New Model Developed In The U.S. Promises To Predict Submarine Landslides And Protect Oil Rigs

Written by Fabio Lucas Carvalho

Published on 28/05/2025 at 16:58

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Model Developed by Texas A&M Researchers Predicts Underwater Landslides and Helps Protect Offshore Structures Such As Oil Platforms.

Scientists from the United States announced an important breakthrough in predicting underwater landslides.

The innovation, developed by specialists at Texas A&M University, has the potential to protect oil platforms and other structures on the seabed, reducing serious geological risks that directly affect the energy sector.

Landslides Are a Real Threat to the Offshore Sector

Underwater landslides are among the most dangerous geological events in the marine environment. They involve the sudden displacement of large masses of sediment on the ocean floor, potentially destroying pipelines, anchors, cables, and compromising the entire structure of an offshore platform. In addition to material damage, these landslides can even trigger tsunamis.

ARTICLE CONTINUES BELOW

Bayesian Model Integrates Data and Improves Predictions

Led by Professor Zenon Medina-Cetina from the civil and environmental engineering department, the Texas A&M team created a model that combines geological data with statistical techniques to predict the risk of landslides. The model uses a Bayesian approach, which allows for continuous refinement of predictions by integrating new data.

The process begins with the collection of information from the site, involving experts from different fields. Geophysicists, geologists, geomatics professionals, and geotechnical engineers work together, each contributing data that feeds the system. The order in which these specialists operate is essential to ensure the accuracy of the results.

Order of Data Affects the Safety of Platforms

According to Medina-Cetina, following the correct sequence in data collection and analysis is what ensures reliable predictions. He emphasizes that interrupting this sequence, whether due to time constraints or budget cuts, can compromise the entire modeling process.

“It is very important to start with the geophysicist, then bring in the geologist, and finally have the geomatics group working with the geotechnical engineers,” the professor stated. He compared the process to a child learning: you cannot run before you learn to walk.

The Bayesian model is structured so that each stage of the analysis is based on the previous one. This allows predictions to become more accurate over time. For companies operating offshore, this represents a strategic tool for assessing risks more safely.

Model Shows Benefits in Practice

With the application of the new approach, researchers claim it is possible to increase confidence in the data obtained and, thus, reduce uncertainties. This helps companies avoid losses and make more accurate decisions regarding the installation and maintenance of their underwater infrastructures.

The initiative demonstrates that integrating technical knowledge with statistical analysis can make a difference in preventing disasters in the offshore environment.

The study was published in the journal Landslides.

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New Model Developed In The U.S. Promises To Predict Submarine Landslides And Protect Oil Rigs

Model Developed by Texas A&M Researchers Predicts Underwater Landslides and Helps Protect Offshore Structures Such As Oil Platforms.

Landslides Are a Real Threat to the Offshore Sector

Bayesian Model Integrates Data and Improves Predictions

Order of Data Affects the Safety of Platforms

Model Shows Benefits in Practice

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New Model Developed In The U.S. Promises To Predict Submarine Landslides And Protect Oil Rigs

Model Developed by Texas A&M Researchers Predicts Underwater Landslides and Helps Protect Offshore Structures Such As Oil Platforms.

Landslides Are a Real Threat to the Offshore Sector

Bayesian Model Integrates Data and Improves Predictions

Order of Data Affects the Safety of Platforms

Model Shows Benefits in Practice

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