{"version":"1.0","provider_name":"\u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb","provider_url":"http:\/\/www.geology.com.ua\/en","author_name":"\u0410\u0434\u043c\u0456\u043d\u0456\u0441\u0442\u0440\u0430\u0442\u043e\u0440","author_url":"http:\/\/www.geology.com.ua\/en\/blog\/author\/andriy\/","title":"(\u0423\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u0430) Geoinformatika 2014; 4(52) : 30-36 - \u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"C0TWNcalYI\"><a href=\"http:\/\/www.geology.com.ua\/en\/2070-2\/\">(\u0423\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u0430) Geoinformatika 2014; 4(52) : 30-36<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"http:\/\/www.geology.com.ua\/en\/2070-2\/embed\/#?secret=C0TWNcalYI\" width=\"600\" height=\"338\" title=\"&#8220;(\u0423\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u0430) Geoinformatika 2014; 4(52) : 30-36&#8221; &#8212; \u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb\" data-secret=\"C0TWNcalYI\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=http:\/\/www.geology.com.ua\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","description":"Geoinformatika 2014; 4(52) :\u00a030-36\u00a0 (in Russian) HYPERSPECTRAL METHODS IN GEOLOGY: CURRENT STATE AND PROSPECTS V.A. Yatsenko1,2, N.D. Voronov2,\u00a0 V.V. Gnidenko3, N.V. Nalivaychuk3 1Scientific Foundation of Scientists and Spesialists on Molecular Cybernetics and Informatics,\u00a0\u0410cademica Glushkova Ave., 40, bild.\u00a0 4\/1, \u041ayiv 03680, Ukraine, e-mail: vyatsenko@gmail.com 2Space Research Institute of NASU and SSAU, \u0410cademica Glushkova Ave., 40, bild.\u00a0 4\/1, \u041ayiv 03680, Ukraine 3National Technical University of Ukraine \u201cKyiv Polytechnic Institute\u201d, Peremogy Ave., 37,\u00a0 \u041ayiv \u00a03056, Ukraine,e-mail: nnv@scs.ntu-kpi.kiev.ua Purpose. Remote sensing (RS) began in the early 60s with the development of image processing of satellite imagery. Wide use of radiometers and hyperspectrometers in RS led to the accumulation of huge volume of experimental data that can now be used for remote detection of minerals. Imaging spectrometry data or hyperspectral imagery acquired by airborne systems have been used in geologic since the early 1980\u2019s and represent a mature technology. The solar spectral range 0,4\u20132,5 mm provides abundant information about hydroxyl-bearing minerals, sulfates and carbonates common to many geologic units and hydrothermal alteration assemblages. The purpose of this paper is to show the feasibility of hybrid information technology and new sensors for identification of oil and gas. Design\/methodology\/approach. We propose to combine hyperspectral, spectral and gravimetric data for oil forecasting using most informative parameters and the SVM-method. Behind the method is the idea of intelligent analysis based on models. Guided by this methodology, we demonstrate some possibilities involving four types of data such as hyperspectral, gravimetric, seismic, and geological data. Our method is also based on Spectral Angle Mapper (SAM) as a tool for matching the separated and members with pure spectra from databases. The analysis of SAM is provided in three spectral regions: VIS, IR and VIS+IR combined. Three kinds of available influences can be analysed: additive noise, constant offset, and slant offset. Findings. This paper presents an overview of support vector machines (SVM) as one of the most promising intelligent techniques for data analysis, as theoretical approaches and sophisticated applications developed for various research areas and problem domains. It is an attempt to provide a survey of the applications of SVM for oil and gas exploration. The applications of SVM have been grouped and summarized in the different areas of the exploration phase, which can be used as a guide to assess the effectiveness of SVM as against other data mining algorithms. The study introduces an image specific algorithm for oil identification and discusses the implications for geology. Based on the hydrocarbon infiltration theory, gravimetric data, the analysis of crude oil in soil, spectral data of crude oil in sea water, and Hyperion hyperspectral remote sensing images were used to develop the synergetic approach to oil-gas exploration. Practical value\/implications. Our methodology proves to be practical for thorough data analysis in the exploration and production of oil and gas.