AUV-Based 3D Laser Inspection for Structural Integrity Management in Deepwater Fields

2014 ◽  
Author(s):  
T. Reeves ◽  
D. McLeod ◽  
C. Embry ◽  
B. Nickerson
Keyword(s):  
Structural Integrity ◽  
Integrity Management

Testing of Acoustic Emission Technology to Detect Cracks and Corrosion in the Marine Environment

2010 ◽  
Vol 26 (02) ◽  
pp. 106-110
Author(s):  
Ge Wang ◽  
Michael Lee ◽  
Chris Serratella ◽  
Stanley Botten ◽  
Sam Ternowchek ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Structural Integrity ◽  
Pilot Project ◽  
Development Project ◽  
Management Program ◽  
Pipeline System ◽  
Inspection Planning ◽  
Structural Degradation ◽  
Integrity Management ◽  
Acoustic Emission Technology

Real-time monitoring and detection of structural degradation helps in capturing the structural conditions of ships. The latest nondestructive testing (NDT) and sensor technologies will potentially be integrated into future generations of the structural integrity management program. This paper reports on a joint development project between Alaska Tanker Company, American Bureau of Shipping (ABS), and MISTRAS. The pilot project examined the viability of acoustic emission technology as a screening tool for surveys and inspection planning. Specifically, testing took place on a 32-year-old double-hull Trans Alaska Pipeline System (TAPS) trade tanker. The test demonstrated the possibility of adapting this technology in the identification of critical spots on a tanker in order to target inspections. This targeting will focus surveys and inspections on suspected areas, thus increasing efficiency of detecting structural degradation. The test has the potential to introduce new inspection procedures as the project undertakes the first commercial testing of the latest acoustic emission technology during a tanker's voyage.

A Hybrid Topside Structural Approach to the Management of Aging Fleet

2021 ◽  
Author(s):  
Biramarta Isnadi ◽  
Luong Ann Lee ◽  
Sok Mooi Ng ◽  
Ave Suhendra Suhaili ◽  
Quailid Rezza M Nasir ◽  
...  
Keyword(s):  
Structural Integrity ◽  
Metal Loss ◽  
Web Based ◽  
Strong Basis ◽  
Asset Risk ◽  
Risk Ranking ◽  
Design Life ◽  
Industry Standards ◽  
Integrity Management ◽  
Inspection Data

Abstract The objective of this paper is to demonstrate the best practices of Topside Structural Integrity Management for an aging fleet of more than 200 platforms with about 60% of which has exceeded the design life. PETRONAS as the operator, has established a Topside Structural Integrity Management (SIM) strategy to demonstrate fitness of the offshore topside structures through a hybrid philosophy of time-based inspection with risk-based maintenance, which is in compliance to API RP2SIM (2014) inspection requirements. This paper shares the data management, methodology, challenges and value creation of this strategy. The SIM process adopted in this work is in compliance with industry standards API RP2SIM, focusing on Data-Evaluation-Strategy-Program processes. The operator HSE Risk Matrix is adopted in risk ranking of the topside structures. The main elements considered in developing the risk ranking of the topside structures are the design and assessment compliance, inspection compliance and maintenance compliance. Effective methodology to register asset and inspection data capture was developed to expedite the readiness of Topside SIM for a large aging fleet. The Topside SIM is being codified in the operator web-based tool, Structural Integrity Compliance System (SICS). Identifying major hazards for topside structures were primarily achieved via data trending post implementation of Topside SIM. It was then concluded that metal loss as the major threat. Further study on effect of metal loss provides a strong basis to move from time-based maintenance towards risk-based maintenance. Risk ranking of the assets allow the operator to prioritize resources while managing the risk within ALARP level. Current technologies such as drone and mobile inspection tools are deployed to expedite inspection findings and reporting processes. The data from the mobile inspection tool is directly fed into the web based SICS to allow reclassification of asset risk and anomalies management.

