[CCoE Notice] Thesis Announcement

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[Dissertation Defense Announcement at the Cullen College of Engineering]

REDUCING THE RISK OF GAS LEAKS INTO THE OCEAN FLOOR INDUCED BY OFFSHORE PRODUCTION WELL FAILURE IN THE GULF OF MEXICO

Thales de Oliveira Souza

December 2, 2022; 9:00 AM - 11:00 AM (CST) Location: Technology Bridge Room 104
Committee Chair:
Kyung Jae Lee, Ph.D.

Committee Members:
Christine Ehlig-Economides, Ph.D. | George K. Wong, Ph.D. | S.M. Farouq Ali, Ph.D.

Abstract

Considering the high number of wells in the Gulf of Mexico having a risk of leaking gas into the surrounding formations, a deep understanding of the fate and transport of gas released from damaged wells is of special relevance for hazard assessment and prevention in offshore operations. This work explores a novel strategy to reduce the risk and impact of contaminant releases in the Gulf of Mexico by analyzing the applicability of machine learning technology as a tool to forecast the broaching information in a loss of containment scenario of an offshore well.

A conceptual 3-D model was used to simulate different cases of subsurface containment failure. The TOUGH+HYDRATE code for the simulation of system behavior in hydrate-bearing media was used to generate the data regarding the broaching day and location, and the hydrate mass generated and the total released CH4 in gas phase in the system.

We trained six Artificial Neural Networks (ANN) to be data-driven models for the prediction of the different outputs. From the six models created and trained, four of them were able to find a strong or very strong correlation between the input and output features during training and when tested with the full dataset.

We used an additional permeability model for measuring the network’s generalization. When presented with this validation dataset, the outstanding performance of the ANN models indicated their reliability in the prediction of the broaching parameters, and the significant generalization capability of the models. [Engineered For What's Next]




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