THE STRUCTURAL INTEGRITY MONITORING SUBMERSIBLE PLATFORM
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The majority of offshore platforms have passed their design lives. The ageing related problems and how to manage these problems is key concern for oil and gas offshore structures. For this reason, offshore structures, especially fixed jacket platforms, should be appropriate conditions for their intended use through their service life. The need to maintain offshore structural integrity has been increased in recent years and plays a significant role in continuous integrity and life extension. This study assess the to assess the integrity of existing offshore infrastructure by collecting data on the offshore environment, associating structural and environmental characteristics to infrastructure, and analyzing the relationships between those variables and the proxy variable used to measure integrity and to identify areas or specific infrastructure that are at-risk of potential failure given the identified relationships between infrastructure integrity and the associated structural and environmental variables.
Chapter One
Introduction
1.1 Background of the study
1.2 Statement of the problem
1.3 Aims of the study
1.4 Objectives of the study
1.5 Justification of the study
1.6 Scope of research
1.7 Limitation of the study
Chapter 2
Literature Review
Chapter 3
Materials and Methods
Chapter 4
Results and Discussion
Chapter 5
Conclusion and Recommendation
CHAPTER ONE
1.0 INTRODUCTION
1.1 BACKGROUND OF THE STUDY
The majority of offshore structures worldwide are reaching or are beyond their design lives. The expected life for offshore structure platforms is not so precise. However, the design life is predicted to be between 20 to 25 years depending on excessive loads, for example, environmental loads including wave, current loads, and impact loads during lifetime. These loads cause fatigues, cracks, corrosion and other essential damages in structures. Such ageing structures should always be under supervision and extensively maintained to decrease the possibility of damage from early stages that could result in loss of integrity. This can be achieved by developing robustness, accuracy, efficiencies and cost-effectiveness that allow data collection about the condition of the platform (Aeran et al., 2017).
Almost half of the North Sea offshore platforms are approaching or have already passed their design life and creating complicated problems for the SI management of these platforms (Ersdal et al., 2018). Therefore, there is a requirement for SI Monitoring techniques to increase certainty in structural integrity and to minimize inspection expenses. With SI monitoring techniques, structures can be inspected over an interval using various measurements, providing information about the offshore platforms' structural integrity, safety, and reliability (May et al., 2018).
Structural integrity provides data to ensure the continuing safety of vital structures. The real-time information obtained through structural integrity monitoring systems can be used during normal operation, construction, repair or upgrades. This continuous monitoring of structures means that potential issues can be identified and appropriate action taken to rectify them.
SIM techniques to detect these failure modes in the last ten years. The description of SIM techniques, as well as advantages, limitations, maturity in the offshore industry, probability of detection (POD) and monitoring capabilities of these techniques, have been reviewed in this thesis study.
1.2 STATEMENT OF THE PROBLEM
The majority of submersible platforms have passed their design lives. The ageing related problems and how to manage these problems is key concern for oil and gas offshore structures. For this reason, offshore structures, especially fixed jacket platforms, should be appropriate conditions for their intended use through their service life. The need to maintain offshore submersible structural integrity has been increased in recent years and plays a significant role in continuous integrity and life extension. Early detection of damaged items can prolong the life of platforms by replacing them and results in reducing maintenance expenses and increasing safety. Therefore, SI monitoring techniques are widely used for the early detection of damage in offshore submersible structures. This study provides a structural integrity monitoring submersible platform.
1.3 AIM OF THE STUDY
The purpose of this thesis is to study the structural integrity monitoring submersible platform.
1.4 OBJECTIVES OF THE STUDY
The objectives of this study are:
- To provide the basic information on generally available SI monitoring techniques.
- To assess the integrity of existing offshore infrastructure by collecting data on the offshore environment, associating structural and environmental characteristics to infrastructure, and analyzing the relationships between those variables and the proxy variable used to measure integrity.
- To identify areas or specific infrastructure that are at-risk of potential failure given the identified relationships between infrastructure integrity and the associated structural and environmental variables.
1.5 MOTIVATION OF THE STUDY
As stated earlier, early detection of damaged items can prolong the life of platforms by replacing them and results in reducing maintenance expenses and increasing safety. The importance of maintaining structural integrity offshore is increasingly recognized and structural inspection plays a significant role in demonstrating ongoing integrity and the potential for life extension. Structural integrity (SI) monitoring provides greater confidence in structural integrity or to reduce inspection cost. It has been found that offshore experience of SI monitoring is limited to date and that current systems are for bespoke applications.
