Data-centric Preventive Maintenance in the Oil and Gas Industry

Hurricane Harvey hit Houston hard. Harder than many expected, including a number of the oil and gas companies located in the area. Some evacuated early and had no idea when they would reopen for business.

“How soon they reopen depends on the severity of flooding and the resumption of power to the areas. Experts say it's still too early to say, with the storm still moving through the region. But they believe gas prices will increase 5 cents, to 25 cents per gallon.” (CNBC.com)

 Cognitive Search in the Oil & Gas Industry

Harvey has come and gone, but 2 other hurricanes are in motion, and other types of weather events can impact the oil and gas industry. These storms have resulted in a lot of drilling nonproductive time (NPT) for gas wells. It couldn’t have been avoided - at least not completely. But advances in agile business intelligence and machine learning can help oil and gas companies better predict problems before they happen. Starting with the weather. 

A recent article on Nature.com discussed the ability to improve climate forecasts.

“Climate is now a data problem,” says Claire Monteleoni, a computer scientist at George Washington University who has helped to pioneer the marriage of machine-learning techniques with climate science. In machine learning, AI systems improve in performance as the amount of data that they analyze grows. This approach is a natural fit for climate science: a single run of a high-resolution climate model can produce a petabyte of data.

Preventive Maintenance Reduces Nonproductive Time

What if you could take that climate data, combine it with other structured and unstructured data such as maintenance notes and drilling reports, and then apply machine learning to detect trends and patterns that indicate NPT? Suddenly, you aren’t reacting to the weather as it hits (or after). You are proactively building predictive models that look at all the potential inputs, including the weather, aligning it to other pertinent data and making the right decisions before a problem happens.

The ability to harvest Big Data, including climate data, can have a huge impact on the oil and gas industry. A broader, data-centric understanding of the patterns that affect oil production drives preventive maintenance, protects systems, and prevents failures. 

 

Subscribe to the Blog

Tweet This

Data-centric Preventive Maintenance in the Oil & Gas Industry #MachineLearning