MT Data Set Research Articles

Magnetotelluric evidence for the deep causes of different eruptive styles of Changbaishan Tianchi and Longgang volcanoes

Longgang Volcano (LGV) and Changbaishan Tianchi Volcano (CTV) share a common magmatic source at mantle depths. However, the two volcanoes have produced completely different types of eruptions. By performing 3D inversion of an MT dataset that completely covers the LGV and CTV, we have obtained high-resolution electrical resistivity images. The results reveal that the two volcanoes have distinct magmatic plumbing systems, and this is likely the reason for their different eruptive styles. Results from 3D modeling do not show a magma chamber in the shallow crust beneath LGV, interpreted as the rapid rise of the magma from the mantle is responsible for producing a series of densely distributed volcanic cones in the LGV field. In contrast, there is a magma chamber in the upper crust beneath the CTV, where the fractional crystallization and mixing of magma has occurred. This magma chamber has facilitated multiple centralized eruptions, and thereby has led to the formation of the large CTV volcanic cone. These results indicate that differences in their crustal structures may have controlled the different eruptive activities of the LGV and CTV in CVS, Northeast China.

The Pannon LitH2Oscope magnetotelluric array in the Pannonian Basin

The Pannonian Basin is one of the best natural laboratories in the world to study the lithospheric response to continental extension and subsequent tectonic inversion. Here we address the topic of lithospheric structure by a combined geochemical and magnetotelluric analysis, which has been carried out in the framework of the Pannon LitH2Oscope project. The main objective was to detect the resistivity distribution over the entire lithosphere by magnetotelluric measurements, considering the lithological resistivity properties and relate the results to the structure and evolution of the Pannonian Basin. The Pannon LitH2Oscope MT array was used to estimate the depth of the Lithosphere-Asthenosphere Boundary (LAB), considering the legacy MT data and compared to previous estimates for the region. Using the MT and geomagnetic response functions, major structural zones of the Pannonian basin, such as the Mid-Hungarian Shear Zone or fault systems like the Makó Trough and the Békés Basin, were also imaged. In addition, we used the apparent resistivity soundings to compare 1D resistivity models computed from geochemistry and obtained from field MT measurements. This comparison provided new constrains for the composition, fluid and melt content variations at the local lithosphere-asthenosphere boundary. The Pannon LitH2Oscope MT dataset and the results presented in this paper provide input for more complex 3D inversions and further investigations of the lithospheric structure in the Carpathian-Pannonian region.

Development of a cross-scale weighted feature fusion network for hot-rolled steel surface defect detection

Surface defects of hot-rolled steel would affect the performance and appearance of the final products. In order to detect steel surface defects efficiently, a cross-scale weighted feature fusion network for identifying defect categories and locating defects is proposed in this work. Combined with Laplace sharpening, the backbone in the YOLOv5s model is used to extract multi-scale defect features from input images. And then, an improved weighted bi-directional feature pyramid network embedded with residual modules is proposed to aggregate multi-scale feature maps for enhancing the robustness of multi-size defect representation. Finally, four prediction branches accompanied with prior bounding boxes by a k-means clustering algorithm are responsible for predicting defects with different sizes. The proposed detection network is verified on the NEU-DET dataset, and experimental results show that the proposed network can achieve 86.8% mAP with the IoU threshold of 0.5, and can efficiently process images at 51 fps with the RGB image size 640 × 640. The Laplace sharpening module, the k_means clustering module and the improved C3-BiFPN module all contribute to the improvement of performance (mAP) of the proposed network by 1.8%, 2.7% and 3.8%, respectively. Our experimental results demonstrate that the proposed framework can effectively detect the surface defects of hot-rolled steel, and has potential to be used for real-time surface defect detection. Meanwhile, the versatility of the proposed network for other types of defect detection is also evaluated on the MT dataset and the DAGM dataset.

