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 2017, which has resulted in at least 15 named storms, and counting.
In an October report from Aberdeen, Scotland, newspaper, The Press and Journal, titled “Digitalization and big data could help to weather future storms,” the case for better utilization of digital technologies to deal with hurricanes and tropical storms is made by Ewen MacLean, director at UK-based Calash, an oil and gas consulting group. 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, Ewen 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 improvement has 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 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,” Ewen says. “Rarely is this interpretation of combined data carried out, unfortunately, resulting in higher costs associated with major repairs or replacement.”
One impediment to this type of innovation in the oil and gas industry is data sets that are disparate and located in silos. Not only does this occur between organizations, due to the proprietary nature of the oil and gas industry, but even between departments within companies, Ewen says. “In our often-complex oil and gas supply chain, operators and service companies, alike, collect key pieces of the data puzzle individually, and for fear of competition or unless of direct benefit to them or remunerated somehow, are reluctant to share this information,” he writes. “In our experience, they often don’t recognize the value of the information they have within their organization and how it could help others, and also help themselves.”
Another hurdle is a lack of digital information in the industry, as many records are still kept on paper, in file cabinets. Ewen asserts that “digitalizing the information allows it to interact with other disparate information sources, and the collation and sharing of this new, unique data within the organization often leads to significant commercial gain.”
Above all, Ewen 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.”