1.6 SCOPE OF THE STUDY
The scope of this work covers the review and appraisal of SI monitoring methods which can be applied to submersibles structures. The study also identify factors involved in infrastructure degradation through the development and application of big data analytics, machine learning, and advanced spatio-temporal analysis. The project leverages existing data and combines it with new information on offshore oil and gas structures and the ambient offshore environment in an effort to identify patterns associated with infrastructure integrity. Building on the identified trends and patterns, this project incorporates exploratory analytics and spatial analysis tools in conjunction with machine learning and statistical models to characterize the condition of existing platforms in the offshore environment and predict their risk of failure.
CHAPTER FIVE
The purpose of this project was to develop and apply big data analytics, ML, and advanced spatio-temporal analysis to assess the current state of existing infrastructure. In this first phase of research, the team uncovered several important factors related to the integrity of offshore infrastructure. This included both structural and environmental correlates, as well as other information on tropical storms and hurricanes. Furthermore, this work supports the continued exploration of integrity from several vantage points. Here, three predictive models with varying strengths and weaknesses were developed. Although different, these models work together to corroborate findings and support the re-evaluation of contradictory information. This happened in several instances which has made this investigation into offshore integrity more robust.
Several important strides were made through this work, that will support a deeper understanding of offshore integrity and the factors that effect it.
First, to the best of the research team’s knowledge there is no publicly available dataset related to offshore infrastructure integrity. This is likely due to the fact that the integrity of individual structures is proprietary information. The costs of collecting the data using advanced monitoring is perhaps one reason for this deficiency. Moreover, a dataset that spanned all GoM structures is even less likely. To that extent, this report has outlined a possible method for investigating offshore integrity across a broad geographic range using a unique set of variables that are hypothesized to relate to integrity. What’s more, this method is not unique to the GoM and could theoretically be deployed to any offshore (or even onshore) location in the world. With this information in hand, the state of offshore infrastructure can be made more transparent, enabling more proactive approaches to impact mitigation, response planning, and infrastructure management.
Second, the correlation analysis was used to investigate the relationship between the components associated with each structure and a measure of integrity visa vis incidents and incident severity. Multiple structural factors were significantly correlated with integrity; however, the correlation analysis also revealed that several of these structural components were correlated with one another. These results informed later models and identified pathways toward more parsimonious model formulations.
Third, the predictive models developed in this work show a respectable degree of accuracy when it comes to predicting the age at which platforms are removed. Admittedly, a lot of that predictive power comes from only a few variables, several of which are related to hurricanes and storms. Conceptually, the interaction between storms and age at removal makes sense; more storms put higher stress on structural components which leads to earlier removal. However, it would also be true that as structures age they will inherently experience more storms. At this point it cannot be determined from this analysis with certainty whether tropical storms are causing the platforms to be removed. If in the model tropical storms are contributing to the removal, it would be prudent to understand the significance of that role in relation to other potential factors that contribute to the deterioration of integrity.
When it comes to next steps, there are many. The continued identification of data that can be leveraged to explain integrity is perhaps the most prudent. This includes the ongoing work of translating historical structure incidents into a useable data format and adding well and geohazard information to the analysis for a more system-wide approach. The current models rely heavily on a small subset of factors that may or may not be causing a decrease in integrity.
5.3 RECOMMENDATION
Future recommended research includes causal relations, for example with statistical tests such as Granger Causality (Runge et al., 2019), or through information theory estimates (San Liang, 2014, 2015). Much of this future work will rely on the ability to collect and integrate new data and sources of information, but it will also depend on the ability to enhance the measure of integrity should there be a need in the future.
CHAPTER TWO: The chapter one of this work has been displayed above. The complete chapter two of"the structural integrity monitoring submersible platform"is also available. Order full work to download. Chapter two of"the structural integrity monitoring submersible platform"consists of the literature review. In this chapter all the related work on"the structural integrity monitoring submersible platform"was reviewed.
CHAPTER THREE: The complete chapter three of"the structural integrity monitoring submersible platform"is available. Order full work to download. Chapter three of"the structural integrity monitoring submersible platform"consists of the methodology. In this chapter all the method used in carrying out this work was discussed.
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CHAPTER FIVE: The complete chapter five of"the structural integrity monitoring submersible platform" is available. Order full work to download. Chapter five of"the structural integrity monitoring submersible platform" consist of conclusion, recommendation and references.
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