Swin-MFINet: Swin transformer based multi-feature integration network for detection of pixel-level surface defects

Automatic surface defect detection is critical for manufacturing industries, such as steel, fabric, and marble industries. This study proposes a Swin transformer-based model called Multi-Feature Integration Network (Swin-MFINet) for pixel-level surface defect detection. The proposed model consists of an encoder, a Swin transformer-based decoder, and Multi-Feature Integration (MFI) modules. In the encoder module of the proposed model, a pre-trained Inception network is used to extract key features from small-size datasets. In the decoder section, global semantic features are obtained from the initial features by using the Swin-transformer block, which is the newest transformer technology of today. In addition, the convolution layer is used in the last step of the decoder, since transformers are limited in acquiring small spatial details such as edges, colors, and textures, which are important in detecting some small defects. In the last module called MFI, feature maps from different decoder stages are combined, and the channel squeeze-spatial excitation block is applied to reveal important features. Finally, a prediction map is obtained by applying a convolution layer and sigmoid activation function to the MFI module output, respectively. The performance of proposed model is analyzed over MT and MVTec datasets containing surface defect images. The proposed model obtained mIoU scores of 81.37%, and 77.07% respectively, for these two datasets These results outperform the state-of-the-art for the surface defect detection problem.

CUMTGAN: An instance-level controllable U-Net GAN for facial makeup transfer

Instance-level makeup transfer refers to transferring a specific makeup style to a particular face without cosmetic, while keeping its facial structure. To solve the challenges such as face structure loss and uncontrollable shade of makeup transfer in the existing makeup transfer methods, in this paper, we propose an instance-level face makeup transfer algorithm with generative adversarial network (CUMTGAN, Controllable U-Net Makeup Transfer GAN). The network uses the results of face semantic segmentation to put on or remove makeup on specific areas such as eyes, lips, while constraining the parts such as image background. It uses the characteristics of the skip connections of the U-Net structure to achieve hierarchical feature fusion. A Superimposed Module is also proposed to provide a controllable shade of makeup for the generated images, making the control of the makeup more arbitrary. Especially, we propose a new quantitative evaluation method to evaluate facial structure and makeup style respectively. To our best knowledge, it is the first time to evaluate generated samples from two aspects. The experimental results on the MT dataset show that the proposed method can generate natural and visual makeup images and makeup removal images, which is superior to the baseline methods in facial structure and makeup style.

Yüzey Hata Tespiti için Sonuç Ağırlıklandırma Tabanlı Resnet Öznitelik Piramit Ağ Mimarisi

Surface defect detection is very important in manufacturing systems to ensure high quality products. Unlike manual inspections under human supervision, automatic surface defect detection is both efficient and highly accurate. In this study, a Result Weighting-based Resnet Feature Pyramid Network (SA-RÖPA) model has been developed for automatic pixel-level surface defect detection. In the first stage of the proposed model, the pre-trained Resnet50 network was used, and feature maps were extracted from the different levels of this network. In the second stage, Feature Pyramid Model was applied to these feature maps in order to hierarchically share important information in defect detection. In the third stage, 4 different error detection results were obtained by using these feature maps. In the last stage, four different results obtained using the developed Result Weighting (SA) module were effectively combined. The proposed SA-ROPA model has been tested with MT, MVTex-Doku, and AITEX datasets, which are widely used in defect detection studies. In experimental studies, the mIoU value obtained for the MT and AITEX datasets using the proposed model was calculated as 79.92%, 76.37%, and 82.72%, respectively. These results have shown that the proposed SA- ROPA model is more successful than other state-of-the-art models.

