Comparison of Seismic Traces Clustering Efficiency of Different Unsupervised Machine Learning Algorithms in Forward Seismic Models; 81st EAGE Conference and Exhibition 2019
| Parent link: | 81st EAGE Conference and Exhibition 2019.— 2019.— [4 p.] |
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| Awduron Corfforaethol: | , |
| Awduron Eraill: | , , , , , |
| Crynodeb: | Title screen In this study, it is proposed to build geological model based on proportions of fluvial deposits outcrop. Then forward seismic model is constructed and clustering of seismic traces by using different unsupervised algorithms (k-means, DBSCAN and Agglomerative clustering) is performed. Results are compared with ground truth, which in our case is NTG map of interval of interest in geological model. Finally the optimal settings of the algorithms and the most accurate clustering method are identified. Режим доступа: по договору с организацией-держателем ресурса |
| Iaith: | Saesneg |
| Cyhoeddwyd: |
2019
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| Cyfres: | AI/Digitalization for Interpretation - Various Application |
| Pynciau: | |
| Mynediad Ar-lein: | https://doi.org/10.3997/2214-4609.201901390 |
| Fformat: | Electronig Pennod Llyfr |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=660618 |
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| 200 | 1 | |a Comparison of Seismic Traces Clustering Efficiency of Different Unsupervised Machine Learning Algorithms in Forward Seismic Models |f I. I. Churochkin [et al.] | |
| 203 | |a Text |c electronic | ||
| 225 | 1 | |a AI/Digitalization for Interpretation - Various Application | |
| 300 | |a Title screen | ||
| 330 | |a In this study, it is proposed to build geological model based on proportions of fluvial deposits outcrop. Then forward seismic model is constructed and clustering of seismic traces by using different unsupervised algorithms (k-means, DBSCAN and Agglomerative clustering) is performed. Results are compared with ground truth, which in our case is NTG map of interval of interest in geological model. Finally the optimal settings of the algorithms and the most accurate clustering method are identified. | ||
| 333 | |a Режим доступа: по договору с организацией-держателем ресурса | ||
| 463 | |t 81st EAGE Conference and Exhibition 2019 |o proceedings, London, June 3-6, 2019 |v [4 p.] |d 2019 | ||
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a сейсмические трассы | |
| 610 | 1 | |a неконтролируемые процессы | |
| 701 | 1 | |a Churochkin |b I. I. |c geophysicist |c Research Engineer, Tomsk Polytechnic University |f 1993- |g Iljya Igorevich |3 (RuTPU)RU\TPU\pers\44399 |9 21804 | |
| 701 | 1 | |a Volkova |b A. A. |c mining engineer |c engineer, senior lecturer of Tomsk Polytechnic University |f 1993- |g Aleksandra Aleksandrovna |3 (RuTPU)RU\TPU\pers\43340 |9 21644 | |
| 701 | 1 | |a Gavrilova |b E. | |
| 701 | 1 | |a Bukhanov |b N. V. |c geologist |c engineer of Tomsk Polytechnic University |f 1986- |g Nikita Vladimirovich |3 (RuTPU)RU\TPU\pers\34016 |9 17583 | |
| 701 | 1 | |a Butorin |b A. V. |g Aleksandr Vasiljevich | |
| 701 | 1 | |a Rukavishnikov |b V. S. |c Director of the Center for Training and Retraining of Oil and Gas Specialists, Associate Professor of Tomsk Polytechnic University, Candidate of Technical Sciences |c Engineer of Tomsk Polytechnic University |f 1984- |g Valery Sergeevich |3 (RuTPU)RU\TPU\pers\34050 |9 17614 | |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет (ТПУ) |b Институт природных ресурсов (ИПР) |b Центр подготовки и переподготовки специалистов нефтегазового дела (ЦППС НД) |b Лаборатория геологии месторождений нефти и газа (ЛГМНГ) |3 (RuTPU)RU\TPU\col\19125 |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Институт природных ресурсов |b Центр подготовки и переподготовки специалистов нефтегазового дела |3 (RuTPU)RU\TPU\col\23177 |
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