How Top Oil & Gas Companies Use Predictive Analytics
Do fears of keeping your project on schedule, within budget, and at full productivity ever keep you up at night?
What if you had a reliable way to analyze your current performance, model future trends and figure out where the bumps in the road will be, long in advance?
Let’s take a look at the role predictive analytics takes in making this a reality.
Imagine if you could apply automated analytics models that use machine learning to predict when your industrial equipment will need maintenance.
That’s exactly what predictive analysis platforms aim to do. Sensors collect live data from parts, drills and other equipment, as well as liquid and gas flow rates, tank levels, composition analyzers, and weather conditions or other environmental factors.
From there, you can easily monitor daily throughputs and equipment performance rates. This helps you figure out when issues are starting to form which need swift intervention and when things are ticking over just fine, avoiding the need to stop work for unnecessary routine processes.
Or, you could pull and analyze data from things like pump failures, helping you to better assess the root causes, diagnose solutions and predict what will cause problems in the future with a high degree of accuracy.
Predicting Operational Outcomes
How do you combine Big Data from multiple sources and draw out genuinely meaningful, useful insights from it?
Right now, the oil & gas industry is seeing a new generation of exciting business intelligence (BI) platforms emerge that are capable of storing and processing vast quantities of structured and unstructured data. These include seismic and sensor data, geolocations, pump data, fluid temperatures, and information from drilling and completions, as well as non-traditional sources such as natural language text, video, images, and social media posts.
Once you have this rich, detailed data at your fingertips, you can start to figure out how different factors interplay out in the (oil)field - and create predictive models based on different inputs.
Final Thoughts: Making Better Decisions
No one can see into the future. With complete, accurate data and robust predictive analytics, though, you can get pretty close.
Predictive analytics give you a compelling, well-rounded picture of how things will likely turn out, based on past performance and external factors. This helps you to make smarter, more effective, data-driven decisions. It helps you to set benchmarks and analyze performance in real-time.
Most importantly, it helps you plan for any eventuality, figuring out in advance when you need to schedule maintenance or scale up production. The bottom line is this: when you know what’s coming, you can pull out all the stops to avoid any costly downtime.