Oil Spill Modelling in the Balikpapan Bay Case Study : Incident of 31 March 2018

Summary

The 2018 oil spill in Balikpapan Bay, Indonesia, was a devastating environmental disaster caused by a ruptured subsea pipeline. The spill, which resulted in significant pollution and the deaths of five fishermen, highlighted challenges in emergency response due to limited real-time data. The Indonesian government coordinated efforts to contain the spill, using predictive modeling, satellite imagery, and high-performance computing. The response was informed by the OpenOil model, which helped predict oil movement and its environmental impact. Despite challenges, the incident underscored the importance of advanced technology in managing oil spills and improving response times.

Takeaways

• 😀 The oil spill in Balikpapan Bay, Indonesia, occurred in 2018 due to a ruptured subsea pipeline caused by an anchor dragging and damaging the pipeline.
• 😀 The spill caused significant environmental damage, including the death of five fishermen and widespread contamination of the surrounding area.
• 😀 Indonesian government agencies, including Pertamina, Ministry of Environment, and Ministry of Marine Affairs, responded to the oil spill, but initial response efforts were hindered by incomplete data.
• 😀 The oil spill spread rapidly due to tidal currents in Balikpapan Bay, with the maximum spread occurring during ebb or flood tides.
• 😀 Satellite imagery and ocean models were crucial in predicting the oil spill's trajectory, allowing responders to make informed decisions in real time.
• 😀 The OpenOil model was used to predict the movement of the spill, utilizing data from the ROMS ocean model and ECMWF ERA-5 wind data.
• 😀 The model's performance was validated by comparing the predicted oil spill distribution with satellite images from the same time period.
• 😀 The study showed that high-performance computing systems significantly sped up the modeling process, allowing for quicker predictions and a more efficient response.
• 😀 Within 24 hours, about 50% of the spilled oil mass naturally weathered due to physical, chemical, and biological processes.
• 😀 The use of integrated predictive modeling, satellite images, and field observations proved effective in responding to the oil spill, improving coordination and response time.

Q & A

What were the main causes of oil spill accidents in Indonesian waters as mentioned in the script?

The main causes of oil spill accidents in Indonesia include fitting leaks, boiler leaks, offsite leaks, feed line leaks, oil tank leaks, fires, storm damage, and other common issues during oil loading or discharge operations.

What is the significance of the 2018 Balikpapan Bay oil spill in Indonesia?

The 2018 Balikpapan Bay oil spill is considered one of the worst environmental disasters in Indonesia, where a subsea pipeline burst, leading to a large-scale oil spill. It caused extensive environmental damage and resulted in the tragic loss of five fishermen’s lives.

How did the oil spill in Balikpapan Bay occur?

The spill occurred when the anchor of a bulk carrier got stuck and dragged a subsea pipeline in the sea bed, causing it to bend and break. This resulted in a crude oil leak, which later caught fire and caused further destruction.

What were the challenges faced by the response team during the initial stages of the oil spill emergency?

One of the major challenges was the incomplete data and information available at the site during the first hours after the spill. Additionally, the incident occurred at night, limiting direct visual observation, and satellite imagery was dependent on the satellite's position and coverage.

How does the use of predictive modeling support oil spill response efforts?

Predictive modeling helps by forecasting the movement of the oil spill, providing crucial early-stage information about its trajectory and potential environmental impacts. This assists response teams in planning and executing effective countermeasures.

Which oil spill contingency plan did Indonesia refer to in this case, and what is its goal?

Indonesia’s response plan for oil spill emergencies aims to be fast, precise, and coordinated. The goal is to prevent the spread of oil spills at sea and mitigate environmental damage while minimizing public losses.

How did international models, like the U.S. NOAA model, contribute to the response efforts in this case?

International models, such as NOAA’s Office of Response and Restoration model, were used to predict the oil spill’s movement, based on past successful applications like the Exxon Valdez spill. These models provide early insights into spill behavior and potential impact, aiding response planning.

What data was used in the OpenOil model for the Balikpapan Bay oil spill prediction?

The OpenOil model used hourly current velocity data from the ROMS ocean model and wind speed data from the ECMWF’s ERA-5 dataset. These inputs helped to predict the oil spill's movement and potential environmental effects.

What role did high-performance computing play in the oil spill modeling during the incident?

High-performance computing systems were essential for running complex numerical models quickly, allowing for faster predictions and more timely responses. This technology helped to solve complex equations that ordinary computers would have struggled with, supporting the task force’s efforts.

What was the observed behavior of the oil spill in Balikpapan Bay, and how did it spread?

The oil initially rose to the surface due to the difference in density between oil and seawater. It spread across the bay’s surface, carried by tidal currents. The extent of the spill was greatest during ebb or flood tides, and within 12 hours, half of the spilled oil had been naturally weathered and broken down.