scholarly journals Integrity Management of Marine Structures; With Emphasis on Design for Structural Robustness

2018 ◽  
Author(s):  
Torgeir Moan
Keyword(s):  
Structural Damage ◽  
Structural Integrity ◽  
Oil And Gas ◽  
Offshore Structures ◽  
Design Standards ◽  
Limit States ◽  
Fabrication Errors ◽  
Integrity Management ◽  
Operational Errors ◽  
And Control

Based on relevant accident experiences with oil and gas platforms, a brief overview of structural integrity management of offshore structures is given; including an account of adequate design criteria, inspection, repair and maintenance as well as quality assurance and control of the engineering processes. The focus is on developing research based design standards for Accidental Collapse Limit States to ensure robustness or damage tolerance in view damage caused by accidental loads due to operational errors and to some extent abnormal structural damage due to fabrication errors. Moreover, it is suggested to provide robustness in cases where the structural performance is sensitive to uncertain parameters. The use of risk assessment to aid decisions in lieu of uncertainties affecting the performance of novel and existing offshore structures, is briefly addressed.

Structural Integrity Management (Sim) via a Digitalized Structural Integrity Compliance System

2021 ◽  
Author(s):  
Riaz Khan ◽  
Sok Mooi Ng ◽  
Biramarta Isnadi ◽  
Luong Ann Lee ◽  
Syahnaz Omar ◽  
...  
Keyword(s):  
Structural Integrity ◽  
Integrity Management

Structural Integrity Management Framework for Mobile Installations

2011 ◽  
Author(s):  
A. Stacey ◽  
J. V. Sharp
Keyword(s):  
Structural Integrity ◽  
Hazard Identification ◽  
Management Policy ◽  
Audit Review ◽  
Offshore Installations ◽  
Safety Case ◽  
Integrity Management ◽  
Policy Objectives ◽  
Systems Maintenance ◽  
The Uk

This paper presents a primary integrity management (PIM) framework for mobile installations (semi-submersibles and self elevating installations) and permanently moored floating installations (FPSOs, FSUs, etc.). The primary integrity of self-elevating and floating installations depends on both the primary structure and additional systems. The framework is based upon the UK regulatory requirements for offshore installations, including the need for a thorough review of the safety case accounting for any changes in condition and future plans and verification of the primary integrity management (PIM) process. Requirements and guidance are provided for all aspects of the integrity management process covering: • primary integrity hazard identification and risk control; • resources, organisation and management, including competency assurance; • information management and documentation; • primary integrity management policy, objectives and strategy; • inspection, examination and testing; • evaluation of structure and other primary systems; • maintenance, repair and upkeep; • audit, review and continual improvement. The framework also contains guidance based on the application of existing standards and industry published documents. Finally, guidance is given on the implementation of the framework.

Alternative Framework for Structural Integrity Management of Jacket Platform Beyond its Design Life

2017 ◽  
Author(s):  
A. Kongchang ◽  
A. Danthainum ◽  
T. Chattratichart ◽  
P. Sonachai ◽  
T. Thavornsuk ◽  
...  
Keyword(s):  
Structural Integrity ◽  
Jacket Platform ◽  
Alternative Framework ◽  
Design Life ◽  
Integrity Management

Safe Operation of Jacket Platforms in a Major Oil Field in the North Sea

2018 ◽  
Author(s):  
Ingar Scherf ◽  
Trine Hansen ◽  
Gudfinnur Sigurdsson
Keyword(s):  
Emergency Preparedness ◽  
Structural Integrity ◽  
Fatigue Cracks ◽  
Regulatory Compliance ◽  
Offshore Structures ◽  
Oil Field ◽  
Inspection Planning ◽  
Original Design ◽  
Safe Operation ◽  
Integrity Management

