functions and vertical magnetic and electric transfer functions. For both synthetic examples, the inversion models resulting from surface and borehole measurements have higher similarity to the true models than models computed exclusively from surface measurements. However, the most prominent improvements were obtained for the first example, in which a deep small-sized ore body is more easily distinguished from a shallow main ore body penetrated by a borehole and the extent of the shadow zone (a conductive artefact) underneath the main conductor is strongly reduced. Formal model error and resolution analysis demonstrated that predominantly the skin-effect transfer functions improve model resolution at depth below the sensors and at distance of $ 300-1000 m laterally off a borehole, whereas the vertical electric and magnetic transfer functions improve resolution along the borehole and in its immediate vicinity. Furthermore, we studied the signal levels at depth and provided specifications of borehole magnetic and elect...

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The upper crustal 3-D resistivity structure of the Kristineberg area, Skellefte district, northern Sweden revealed by magnetotelluric data

Cited by 18 publications

References 33 publications

Uncertainty and Resolution Analysis of 2D and 3D Inversion Models Computed from Geophysical Electromagnetic Data

Uncertainty and Resolution Analysis of 2D and 3D Inversion Models Computed from Geophysical Electromagnetic Data

MT and reflection seismics in northwestern Skellefte Ore District, Sweden

Two-Dimensional Magnetotelluric Modelling of Ore Deposits: Improvements in Model Constraints by Inclusion of Borehole Measurements

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