93 research outputs found

    ΠšΠΎΡΠΌΠΎΡΡ‚Ρ€ΡƒΠΊΡ‚ΡƒΡ€Π½Ρ‹Π΅ ΠΏΠΎΠ·ΠΈΡ†ΠΈΠΈ Π·ΠΎΠ»ΠΎΡ‚ΠΎΡ€ΡƒΠ΄Π½Ρ‹Ρ… ΠΎΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ² заангарской части ЕнисСйского кряТа

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    Π˜Π·ΡƒΡ‡Π΅Π½Ρ‹ космоструктуры заангарский части ЕнисСйского кряТа ΠΏΠΎ ΠΌΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Π°ΠΌ ΠΌΡƒΠ»ΡŒΡ‚ΠΈΡΠΏΠ΅ΠΊΡ‚Ρ€Π°Π»ΡŒΠ½Ρ‹Ρ… космичСских систСм Modis ΠΈ Landsat ETM+. Π’Ρ‹Π΄Π΅Π»Π΅Π½Ρ‹ Ρ‡Π΅Ρ‚Ρ‹Ρ€Π΅ систСмы ΠΊΠΎΠ»ΡŒΡ†Π΅Π²Ρ‹Ρ… структур ΠΏΠ΅Ρ€Π²ΠΎΠ³ΠΎ порядка, ΠΈΠ½Ρ‚Π΅Ρ€ΠΏΡ€Π΅Ρ‚ΠΈΡ€ΡƒΠ΅ΠΌΡ‹Π΅ ΠΊΠ°ΠΊ Π³Π»ΡƒΠ±ΠΈΠ½Π½Ρ‹Π΅ ΠΎΡ‡Π°Π³ΠΈ Π³Ρ€Π°Π½ΠΈΡ‚ΠΈΠ·Π°Ρ†ΠΈΠΈ. ΠŸΠΎΠΊΠ°Π·Π°Π½Ρ‹ закономСрности размСщСния Π·ΠΎΠ»ΠΎΡ‚ΠΎΠ³ΠΎ орудСнСния Π² космогСологичСских структурах. Π’Ρ‹Π΄Π΅Π»Π΅Π½Π½Ρ‹Π΅ Ρ€Π°Π·Π½ΠΎΡ€Π°Π½Π³ΠΎΠ²Ρ‹Π΅ космогСологичСскиС структуры находят ΠΎΡ‚Ρ€Π°ΠΆΠ΅Π½ΠΈΠ΅ Π² Π°Π½ΠΎΠΌΠ°Π»ΡŒΠ½Ρ‹Ρ… структурах гСохимичСских ΠΏΠΎΠ»Π΅ΠΉ

    КомплСксноС ΠΌΠΎΠ΄Π΅Π»ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ виброакустичСских, Ρ‚Π΅ΠΏΠ»ΠΎΠ²Ρ‹Ρ… ΠΈ динамичСских Π²ΠΎΠ·ΠΌΡƒΡ‰Π΅Π½ΠΈΠΉ Π² Ρ‚Ρ€ΡƒΠ±ΠΎΠΏΡ€ΠΎΠ²ΠΎΠ΄Π΅, ΠΏΠΎΠ΄Π²Π΅Ρ€ΠΆΠ΅Π½Π½ΠΎΠΌ Π²ΠΎΠ·Π΄Π΅ΠΉΡΡ‚Π²ΠΈΡŽ климатичСских условий

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    Electrical borehole wall images represent grey-level-coded micro-resistivity measurements at the borehole wall. Different scientific methods have been implemented to transform image data into quantitative log curves. We introduce a pattern recognition technique applying texture analysis, which uses second-order statistics based on studying the occurrence of pixel pairs. We calculate so-called Haralick texture features such as contrast, energy, entropy and homogeneity. The supervised classification method is used for assigning characteristic texture features to different rock classes and assessing the discriminative power of these image features. We use classifiers obtained from training intervals to characterize the entire image data set recovered in ODP hole 1203A. This yields a synthetic lithology profile based on computed texture data. We show that Haralick features accurately classify 89.9% of the training intervals. We obtained misclassification for vesicular basaltic rocks. Hence, further image analysis tools are used to improve the classification reliability. We decompose the 2D image signal by the application of wavelet transformation in order to enhance image objects horizontally, diagonally and vertically. The resulting filtered images are used for further texture analysis. This combined classification based on Haralick features and wavelet transformation improved our classification up to a level of 98%. The application of wavelet transformation increases the consistency between standard logging profiles and texture-derived lithology. Texture analysis of borehole wall images offers the potential to facilitate objective analysis of multiple boreholes with the same lithology

    Influence of depth, temperature, and structure of a crustal heat source on the geothermal reservoirs of Tuscany: numerical modelling and sensitivity study

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    Β© 2016, Ebigbo et al.Granitoid intrusions are the primary heat source of many deep geothermal reservoirs in Tuscany. The depth and shape of these plutons, characterised in this study by a prominent seismic reflector (the KΒ horizon), may vary significantly within the spatial scale of interest. In an exploration field, simulations reveal the mechanisms by which such a heat source influences temperature distribution. A simple analysis quantifies the sensitivity of potentially measurable indicators (i.e. vertical temperature profiles and surface heat flow) to variations in depth, temperature, and shape of the heat source within given ranges of uncertainty

    Log interpretation in the RWTH-1 borehole

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