IIARD International Institute of Academic Research and Development

International Journal of Engineering and Modern Technology (IJEMT )

E-ISSN 2504-8848
P-ISSN 2695-2149
VOL. 9 NO. 2 2023

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Compressive Strength and Thickening Time of Cement: A Critical Review of Existing Models

odwin Ededem UDO and Okorie E. Agwu

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Abstract

The quality and integrity of a cement job can determine how long a well will be stable and productive before it needs to be repaired. This is primarily determined by the compressive strength of the cementing material. Because of the economic implications of drilling and cementing oil and gas wells, the oil and gas community and academia have maintained an interest in compressive strength and thickening time of cement measurements. Despite the growing number of published articles on this subject, there is no comprehensive critical review, to the best of the authors' knowledge. The goal of this paper is to provide a broad overview of models and modeling techniques used to estimate cement compressive strength and thickening time, as well as to critically evaluate them. The review's findings are presented in tables in a concise manner for clarity and ease of reference. The information for this review was gathered from a variety of sources. This work heavily relied on several key drilling fluid texts for the theoretical pieces related to compressive strength and thickening time of cement in general. The researcher relied on conference proceedings from the Society of Petroleum Engineers for operational and field studies. In order to contextualize the subject in terms of current practices, these sources were supplemented with articles from peer-reviewed journals. This review is interspersed with critiques of the models, as well as areas in need of improvement. Despite massive efforts in this direction, the results of the bibliometric analysis show that there is no universal model for all situations. Furthermore, a broad review of the literature on recent compressive strength and thickening time models reveals that researchers are drawn to the field of artificial intelligence because of the tremendous opportunities it provides. This review is the first critical compilation of models used to predict compressive strength and thickening time of oilfield ce

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References:

Adamson, K., Birch, G., Gao, E., Hand, S., Macdonald, C., Mack, D and Quadri, A. (1998). High
Pressure High Temperature Well Construction. Oil Field Review, 10(2):36-39.
Ahmad, A., Chaiyasarn, K. Farooq, F., Ahmad, W., Suparp, S. and Aslam, F. (2021). Compressive
Strength Prediction via Gene Expression Programming and Artificial Neural Network (ANN)
For Concrete Containing RCA. Standard Journal of Construction and Buildings. 11:324.

Akintunde, O. P., Olutoge, F. A., Olawale1, S. A. and Afolabi, M. O. (2020). Prediction of the
Compressive Strength of Concrete Containing Bentonite using Artificial Neural Network.
International Journal of Research Studies in Science, Engineering and Technology, 7(11): 13-
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