{"id":2551,"date":"2015-02-24T11:51:03","date_gmt":"2015-02-24T09:51:03","guid":{"rendered":"http:\/\/www.geology.com.ua\/?page_id=2551"},"modified":"2015-04-02T13:46:40","modified_gmt":"2015-04-02T11:46:40","slug":"2551-2","status":"publish","type":"page","link":"http:\/\/www.geology.com.ua\/en\/2551-2\/","title":{"rendered":""},"content":{"rendered":"<p>Geoinformatika 2012; 4(44) : 46-52<\/p>\n<h4>PREDICTION OF THE SHEAR WAVES VELOCITIES MODEL ACCORDING TO THE DATA\u00a0OF GEOPHYSICAL RESEARCHES OF WELLS AND SEISIMIC-SURVEY USING NEURAL NETWORKS<\/h4>\n<h5><em>Kh.B. Aghayev\u00a0 <\/em><\/h5>\n<p style=\"text-align: justify;\">The properties of prediction of thin-layered two-dimensional model on velocities of shear waves are given. Prediction method of two- and three-dimensional models of velocities was developed on the basis of GSW (Geophysical Studying of Wells) data on pressure and shear waves, and seismic survey of 2D\/3D on pressure waves. The method was based on a creation of medium physical properties models, conducting of cluster analysis and prediction of velocities using neural networks. The model of velocities of shear waves is predicted by \u201cTeaching\u201d neural networks on GSW data according to the results of seismic inversion. The method was tested on geophysical data of one of the South-Caspian Basin structures. The complicated character was revealed between petrophysical properties of medium on cluster analysis.\u00a0 As a result of prediction the section on velocities is more differentiated on depth and profile than on empirical dependences.<\/p>\n<p style=\"text-align: justify;\"><strong>Keywords:<\/strong>\u00a0 Neural network, cluster, prediction, velocity of shear waves, seismic inversion, time section, elastic parameters, one- and two- dimensional models of medium.<\/p>\n<p><a href=\"http:\/\/www.geology.com.ua\/wp-content\/uploads\/2014\/09\/06_Agaev.pdf\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-790 alignleft\" src=\"http:\/\/www.geology.com.ua\/wp-content\/uploads\/2013\/09\/pdf.jpg\" alt=\"pdf\" width=\"48\" height=\"48\" srcset=\"http:\/\/www.geology.com.ua\/wp-content\/uploads\/2013\/09\/pdf.jpg 128w, http:\/\/www.geology.com.ua\/wp-content\/uploads\/2013\/09\/pdf-150x150.jpg 150w\" sizes=\"auto, (max-width: 48px) 100vw, 48px\" \/><\/a><\/p>","protected":false},"excerpt":{"rendered":"<p>Geoinformatika 2012; 4(44) : 46-52 PREDICTION OF THE SHEAR WAVES VELOCITIES MODEL ACCORDING TO THE DATA\u00a0OF GEOPHYSICAL RESEARCHES OF WELLS AND SEISIMIC-SURVEY USING NEURAL NETWORKS Kh.B. Aghayev\u00a0 The properties of prediction of thin-layered two-dimensional model on velocities of shear waves are given. Prediction method of two- and three-dimensional models of velocities was developed on the basis of GSW (Geophysical Studying of Wells) data on pressure and shear waves, and seismic survey of 2D\/3D on pressure waves. The method was based on a creation of medium physical properties models, conducting of cluster analysis and prediction of velocities using neural networks. The model of velocities of shear waves is predicted by \u201cTeaching\u201d neural networks on GSW data according to the results of seismic inversion. The method was tested on geophysical data of one of the South-Caspian Basin structures. The complicated character was revealed between petrophysical properties of medium on cluster analysis.\u00a0 As a result of prediction the section on velocities is more differentiated on depth and profile than on empirical dependences. Keywords:\u00a0 Neural network, cluster, prediction, velocity of shear waves, seismic inversion, time section, elastic parameters, one- and two- dimensional models of medium.<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"open","template":"","meta":{"footnotes":""},"class_list":["post-2551","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>- \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<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"http:\/\/www.geology.com.ua\/en\/2551-2\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"- \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\" \/>\n<meta property=\"og:description\" content=\"Geoinformatika 2012; 4(44) : 46-52 PREDICTION OF THE SHEAR WAVES VELOCITIES MODEL ACCORDING TO THE DATA\u00a0OF GEOPHYSICAL RESEARCHES OF WELLS AND SEISIMIC-SURVEY USING NEURAL NETWORKS Kh.B. Aghayev\u00a0 The properties of prediction of thin-layered two-dimensional model on velocities of shear