Evolution Well Services, LLC & Arundo Analytics, Inc Announce First of Its Kind Digital Partnership to Advance Hydraulic Fracturing
THE WOODLANDS, Texas – (October 1st, 2020) – Evolution Well Services, LLC (“EWS”) and Arundo Analytics (“Arundo”) announce a partnership focused on next generation hydraulic fracturing operations. EWS, the leader in electric hydraulic fracturing, offers pressure pumping services to the major shale basins of North America, and Arundo Analytics is a global firm focused on creating value from data in industrial applications.
Evolution Well Services introduced its electric hydraulic fracturing services to the market in 2016, and in four short years, grew its fleet assets by 700% to become a premier player in the North American shale industry. According to Nick Ruppelt, Director of Sales & Marketing, “our growth as a company is attributed to the increased operational, environmental, & financial performance that EWS electric fleets provide E&Ps, but one major influence is EWS’ constant desire to be data driven. By partnering with Arundo, we aim to further push the limits of what is possible in hydraulic fracturing and continue lowering our customers’ cost to produce oil & natural gas in an environmentally friendly manner.”
Within the partnership, the joint team of subject matter experts and data scientists are focusing on use cases that deliver high business value, rapidly. Many hydraulic fracturing companies are just now focusing on cloud connectivity, but EWS completed its cloud transformation in 2019. The Arundo Analytics & Evolution Well Services partnership builds on a cloud-based and edge-enabled foundation to provide high ROI machine learning algorithms with a 30 to 60 day time to value (TTV). EWS began a scaled implementation of Arundo’s Edge Agent software and Marathon application that enabled the business to implement AI and machine learning models on the edge. By implementing models on the edge, EWS can execute on the analytic insights delivered by the Arundo software even in the most remote locations.
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