Probabilistic downtime estimation for sequential marine operations

Abstract A marine project consists of series of operations, with each operation subject to a predefined operational limit and duration. If actual weather conditions exceed the operational limit, the operation cannot be executed and hence downtime occurs. An accurate assessment of uncertainties and the expected downtime during a marine project is important in the tender and execution phase. This paper proposes a new probabilistic model for downtime estimation. It utilizes linked Markov chains that use actual metocean conditions to produce binary workability sequences for each operation. Synthetic time-series can be generated based on the statistics of the past observations and more project simulations are realizable, reducing the simulation uncertainty. The capabilities and limitations of the proposed approach are illustrated in a case study for a hypothetical project in the Tasman Sea.

[1]  K. Anastasiou,et al.  Operability analysis of marine projects based on Markov theory , 1996 .

[2]  Michael Muskulus,et al.  A multivariate Markov Weather Model for O&M Simulation of Offshore Wind Parks☆ , 2013 .

[3]  Rachel Nicholls-Lee,et al.  Optimisation of marine energy installation operations , 2013 .

[4]  D. Vere-Jones.  Markov Chains , 1972, Nature.

[5]  Wei Xie,et al.  Statistical Uncertainty Analysis for Stochastic Simulation , 2020, 2011.04207.

[6]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[7]  David Infield,et al.  Offshore wind turbine maintenance access: a closed‐form probabilistic method for calculating delays caused by sea‐state , 2013 .

[8]  J. J. de Wilde,et al.  Direct Time Domain Downtime Assessment For LNG Operations Using Computer Cluster , 2009 .

[9]  Baris Tan,et al.  Markov chain test for time dependence and homogeneity: An analytical and empirical evaluation , 2002, Eur. J. Oper. Res..

[10]  J N Hall.  Use of risk analysis in North Sea projects , 1986 .

[12]  A Nonhomogeneous Markov Model for Daily Precipitation , 1996 .

[13]  M. Mathiesen,et al.  Estimation of wave height duration statistics , 1994 .

[14]  T. W. Anderson,et al.  Statistical Inference about Markov Chains , 1957 .

[15]  Yuka Kikuchi,et al.  Assessment of weather downtime for the construction of offshore wind farm by using wind and wave simulations , 2016 .

[16]  T. Lewis,et al.  Weather window analysis of Irish west coast wave data with relevance to operations & maintenance of marine renewables , 2013 .

[17]  John Bowers,et al.  Weather Risk in Offshore Projects , 1994 .

[18]  A. Ang,et al.  Analysis of Activity Networks under Uncertainty , 1975 .

[19]  K. Anastasiou,et al.  Persistence statistics of marine environmental parameters from Markov theory, Part 1: analysis in discrete time , 1996 .

[20]  J. Rip.  Probabilistic downtime analysis for complex marine projects: A state-of-the-art model based on Markov theory to generate binary workability sequences for sequential operations , 2015 .

[21]  Marc Prevosto,et al.  Survey of stochastic models for wind and sea state time series , 2007 .

[22]  Remmelt J. van der Wal,et al.  Downtime Analysis Techniques for Complex Offshore and Dredging Operations , 2004 .

[23]  Sheldon M. Ross,et al.  Introduction to probability models , 1975 .

[24]  Oswaldo Morales-Nápoles,et al.  Probabilistic scheduling of offshore operations using copula based environmental time series: An application for cable installation management for offshore wind farms , 2016 .

[25]  Finn Gunnar Nielsen,et al.  Seasonal Modeling of Multivariate Distributions of Metocean Parameters With Application to Marine Operations , 2004 .

[26]  Tak Kuen Siu,et al.  Markov Chains: Models, Algorithms and Applications , 2006 .

[27]  N. Hogben,et al.  The estimation of wave height and wind speed persistence statistics from cumulative probability distributions , 1986 .

[28]  P.H.A.J.M. van Gelder,et al.  Statistical methods for the risk-based design of civil structures , 2000 .

[29]  Carlos Guedes Soares,et al.  Weather window analysis of a site off Portugal , 2014 .

[30]  Felice Arena,et al.  Estimation of Downtime and of Missed Energy Associated with a Wave Energy Converter by the Equivalent Power Storm Model , 2015 .

[31]  William H. Press,et al.  Numerical recipes in C , 2002 .

[32]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[33]  Lars Johanning,et al.  Calculating weather windows: Application to transit, installation and the implications on deployment success , 2013 .