Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model

Shitao Wang, Mohamed Iskandarani, Ashwanth Srinivasan, W. Carlisle Thacker, Justin Winokur, Omar M. Knio

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Polynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model's estimates of the plume's trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate's contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95% percentile of the droplet size and in the entrainment parameters.

Original languageEnglish (US)
Pages (from-to)3488-3501
Number of pages14
JournalJournal of Geophysical Research C: Oceans
Volume121
Issue number5
DOIs
StatePublished - May 1 2016

Fingerprint

Uncertainty analysis
uncertainty analysis
sensitivity analysis
Gas oils
Sensitivity analysis
plumes
flow velocity
plume
oils
entrainment
chaotic dynamics
droplet
propagation
chaos
oil
output
polynomials
gases
gas
traps

Keywords

  • deep water horizon
  • integral plume model
  • polynomial chaos
  • sensitivity analysis
  • uncertainty quantification

ASJC Scopus subject areas

  • Geochemistry and Petrology
  • Geophysics
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science
  • Oceanography

Cite this

Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model. / Wang, Shitao; Iskandarani, Mohamed; Srinivasan, Ashwanth; Thacker, W. Carlisle; Winokur, Justin; Knio, Omar M.

In: Journal of Geophysical Research C: Oceans, Vol. 121, No. 5, 01.05.2016, p. 3488-3501.

Research output: Contribution to journalArticle

Wang, Shitao ; Iskandarani, Mohamed ; Srinivasan, Ashwanth ; Thacker, W. Carlisle ; Winokur, Justin ; Knio, Omar M. / Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model. In: Journal of Geophysical Research C: Oceans. 2016 ; Vol. 121, No. 5. pp. 3488-3501.
@article{2040145110eb44d58e8215b30309d31c,
title = "Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model",
abstract = "Polynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model's estimates of the plume's trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate's contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95{\%} percentile of the droplet size and in the entrainment parameters.",
keywords = "deep water horizon, integral plume model, polynomial chaos, sensitivity analysis, uncertainty quantification",
author = "Shitao Wang and Mohamed Iskandarani and Ashwanth Srinivasan and Thacker, {W. Carlisle} and Justin Winokur and Knio, {Omar M.}",
year = "2016",
month = "5",
day = "1",
doi = "10.1002/2015JC011365",
language = "English (US)",
volume = "121",
pages = "3488--3501",
journal = "Journal of Geophysical Research: Oceans",
issn = "2169-9275",
publisher = "Wiley-Blackwell",
number = "5",

}

TY - JOUR

T1 - Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model

AU - Wang, Shitao

AU - Iskandarani, Mohamed

AU - Srinivasan, Ashwanth

AU - Thacker, W. Carlisle

AU - Winokur, Justin

AU - Knio, Omar M.

PY - 2016/5/1

Y1 - 2016/5/1

N2 - Polynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model's estimates of the plume's trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate's contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95% percentile of the droplet size and in the entrainment parameters.

AB - Polynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model's estimates of the plume's trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate's contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95% percentile of the droplet size and in the entrainment parameters.

KW - deep water horizon

KW - integral plume model

KW - polynomial chaos

KW - sensitivity analysis

KW - uncertainty quantification

UR - http://www.scopus.com/inward/record.url?scp=84971233869&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84971233869&partnerID=8YFLogxK

U2 - 10.1002/2015JC011365

DO - 10.1002/2015JC011365

M3 - Article

VL - 121

SP - 3488

EP - 3501

JO - Journal of Geophysical Research: Oceans

JF - Journal of Geophysical Research: Oceans

SN - 2169-9275

IS - 5

ER -