Electrical Resistivity Structure Around the Atotsugawa Fault, Central Japan, Revealed by a New 2‐D Inversion Method Combining Wideband‐MT and Network‐MT Data Sets

AbstractThe Atotsugawa fault is one of the most active faults in Japan, and the strain accumulation at the fault is considered to be caused by an aseismic shear zone in the fluid‐rich lower crust. To identify the shear zone and investigate the origin of the aqueous fluid in the lower crust, we deployed a Network‐MT survey in addition to a conventional wideband‐MT survey around the fault and performed an inversion combining both the MT data sets. In the inversion, by modifying a conventional inversion algorism, we accurately represented kilometer‐scale dipoles of the Network‐MT measurement to provide constraints on the electrical resistivity structure. In the lower crust under the study area, there are localized conductive anomalies below the Atotsugawa fault, the Ushikubi fault, and the Takayama‐Oppara fault zone. Comparing our electrical resistivity structure with the seismic velocity structure, we interpreted that the lower‐crustal conductors are localized ductile shear zones with highly connected fluid. We considered that the localized ductile shear zones are responsible for the strain accumulation along the respective active faults. In addition, in the mantle wedge above the subducting Philippine Sea slab and its downward extension, a highly conductive portion is detected, which may be attributed to the fluid dehydrated from the Philippine Sea slab and/or the Pacific slab. The existence of the large conductive area supports the suggestion of previous seismic and geochemical studies that the fluid of the lower crust around the Atotsugawa fault originated from subducting slabs.

Improving neural sentence alignment with word translation

Sentence alignment is a basic task in natural language processing which aims to extract high-quality parallel sentences automatically. Motivated by the observation that aligned sentence pairs contain a larger number of aligned words than unaligned ones, we treat word translation as one of the most useful external knowledge. In this paper, we show how to explicitly integrate word translation into neural sentence alignment. Specifically, this paper proposes three cross-lingual encoders to incorporate word translation: 1) Mixed Encoder that learns words and their translation annotation vectors over sequences where words and their translations are mixed alternatively; 2) Factored Encoder that views word translations as features and encodes words and their translations by concatenating their embeddings; and 3) Gated Encoder that uses gate mechanism to selectively control the amount of word translations moving forward. Experimentation on NIST MT and Opensubtitles Chinese-English datasets on both non-monotonicity and monotonicity scenarios demonstrates that all the proposed encoders significantly improve sentence alignment performance.

Structure‐Coupled 3‐D Imaging of Magnetotelluric and Wide‐Angle Seismic Reflection/Refraction Data With Interfaces

AbstractMagnetotelluric (MT) and wide‐angle seismic reflection/refraction surveys play a fundamental role in understanding the crustal rheology and lithospheric structure of the Earth. In recent years, the integration of the two methods in order to improve the robustness of the inversion has started to gain attention. We present a new approach for joint 3‐D inversion of MT and wide‐angle seismic reflection/refraction data to accurately determine crustal structures and Moho depth. Based on H‐κ stacking of teleseismic receiver functions, we estimate an initial reference Moho. This is used as input for the subsequent MT/seismic joint inversion, where the Moho interface is updated and crustal structures are added to the model. During the joint inversion process, structural similarity is facilitated through the cross‐gradient constraint. Synthetic model tests show an improvement of the inversion results over separate inversions. In particular, the tests based on two geologically realistic models demonstrate that the crustal structure and even the trade‐off between velocity and Moho interface can be sufficiently resolved by combined MT and seismic data sets when using the estimates from analysis of receiver functions. These results show that the new method can provide useful constraints on crustal structures including their geophysical properties and discontinuities.

Reservoir characterization and basement estimates in the Papuan Fold belt (Papua New Guinea-PNG), from reanalysis of the PNG MT data set

