Solaris Oilfield Infrastructure Inc. revealed on Dec. 2 a collaboration with Amazon Web Services Inc. (AWS) to provide its customers greater insights into oilfield data, including materials and storage usage, trend analysis, equipment and performance analytics, and predictive maintenance features.
Solaris believes a data platform that can both process the record levels of data being generated by operators and oil service companies today and allow customization of data capture and display will give its customers a valuable tool for analysis and data interpretation. The resulting data analytics could be used to drive improvements in safety, efficiency and ultimately lower well costs.
In order to provide these individualized data solutions for its customers, Solaris leveraged multiple AWS analytics capabilities including Amazon Timestream, Amazon Kinesis, Amazon QuickSight, Amazon Athena, and Amazon SageMaker, AWS’s machine learning service that enables data scientists and developers to build, train, and deploy machine learning models quickly.
“Our customers continue to focus on increasing operational efficiencies in order to maximize cash flow. We firmly believe that innovative data analytics will be a key driver in generating sustainable and quantifiable efficiencies for our customers. Through the use of data analytics and software, our end goal is to leverage machine learning to further automate processes, utilize predictive maintenance, and essentially do more with less, and AWS is helping us accomplish this,” Bill Zartler, Solaris’ chairman and CEO, said.
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