If your SCADA system is eLynx, you can be confident your data has the accuracy and overall quality to support advanced Predictive Analytics. But if you're not using eLynx, do you know how good your data really is? We can help. Our data science and production experts start by working with your team to understand your operational priorities. Then, our validation tools test for out-of-bounds or missing data. Together, we decide whether your data has the accuracy and completeness to support advanced analytics. If it does, let's discuss our latest developments. If not, we can help with data collection options to reach a new level of data quality.
Production teams need to know ASAP about changes to well conditions, but don’t have time to chase false alarms. Using machine learning to interpret subtle patterns in multivariate sensor data, we can identify wells needing attention. We’re seeing early notice of downhole restrictions like sand bridges or paraffin and surface restrictions like salt precipitants. A timely alert about potential problems combined with fewer false alarms makes production teams more effective and productive.
Before equipment fails, it often sends a signal — a pattern in the SCADA data. These patterns may be too subtle for even the most-observant production engineer to notice, but they are exactly where data science excels. Our machine learning recognizes patterns to forecast looming equipment failures. Our first targets include plunger logoffs, rod pump fractures, and ESP pump failures, with more on the way. With a warning hours or days ahead, you can often adjust your routine maintenance rather than dealing with an emergency.
Well setting choices are usually a mix of deep production team experience, intuition, experimentation, and vendor defaults. To that list, we add science. Our digital twin models can simulate and test more combinations of settings than could ever be feasible in the field. As a result, you will discover simple ways to increase production quickly, usually at no additional cost.
eLynx Predictive Analytics improves oil field production and cuts costs by suggesting optimal well settings and forecasting looming problems in time to take action.
Predictive Analytics in the patch takes three things: extraordinary historical data, hands-on oil field experience, and wicked-smart developers. Our data from 17 years tracking tens of thousands of wells in every major North American basin is second to none. Our founders alone have 90 years combined experience drilling and operating 5,000 wells and laying hundreds of miles of the first low-pressure pipelines in Texas. And on our analytics team, accomplished data scientists and seasoned production engineers work hand-in-hand to apply data science to critical real-world problems.
We’re building “digital twins” — computer models replicating above and below ground well behavior — for every major artificial lift type. We’ve learned how to connect subtle shifts in sensor readings to down hole issues … and opportunities. Like plunger timing preventing a well from hitting it's potential. Or a rod or submersible pump that won't last the week without service. Or overuse of chemicals killing your LOE and making a solid well look uneconomic.
And we’re seeing real-world results. We delivered an average production improvement of 6.8% across the entire population of wells. We’re using anomalies in the data flow to forecast shut ins and equipment failure hours or even days ahead — in time to take action and prevent emergencies.
Our team works hand-in-hand with you to apply these new techniques. And when you work with eLynx, you’re also connected with other industry leaders. We are partnering with the famed University of Tulsa Artificial Lift Project and work closely with Microsoft’s analytics team.
In your car, you've moved from driving with an out-of-date map to outsmarting traffic with a GPS. Why wouldn't you apply that to your oil field? We’re ready to make our analytics team part of your team.