The PNG MT data set covering a section of the Papuan Fold Belt (PFB) in Papua New Guinea (PNG), which is known for its extensive hydrocarbon resources, re-analyzed using advanced dimensionality technique and inversion algorithms. Although the phase tensor analysis retrieved a dominant 2D conductivity direction matching the regional tectonic trend, a mild 3D behavior with some local strong 3D effect is apparent. The 3D and 2D inversions carried out yielded resistivity features related to the broad stratigraphic column of the area, but with variations in the depth of occurrence and thicknesses of resistivity structures between the inversion models. The preferred 3D model shows an about 1 km thick resistive Miocene Darai limestone cover, thickening towards northeast of the profile, and supports a thick-skinned thrust model. The 3D resistivity section shows an additional differentiation within the underlying Mesozoic column, a highly conductive (∼1 Ωm) and moderately conductive (10–40 Ωm) layer, sandwiched between the Darai formation and crystalline basement. The upper highly conductive layer can be related to the Cretaceous Ieru shale formation, which acts as the regional cap rock in the PFB, and the below moderately conductive layer represents the stack of Mesozoic strata that possibly comprise of the Neocomian Toro sandstone reservoir rocks and underlying Jurassic source rock formations. Nevertheless, the resolution tests do not fully support the demarcation between the Ieru formation and underlying Mesozoics containing the reservoir and source formations, and demand additional constraints for confirmation.

4D inversion of time-lapse magnetotelluric data sets for monitoring geothermal reservoir

The productivity of a geothermal reservoir, which is a function of the pore-space and fluid-flow path of the reservoir, varies since the properties of the reservoir changes with geothermal reservoir production. Because the variation in the reservoir properties causes changes in electrical resistivity, time-lapse (TL) three-dimensional (3D) magnetotelluric (MT) methods can be applied to monitor the productivity variation of a geothermal reservoir thanks to not only its sensitivity to the electrical resistivity but also its deep depth of survey penetration. For an accurate interpretation of TL MT-data sets, a four-dimensional (4D) MT inversion algorithm has been developed to simultaneously invert all vintage data considering time-coupling between vintages. However, the changes in electrical resistivity of deep geothermal reservoirs are usually small generating minimum variation in TL MT responses. Maximizing the sensitivity of inversion to the changes in resistivity is critical in the success of 4D MT inversion. Thus, we further developed a focused 4D MT inversion method by considering not only the location of a reservoir but also the distribution of newly-generated fractures during the production. For the evaluation of the 4D MT algorithm, we tested our 4D inversion algorithms using synthetic TL MT-data sets.

Quantitative comparison of two 3-D resistivity models of the Montelago geothermal prospect

A combined TEM-MT survey was carried out in the Montelago geothermal prospect, situated on Mindoro Island, the Philippines, with the aim to obtain the dimensions and depth of the geothermal reservoir as well as to formulate the prospects' conceptual model. The acquired MT data are static shift corrected using the TEM measurements. Two different 3D inversion codes are used to create subsurface resistivity models of the corrected MT data set. The similarities and differences between the two resistivity models are quantitatively assessed using a set of structural metrics. Both resistivity models can be generalized by a three-layered model. The model consists of a thin heterogeneous, conductive layer overlying a thick resistive layer, while the basement has a decreased resistivity. Although this is a common characteristic resistivity response for the alteration mineralogy of a volcanic geothermal system, the temperatures at depth are lower than would be expected when interpreting the modelled resistivity model accordingly. Since the last volcanic activity in the area was about one million years ago, it is anticipated that the resolved resistivity structure is a remnant of a hydrothermal system associated with a volcanic heat source. This model interpretation is validated by the alteration minerals present in the exploration wells, where high temperature minerals such as epidote are present at depths with a lower temperature than epidote's initial formation temperature. This generalized description of the resistivity model is confirmed by both resistivity models. In this paper the two inversion models are not only compared by assessing the inversion models, but also by reviewing a set of gradient based structural metrics. An attempt is made to improve the interpretation of the conceptual model by analyzing these structural metrics. Based on these analyses it is concluded that both inversions resolve similar resistivity structures and that the location of the two slim holes drilled are well chosen.

