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Determining proper oil well placement and spacing is a difficult task, but getting it right is vital to effective production. More complex than one might think, well spacing depends on a number of factors—there is no one-distance-fits-all to determine the perfect grid pattern for oil fields. 

Each reservoir has its own distinct properties that must be analyzed before drilling a well; drilling too closely to another reservoir could mean millions of dollars worth of oil is lost while leaving too much space in between is a missed opportunity for extraction. 

That’s where Texas-based oilfield intelligence company OAG Analytics comes in. The firm has designed a solution that combines reservoir properties with machine learning capabilities in order to determine optimal well placement. With the help of data visualization technologies, OAG Analytics has helped well operators automate their spacing process. They are now able to determine spacing up to five times faster and at one-tenth of the cost of previous efforts. 

OAG Analytics saw an opportunity when an abundance of evidence had shown that producers that were open to using technology in the field were more successful than those who had yet to embrace technology to its fullest potential. While industry standards to estimate production already existed, OAG Analytics put machine learning algorithms behind those estimates to automate and vastly accelerate the process. The solution is now being used by every major unconventional basin in the United States. 

For more details on how OAG Analytics helps well operators save billions of dollars with its data visualization solutions, read the full case study.