1,720,959 research outputs found
Joint Inversion of DC Resistivity and Magnetic Data, Constrained by Cross Gradients, Compactness and Depth Weighting
No full textIn this paper we perform a 2-D joint inversion of DC resistivity and magnetic data, constrained by cross-gradients. Inspired by methods developed for potential fields, we introduce into both the separate and joint inversion algorithms also compactness and depth weighting functions, under the form of a model weighting-function. These constraints, usually not considered for DC resistivity inversion, reveal to be decisive for its joint inversion with magnetic data. A linear approximated forward problem of the resistivity is used for the joint inversion so that both the resistivity and magnetic problems are expressed as a linear integral equation under the form of a Fredholm integral of 1st kind. To examine the feasibility of the joint inversion algorithm, we first test the method with two synthetic cases: a thick dyke in a two-layered medium and a cavity located above a conductor. A third synthetic case involves a multisource model. The results are encouraging, revealing that the cross-gradient constraint is an effective tool to improve the separate inversions of DC resistivity and magnetic data. The joint inversion algorithm is also applied to data in the archeological area of the old Pompeii city, nearby Naples. Comparing the results of joint and separate inversions, we obtain a significant improvement in the interpretation of both kind of data in terms of buried walls of an ancient roman villa. In all the studied cases, the cross-gradient constraint appears to be a key-diagnostic tool to assess whether actual coherence is gained among DC resistivity and magnetic susceptibility models
The role of model weighting functions in the gravity and DC resistivity inversion
Full text linkThis paper aims at analyzing the inversion with the mostly used model weighting functions, for both gravity and DC resistivity data. We show that the model weighting function built with depth weighting and compacting factor, formerly formulated for the gravity and magnetics problems, can be useful also for DC resistivity data. We provide a number of synthetic cases to discuss the pros and cons of each model-weighting function. For gravity and DC resistivity data, the comparison was made using the depth weighting with different exponents, the compactness and, for the DC resistivity nonlinear problem, the roughness matrix under the L1- and L2-norm Constrained Optimization. As for the depth weighting, the value of the β exponent is decisive for the gravity problem, ranging from very low values for interfaces to 1 for compact sources. DC resistivity data inversion is less sensitive to β but the above indicated choice leads to a faster convergence. Similarly, the role of compactness is decisive for reconstructing a compact source from gravity, while for DC resistivity it is especially useful to warrant an even faster convergence. Using the roughness matrix tends instead to provide a decrease in resolution at depth. We obtained interesting results for different types of DC resistivity arrays: the weighting function built with depth-weighting and compactness yields a more coherent source reconstruction than that using the roughness matrix. We also analyze two different real DC resistivity cases, which confirm, again, the usefulness of the depth weighting and compactness to model the deep resistive sources
DC resistivity inversion constrained by magnetic method through sequential inversion
No full textIn the inversion of geophysical data, an attempt is made to obtain a model with the best fit on the observed data. Unfortunately, the results are usually accompanied by non-uniqueness and ambiguity. These inversion problems can be reduced by inverting different geophysical datasets. Sequential inversion is one of the most common ways to integrate two or more geophysical datasets, to obtain a model that is compatible with all geophysical data, thus reducing the amount of ambiguity. This paper presents separate inversions of DC resistivity and magnetic data and sequential inversion of DC resistivity constrained by magnetic data. Here, the inverse model of magnetic data is considered the initial model for the sequential inversion of DC resistivity data. At first, the algorithm is applied to a synthetic model composed of four conductive and magnetized bodies, and the results show notable improvement for the resistivity model after sequential inversion, compared with the separate resistivity inversion model. Finally, encouraged by the results obtained in the synthetic case, the algorithm was applied to DC resistivity and magnetic datasets that were collected in the archeological area of old Pompeii city nearby Naples, Italy. The result of the sequential resistivity inversion model was notably superior to the corresponding resistivity model obtained from standard separate inversion
Cross-Gradient Joint Inversion of DC Resistivity and Gravity Gradient Data: A Multi-Disciplinary Approach for Geoscience, Heritage, and the Built Environment
Full text linkAccurate subsurface imaging is crucial for understanding complex geological structures. Traditional approaches often involve separate inversion of different geophysical datasets, which may not fully capture the structural similarities between the models. Joint inversion, integrating multiple datasets, offers a more comprehensive view by enhancing the resolution and the accuracy of subsurface models. In this study, we propose a joint inversion technique for DC resistivity and vertical gravity gradient data, leveraging the cross-gradient constraint to enforce structural similarities between the resulting models. This method is applied to both synthetic and real datasets, including case studies involving qanats in Iran and a dolerite dyke in South Africa. The results demonstrate that joint inversion significantly improves the accuracy of resistivity and density models compared to independent inversion, particularly in resolving intricate geological features. This approach has proven effective in enhancing subsurface mapping for multi-disciplinary purposes, including resource exploration, heritage conservation, and risk mitigation for the built environment
Joint interpretation of magnetic and gravity data at the Golgohar mine in Iran
No full textGeophysical modelling can take advantage of combining more geophysical data with the aim of decreasing the non-uniqueness of the resulting interpretation. The combination of gravity and magnetic data can yield useful information about the source properties by using the Poisson's analysis, which may help to infer the source properties, density and magnetic susceptibility, of the causative sources. Such estimates can be set as constraints for further interpretation. We consider first the synthetic data of a homogeneous block, for which correlation analysis allows the estimation of the Poisson ratio. The estimated source parameters are then used to invert gravity and magnetic data successfully. We applied this approach to the gravity and magnetic datasets in the Golgohar iron ore complex area, located in the Sanandaj-Sirjan zone (Iran). We performed a correlation analysis between the reduced to the pole magnetic data and the vertical gravity gradients of the 1st and 2nd order, respectively. We estimated strong magnetization contrasts between the mineral rocks and the surrounding host rocks. Further quantitative information about the source depth and geometry are obtained by 2D inverse modelling of both gravity and magnetic data, based on the damped weighted minimum-length solution. Even in this case, a-priori information from the correlation analysis leads to constrain the inverse process of both gravity and magnetic data. Inverse modelling confirms a high correlation between both susceptibility and density models, both horizontally and vertically, and show the presence of isolated sources with high density and magnetization contrasts, in good accordance with the average physical parameters of iron‐gold deposit formations
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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