DEVELOPMENT OF OIL SPILL SCENARIOS FOR CONTINGENCY PLANNING ALONG THE BRAZILIAN COAST

José Antonio Lima1, Angelo Sartori1, Eduardo Yassuda2, Eric Anderson3, José Edson Pereira2, Edmo Campos4

1 PETROBRAS – Petroleo Brasileiro S.A., 2 ASATM Brasil,

3 Applied Science Associates, Inc., 4 LABMON – IOUSP

ABSTRACT

After an oil spill in Guanabara Bay due to the collapse of a marine fuel pipeline in

January 2000, PETROBRAS (a Brazilian company among the 15 largest oil companies in the

world) is facing important challenges regarding its environmental commitment to Brazilian

society. To face these new challenges, PETROBRAS launched a program for excellence in

environmental, health and safety management that includes the development of oil spill

contingency plans for its facilities. The present paper describes an oil spill modeling project

for 25 facilities along the Brazilian coast. The implementation of the project involved a

detailed meteorological and oceanographic characterization of each study area with a review

of existing data, data collection, and hydrodynamic modeling covering more than 9,000 km

of coastline. Based on the requirement of scenarios for both typical and critical conditions,

the oil fates and trajectory modeling system OILMAP was applied to simulate oil spill

incidents in all 25 sites, most of them oil terminals from TRANSPETRO, a PETROBRAS

subsidiary. Due to Brazil’s continental dimensions, the environmental conditions simulated

ranged from the subtropical Patos Lagoon in the southernmost part of the country to the

equatorial Solimoes River, including estuaries, coastal zones, and offshore sites. The

developed modeling system allows oil spill contingency specialists to develop response plans

for typical spills in the selected locations. By performing reverse trajectory calculations from

sensitive sites such as water intakes or fragile wetlands, it is also be possible to identify

probable release locations of spills and principal avenues of vulnerability for these important

resources. This paper presents a description of the implementation of the system and the

results of this modeling approach for a typical oil terminal located in the city of Vitoria,

eastern Brazilian coast.

1. INTRODUCTION

In April 2000, PETROBRAS launched a Program for Excellence in Environmental

and Operational Safety Management called PEGASO with investments in the order of US$ 1

billion until 2003 to reduce emissions and residues, and to improve the prevention and

control of accidents in all its facilities. The PETROBRAS subsidiary TRANSPETRO is

applying a portion of this budget to develop automated contingency plans for oil terminals

and to improve the maintenance and operational control over its 10,500 km pipeline network.

As a part of this program, the present paper describes the development of oil spill

modeling for 25 sites along the Brazilian Coast. The implementation of a project this size was

designed in five phases (Lima et al., 2001). Initially, a detailed meteorological and

oceanographic (hereafter abbreviated as metocean) characterization of each study area was

developed including a far-reaching review of existing data from federal, state, and municipal

agencies, universities, and private organizations. This first phase provided the background

information for the relevant processes to be simulated as a basis for the design of

computational grid and boundary conditions. The second phase involved data collection for

the sites where existing datasets were not sufficient to calibrate the hydrodynamic model. The

third phase comprised the implementation and calibration of the hydrodynamic model. The

fourth phase produced preliminary oil spill scenarios for fine tuning of the models, and the

fifth phase provided the definitive oil spill scenarios for the development of contingency

plans. Highlights of the project and modeling approach are presented in the following text.

2. CHARACTERIZATION OF THE STUDY AREAS

One of the main challenges of this project was to develop a detailed metocean

characterization of each study area. Figure 1 shows the map of Brazil with the locations of

the 25 sites. The Brazilian territory contains very diverse environmental conditions ranging

from latitude 32o S in the southernmost part of the country where the oil terminal Rio Grande

is located all the way to latitude 1o S where terminal Belem is situated, including tropical

estuaries, coastal zones, offshore sites and equatorial rivers where terminals Manaus and

Coari are located.

Available metocean data including wind, tide, current, salinity, and temperature time

series were acquired from many different sources. The time series were initially analyzed for

quality control. The QC tests were developed to identify errors and correct them whenever

possible. Acceptance criteria for the data were based on the specifications presented in a

PETROBRAS standard for metocean measurements (PETROBRAS, 1998). Only data

collected with properly identified methods by reliable sources were used.