waves are given. Prediction method of two- and three-dimensional models of velocities was developed on the basis of GSW (Geophysical Studying of Wells) data on pressure and shear waves, and seismic survey of 2D\/3D on pressure waves. The method was based on a creation of medium physical properties models, conducting of cluster analysis and prediction of velocities using neural networks. The model of velocities of shear waves is predicted by \u201cTeaching\u201d neural networks on GSW data according to the results of seismic inversion. The method was tested on geophysical data of one of the South-Caspian Basin structures. The complicated character was revealed between petrophysical properties of medium on cluster analysis.\u00a0 As a result of prediction the section on velocities is more differentiated on depth and profile than on empirical dependences. Keywords:\u00a0 Neural network, cluster, prediction, velocity of shear waves, seismic inversion, time section, elastic parameters, one- and two- dimensional models of medium.\" \/>\n<meta property=\"og:url\" content=\"http:\/\/www.geology.com.ua\/en\/2551-2\/\" \/>\n<meta property=\"og:site_name\" content=\"\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\" \/>\n<meta property=\"article:modified_time\" content=\"2015-04-02T11:46:40+00:00\" \/>\n<meta property=\"og:image\" content=\"http:\/\/www.geology.com.ua\/wp-content\/uploads\/2013\/09\/pdf.jpg\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/2551-2\\\/\",\"url\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/2551-2\\\/\",\"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\",\"isPartOf\":{\"@id\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/2551-2\\\/#primaryimage\"},\"image\":{\"@id\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/2551-2\\\/#primaryimage\"},\"thumbnailUrl\":\"http:\\\/\\\/www.geology.com.ua\\\/wp-content\\\/uploads\\\/2013\\\/09\\\/pdf.jpg\",\"datePublished\":\"2015-02-24T09:51:03+00:00\",\"dateModified\":\"2015-04-02T11:46:40+00:00\",\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[[\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/2551-2\\\/\"]]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/2551-2\\\/#primaryimage\",\"url\":\"http:\\\/\\\/www.geology.com.ua\\\/wp-content\\\/uploads\\\/2013\\\/09\\\/pdf.jpg\",\"contentUrl\":\"http:\\\/\\\/www.geology.com.ua\\\/wp-content\\\/uploads\\\/2013\\\/09\\\/pdf.jpg\"},{\"@type\":\"WebSite\",\"@id\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/#website\",\"url\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/\",\"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\",\"description\":\"\u0426\u0435\u043d\u0442\u0440 \u043c\u0435\u043d\u0435\u0434\u0436\u043c\u0435\u043d\u0442\u0443 \u0442\u0430 \u043c\u0430\u0440\u043a\u0435\u0442\u0438\u043d\u0433\u0443 \u0432 \u0433\u0430\u043b\u0443\u0437\u0456 \u043d\u0430\u0443\u043a \u043f\u0440\u043e \u0417\u0435\u043c\u043b\u044e\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"- \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","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"http:\/\/www.geology.com.ua\/en\/2551-2\/","og_locale":"en_US","og_type":"article","og_title":"- \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","og_description":"Geoinformatika 2012; 4(44) : 46-52 PREDICTION OF THE SHEAR WAVES VELOCITIES MODEL ACCORDING TO THE DATA\u00a0OF GEOPHYSICAL RESEARCHES OF WELLS AND SEISIMIC-SURVEY USING NEURAL NETWORKS Kh.B. Aghayev\u00a0 The properties of prediction of thin-layered two-dimensional model on velocities of shear waves are given. Prediction method of two- and three-dimensional models of velocities was developed on the basis of GSW (Geophysical Studying of Wells) data on pressure and shear waves, and seismic survey of 2D\/3D on pressure waves. The method was based on a creation of medium physical properties models, conducting of cluster analysis and prediction of velocities using neural networks. The model of velocities of shear waves is predicted by \u201cTeaching\u201d neural networks on GSW data according to the results of seismic inversion. The method was tested on geophysical data of one of the South-Caspian Basin structures. The complicated character was revealed between petrophysical properties of medium on cluster analysis.\u00a0 As a result of prediction the section on velocities is more differentiated on depth and profile than on empirical dependences. 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