N. Mousavi; J. Ebbing; V. Ebrahimzadeh Ardestani
Abstract
We apply two forward methodologies in order to study density and susceptibility structure of the crust and upper mantle. The study area is a profile crossing the Zagros collision zone located as margin of Eurasia-Arabia converging plates. Gravity modeling focusing on lithospheric structure is performed ...
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We apply two forward methodologies in order to study density and susceptibility structure of the crust and upper mantle. The study area is a profile crossing the Zagros collision zone located as margin of Eurasia-Arabia converging plates. Gravity modeling focusing on lithospheric structure is performed in thermodynamic framework in which chemical composition is important and provides an understanding of deep layers in lithosphere like Moho and Lithosphere-Asthenosphere Boundary. Results on the crustal thickness show minimum values beneath the Arabia Platform and Central Iran (42–43 km), and maximum values beneath the Sanandaj Sirjan zone (SSZ; 55–63 km). Results on the lithosphere thickness a long profile also indicate that the Arabian lithosphere is approximately 220 km thick, toward North West of Iran especially below the Central Iran rises up to 90 km. In the profile (central Zagros), lithosphere thinning occurs in wider region, from the Zagros fold thrust belt to the Sanandaj Sirjan zone. Our results are based on application of average Proterozoic mantle compositions in modeling beneath the Arabian Platform, Mesopotamian Foreland Basin and Iranian Plateau. After rough estimation of upper crust via integrated modeling by elevation, gravity and geoid data, the distribution of density and magnetic susceptibility values allows us to perform a study in crustal scale. Afterwards, determination of the homogenous blocks with the same density and susceptibility, the geometry to different crustal layers including sediments, upper, middle and lower crust deep to Moho boundary were refined in crust-scale study based on regional model in lithospheric scale. Presence of Main Zagros Fault is a bold point in our modeling which leads to better fit of gravity data.
M Mirzaei; L Soheili; V Ebrahimzadeh Ardestani; A Teymorian Motlagh
Abstract
The main objective of interpretation of acquired gravity data on the Earth's surface is to determine the contrasts in density or shape/dimension of mass anomalies. Interpretation of gravity data can be done through an inversion process. In this research, a block model has been considered for the subsurface ...
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The main objective of interpretation of acquired gravity data on the Earth's surface is to determine the contrasts in density or shape/dimension of mass anomalies. Interpretation of gravity data can be done through an inversion process. In this research, a block model has been considered for the subsurface anomalous mass. By considering a constant initial density (about 2.6 gr/cm3) for all blocks and by using inversion method, distribution of density of the anomalous mass was estimated and interpreted. In this research, Occam method is used to invert 246 gravity data collected in 2007. Results of the gravity data inversion show sufficient fit between observed and calculated gravity data. Using this inversion method, distribution of density in the subsurface layers related to sediments and basement are estimated in this area. Since there is a density contrast between sedimentary layers and basement, the estimated density distribution can help to explore the lithology of formations as well as the discontinuities in them. Densities less than 2 gr/cm3 in horizontal and vertical sections obtained from the inversion are attributed to the alluviums. The depth of these sediments, which include sand, silt and clay of different percentages, is estimated to be less than about 200 m. Unequal density distribution along the layers is taken to indicate fractures. In fact, these fractures are associated with part of the Tabarteh fault in this area, which caused numerous earthquakes (but less than 5 Richters in magnitude) around the Arak and Dawood Abad cities in past years.
M.E Hekmatian; V Ebrahimzadeh Ardestani; M.A Riahi; A Memar Koucheh Bagh; J Amini
Abstract
Pattern recognition algorithms especially neural network in geophysical interpretations and other Earth sciences have been used since some years ago. In neural network and other pattern recognition algorithms like support vector classifier (SVC) that the latter method is used in this research, by using ...
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Pattern recognition algorithms especially neural network in geophysical interpretations and other Earth sciences have been used since some years ago. In neural network and other pattern recognition algorithms like support vector classifier (SVC) that the latter method is used in this research, by using the values of the features, which has been extracted from the objects (in our work gravity profiles are objects), classification of the objects can be done. Usually the features are selected subjectively. In this paper, we have presented a homemade software that can select proper features objectively. By using SVC and the mentioned features selection (FS) software, depth estimations of anticlines have been done in this research. We have shown the difference of using proper features and improper ones in the mentioned depth estimation (a kind of classification). In this paper, twenty synthetic gravity profiles with anticline shape sources are created for training SVC and the same amount of synthetic profiles are created for testing. It has shown that depth estimation with proper features is more precise than depth estimation with improper features. Also it should be emphasized that FS is important not only in depth estimation of anticlines, but also in all kinds of classifications in Earth sciences and the mentioned homemade software code is applicable in all of them.
A. Nejati Kalate; V. Ebrahimzadeh Ardestani; E. Shahin; S. H. Motavalli Anbaran; Sh. Ghomi; E. Javan
Abstract
Determination of the geometry of bedrock, by nonlinear inverse modeling of gravity data, is the aim of this paper. In this method, reliable geological structures can be obtained by minimum geology priori information. The usual practice of inverting gravity anomalies of two-dimensional bodies replaced ...
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Determination of the geometry of bedrock, by nonlinear inverse modeling of gravity data, is the aim of this paper. In this method, reliable geological structures can be obtained by minimum geology priori information. The usual practice of inverting gravity anomalies of two-dimensional bodies replaced by n-sides polygon for determining location of the vertical that best explain the observed anomalies. In this method, the geometry of the bedrock is replaced by a series of juxtaposing prisms. Finally the length of each prism is the depth of the bedrock at that point.
The algorithm uses a nonlinear iterative procedure for simulation of bedrock geometry. At the first step, the nonlinear problem changes to a linear problem by a proper approximation and standard method. The second step is the parameterization of the model. Finally, an initial model is suggested on the basis of geological and geophysical assumption and using the numerical analysis, Jacobean matrix is calculated. In each iteration the inversion will improve the initial model, considering the differences between observed and calculated gravity anomalies, based on Levenberg-Marquardt's method.
The practical effectiveness of this method is demonstrated by inversion of synthetic (free noise and noise contaminated data) and real examples. The real data is acquired over the Moghan area and the results compared with the geological information.
