Real-time prediction of rate of penetration while drilling complex lithologies using artificial intelligence techniques

Author:

Elkatatny SalaheldinORCID

Publisher

Elsevier BV

Subject

General Engineering

Reference63 articles.

1. Standard handbook of petroleum and natural gas engineering;Lyons,2004

2. Eren T, Ozbayoglu ME. Real time optimization of drilling parameters during drilling operations. Paper presented in the SPE Oil and Gas India Conference and Exhibition., Mumbai, India, 20-22 January. SPE-129126-MS. https://doi.org/10.2118/129126-MS; 2019.

3. Payette GS, Spivey BJ, Wang L, Bailey JR, Sanderson D, Kong R, et al. Real-time well-site based surveillance and optimization platform for drilling: technology, basic workflows and field results. Paper presented at the SPE/IADC Drilling Conference and Exhibition, The Hague, The Netherlands, 14-16 March. SPE-184615-MS; 2017. https://doi.org/10.2118/184615-MS.

4. Machine learning methods applied to drilling rate of penetration prediction and optimization-A review;Barbosa;J Petrol Sci Eng,2019

5. Real-time predictive capabilities of analytical and machine learning rate of penetration (ROP) models;Soares;J. Pet. Sci. Eng.,2019

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