Forecasting Marine and Structural Integrity Parameters for Offshore Platforms

2015 ◽  
Author(s):  
Igor Prislin ◽  
Reza Jafarkhani ◽  
Soma Maroju
Keyword(s):  
Machine Learning ◽  
Data Management ◽  
Structural Integrity ◽  
Operational Risk ◽  
Computer Programs ◽  
Measured Data ◽  
Offshore Platforms ◽  
Integrity Monitoring ◽  
Design Values ◽  
Paper Address

Marine and structural integrity monitoring for offshore platforms is the cornerstone for managing operational risk and safety. Measuring platform responses and loads enables comparisons with design values thus ensuring that the risk does not exceed the designed limits. This paper discusses an advanced data management that is based on machine learning, a set of specialized computer programs that can learn and generalize the platform responses from measured data. The programs should produce sufficiently accurate predictions in previously unseen cases. Examples provided in the paper address capabilities for forecasting the marine and structural integrity parameters.

Operational Supports for Offshore Platforms: From System Integrity Monitoring to Marine Assurance and Safety

2008 ◽  
Author(s):  
Igor Prislin ◽  
Michael Goldhirsh
Keyword(s):  
Data Management ◽  
Data Center ◽  
Historical Data ◽  
Offshore Platforms ◽  
Integrity Monitoring ◽  
Full Life Cycle ◽  
System Integrity ◽  
Client Data ◽  
System Maintenance

The paper discusses typical full life-cycle of operational support for offshore platforms based on integrity monitoring systems, data management, and system maintenance services. The paper focuses on data management using a Client Data Center that provides offshore and onshore data hosting, postprocessing, and long term archive via the Internet. Properly selected, operational support provides elements to manage historical data critical to future assessments of the offshore-platform structural health, including the fatigue life of vital systems like mooring, tendons, and risers. The paper highlights the benefits of carrying out operational support continuously with the major goal — to make offshore platforms safe and profitable.

Managing Structural Integrity of Offshore Platforms: Looking Back to Drive the Future

2013 ◽  
Author(s):  
Roberto Piva ◽  
Margherita Latronico ◽  
Andrea Nero ◽  
Stefano Sartirana
Keyword(s):  
Structural Integrity ◽  
Offshore Platforms ◽  
The Future ◽  
Looking Back

scholarly journals The Open Data Challenge: An Analysis of 124,000 Data Availability Statements and an Ironic Lesson about Data Management Plans

2020 ◽  
Vol 2 (4) ◽  
pp. 554-568
Author(s):  
Chris Graf ◽  
Dave Flanagan ◽  
Lisa Wylie ◽  
Deirdre Silver
Keyword(s):  
Machine Learning ◽  
Data Management ◽  
Open Data ◽  
Research Data ◽  
Data Availability ◽  
Policy Changes ◽  
Management Plans ◽  
Trends Over Time ◽  
New Research ◽  
Over Time

Data availability statements can provide useful information about how researchers actually share research data. We used unsupervised machine learning to analyze 124,000 data availability statements submitted by research authors to 176 Wiley journals between 2013 and 2019. We categorized the data availability statements, and looked at trends over time. We found expected increases in the number of data availability statements submitted over time, and marked increases that correlate with policy changes made by journals. Our open data challenge becomes to use what we have learned to present researchers with relevant and easy options that help them to share and make an impact with new research data.

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