Fusion of acoustic imaging, precision magnetic data and machine learning

What is it about?

An innovative approach using acoustic imaging and magnetometer data has been developed and applied to train an AI application that can deeply analyze magnetometer responses over a site where an oil platform was catastrophically destroyed during a hurricane. This application detected and captured high-resolution images of deeply buried conductor pipes lost beneath the subseabed in the Gulf of Mexico. By utilizing extensive Machine Learning training models exploiting details from the acoustic responses to investigate the magnetometer data, the AI revealed the presence and connectivity of these pipes. This showed the damaged and buried pipes were still connected to their original well basin.

Featured Image

Photo by Pietro Jeng on Unsplash

Photo by Pietro Jeng on Unsplash

Why is it important?

After many failed conventional-based geophysical surveys and probing over the past ten years, the approach first revealed the exact presence and character of the buried debris field. The unprecedented results paved the way for understanding the situation at the original oil platform site and the reason for oil and gas appearing further away on the surface. The techniques and fusion of acoustics, magnetics, and AI show an innovative way forward for sharpening features captured in a magnetometer survey and presenting a cost-effective, detailed investigation technique for future decommissioning applications.

Perspectives