Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
Facies classification from well logs using machine learning methods : A survey. / Erzikova, Julia; Grafeeva, Natalia.
Education and Accreditation in Geosciences; Environmental Legislation, Multilateral Relations and Funding Opportunities. 2.1. ред. International Multidisciplinary Scientific Geoconference, 2019. стр. 281-288 (International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM; Том 19, № 2.1).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
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TY - GEN
T1 - Facies classification from well logs using machine learning methods
T2 - 19th International Multidisciplinary Scientific Geoconference, SGEM 2019
AU - Erzikova, Julia
AU - Grafeeva, Natalia
N1 - Conference code: 19
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
KW - Core
KW - Facies classification
KW - Machine learning
KW - Supervised multiclass classification problem
KW - Well log data
UR - http://www.scopus.com/inward/record.url?scp=85073322107&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85073322107
SN - 9786197408768
T3 - International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM
SP - 281
EP - 288
BT - Education and Accreditation in Geosciences; Environmental Legislation, Multilateral Relations and Funding Opportunities
PB - International Multidisciplinary Scientific Geoconference
Y2 - 9 December 2019 through 11 December 2019
ER -
ID: 48946897