Abstract:
Model data used for forward propagation of uncertainty and sensitivity analysis in an integral plume model. This dataset consists of oil plume ensemble simulations generated using Texas A&M oil calculator (TAMOC, version 0.1.5, https://github.com/socolofs). We quantify the uncertainty of the model outputs caused by the uncertainty of 6 model inputs parameters in this experiment, including entrainment coefficient, entrainment ratio, gas to oil ratio, flow rate, 95 percentile of droplet size (d95) and droplet size distribution spreading ratio. Only plume trap height, peel height and various gas mass fluxes (methane, ethane, propane) as a function of depth are included. Two experiments were conducted: one for low flow rate uncertainty scenario and one for high flow rate uncertainty scenario. For each experiment, a training dataset and a validation dataset are included. This dataset supports the following publication: Wang, S., Iskandarani, M., Srinivasan, A., Thacker, W. C., Winokur, J., & Knio, O. M. (2015). Propagation of uncertainty and sensitivity analysis in an integral oil‐gas plume model. Journal of Geophysical Research: Oceans.
Suggested Citation:
Shitao Wang. 2017. Four ensembles of TAMOC integral oil-gas plume simulations for uncertainty analysis on May 30, 2010. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N73T9F80
Data Parameters and Units:
This dataset consists different ensemble simulations of the plume trap height (m), peel height (m) and various gas mass fluxes (kg/s) (methane, ethane, propane) as a function of depth (m) . The trap height is defined as the level where the momentum of the downward-moving outer plume becomes zero and the peel height is defined as the level where the momentum of the upward-rising inner plume becomes zero. All the plume simulations use the CTD profile from R/V Brooks McCall at Station B54 (28°43.945'N, 88°22.607'W). The six uncertainty input parameters are entrainment coefficient, entrainment ratio, gas to oil ratio, flow rate, 95 percentile of droplet size (d95) and droplet size distribution spreading ratio. This dataset consists the perturbations we applied on these parameters (normalized to [-1,1]). The details of each data file and their purposes are as follows: Training dataset: 1) 200-memeber Latin Hypercube Sampling (LHS) training ensemble for high uncertainty experiment. (simulation_high_training.mat) 2) 200-memeber LHS training ensemble for low uncertainty experiment. (simulation_low_training.mat) Validation dataset: 3) 2000-memeber LHS validation ensemble for high uncertainty experiment. (simulation_high_validation.mat, only 1999 ensemble members are included since one simulation fails due to the model instability) 4) 2000-memeber LHS validation ensemble for low uncertainty experiment. (simulation_low_validation.mat, only 1998 ensemble members are included since two simulations fail due to the model instability) Each dataset file contains: 1) gas1(methane): methane mass fluxes as a function of depth. data dimension: depth*ensemble member (the index of the depth is in reverse order from 1500m depth to 1000m depth, e.g. 1 represents 1500m depth, 2 represents 1499m depth etc.) 2) gas2(ethane): ethane mass fluxes as a function of depth. data dimension: same as gas1. 3) gas3(propane): propane mass fluxes as a function of depth. data dimension: same as gas1. 4) lhs_sample: normalized perturbations for six uncertain inputs. data dimension: ensemble member*uncertain parameters The order of the parameters in the perturbation is as follows: Column 1 = entrainment coefficient Column 2 = entrainment ratio Column 3 = gas to oil ratio Column 4 = flow rate Column 5 = 95 percentile of droplet size (d95) Column 6 = droplet size distribution spreading ratio 5) peel_lhs: peel heights simulated from different perturbations. 6) trap_height: trap heights simulated from different perturbations
View Metadata