\u00a0 The results indicate that the area of the oil-gas reservoir could be delimited in two ways: a)\u00a0directly, by the absorption bands near 1730\u00a0nm in Hyperion image; b) indirectly, by using Linear Spectral Unmixing (LSU) and Spectral Angle Matching (SAM) of alteration mineral (e.g. kaolinite, illite). In addition, combined with the optimal bands in the region of visible\/near-infrared, SAM can be used to extract the thin oil slick of microseepage. Keywords: hyper spectral, hyperion, gravimeter, land, sea, oil-gas reservoir, detection, forecasting, SVM-method, mapper. The full text of papers References Arhipov A.I., Tovstjuk Z.M., Levchik O.I., Arhipova Ljalko V I., Popov M.A. Metodologija i opyt poiska zalezhej uglevodorodov na sushe s ispol&#8217;zovaniem ajerokosmicheskoj informacii [Methodology and experience finding hydrocarbon deposits on land using aerospace information]. Nauky pro zemlyu ta kosmos suspilstvu. Pratsi Pershoyi naukovoyi konferentsiyi [Earth science and space community. Proceedings of the First Conference, 25-27 chervnya 2007 r.]. Kyiv, 2007, pp. 55-60. Hnidenko V., Nalyvaychuk M., Yatsenko V. Neiromerezheve otsiniuvannia\u00a0 slabkykh vplyviv na kerovane levituiuche probne tilo [Neural network estimation of weak effects on controlled levitation test subject]. Naukovi pratsi Natsionalnoho universytetu kharchovykh tekhnolohii [Proceedings of National University of food tehnolohiy],\u00a0 2013, no. 48, pp. 44-48. Gorny V. I., Tronin A. A. Obzor dostizhenij poslednego desjatiletija v oblasti primenenija sputnikovih metodov distancionnogo zondirovanija pri geologicheskih i geofizicheskih issledovanijah [Overview of the achievements of the last decade in the use of satellite remote sensing methods in geological and geophysical studies]. Sovremennye problemy distancionnogo zondirovanija Zemli i kosmosa [Modern Problems of Remote Sensing and Space], 2012, vol. 9,\u00a0 no. 5,\u00a0 pp. 116-132. Kozorez V.V. Dinamicheskie sistemy svobodnyh magnitno vzaimodejstvujushhih tel [Dynamical systems magnetically interacting free subject]. Kyiv, Naukova dumka, 1981, 140 p. Nalyvaychuk M., Yatsenko V., Hnidenko V. Vymiriuvalno-obchysliuvalna systema dlia otrymannia operatyvnoi informatsii shchodo hravitatsiinoho polia [Measurement and computer system to obtain timely information on the gravitational field]. Kompiuterno-intehrovani tekhnolohii: osvita, nauka, vyrobnytstvo [Integrated Computer: education, science, vyrobnytstvo]. Luck, Publisher Lutsk National Technical University, 2013, no. 12, pp. 167-173. Nalivajchuk N., Yatsenko V. Apparatno programmnoe obespechenie adaptivnogo opto-kriogennogo gravimetra na osnove nanostruktur [Hardware software adaptive opto-cryogenic gravimeter based on nanostructures] Zbirnyk tez 13-yi ukrainskoi konferentsii z kosmichnykh doslidzhen. [Abstracts of the 13th Ukrainian Conference on Space doslidzhen]. Kyiv, Kafedra, 2013, 139 p. Yatsenko V.O., Nalyvaychuk M.V. Modeliuvannia ta optymizatsiia adaptyvnoho kriohennoho hravimetra [Modeling and optimization of adaptive cryogenic gravimeters]. 19 Mizhnarodna konferentsiya z avtomatychnoho keruvannya, Kyiv, 26-28 veresnya 2012 [19th International Conference on Automatic Control, Kyiv 26-28 September 2012]. Kyiv, Ukraine, 2012, 344 p. Goodkind J.M. The superconducting gravimeter. Rev. Sci. Instr., 1999, vol. 70, no. 11, pp. 4131-4152. Goodkind J.M., Warburton R.J. Superconductivity applied to gravimetry. IEEE Transactions on Magnetics, 1975, vol. 11, no.2, pp. 708-711. Kozoriz V. Novel Magnetic Levitation and Propulsion Phenomena. Zaporizhya, 1999, 271 p. Moon F.C. Superconducting Levitation: Application to bearings and magnetic transportation. New York, John Willey &amp; Sons, 1994, 295 p. Prothero W.A., Goodkind. J. M. A superconducting gravimeter. Rev. Sci. Instr,1968, vol. 39, , no. 9, pp. 1257-1261. Yatsenko V., Nalyvaichuk M. Cryogenic-Optical Gravimeter: Principles, Methods and Applications. Kharkov University Vestnik, Ser. Radiophysics and Electronics, 2011, pp. 107-113. Yatsenko V., Pardallos P. Global optimization of cryogenic-optical sensor, in Sensors, Systems, and Next-Generation Satellites. Eds K. W.H. Fujisada, J. Lirie. Proc. [&hellip;]"}