When most people hear “big data,” they think “big money.” And they’re right. There are big costs associated with switching to a distributed data analytics system, especially in the oilfield.
It’s not unusual for operators to collect and mine data from new discoveries made by geoscientists with historical data collected during drilling of past wells. They process and scan logs and scout tickets to gather data before they hit the paper shredder. In one case, more than 2 million documents of drilling information were processed in a single week of data discovery.¹
Why make the switch? You can store much more data, at a far lower cost per terabyte. And, you can make more informed oil production and transportation decisions more quickly than competitors who don’t switch.
Getting Maximum Efficiency from your Data Management System
Efficiency is about completing a process quickly and cheaply. With big data analytics, you can use many lower-cost machines instead of a very expensive one. Think about your current EDW. How much oilfield, equipment and other operations data can you store without running out of space?
The same goes for new calculations. Data is stored in its atomic (most detailed) form, so manipulating or adding calculations is never an issue. Neither is losing historical data. It’s just there, and it just works.
Getting Maximum Benefits from Your Data Resources
Effectiveness is getting the greatest benefit from your resources. Analysts spend up to 80 percent of their time locating and cleaning data and waiting for analytics processes to complete. So, of the $100,000 or more annual salary each analyst earns, at least $80,000 is spent unnecessarily—hardly what I’d call effective!
In a BDA environment, processing requires little time, and all data is quickly available. This reduces data overhead from 80 percent to 10 percent or less. This saves about $70,000 per analyst per year. When you consider that most operations have at least five analysts, you’re ahead $350,000 per year using big data!
The Worth of Tools and Value-Added Skills
This data overhead calculation does not include an important factor: the worth of tools and what analysts and engineers do with the time they save.
BDA tools can improve oilfield operations effectiveness. For example, companies wanting to operate more efficiently should consider using BDA tools to use real-time and sensor data to optimize production across an entire oilfield or region.
What if your engineers produced a model that better predicts well abandonment points by 5 percent? A 50-year well would reduce the costs of half a year’s non-profitable production. A conservative estimate: you’ve reduced per-well costs by $500,000! ($1million per well per year.)
The value of Big Data Analytics in the oilfield is very real. Companies willing to adopt these technologies early on will see the greatest long-term benefits, in terms of cost savings and competitive advantage.
And if you want to calculate cost savings and ROI of a BDA platform, visit us at https://www.syntelli.com/.
¹https://www.mrt.com/blogs/news_blogs/article_f1d6556e-f510-11e4-8a54-bf4bee9b2fa8.html
Daniel Smith
Director of Data Science and Innovation
About Daniel: Using Business Intelligence platforms to bridge the gap between Advanced Data Analytics and the efficient effective principles of accounting, Daniel applies technology and mathematics to make business faster and smarter.
Daniel has managed solutions for diverse client sectors such as as advertising, military, insurance, and oil & gas. These solutions include Business Intelligence Platform management, online key performance indicator identification and tracking, to full predictive data model construction. Although the analytic solutions are often mathematically complex, Daniel’s presentation and academic background ensures any insights delivered by solutions are relevant and simple to understand.
