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An investigation of casing structural integrity in shale gas horizontal wells during hydraulic fracturing using FEA and machine learning algorithms. (2021)
Thesis
MOHAMMED, A.I. 2021. An investigation of casing structural integrity in shale gas horizontal wells during hydraulic fracturing using FEA and machine learning algorithms. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1603216

Unconventional oil and gas operators are currently facing the challenge of casing lateral buckling and/or deformation during shale gas wells stimulation through hydraulic fracturing. Failure of the casing during this process can lead to huge financia... Read More about An investigation of casing structural integrity in shale gas horizontal wells during hydraulic fracturing using FEA and machine learning algorithms..

An application of FEA and machine learning for the prediction and optimisation of casing buckling and deformation responses in shale gas wells in an in-situ operation. (2021)
Journal Article
MOHAMMED, A.I., BARTLETT, M., OYENEYIN, B., KAYVANTASH, K. and NJUGUNA, J. 2021. An application of FEA and machine learning for the prediction and optimisation of casing buckling and deformation responses in shale gas wells in an in-situ operation. Journal of natural gas science and engineering [online], 95, article 104221. Available from: https://doi.org/10.1016/j.jngse.2021.104221

This paper proposes a novel way to study the casing structural integrity using two approaches of finite element analysis (FEA) and machine learning. The approach in this study is unique, as it captures the pertinent parameters influencing the casing... Read More about An application of FEA and machine learning for the prediction and optimisation of casing buckling and deformation responses in shale gas wells in an in-situ operation..

Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem. (2021)
Conference Proceeding
ALZA, J., BARTLETT, M., CEBERIO, J. and MCCALL, J. 2021. Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem. In Chicano, F. (ed.) GECCO '21: proceedings of 2021 Genetic and evolutionary computation conference companion, 10-14 July 2021, [virtual conference]. New York: ACM [online], pages 1405-1413. Available from: https://doi.org/10.1145/3449726.3463139

Recent work in combinatorial optimisation have demonstrated that neighbouring solutions of a local optima may belong to more favourable attraction basins. In this sense, the perturbation strategy plays a critical role on local search based algorithms... Read More about Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem..