The primary objective of Production Operations is to operate every well in the field at peak economic efficiency levels at all times. That is to say, the goal is to sustain maximum fluid production with minimum cost inputs across the field, keeping lease operating expenses (LOE) down while keeping profits up. The highest value lever by which this is achieved is through artificial lift optimization.
Topics: Production Operations, Value Creation, Feature Engineering, Data Science, Artificial Intelligence, Machine Learning, Advanced Analytics, Optimization, Set Point Management
"Digital service companies such as Ambyint are working toward autonomous well operations, promoting its technology as the oil and gas industry’s answer to the 'self-driving car.' Ambyint CEO Alex Robart, who spoke at Hart Energy’s DUG Permian conference in May, is using Edge, Internet of Things and AI/machine learning to transition to the 'autonomous oil field.'"
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Topics: Machine Learning, Industrial IoT, Technology Adoption, O&G, Pump by Exception, Deep Learning, Edge Computing
As a former Marathon Oil production and reservoir engineer who has personally managed nearly 1,000 wells in the company’s core play, Jesse Filipi understands first hand how time-consuming set point optimization can be. During his time at Marathon, the company underwent a massive well expansion. But, despite the steep growth curve, Jesse felt that he and his team were not given the tools to be successful. Considering that the engineering team is effectively the revenue center of any production company, he knew there had to be a better way to effectively manage large scale well operations.
Topics: Production Operations, SCADA, Value Creation, Feature Engineering, Data Science, Artificial Intelligence, Machine Learning, Optimization, Horizontal Wells, Automation, Production Engineering, Artificial Lift, Disruptive, Pump by Exception, Essential Well Management
For as long as there has been a future, people have been envisioning what it could look like. From flying cars that zip around sky cities to handheld devices that teleport you away just as fast as you can say “beam me up, Scottie!”, we have always had lofty goals in mind. But, now we live in a world that looks remarkably like something out of a sci-fi film, and nothing exemplifies just how far we’ve come quite like the ‘Lights-Out’ Factory. It’s pretty much exactly what it sounds like: a factory that employs robots rather than humans, humming along in perfect synchronization, to the extent that one could simply turn the lights off without affecting the march of progress in the slightest. To break it down a little further, here is a helpful summary from PWC of what a lights-out factory is (and isn’t):
Topics: Artificial Intelligence, Machine Learning, Optimization, Automation, Industrial IoT, Technology Adoption, Lights out, Manufacturing, Robotics
Last week, Ambyint took the stage at the 2018 Global Petroleum Show (GPS). The annual conference and exhibition is one of Calgary's most highly anticipated events for oil and gas professionals across North America. This year's turnout did not disappoint, with over 1,000 exhibiting companies and ~50,000 attendees. In addition to maintaining a booth presence over the course of the three-day event, Ambyint hosted three speaking slots and an auxiliary breakfast seminar, successfully keeping Ambyint at top-of-mind throughout the week.
Topics: Production Operations, Data Science, Artificial Intelligence, Machine Learning, Advanced Analytics, Optimization, Automation, Rod Pump, Industrial IoT, Conference, Presentation, Global Petroleum Show
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
In 1997, Clayton Christensen coined the term “Disruptive Innovation” in his thoughtful book, The Innovator’s Dilemma. Since then, the term has been shortened to simply ‘disruption’ and it has taken on a life of its own across the technology and media complex.
Topics: Artificial Intelligence, Machine Learning, Disruption, Disruptive, Upstream, Oil and Gas, Industrial IoT, Silicon Valley, Technology Adoption, O&G, Innovative
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.
Topics: Production Operations, Value Creation, Predictive Analytics, Artificial Intelligence, Machine Learning, Advanced Analytics, Optimization, Horizontal Wells, Pareto Principle, Automation, Production Engineering, Rod Pump, Artificial Lift
With data science and analytics permeating industrial, financial, and consumer technology sectors, oil and gas producers have begun to invest in and explore the potential for these tools to add value in upstream activities. To date, most E&Ps have experienced mixed success, with value coming mainly in the drilling & completions business units (1-4).
Topics: Production Operations, SCADA, Value Creation, Feature Engineering, Data Science, Predictive Analytics, Artificial Intelligence, Machine Learning