Figure 1 – Locations of PETROBRAS and TRANSPETRO facilities comprising this project.

Available metocean data were used to develop datasets for model evaluation, to

provide inputs for the model simulations, and to assist in the design of data measurement

programs, where appropriate.

3. APPLICATION OF COMPUTATIONAL MODELS FOR OIL SPILL

SCENARIOS

The selection of the most suitable modeling system to accurately simulate the variety

of environments described in the previous section was based on the physics used in the model

formulation, as well as on operational aspects of the model structure and facilities to input

data and output simulation results.

3.1. HYDRODYNAMIC MODEL

The criteria used to select the hydrodynamic model was a balance between its

scientific background considering: a) relevant physical processes (e.g., tide, wind and

baroclinic forcings); b) operational aspects covering many different conditions; c) open

source code with easily modified model routines; and d) a user-friendly interface to achieve

the needs of the project. Based on these criteria, a hydrodynamic modeling system based on

the Princeton Ocean Model (POM) was selected. Originally developed by Blumberg &

Mellor (1987), the hydrodynamic model is written on a tri-dimensional sigma coordinate

structure, fully non-linear, curvilinear orthogonal discretization scheme, second order

turbulent closure formulation, and split barotropic and baroclinic modes.

Using this modeling approach, all the information collected or generated for a specific

study area was pre-processed and compiled in one file. The model was modified to read from

this file all the forcing and variables required to start a simulation. The run keys and model

parameters were intentionally kept separate, to assist in future developments of the model

structure.

Figure 2 shows the sketch of the modeling structure. At its center resides a netCDF

(Brown et al., 1993) file that contains and describes all the information required to run the

model under calibration conditions or in operational conditions. The upper part of the

flowchart presents the initial procedures to compile that input file, including the curvilinear

grid generation, meteorological and oceanographic boundary conditions, river inflows and

mean sea level variations. The hydrodynamic model provides feedback to that file providing

grid corrections and the coastline shape final tuning. Model results are then automatically

transferred to the OILMAP format requirements.

The development of this modeling system is an ongoing process and at this point it is

partially automated. The model structure is now highly user-friendly. Improvements are

being made as the project progresses.

Figure 2 - Hydrodynamic model input-output structure.

3.2. OIL FATES AND TRAJECTORY MODEL

In order to develop an effective response system, the trajectory of the spill has to be

predicted by a fast and accurate modeling system. The modeling system OILMAP developed

by Applied Science Associates, Inc. (ASA) was implemented in all 25 sites to meet this

requirement. OILMAP is a state-of-the-art, personal computer based oil spill response

system applicable to oil spill contingency planning and real time response (Jayko and

Howlett, 1992; Spaulding et al., 1992a,b). OILMAP was designed in a modular structure so

that different types of spill algorithms could be incorporated within the basic system, as well

as a suite of sophisticated environmental data management tools, without increasing the

complexity of the user interface. Figure 3 shows the structure of the OILMAP modeling

system.

User Input:

Spill Type, Location, Date,Winds, Spill Response

Geographical Graphical HydrodynamicsEnvironmental User Model

Database Interface

Physical CurrentsFates DatabaseModel

TacticalResponse

ModelSurface Oil, Shoreline Oil,

Water and Bottom Oil Concentrations,Database Information

Impacts

Figure 3 - OILMAP modeling structure.

The trajectory and fates model predicts the transport and weathering of oil from

instantaneous or continuous spills. Predictions show the location and concentration of the

surface and subsurface oil versus time. The model estimates the time variation of the oil’s

area coverage, oil thickness, and oil viscosity. The model also predicts the oil mass balance:

the amount of oil on the free surface, in the water column, evaporated, on the shore, and

outside the study domain versus time. The fate processes in the model include spreading,

evaporation, entrainment or natural dispersion, and emulsification. Spreading is represented

using the thick slick portion of Mackay et al.’s (1980, 1982) thick-thin approach.

