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  • Author or Editor: P. N. Szabó x
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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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International Review of Applied Sciences and Engineering
Authors:
G. Szabó
,
P. Enyedi
,
Gy. Szabó
,
I. Fazekas
,
T. Buday
,
A. Kerényi
,
M. Paládi
,
N. Mecser
, and
Sz. Szabó

According to the challenge of the reduction of greenhouse gases, the structure of energy production should be revised and the increase of the ratio of alternative energy sources can be a possible solution. Redistribution of the energy production to the private houses is an alternative of large power stations at least in a partial manner. Especially, the utilization of solar energy represents a real possibility to exploit the natural resources in a sustainable way. In this study we attempted to survey the roofs of the buildings with an automatic method as the potential surfaces of placing solar panels. A LiDAR survey was carried out with 12 points/m2 density as the most up-to-date method of surveys and automatic data collection techniques. Our primary goal was to extract the buildings with special regard to the roofs in a 1 km2 study area, in Debrecen. The 3D point cloud generated by the LiDAR was processed with MicroStation TerraScan software, using semi-automatic algorithms. Slopes, aspects and annual solar radiation income of roof planes were determined in ArcGIS10 environment from the digital surface model. Results showed that, generally, the outcome can be regarded as a roof cadaster of the buildings with correct geometry. Calculated solar radiation values revealed those roof planes where the investment for photovoltaic solar panels can be feasible.

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Abstract  

Radon can accumulate in underground areas such as show caves. Repairmen and tourist guides working in such caves may thus be exposed to significant radiation doses. Therefore, it is necessary to measure the radon concentration to estimate the exact radiation dose caused by radon. Considering that the radon concentration in caves usually shows significant seasonal fluctuations, the monthly change of radon concentration was studied for 1 year in nine show caves opened to the public in Hungary. Despite the fact that all of the caves were formed in karst rocks, the annual average radon concentration levels were rather different between each other (541–8287 Bq m−3). The significant monthly fluctuation of the radon concentration indicates that the annual average radon concentration in caves can only be accurately obtained by year-long measurements.

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