The Application of S‐transform Spectrum Decomposition Technique in Extraction of Weak Seismic Signals

AbstractIn processing of deep seismic reflection data, when the frequency band difference between the weak useful signal and noise both from the deep subsurface is very small and hard to distinguish, the usefulness of traditional method of filtering will be limited. To solve this problem, we apply different spectral decomposition methods respectively to experimental data and real data and compare the results from these methods. Our purpose is to find an effective way to protect weak signals during processing deep seismic reflection data.The spectral decomposition method is based on the discrete Fourier transform, which uses the signal frequency‐amplitude spectrum and other information to generate a high‐resolution seismic image. Typically, it is used to identify the lateral distribution of medium properties, solve spectrum changes within complex media and local phase instability and other issues, such as locating faults and small‐scale complex fractures. S‐transform as a new time‐frequency analysis method, which is a generalization of STFT developed by Stockwell in 1994, has the ability to automatically adjust the resolution. This method has been widely applied to exploration seismic, MT and other geophysical datasets in recent years. It has become one of the effective methods in noise suppressing during geophysical data processing. Comparing with conventional oil reflection seismic data, in order to probe deep structure, deep seismic reflection employs a large quantity of explosives, long observing systems, leading to a phenomenon that valid signals from the deep and noise are mixed together both in time domain and frequency domain. Considering these characteristics of deep reflection data, this paper combines spectral decomposition with S transform technology. First we design a simple pulse function experimental data to confirm the validity of the S transform method. Then we illustrate the effectiveness of spectral decomposition which is influenced by the choice of frequency analysis methods, especially the transform window function which determines the resolving power of the method. On this basis, S transform spectrum decomposition is applied to a single channel of deep reflection seismic data and the stacked profile, then the application results of traditional transform spectral decomposition and S transform spectral decomposition are compared.Comparison of single channel data shows that compared with traditional spectral decomposition, the S transform spectral decomposition method is able to automatically adjust the resolution, accurately calibrate frequency component of weak signals at different times in deep reflection seismic data. Application to stacked profile data shows that the results obtained by the S transform spectral decomposition and those from other spectral decomposition method are largely consistent, while the results of S transform spectral decomposition clearly depict the characteristics of low‐frequency details which are superimposed by noise in original stacked profile. At the same time, it improves the resolution and enhances the phase axis continuity on the stacked profile. Comparison also clearly indicates that the phase axis on the resultant profile obtained by Gabor transform spectral decomposition is more broken, which is caused by fixed‐length window function used by Gabor transform decomposition, the length of the window function parameters can only be selected before the start of processing and is set to a certain value, while the S transform spectral decomposition method chooses the variable length of the window function according to signal change. It can automatically adjust the frequency characteristics of the signal by the local window length to better characterize the details of each frequency range. Such an effect is very obvious in deep reflection seismic imaging.Our results show that the key of the spectral decomposition technique is to select the transform window function. The S transform spectral decomposition technology used in real deep reflection seismic data processing can effectively protect the weak low‐frequency signals. It can effectively improve the signal to noise ratio and the resolution of weak reflection signals from the deep subsurface, while depicting the characteristics of low‐frequency details on the stacked section and ultimately obtaining better imaging results.

수직 횡등방성 전기적 이방성을 고려한 자기지전류탐사 모델링

Magnetotelluric (MT) survey investigates electrical structure of subsurface by measuring natural electromagnetic fields on the earth surface. For the accurate interpretation of MT data, the precise three-dimensional (3-D) modeling algorithm is prerequisite. Since MT responses are affected by electrical anisotropy of medium, the modeling algorithm has to incorporate the electrical anisotropy especially when analyzing time-lapse MT data sets, for monitoring engineered geothermal system (EGS) reservoir, because changes in different-vintage MT-data sets are small. This study developed a MT modeling algorithm for the simulation MT responses in the presence of electrical anisotropy by improving a pre-existing staggered-grid finite-difference MT modeling algorithm. After verifying the developed algorithm, we analyzed the effect of vertical transversely isotropic (VTI) anisotropy on MT responses. In addition, we are planning to extend the applicability of the developed algorithm which can simulate not only the horizontal transversely isotropic (HTI) anisotropy, but also the tiled transversely isotropic (TTI) anisotropy.