Evaporation is based on Mackay’s analytic formulation parameterized in terms of evaporative

exposure (Mackay et al., 1980, 1982). Entrainment or natural dispersion is modeled using

Delvigne and Sweeney’s (1988) formulation, which explicitly represents oil injection rates

into the water column by droplet size. The entrainment coefficient, as a function of oil

viscosity, is based on Delvigne and Hulsen (1994). Emulsification of the oil, as function of

evaporative losses and changes in water content, is based on Mackay et al. (1980, 1982). Oil-

shoreline interaction is modeled based on Reed et al. (1989) which formulates the problem in

terms of a shore type dependent holding capacity and exponential removal rate.

The basic configuration of the model also includes a variety of graphically based tools

that allow the user to specify the spill scenario, animate spill trajectories, currents and winds,

import and export environmental data, grid any area within the model operational domain,

generate mean and/or tidal current fields, enter and edit oil types in the oil library, enter and

display data into the embedded geographic information system (GIS) and determine

resources impacted by the spill. The GIS allows the user to enter, manipulate, and display

point, line, polyline, and polygon data geographically referenced to the spill domain. Each

object can be assigned attribute data in the form of text descriptions, numeric fields or

external link files.

In the stochastic mode spill simulations are performed stochastically varying the

environmental data used to transport the oil. Either winds, currents, or both may be

stochastically varied. Utilizing sufficiently long time series, the start time for each of the

individual trajectory simulations is chosen at random among the years available and within

the month(s) selected for the statistical representation. The multiple trajectories generated are

then re-sampled to produce contour maps showing the probability of surface and shoreline

oiling. The trajectories are also analyzed to give travel time contours for the spill. These

oiling probabilities and travel time contours can be determined for user-selected spill

durations. If resource information is stored in the GIS database, a resource hit calculation can

be performed to predict the probability of oiling important resources

OILMAP has been applied to hindcast a variety of spills. These hindcasts were used

to calibrate the performance of the model. Hindcasts of the Amoco Cadiz, Ixtoc and Persian

Gulf War spills and an experimental spill in the North Sea by Warren Springs Laboratory are

reported in Kolluru et al. (1994). Spaulding et al. (1993) also present a hindcast of the Gulf

War spill. Spaulding et al. (1994) present the application of the model to the Braer spill

where subsurface transport of the oil was critical to understanding the oil’s movement and

impact on the sea bed. Recently Spaulding et al. (1996a) have applied the model to hindcast

the surface and subsurface transport and fate of the fuel oil spilled from the North Cape

barge. Integration of OILMAP with a real time hydrodynamic model and the hindcast of the

movement of oil tracking buoys in Narragansett Bay are presented in Spaulding et al.

(1996b).

4. EXAMPLE OF THE OIL SPILL MODEL FOR A BRAZILIAN COAST SITE

The oil terminal of Vitoria is located at latitude 20o 19´ S and longitude 40o 17´ W,

within the harbor complex of Tubarao, inside Espirito Santo Bay. The hydrodynamic

circulation in the bay is affected by tidal and wind forcing. Figure 4 presents the model grid

domain over nautical chart DHN 1410 of the Brazilian Navy.

The grid was designed to have a higher resolution close to the terminal (on the order

of 50-meter grid spacing) and gradually increase the spacing when approaching the

boundaries. It was required to extend the grid over the continental shelf in order to avoid

distortions of the tidal long waves. The effects of wind forcing were also better represented

with this extended grid.

Figure 4 - Orthogonal curvilinear grid used to simulate the hydrodynamic circulation within Espirito Santo Bay and adjacent continental shelf.

The model was carefully calibrated to reproduce current measurements made in

February 2002 at the harbor entrance. Many other simulations were performed and the model

provided good results for both the currents within the bay and in the adjacent area. The

hydrodynamic current fields were transferred to the oil model OILMAP to run the fates and

trajectory model. Figure 5 presents a snapshot of the predicted ebb tidal currents of the

hydrodynamic model.

Figure 5 – Ebb tidal currents in the Espirito Santo Bay as simulated using the hydrodynamic model.

