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In the paper a combined inversion algorithm solving the nonlinear geophysical well-logging inverse problem is presented. We apply a successive combination of a float-encoded Genetic Algorithm as a global optimization method and the well-known linearized Marquardt algorithm forming a fast inversion procedure. The technique is able to decrease the CPU run time at least one order of magnitude compared to the Genetic Algorithm and gives the parameter estimation errors having a few linearized optimization steps at the end of the iteration process. We use depth-dependent tool response equations to invert all the data of a greater depth-interval jointly in order to determine petrophysical parameters of homogeneous or inhomogeneous layers in one inversion procedure. The so-called interval inversion method gives more accurate and reliable estimation for the petrophysical model parameters than the conventional point by point inversion methods. It also enables us to determine the layer-thicknesses that can not be extracted from the data set by means of conventional inversion techniques. We test the combined interval inversion method on synthetic data, and employ it to the interpretation of well logs measured in a Hungarian hydrocarbon exploratory borehole.

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In the paper a 2D joint inversion method is presented, which is applicable for the simultaneous determination of layer thickness variation and petrophysical parameters by processing well-logging data acquired in several boreholes along the profile. The so-called interval inversion method is tested on noisy synthetic data sets generated on hydrocarbon-bearing reservoir models. Numerical experiments are performed to study the convergence and stability of the inversion procedure. Data and model misfit, function distance related to layer thickness fitting are measured as well as estimation errors and correlation coefficients are computed to check the accuracy and reliability of inversion results. It is shown that the actual inversion procedure is stable and highly accurate, which arises from the great over-determination feature of the inverse problem. Even a case study is attached to the paper in which interval inversion procedure is applied for processing of multi-borehole logging data acquired in Hungarian hydrocarbon exploratory wells in order to determine petrophysical parameters and lateral changes of layer thicknesses.

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Seismic data integration in reservoir modeling workflows is the one of the fastest-growing fields in the Earth Sciences. The actual geostatistical methods (co-kriging, stochastic simulation) can use seismic data as a secondary variable if there is a well-determined linear correlation between well log data and seismic attribute. Seismic interpreters must often increase this correlation. The application of multi-attributes via neural network may help in this case. A neural network type, called multi-layer perceptron, and its application in 3D porosity distribution prediction in a Hungarian natural gas reservoir, are described in this paper.

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Wireline logging surveys are routinely used for the reconnaissance and quantitative characterization of multi-mineral hydrocarbon structures. The interpretation of well-logging data, however, is quite a challenging task, because the conventionally used local inversion procedure becomes either an underdetermined or a slightly overdetermined problem that may result in poor parameter estimation. In order to determine the petrophysical model composed of several parameters, such as specific volumes of matrix components, water saturation, primary and secondary porosity and numerous zone-parameters, in a more reliable way a new inversion methodology is required. We suggest a joint inversion technique for the estimation of model parameters of multi-mineral rocks that inverts data acquired from a larger depth interval (hydrocarbon zone). The inverse problem is formulated assuming homogeneous intervals within the zone to get a highly overdetermined inversion procedure. The interval inversion method has been applied to shaly sandy hydrocarbon reservoirs, in this study, that is used for the estimation of petrophysical parameters of complex reservoirs. Numerical results with synthetic and field data demonstrate the feasibility of the inversion method in investigating carbonate and metamorphic structures.

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In the present study the crustal structures of Nile Delta, including Greater Cairo province, and its surroundings, were evaluated using 3D forward gravity and magnetic modeling. The interpretation is also based on the seismic reflection results, well logs data and previous density models. The present results allow to improve the understanding of both the crustal thicknesses and density distributions between the sedimentary cover and the upper mantle in the study area.The high Bouguer anomalies near the Mediterranean coast are mainly caused by deep-seated structures. The crust beneath the Mediterranean coastal region is typically continental, with a thickness of 24 km beneath Rositta and Damitta branches, which increases toward the south. The Greater Cairo province has been modeled with maximum crustal thickness of ca. 34 km. The negative gravity anomalies with minimum values are due to the effect of sedimentary cover and/or basement relief geometry.The main results of this work suggest that the study area could be divided into three different distinctive tectonic zones according to their Moho depth and crustal structures. The southern zone (unstable shelf zone) which covers the Greater Cairo province is characterized by maximum crustal modeled thickness. It also represents the most seismically active tectonic zone in the study area. On the contrary the middle and northern zones show a thinned crustal layer and a correspondingly thicker sedimentary cover.Furthermore, the magnetic anomalies along the Greater Cairo, as deduced from the 3D magnetic modeling, are mainly caused by the upper crustal structures. In particular, the high magnetic anomalies of the southern part of the studied area are interpreted as related to variation in the basement relief near the surface, resulting from block faulting and/or compressional folds.In the northern region near the Mediterranean coastal area the highest magnetic susceptibility anomaly values is affected by the shallow smooth relief of the lower crustal layer. Finally, limited, shallow-seated basaltic intrusions were modeled beneath the western side of Nile Delta. The existence of these basaltic intrusions suggests that the study area was influenced by the opening of the Red Sea and/or Gulf of Suez during the Oligocene time.

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author would like to thank MOL Plc. for providing the well-log data set and reservoir identification report, as well as the Department of Geology and Paleontology (University of Szeged) for the technical background and for professional help. The author

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% Upscaling of well logs The aim of well log data upscaling – or also known as blocking – is to synchronize the vertical resolution of the petrophysical logs with the 3D grid ( Zakrevsky, 2011 ). As computational performance increases exponentially according

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. , T.M. Tóth 2016 : Localisation of ductile and brittle shear zones along the Szentlőrinc-1 well in the Mecsekalja Zone using quartz microstructural and well-log data . – Acta Geodaetica et

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mapping using petrographic and well-log data suggests that the cataclasite follows thin horizons a few tens of meters thick with an ENE dip in the DH. The significant difference between the peak metamorphic temperatures of the adjacent blocks, the fact

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