Unconfined compressive strength (UCS) prediction in real-time while drilling using artificial intelligence tools
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-020-05546-7.pdf
Reference45 articles.
1. Chau KT, Wong RHC (1996) Uniaxial compressive strength and point load strength of rocks. Int J Rock Mech Min Sci Geomech Abstracts 33(2):183–188. https://doi.org/10.1016/0148-9062(95)00056-9
2. Fjar E, Holt RM, Raaen AM, Horsrud P (2008) Petroleum related rock mechanics. Elsevier, Amsterdam
3. Shi X, Meng Y, Li G, Li J, Tao Z, Wei S (2015) Confined compressive strength model of rock for drilling optimization. Petroleum 1(1):40–45.
4. Liu H (2017) Rock mechanics. In: Principles and applications of well logging. Springer, Berlin, Heidelberg. pp. 237–269. https://doi.org/10.1007/978-3-662-54977-3
5. Abdulraheem A, Ahmed M, Vantala A, Parvez T (2009) Prediction of rock mechanical parameters for hydrocarbon reservoirs using different artificial intelligence techniques. In: SPE Saudi Arabia section technical symposium. Society of Petroleum Engineers., https://doi.org/10.2118/126094-MS
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