How Big Data Could Help Operators Prepare for Hurricanes

Add storm prep to the list of operations that big data analytics can help oil and gas companies improve upon. The need for optimization in this area has been underscored by the turbulent hurricane season of 2019, which resulted in 18 named storms.

A report from The Press and Journal titled “Digitalization and big data could help to weather future storms” by Ewen MacLean makes the case for better utilization of digital technologies to deal with hurricanes and tropical storms. Collated historical records on offshore assets should be digitized and combined with weather records, using algorithms to simulate models on the effects that weather events could have on equipment, MacLean says. Such models could affect insurance premiums, life-of-field management, HSE management, inspection, repair, and maintenance workloads. He points to digitalization of shallow-water subsea pipelines in the Gulf of Mexico as one example where improvements have been made.

Data from the pipelines and their operational characteristics are run through algorithms with information from the operators, including in-house data and public data, such as soil condition, seabed topography, and wave action. These simulations help to identify pipelines that are at varying risk of damage, depending on storm type and ferocity.

“The same approach could be adopted for all other assets using appropriate measurements,” MacLean says. “Rarely is this interpretation of combined data carried out, unfortunately resulting in higher costs associated with major repairs or replacement.”

Above all, MacLean advocates for an “open book” type of approach to data. “Management and interpretation of big data is already here and delivering value across our industry, but there is a lot more we can do throughout the supply chain; so next time you come across some interesting information, consider if there is value in digitizing it, making it accessible first throughout your own organization, and then with your supply chain.”