Exploring the Spatial Variations of Stressors Impacting Platform Removal in the Northern Gulf of Mexico

Jake R. Nelson,Rodrigo Duran,Lucy Romeo

doi:10.3390/jmse9111223

Abstract

Although progress has been made to advance our understanding of the risks involved in offshore oil extraction activities, a regional scale understanding of factors contributing to losses in infrastructure integrity are lacking. Recent data integration efforts have resulted in a comprehensive database that allows for an unprecedented study of the external and internal factors that impact the structural and operational integrity of offshore platforms in the Gulf of Mexico. This study constitutes some of the initial explorations into that database by focusing on the relationships among a diverse set of variables and the age at which a platform is removed. We apply Geographically Weighted Regression to account for the heterogeneity of the operating environment, finding robust yet unexpected relationships that shed light on some of the factors that influence platform removal. Our findings pave the way for future studies aimed at building actionable knowledge.

Highlights

The majority of offshore oil platforms have an operational design life of 20 to 30 years.Currently, more than 60% of the operating platforms in the Gulf of Mexico (GoM) were installed more than three decades ago [1,2]
structural integrity management (SIM) and other life cycle analytical strategies have been adapted to incorporate stress from additional features, such as the application of corrosion models to predict fatigue life on jacket structures [37]. These evaluations typically focus on one structure at a time and are highly dependent on accurate and consistent inspection records, which tend to be lacking with older platforms [27]
We began by applying singular value decomposition (SVD) to reduce the dimensionality of the platform data set while distilling the data down to the key variables that covary with our target variable, All processing and analyses were performed in Python using the MGWR (Multis Geographically Weighted Regression) and Pysal libraries [68]

Summary

Introduction

The majority of offshore oil platforms have an operational design life of 20 to 30 years.Currently, more than 60% of the operating platforms in the Gulf of Mexico (GoM) were installed more than three decades ago [1,2]. Part of the reason for this extension in operating life comes from advances in reconstruction, repair, and retrofitting techniques on the platforms. Another reason is that extending the operating life is economically attractive [3]. Increasing the time that existing infrastructure remains operational will eventually reduce costs while maximizing energy production and profit. It may play an important role in converting these structures to meet renewable energy demands. This has been a trend since the onset of offshore energy exploration and development [4]. Platform life extension depends heavily on proactive maintenance and monitoring to reduce the risk that critical components fail, resulting in a loss-of-control event [5,6]

Methods

Results

Conclusion