{"id":59916,"date":"2025-07-09T23:49:08","date_gmt":"2025-07-09T20:49:08","guid":{"rendered":"https:\/\/geoconversation.org\/news\/gazprom-neft-innopolis-university-and-nedra-digital-will-develop-a-digital-system-for-field-modeling\/"},"modified":"2025-07-09T23:49:08","modified_gmt":"2025-07-09T20:49:08","slug":"gazprom-neft-innopolis-university-and-nedra-digital-will-develop-a-digital-system-for-field-modeling","status":"publish","type":"news","link":"https:\/\/geoconversation.org\/en\/news\/gazprom-neft-innopolis-university-and-nedra-digital-will-develop-a-digital-system-for-field-modeling\/","title":{"rendered":"Gazprom Neft, Innopolis University and Nedra Digital will develop a digital system for field modeling"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Major players <a data-id=\"https:\/\/geoconversation.org\/ne-byvaet-zhenskih-i-muzhskih-professij\/\" data-type=\"link\" href=\"https:\/\/geoconversation.org\/ne-byvaet-zhenskih-i-muzhskih-professij\/\">oil and gas<\/a> industries join forces to create an innovation platform based on<a data-id=\"https:\/\/geoconversation.org\/intellektualnyj-pomoshhnik-geologa\/\" data-type=\"link\" href=\"https:\/\/geoconversation.org\/intellektualnyj-pomoshhnik-geologa\/\"> artificial intelligence<\/a>. The system is designed for geomechanical modeling of oil and gas fields, which will allow more accurate assessment of their potential and optimization of production.\u00a0<\/p>\n\n\n<p class=\"wp-block-paragraph\">The digital platform will combine data from seismic surveys, laboratory studies and historical production indicators. Artificial intelligence will analyze this information, creating detailed 3D models of the formations. This will help:\u00a0<\/p>\n\n\n<ul class=\"wp-block-list\">\n<li>Predict changes in rock properties during development <a data-id=\"https:\/\/geoconversation.org\/ai-nahodit-mestorozhdeniya\/\" data-type=\"link\" href=\"https:\/\/geoconversation.org\/ai-nahodit-mestorozhdeniya\/\">deposits<\/a>;\u00a0<\/li>\n\n\n<li>Reduce the risks of accidents and complications during production;\u00a0<\/li>\n\n\n<li>Select the most effective development methods for each site.\u00a0<\/li>\n<\/ul>\n\n\n<p class=\"wp-block-paragraph\">\u201cGeomechanical modeling is the basis for decision-making in the modern oil and gas industry,\u201d noted Alexey Vashkevich, a representative of Gazprom Neft. \u201cThe new system will allow us to anticipate possible problems in advance and find optimal solutions.\u201d\u00a0<\/p>\n\n\n<p class=\"wp-block-paragraph\">The project will combine the expertise of three organizations:\u00a0<\/p>\n\n\n<ol class=\"wp-block-list\">\n<li>Gazprom Neft\u2014practical experience in exploration and production;\u00a0<\/li>\n\n\n<li>Innopolis University &#8211; developments in the field of AI and big data;\u00a0<\/li>\n\n\n<li>Nedra Digital &#8211; technologies for processing geological data.\u00a0<\/li>\n<\/ol>\n\n\n<p class=\"wp-block-paragraph\">\u201cJoint work will accelerate the digitalization of the industry and increase the economic efficiency of projects,\u201d said Iskander Bariev, director of Innopolis University.\u00a0<\/p>\n\n\n<p class=\"wp-block-paragraph\">It is planned that the system will begin to be used in industrial practice in the coming years. It is especially in demand for the development of complex fields, where traditional assessment methods are less accurate.\u00a0<\/p>\n\n\n<p class=\"wp-block-paragraph\">The new technology will not only increase production volumes, but also make production processes safer. This is an important step in the development of digital transformation of the Russian oil and gas industry.\u00a0<\/p>\n\n\n<p class=\"has-text-align-right wp-block-paragraph\"><sub>The material was prepared with the support of the Russian Ministry of Education and Science as part of the Decade of Science and Technology<\/sub><\/p>\n\n\n<p class=\"has-text-align-right wp-block-paragraph\"><sub>Source: neftegaz.ru<\/sub><\/p>\n\n\n<p class=\"has-text-align-right wp-block-paragraph\"><sub>Image generated by a neural network<\/sub><\/p>\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Major players oil and gas industries join forces to create an innovation platform based on artificial intelligence . The system is designed for geomechanical modeling of oil and gas fields, which will allow more accurate assessment of their potential and optimization of production. The digital platform will combine dat<\/p>\n","protected":false},"author":9,"featured_media":20401,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_seopress_robots_primary_cat":"","_seopress_titles_title":"Gazprom Neft, Innopolis University and Nedra Digital will develop a digital system for field modeling","_seopress_titles_desc":"Find out how a new AI-powered digital platform can help you more accurately estimate oil and gas reserves, improving production efficiency.","_seopress_robots_index":"","_seopress_analysis_target_kw":"","footnotes":""},"categories":[10],"tags":[14,318],"class_list":["post-59916","news","type-news","status-publish","has-post-thumbnail","category-geologorazvedka","tag-geologorazvedka","tag-czifrovye-tehnologii-v-geologii"],"acf":[],"pbg_featured_image_src":{"full":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg.webp",1365,1024,false],"thumbnail":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg-150x150.webp",150,150,true],"medium":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg-300x225.webp",300,225,true],"medium_large":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg-768x576.webp",768,576,true],"large":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg-1024x768.webp",1024,768,true],"1536x1536":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg.webp",1365,1024,false],"2048x2048":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg.webp",1365,1024,false],"bricks_large_16x9":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg-1200x675.webp",1200,675,true],"bricks_large":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg-1200x900.webp",1200,900,true],"bricks_large_square":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg-1200x1024.webp",1200,1024,true],"bricks_medium":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg-600x450.webp",600,450,true],"bricks_medium_square":["https:\/\/geoconversation.org\/wp-content\/uploads\/2025\/07\/ai-geomehanicheskoe-modelirovanie-mestorozhdeniy_jpg-600x600.webp",600,600,true]},"pbg_author_info":{"display_name":"Lyubov Cherkasova","author_link":"https:\/\/geoconversation.org\/en\/author\/amourallis\/","author_img":false},"pbg_comment_info":" No Comments","pbg_excerpt":"Major players oil and gas industries join forces to create an innovation platform based on artificial intelligence . The system is designed for geomechanical modeling of oil and gas fields, which will allow more accurate assessment of their potential and optimization of production. The digital platform will combine dat","_links":{"self":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/news\/59916","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/news"}],"about":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/types\/news"}],"author":[{"embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/comments?post=59916"}],"version-history":[{"count":0,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/news\/59916\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/media\/20401"}],"wp:attachment":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/media?parent=59916"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/categories?post=59916"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/tags?post=59916"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}