In oil well drilling, the quality of cement bonding (CBQ)
between well casing and formation rock, is very important because good CBQ ensures the success of oil and gas exploitation from a reservoir.
I applied ANN to predict network traffic and perform classification. I don't know of paper on how to predict cement bonding quality using ANN. However, ANN as a classification or machine learning optimization technique would require,in your case, some set of previous data containing,say, cement bonding with low quality, cement bond with average quality and that of high quality for supervised learning method so that the ANN can discriminate between different quality of cement bonding and predict the quality. I hope you find this useful.
Yes, there are many papers available at www.OnePetro.org about this topic. See link below for some results:
https://www.onepetro.org/search?q=predicting+Oil+Well+Cement+Bonding+Quality+using+Artificial+Neural+Networks&peer_reviewed=&published_between=&from_year=&to_year=
Thank you Dear Mr. Sallam,
I have see this website it's interesting, but for this articles must be purchased, and I have not a credit card.
Best regards
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