Generating targeted paraphrases for improved translation

Today's Statistical Machine Translation (SMT) systems require high-quality human translations for parameter tuning, in addition to large bitexts for learning the translation units. This parameter tuning usually involves generating translations at different points in the parameter space and obtaining feedback against human-authored reference translations as to how good the translations. This feedback then dictates what point in the parameter space should be explored next. To measure this feedback, it is generally considered wise to have multiple (usually 4) reference translations to avoid unfair penalization of translation hypotheses which could easily happen given the large number of ways in which a sentence can be translated from one language to another. However, this reliance on multiple reference translations creates a problem since they are labor intensive and expensive to obtain. Therefore, most current MT datasets only contain a single reference. This leads to the problem of reference sparsity. In our previously published research, we had proposed the first paraphrase-based solution to this problem and evaluated its effect on Chinese-English translation. In this article, we first present extended results for that solution on additional source languages. More importantly, we present a novel way to generate “targeted” paraphrases that yields substantially larger gains (up to 2.7 BLEU points) in translation quality when compared to our previous solution (up to 1.6 BLEU points). In addition, we further validate these improvements by supplementing with human preference judgments obtained via Amazon Mechanical Turk.

Depth model building by constrained magnetotelluric inversion

In this paper we describe an approach aimed at integrating seismic and magnetotelluric data in a complex geological setting, characterised by thrust structures, in Southern Apennine, Southern Italy. Seismic data were collected by the «Global Offset» technique that is designed to record hight fold data in a wide range of offsets, without losing the benefit of near vertical reflection seismic. First arrivals picked from short to long offsets and the main reflections were inverted in order to produce a tomographic velocity-interface model. It was converted into a resistivity section applying an empirical relationship, obtained by well logs, between resistivity and velocity. That section was used as a reliable reference model for 2D inversion of magnetotelluric data collected along a parallel section very close to the seismic profile. The process was iterative and interactive and was aimed at producing consistent velocity and resistivity sections, honouring seismic and MT data set. The final MT model fits very well the observed apparent resistivity and phase, reproduces the main geological trends and its constrained by a well drilled close to the line.

Detection of sub-basaltic sediments by a multi-parametric joint inversion approach

In many parts of the world sedimentary horizons with potential for hydrocarbon are located below flood basalt provinces. However, the presence of high velocity basaltic overburden makes delineation of sediments difficult due to the low velocity layer problem. Electrical and electromagnetic methods have been used in such scenarios because of the good electrical conductivity contrast between basalts and underlying sediments. However, mapping of the target sediments becomes difficult when the layer is thin as the data errors due to inherent noise lead to equivalent solutions. To tackle such difficult situations, a joint inversion scheme incorporating seismic reflection and refraction, magnetotelluric and deep electrical resistivity datasets is presented. Efficacy of the scheme is tested for a model comprising a thin sedimentary layer sandwiched between a thick basalt cover and a granitic basement. The results indicate that the parameters of the target sedimentary layer are either poorly resolved or equivalent solutions are obtained by the inversion of individual datasets. Joint inversions of seismic reflection (RFLS) and refraction (RFRS), or DC and MT dataset pairs provide improved results and the range of equivalent solutions is narrowed down. Combination of any three of the above datasets leads to further narrowing of this range and improvements in mean model estimates. Joint inversion incorporating all the datasets is found to yield good estimates of the structure. Resolution analysis is carried out to appraise estimates of various model parameters obtained by jointly inverting different combinations of datasets.

