Interview with research talents

Akinyemi Olugbenga Akinsanya
MSc. in Offshore Technology

Akinyemi's background

I have a bachelor degree (BSc first class honours) in Civil Engineering from University of Benin, Nigeria. After graduating, I worked in a leading consulting structural engineering firm: Integrated Advanced Analysts (IAA) Associates Ltd, for 2years where I developed core technical competencies in structural analysis and design. I also worked for Oceon Engineers (a Subsidiary of Subsea7 France) as an offshore/subsea structural engineer for 3.5 years, where I was involved in several local and international oil and gas subsea projects in France and Nigeria. Afterwards, I proceeded to pursue a master’s degree in Offshore Technology with specialization in marine and subsea technology at the University of Stavanger, Norway. I completed my MSc study with a research project in collaboration with IKM Ocean Design, Norway. After completing my MSc degree, I moved to Aalborg with my wife and daughter, to pursue a doctorate (PhD) studies on Risk Informed Asset Integrity Management of Subsurface Wells and Pressure Vessels at Aalborg University in collaboration with the Danish Hydrocarbon Research and Technology Centre (DHRTC).

Present your project

I am currently working on developing a methodology to facilitate the identification of optimal decision strategy for inspection and maintenance of subsea oil and gas production wells and related components with respect to corrosion and scale degradation mechanisms. The overall objective of the project is to reduce high operating cost of production/injection wells, and to preserve and extend their service lives.

What do you expect the major challenges in your area of study will be?

Corrosion and scales deposition are the major cause of degradation of production/injection wells. The development and propagation of these degradation processes are highly stochastic, hence prediction of well performance and monitoring/inspections results are subject to uncertainties (epistemic and aleatory). The main challenge is to identify the optimal strategy for inspection and maintenance under these uncertainties. Other challenge is to model the sequential or non-linear decision problem, since inspection and maintenance decisions (regarding intervention and workover) are based on production and reservoir problematics.

How do you plan to contribute in solving these problems?

I intend to adapt the risk-based approach/methodology for asset integrity management, which includes optimization of decision strategies for inspection and maintenance. The approach will be based on probabilistic models of the production well degradations, monitoring quality or reliability and adverse system consequence model. In practical terms, this means I will: (a) identify and formulate a framework for risk based inspection and maintenance for the production/injection wells; (b) develop a model and tool for consequence evaluation; (c) formulate and design a tool for reliability and risk updating within Bayesian probabilistic framework. The models and tools will take into account both epistemic and aleatory uncertainties associated with degradation prediction, defect detection and defect size precision.

What are your expectations for your future career?

My expectation after the PhD study is to disseminate the knowledge acquired by taken up either an academic (as a researcher-postdoc etc.) or industry position (Research and development) where I can be involved fully  in the development of engineering tools for RBIM and further improve the methods of asset reliability and integrity management.