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Multi-criteria material selection for casing pipe in shale gas wells application. (2022)
Journal Article
MOHAMMED, A.I., BARTLETT, M., OYENEYIN, B., KAYVANTASH, K. and NJUGUNA, J. 2022. Multi-criteria material selection for casing pipe in shale gas wells application. Journal of petroleum exploration and production technology [online], Online First. Available from: https://doi.org/10.1007/s13202-022-01506-0

The conventional method of casing selection is based on availability and/or order placement to manufacturers based on certain design specifications to meet the anticipated downhole conditions. This traditional approach is very much dependent on exper... Read More about Multi-criteria material selection for casing pipe in shale gas wells application..

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..

Does good ESG lead to better financial performances by firms? Machine learning and logistic regression models of public enterprises in Europe. (2020)
Journal Article
DE LUCIA, C., PAZIENZA, P. and BARTLETT, M. 2020. Does good ESG lead to better financial performances by firms? Machine learning and logistics regression models of public enterprises in Europe. Sustainability [online], 12(13), article ID 5317. Available from: https://doi.org/10.3390/su12135317

The increasing awareness of climate change and human capital issues is shifting companies towards aspects other than traditional financial earnings. In particular, the changing behaviors towards sustainability issues of the global community and the a... Read More about Does good ESG lead to better financial performances by firms? Machine learning and logistic regression models of public enterprises in Europe..

Prediction of casing critical buckling during shale gas hydraulic fracturing. (2019)
Journal Article
MOHAMMED, A.I., OYENEYIN, B., BARTLETT, M. and NJUGUNA, J. 2020. Prediction of casing critical buckling during shale gas hydraulic fracturing. Journal of petroleum science and engineering [online], 185, article ID 106655. Available from: https://doi.org/10.1016/j.petrol.2019.106655

Casing deformation during volume fracturing in shale gas horizontal wells is caused by both existing and induced stresses. These stresses jointly alter and compound the stress field around the casing leading to inefficient well stimulation as planned... Read More about Prediction of casing critical buckling during shale gas hydraulic fracturing..

On the definition of dynamic permutation problems under landscape rotation. (2019)
Conference Proceeding
ALZA, J., BARTLETT, M., CEBERIO, J. and MCCALL, J. 2019. On the definition of dynamic permutation problems under landscape rotation. In López-Ibáñez, M. (ed.) Proceedings of the 2019 Genetic and evolutionary computation conference companion (GECCO 2019), 13-17 July 2019, Prague, Czech Republic. New York: ACM [online], pages 1518-1526. Available from: https://doi.org/10.1145/3319619.3326840

Dynamic optimisation problems (DOPs) are optimisation problems that change over time. Typically, DOPs have been defined as a sequence of static problems, and the dynamism has been inserted into existing static problems using different techniques. In... Read More about On the definition of dynamic permutation problems under landscape rotation..

Bayesian network structure learning with integer programming: polytopes, facets and complexity. (2017)
Journal Article
CUSSENS, J., JÄRVISALO, M., KORHONEN, J.H. and BARTLETT, M. 2017. Bayesian network structure learning with integer programming: polytopes, facets and complexity. Journal of artificial intelligence research [online], 58, pages 185-229. Available from: https://doi.org/10.1613/jair.5203

The challenging task of learning structures of probabilistic graphical models is an important problem within modern AI research. Recent years have witnessed several major algorithmic advances in structure learning for Bayesian networks - arguably the... Read More about Bayesian network structure learning with integer programming: polytopes, facets and complexity..

Integer linear programming for the Bayesian network structure learning problem. (2015)
Journal Article
BARTLETT, M. and CUSSENS, J. 2017. Integer linear programming for the Bayesian network structure learning problem. Artificial intelligence [online], 244, pages 258-271. Available from: https://doi.org/10.1016/j.artint.2015.03.003

Bayesian networks are a commonly used method of representing conditional probability relationships between a set of variables in the form of a directed acyclic graph (DAG). Determination of the DAG which best explains observed data is an NP-hard prob... Read More about Integer linear programming for the Bayesian network structure learning problem..