The problem of automatic geophysical facies classification from well logs has played a crucial role in the mining industry from the 1980s to the present day. During this period, many different approaches were proposed to cope with this task; they were based on the methods of machine learning and deep learning. This paper gives a systematic survey of modern effective solutions to the assigned problem. The comparison of the approaches to the solution which are described in the works of various researchers is presented. The analysis of the available results is given. In addition, this paper provides a detailed description of the set of qualitative input well log data suitable for research.

Язык оригиналаанглийский
Название основной публикацииEducation and Accreditation in Geosciences; Environmental Legislation, Multilateral Relations and Funding Opportunities
ИздательInternational Multidisciplinary Scientific Geoconference
Страницы281-288
Число страниц8
Издание2.1
ISBN (электронное издание)9786197408768, 9786197408775, 9786197408782, 9786197408799, 9786197408805, 9786197408812, 9786197408829, 9786197408836, 9786197408843, 9786197408850, 9786197408867, 9786197408874, 9786197408881, 9786197408898
ISBN (печатное издание)9786197408768
СостояниеОпубликовано - 1 янв 2019
Событие19th International multidisciplinary scientific geoconference SGEM 2019 - Болгария, Albena, Болгария
Продолжительность: 9 дек 201911 дек 2019
Номер конференции: 19

Серия публикаций

НазваниеInternational Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM
Номер2.1
Том19
ISSN (печатное издание)1314-2704

конференция

конференция19th International multidisciplinary scientific geoconference SGEM 2019
Сокращенное названиеSGEM2019
Страна/TерриторияБолгария
ГородAlbena
Период9/12/1911/12/19

    Предметные области Scopus

  • Геотехническая инженерия и инженерная геология
  • Геология

ID: 48946897