The Relationship Between the Magnetotelluric Tensor Invariants And The Phase Tensor Of Caldwell, Bibby, And Brown

We examine the relationship between the seven invariants of the complex MT tensor, which we previously proposed as a vehicle for testing the dimensionality of the regional conductivity structure prior to an analysis of MT data, and the three invariants of the real 'phase tensor', recently introduced as an innovative aid in the treatment of MT data. It is found that the relevant invariants, and the necessary conditions on them for galvanically distorted data to be consistent with ID, 2D, or 3D regional structures, agree in almost every detail for the two approaches. The new method does lead, however, to an improved normalisation of the eighth (dependent) invariant previously introduced. It is shown that the phase tensor can be expressed as a sum of three simple matrices, clearly associated with ID, 2D and 3D regional conductivity structures respectively. It is further shown that it can be depicted graphically as a single Mohr circle that retains the principal properties of the separate real and imaginary Mohr circles associated with the MT tensor. The simplicity and elegance of the phase tensor method is achieved by dispensing with the capability of distinguishing between galvanically distorted and undistorted data in ID and 2D regions, a distinction that is ultimately unimportant and unnecessary with real data. The paper concludes with a simple illustrative example of the theory applied to a real MT dataset from NE Australia. A shallow ID regional conductivity structure associated with a sedimentary basin is revealed, and a 2D anomaly with calculated strike angle is also identified.

Electromagnetic imaging of Variscan crustal structures in SW Iberia: the role of interconnected graphite

The western part of the Iberian Peninsula (Iberian Massif) is the best exposed fragment of the Variscan orogen in Europe. Its southern half was generated by an oblique collision between three continental terranes belonging to the margins of Laurassia (Avalonia) – the South Portuguese Zone (SPZ) – and Gondwana – the Ossa Morena Zone (OMZ) and the Central Iberian Zone (CIZ). The boundaries between them are considered to be suture zones. A 200 km long magnetotelluric profile across the three Variscan terranes was done in a NNE direction, approximately perpendicular to the main tectonic features. The results of two-dimensional inversion of the MT dataset reveal high-conductivity zones coinciding with the transitions SPZ/OMZ and OMZ/CIZ. These conductive bodies related to the sutures at depth were interpreted as graphite enrichments along shear planes formed due to the overall transpressive regime. A high-conductivity layer extending along the whole OMZ was found at a depth of 15–25 km, the top of which spatially correlates with a broad reflector detected by a recently acquired deep seismic reflection profile. The high conductivity was interpreted as caused by the Precambrian Serie Negra graphite-rich rocks. Carbon and oxygen X-ray mapping with electron microprobe on polished sections of Serie Negra samples from OMZ revealed the presence of interconnected graphite, which supports the hypothesis that graphite is determinant for the high conductivity. Two graphite types, which help to record the geological evolution, were identified: graphite accumulations in the schistosity surfaces produced by folding and metamorphism, and metallic films of graphite developed along late faults. The conductive layer shows blobs of higher conductivity suggesting macro-anisotropy. Additional mylonitisation and shearing produced by thrusting at depth can be the origin of these zones of enhanced conductivity, given that the detachment level is located within the Serie Negra. Several high-resistivity features were found in the upper crust, related to Devonian and Carboniferous successions and probably to some unexposed plutons in the SPZ and the Palaeozoic series of OMZ plus some granitic intrusions. In the CIZ, a high-resistivity zone extending to the whole crust is correlated with extensive late Variscan granite intrusions.

2-D Interpretation of Minamikayabe MT Data Set by the Controlled Random Search Technique

Within the MT-DIW3 project of the comparison of various MT interpretation techniques, the controlled random search procedure was applied to the 2-D interpretation of the MT data from the Minamikayabe MT polygon in Japan. Three NE-SW profiles together with one perpendicular profile were 2-D modelled, simultaneously for both polarizations of the MT field. Although the 2-D approximation seems to be rather far from the real resistivity conditions, we could obtain relatively consistent interpretation results particularly for data within the short period range, up to 1 s. Better fit was achieved for apparent resistivities than for phases. For all NE-SW profiles, a near-surface conductive body is indicated below the central part of the polygon. At both sides of this body two deeper conductive zones are obvious. As for the perpendicular profile kb*s06, a large conductive zone is required below the SE margin of the profile.