Machine learning enables Equinor to optimize production operations in North Dakota

Author photo: Tim Shea
ByTim Shea
Category:
Industry Trends

ARC takes every opportunity to highlight owner-operators and independent E&P firms that are taking the journey of digital transformation by deploying advanced analytics and machine learning to improve their operational performance and by lowering costs, increasing production and/or EUR, or improving employee productivity as they strive to “do more with less” in an oil & gas market that is moving closer to supply-demand equilibrium as prices trade in the high $60s to mid $70s per barrel of oil. Equinor continues to show itself as one of the more progressive owner-operators in the market in terms of embracing new technologies to improve operational performance, thereby hopefully spurring other operators and independents to follow its lead as they take their journey towards digital transformation.

Ambyint, an emerging player in AI-powered artificial lift and production optimization, and Equinor announced  a few weeks ago 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. During the pilot, Equinor was able to automate rod pump well optimization through use of Ambyint’s autonomous setpoint management functionality. By identifying wells that were over-pumping or under-pumping, controller set points were adjusted with minimal human interference. This kind of proactive optimization resulted in increased production rates and pump efficiency while reducing the well volatility.

machine learning optimizes production in North Dakota

Machine learning helps optimize well performance

“The Ambyint technology has improved the remote data visibility and has delivered a more accurate diagnostic of downhole conditions to our rod pump wells in the Bakken. The Autonomous speed range management tool has leveraged the power of machine learning to optimize our wells by identifying and acting on real opportunities” said Jack Freeman, Production Engineer for Equinor’s Bakken Asset.  “R&T team facilitated the internal technology qualification process by setting up robust and measurable success criteria for the evaluation of pilot. We worked closely with Ambyint to ensure that the technology development and future roadmap meets Equinor’s business needs and priorities”, said Pandurang Kulkarni, principal researcher at Equinor Research and Technology.

Results of IIoT-enabled solution deployments are real and meaningful

Ambyint delivers substantial operating improvements to customers by combining the best of traditional physics-based methods with modern artificial intelligence and machine learning. Ambyint’s data science success is fueled by the industry’s largest repository of labeled training data, totaling nearly 100 million operating hours of high-resolution data. Using its proprietary High-Resolution Adaptive Controllers (HRAC), Ambyint continues to build on both the size and quality of its industry-leading data lake. As a result, Ambyint has already helped customers show 20%+ reductions in operating expenses and as much as 10% improvements in production volumes.

Technology partnerships are critical in enabling digital transformation

“The strong positive results from Ambyint’s pilot in Equinor’s Bakken asset is a direct result of the hard work and deep collaboration between Equinor’s Bakken asset team, Research & Technology team, and the Ventures team,” said Chris Robart, President of Ambyint USA. “Equinor’s commitment to deploying leading-edge and novel technologies into their operations is what made the pilot possible and what ultimately resulted in significant value creation for the Bakken asset.” ARC has been opining for years now that digital transformations that help enable operational excellence almost invariably require strong partnerships between operators and companies that empower change via a myriad of IIoT-enables solutions including advanced analytics, machine learning, AR/VR, enhanced communications, etc.  

Although oil prices have recovered to levels which are spurring renewed interest and investment in deeper water and subsea oil & gas projects, ARC recommends that operators and independents alike continue to forge ahead in embracing digital transformation in order to protect against future potential price swings and market volatility.

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