Statistical analysis of one year of wind time series at Port of Tubarao, combined with

typical oceanographic conditions (flood, ebb tides and adjacent shelf currents) force the final

oil spill scenarios used in the contingency planning. Meteocean statistics, selected spill sites,

volumes and products result in 288 possible scenarios to be simulated.

Typical oceanographic conditions were simulated, which allows a contingency

planner to review the patterns of the oil trajectories, select a suite of predicted oil transport

conditions, and position of oil booms and skimmers to combat these predicted oil trajectories.

To illustrate the spill behavior, Figures 6 and 7 show some results achieved. The

meteorological situation for the example was fixed as Eastern Winds. The oceanographic

condition chosen was spring tides at the beginning of flood currents (Figure 6) and at the

beginning of ebb currents (Figure 7).

Figure 6 – Flood spring tidal condition, eastern winds, 8 hours after the oil release. Red dots are the oil already retained in land, black dots are the instantaneous oil particles and the grey patch is the swept area.

Figure 7 – Ebb Spring tidal condition, eastern winds, 8 hours after the spill. Red dots are oil retained in land, black dots are instantaneous oil particles and the grey patch is the swept area.

5. CONCLUDING REMARKS

This paper presents a brief description of the oil spill modeling efforts developed by

PETROBRAS, ASATM Brasil, and Applied Science Associates, Inc. (ASA) to build a robust

oil spill contingency planning for diverse oil facilities along the Brazilian coast. It is a

pioneering and challenging project that clearly shows the importance placed by

PETROBRAS and its subsidiary TRANSPETRO to achieve excellence in their

environmental and operational safety focus.

It has been a complex study to perform. For instance, the study team had considerable

difficulty to retrieve available metocean data from different agencies and institutions,

working under tight time restrictions for the planning and execution of accurate measurement

programs over a limited period of time, implementing a generic stepwise procedure to design

and improve model grids, introducing initial and boundary conditions comparing the results

and calibration standards, and the finally interacting with contingency plan specialists who

may have biased views about the results of oil spill models. Overall, the project has achieved

very good quality standards and can be considered a remarkable advance to build up an

efficient oil spill response system for marine oil facilities in Brazil.

It is also important to note that oil spill scenarios can be used for both contingency

planning and environmental licensing of oil facilities. After the recent deregulation of the

Brazilian oil sector and the consequent opening of the market, the environmental regulatory

agencies have been developing standards to be followed with requirements equivalent to

other oil producing regions in the world, such as the North Sea and Gulf of Mexico. Aware of

the potential power of numerical modeling as a computational tool for the evaluation of

possible impacts of activities related to the petroleum industry, Brazilian environmental

agencies are already asking for results of hydrodynamic and oil spill models to meet their

requirements.

As an example, the Brazilian institute for the environment (IBAMA) is the agency

that provides licenses for offshore oil activities. IBAMA requires that the interested company

present simulations of dispersion, trajectory and fate of an accidental oil spill, considering

scenarios with specific modeling implementations. This includes probabilistic simulations

considering seasonal conditions, and a critical deterministic condition referring to the worst

case scenario. The modeling projects are to present all the hypotheses, parameters and values

employed. These data should be in accordance with those presented in the diagnostic

definition of the physical environment. The studies are to be based on a combination of

hydrodynamic and oil spill models, with recognized effectiveness and reliability. The project

developed by PETROBRAS, ASATM Brasil, and Applied Science Associates, Inc. (ASA)

was designed to meet these requirements.

6. ACKNOWLEDGMENTS

The authors would like to thank the entire project team without whom this challenge

could not be accomplished. Especially, Dr. Marco Antonio Correa, Dr. Andrea Gallo Xavier,

Marcelo Martinelli, Eoin Howlett, Tatsu Isaji, Ricardo Busoli, Prof. Joseph Harari, Prof.

Ricardo Camargo, Prof. João Luiz Batista de Carvalho, Prof. Osmar Möller, Prof. Ivan

Soares, Prof. Mauricio Mata, Leandro Calado, Hemerson Tonin, Carlos Fonseca, Roderick

Gama, Ágata Romero, André Marquez, João Marcos Azevedo, Leandro Franklin da Silva,

Rafael Bonanata, and PETROBRAS/TRANSPETRO staff.

7. REFERENCES

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