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Better Oilfield ROI Using Advanced Statistical Analytics


In a battle of the balance sheets, the black and white language of ROI is moving business forward. According to Bain & Company, forward thinking oil and gas teams that explore new and more advanced statistical analysis methods find themselves twice as likely to be in the top 25% of the industry’s financial performance metrics. They cite new statistical analysis of well optimization and geology for an uptick of 6-8% in production for these teams. To put that into perspective, that results in a net of about $200,000 in total revenue for the first six months of each well.

This current climate demands companies to do more with less and the prescription has been to turn to big data to make better decisions, faster.

With collateral used to secure 2013-2014 funding now valued at 30% of what it was, new venture deal flow will be way up as companies sell off assets to shore up their debt covenants around the April redetermination dates. Better data allows these evaluation teams to do the following:

  1. Reduce data prep time
  2. Increase internal efficiency in evaluation and presenting action plans
  3. Improve ROI by high grading not only acquisition asset values upfront but how to optimize them

Each of these identified on most companies’ wish lists spills over into the next one. The challenge is getting deeper first looks on more deals or areas while at the same time taking minutes to come to a ‘vet or pass’ decision that could have taken months to arrive at in the past.

Find Top Producers

All Oil and Gas Exploration and Production (E&P) companies face the initial challenge of how to quickly benchmark existing production in the area as a proxy for what a new well or a recompletion of an existing well might produce.

SI Fig 1-1 oilfield roi

Let’s say you are part of a small, growing company looking to acquire a position in one of the unconventional plays. A quick look at average 2015 well performance in each play will get you started.

SI Fig 2-1 oilfield roi
Next, factor in well costs: in the top 2 plays, the average Eagle Ford well will run you $5 million to drill and complete, whereas its neighbor in the north, the Bakken, will cost a little over $7 million per well. With a small, lean company’s balance sheet in mind, the combination of higher average production and lower well costs lead to searching for acreage and prospects in the Eagle Ford.

Perform Break-Even Analysis

SI Fig 5 oilfield roi

Looking at ROI analysis, you can highlight areas that match your company’s objectives within the play. At $30 oil, if you take the average 2015 Eagle Ford well and contrast that with the top quartile of operators in the area:

  1. The Oil EURs jumped 80,000 barrels
  2. ROI flipped from -11% to a 10% return

You now have a list of wells that you can look at the geologic, geophysical, and completion designs to de-risk and optimize your company’s acquisition.


Taking the acreage along the La Salle and Dimmit County border, a new ventures shop can pull in ready-made geologic projects to identify what subsurface factors might be driving production in the tight cluster of top producing wells. This area is high-resistivity, has an API gravity of mid 40s, and enjoys a good lower Eagle Ford thickness of about 130 feet. This is all good news for our little shop.

SI Fig 3 oilfield roi

Tweaking Engineering Factors

Top performing companies are turning to Multivariate statistics to incorporate and prioritize all the potential factors across their geologic, geophysical, and engineering models.  In our example, we have geologic variables and engineering variables from how the surrounding wells were completed. In a multivariate model of the area, the amount of proppant used sticks out as one with the most statistically significant effect on production. Companies are now able to ask what if? What if I pump 500 lbs per foot more proppant? What if I pump 500 lbs per foot less? With 5500 foot laterals and $0.15 per pound, that’s an additional cash outlay of $412,000 upfront, will it be worth it? Using the example area, statistically there is not enough of a return to pump more proppant but at the same time it doesn’t make sense pump less, as production would fall off dramatically. Results in optimization of any given factor, backed in black and white by statistics.

SI Fig 4

Analytics make the Difference

Big Takeaway: Savvy teams are finding the highest ROI by being able to break out of their traditional geographic areas and evaluate deals faster, with less prep time, with more certainty, and with a statistical approach that can soften the hearts of boardrooms and investors alike! Better, faster decisions!

Your Turn

What do you think? Leave a comment below.

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Scott Iceton

Scott Iceton is the Manager of Technical Advisors at Drillinginfo. Since joining the company in 2011, Scott has worked with over 2,500 companies on Geosciences, Engineering, and Land workflows. He has been a part of technical support, sales, and training, and now works closely with clients and the products teams at Drillinginfo. Scott graduated from the University of Texas and earned his Petroleum Land Management certification from University of Houston - Downtown.