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Corrosion Degree Evaluation of Polymer Anti-Corrosive Oil Well Cement under an Acidic Geological Environment Using an Artificial Neural Network

Oil well cement is prone to corrosion and damage in carbon dioxide (CO(2)) acidic gas wells. In order to improve the anti-corrosion ability of oil well cement, polymer resin was used as the anti-corrosion material. The effect of polymer resin on the mechanical and corrosion properties of oil well ce...

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Detalles Bibliográficos
Autores principales: Zhao, Jun, Chen, Rongyao, Liu, Shikang, Zhou, Shanshan, Xu, Mingbiao, Dai, Feixu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10674542/
https://www.ncbi.nlm.nih.gov/pubmed/38006165
http://dx.doi.org/10.3390/polym15224441
Descripción
Sumario:Oil well cement is prone to corrosion and damage in carbon dioxide (CO(2)) acidic gas wells. In order to improve the anti-corrosion ability of oil well cement, polymer resin was used as the anti-corrosion material. The effect of polymer resin on the mechanical and corrosion properties of oil well cement was studied. The corrosion law of polymer anti-corrosion cement in an acidic gas environment was studied. The long-term corrosion degree of polymer anti-corrosion cement was evaluated using an improved neural network model. The cluster particle algorithm (PSO) was used to improve the accuracy of the neural network model. The results indicate that in acidic gas environments, the compressive strength of polymer anti-corrosion cement was reduced under the effect of CO(2), and the corrosion depth was increased. The R(2) of the prediction model PSO-BPNN3 is 0.9970, and the test error is 0.0136. When corroded for 365 days at 50 °C and 25 MPa pressure of CO(2), the corrosion degree of the polymer anti-corrosion cement was 43.6%. The corrosion depth of uncorroded cement stone is 76.69%, which is relatively reduced by 33.09%. The corrosion resistance of cement can be effectively improved by using polymer resin. Using the PSO-BP neural network to evaluate the long-term corrosion changes of polymer anti-corrosion cement under complex acidic gas conditions guides the evaluation of its corrosion resistance.