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{'doi': '10.15530/urtec-2022-3721712', 'member_id': '2', 'member': 'American Association of Petroleum Geologists', 'container-title': 'Proceedings of the 10th Unconventional Resources Technology Conference', 'primary-resource': 'http://archives.datapages.com/data/doi/10.15530/urtec-2022-3721712', 'tld': 'datapages.com', 'clearbit-logo': 'https://logo.clearbit.com/datapages.com', 'coaccess': [], 'multiple-resolution': [{'url': 'https://library.seg.org/doi/10.15530/urtec-2022-3721712', 'tld': 'seg.org', 'clearbit-logo': 'https://logo.clearbit.com/seg.org'}, {'url': 'https://onepetro.org/URTECONF/proceedings/22URTC/489125', 'tld': 'onepetro.org', 'clearbit-logo': 'https://logo.clearbit.com/onepetro.org'}], 'type': 'PROCEEDINGS ARTICLE', 'published_date': '2022', 'publication': 'Proceedings of the 10th Unconventional Resources Technology Conference', 'supplementary_ids': None, 'title': 'Natural Fracture Presence Prediction in Unconventional Reservoirs Using Machine Learning and Geostatistical Methods - Workflow and HFTS1 Case', 'name': None, 'id': None, 'location': None, 'display_doi': 'https://doi.org/10.15530/urtec-2022-3721712', 'grant_info': None, 'editors': None, 'authors': 'Peace C. Eze | Lin Y. Hu', 'chairs': None}
https://doi.org/10.15530/urtec-2022-3721712
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