Offshore Structures operate for decades in extremely hostile environments. It is important during this period that the structural integrity is efficiently managed to ensure continuous and safe operation. Increased use of enhanced oil and gas recovery means it is likely that many existing installations will remain operational for a significant period beyond the original design life. The operator needs to capture, evaluate and, if necessary, mitigate design premise changes which inevitably occur during the life of a structure. Further, advances in knowledge and technology may imply changes in codes and standards as well as in analysis methodologies. Changes in corporate structures, transfer of operator responsibility and retirement of experienced engineers call for reliable means to transfer historical data and experience to new stakeholders. Effective emergency preparedness capabilities, structural integrity assessments and inspection planning presuppose that as-is analysis models and corresponding information are easily accessible. This paper presents an implementation of the in-service integrity management process described in the new revision of NORSOK standard N-005 [1] for a large fleet of jackets at the Norwegian Continental Shelf. The process, comprising management of design premise changes as well as state-of-the-art technical solutions over a range of disciplines, has enabled the operator to prolong the service life with decades at minimum investments. A structure integrity management system (SIMS) has been developed and digitized over years and streamlined to meet the needs and challenges in the operation and management of the jacket platforms. SIMS enables a rather lean organization to control the structural integrity status of all load-bearing structures at any time. Platform reinforcements and modifications along with other operational risk reducing measures like unman the platforms in severe storms enable continued use with the same level of safety as for new manned platforms. Advanced analyses are used to document regulatory compliance. Modern fatigue and reliability based inspection planning analyses have reduced the costs needed for inspection of fatigue cracks significantly. The benefits from the SIMS system are substantial and the resulting safety and productivity gains are apparent. The continuity of knowledge and experience is maintained, reducing risk to safety and regularity. The digital transformation related to management of structural integrity status as described in NORSOK standard N-005 is realized through SIMS.

A Bayesian Machine Learning Approach for Efficient Integrity Management of Steel Lazy Wave Risers

2020 ◽  
Author(s):  
Rasoul Hejazi ◽  
Andrew Grime ◽  
Mark Randolph ◽  
Mike Efthymiou
Keyword(s):  
Machine Learning ◽  
Fatigue Failure ◽  
Learning Process ◽  
Predictive Models ◽  
Structural Integrity ◽  
Degradation Mechanism ◽  
Data Driven ◽  
Practical Implementation ◽  
Integrity Management

Abstract In-service integrity management (IM) of steel lazy wave risers (SLWRs) can benefit significantly from quantitative assessment of the overall risk of system failure as it can provide an effective tool for decision making. SLWRs are prone to fatigue failure within their touchdown zone (TDZ). This failure mode needs to be evaluated rigorously in riser IM processes because fatigue is an ongoing degradation mechanism threatening the structural integrity of risers throughout their service life. However, accurately evaluating the probability of fatigue failure for riser systems within a useful time frame is challenging due to the need to run a large number of nonlinear, dynamic numerical time domain simulations. Applying the Bayesian framework for machine learning, through the use of Gaussian Processes (GP) for regression, offers an attractive solution to overcome the burden of prohibitive simulation run times. GPs are stochastic, data-driven predictive models which incorporate the underlying physics of the problem in the learning process, and facilitate rapid probabilistic assessments with limited loss in accuracy. This paper proposes an efficient framework for practical implementation of a GP to create predictive models for the estimation of fatigue responses at SLWR hotspots. Such models are able to perform stochastic response prediction within a few milliseconds, thus enabling rapid prediction of the probability of SLWR fatigue failure. A realistic North West Shelf (NWS) case study is used to demonstrate the framework, comprising a 20” SLWR connected to a representative floating facility located in 950 m water depth. A full hindcast metocean dataset with associated statistical distributions are used for the riser long-term fatigue loading conditions. Numerical simulation and sampling techniques are adopted to generate a simulation-based dataset for training the data-driven model. In addition, a recently developed dimensionality reduction technique is employed to improve efficiency and reduce complexity of the learning process. The results show that the stochastic predictive models developed by the suggested framework can predict the long-term TDZ fatigue damage of SLWRs due to vessel motions with an acceptable level of accuracy for practical purposes.

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