Ambyint, the emerging player in AI-powered artificial lift and production optimization, and international energy major Equinor today announced that it will deploy Amybint’s technology on all rod pump wells in Equinor’s Bakken asset in North Dakota. The partnership comes at the end of a successful pilot and will expand to full field implementation in this asset.
Artificial lift optimization is one of the core activities Production Engineers and Techs are asked to perform on a daily basis. Rod lift is the most widely used artificial lift type, deployed on horizontal and vertical wells alike. Due to the widespread use of rod pumps, consistent best practices have been established over time. When those operational best practices are adhered to, meaningful increases in field profitability of even the lowest producing wells have followed.
Despite their differences in the horizontal development and vertical legacy well context, industry best practices to optimize rod lift around efficiency, and thus profitability, have a consistent logic and methodology. First, wells are diagnosed as underpumping, dialed in, or overpumping. Second, based on the categorical classification, a consistent remediation workflow is applied based on the available levers to pull that either increase production or lower the number of damaging strokes into the system.
Topics: SCADA, Data Science, Artificial Intelligence, Machine Learning, Rod Pump, Oil and Gas, O&G, Pump by Exception, Essential Well Management, Brownfield, Hierarchy of Needs, Vertical wells, Stripper wells, Legacy wells
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