How Machine Learning Drives Artificial Lift Performance

Logo
Presented by

Andrii Struk - SoftServe, Yaroslav Svyryda - SoftServe, Mohamed Shawky - AWS, David Benham - Laredo Petroleum

About this talk

This Webinar is a recording from June 9, 2021- Unplanned downtime in the oil and gas industry leads to costly problems like production delays. With artificial lift downtime being a primary source of such deferred production, identifying potential problems before they occur is crucial. By applying advanced analytics and machine learning (ML) at scale in the cloud, oil and gas companies can improve their field performance. Using asset diagnostics and acting on real-time monitoring insights, you’ll create data-driven maintenance flows, leading to an increase in production and reduced lease operating expenses. This video explains how AWS production monitoring solutions and services like Amazon SageMaker reduce unscheduled maintenance and deferred production. These tools help you to predict suboptimal equipment performance and potential failures so you can make data-driven operational decisions.

Related topics:

More from this channel

Upcoming talks (2)
On-demand talks (5)
Subscribers (218)
We are advisors, engineers, and designers who deliver innovation, quality, and speed—elevating and accelerating our clients’ digital journeys. Our approach is built on a foundation of empathetic, human-focused experience design that ensures value and continuity from concept to release.