Water, Water Everywhere Using ML and Game Theory To Win at Produced-Water Forecasting
Authors: Feder Judy 
Published: September 2020

In the Bakken-Three Forks play of the Williston Basin, many oil wells that once produced some water have become water wells that produce some oil, as average oil production has flatlined while water production continues to increase.

A complex interplay of stepping out beyond the core to where water saturations are higher, upsizing completions, tighter spacing, and dealing with greater parent-child effects and potential changes in relative permeability is significantly increasing volumes of produced water. Similar situations have been occurring in other basins.

This is a serious threat for the US unconventional oil and gas industry, for which produced water has become a $34-billion industry and exposes operators to numerous operational, environmental, and economic risks.

Software developers are beginning to adapt advanced machine-learning (ML) methods that have proved successful in forecasting oil production and upgrading them with aspects of game theory to make quick and accurate work of understanding and predicting water production in unconventional plays. Novi Labs (Novi), an Austin-based software company focusing on unconventional shale, has developed a solution that is being applied successfully in the Williston Basin to help disentangle the complex interactions of larger completion designs, changing geology, and tighter spacing that contribute to increased water production. According to the firm’s model, fluid per foot ranks as the most important input variable for increasing water production, ranking above proppant per foot and geologic parameters.

Ted Cross, technical advisor at Novi and former senior geologist with Conoco Phillips, presented a paper that discussed the produced water challenge at the 2020 Unconventional Resources Technology Conference (URTeC).

“How often does an engineer dash off a simple water forecast, doing something like applying a flat water-to-oil ratio to their water prediction?” Cross asked rhetorically. In unconventional oil fields, water forecasting and pre-drill water predictions have not received attention commensurate with their economic importance. “Quick is still common,” he said.

Operators, regulators, and water-disposal companies often rely on simplistic water-cut ratios or basin-level extrapolations that ignore the complex interplay of geology, completions, and spacing decisions on water production. “They are starting to realize and incorporate the fact that water-to-oil ratios will evolve over a well’s life, usually increasing. But the critical thing is that the time they spend on water prediction is a tiny fraction of what they spend on oil, and the methods are less sophisticated and developed,” Cross said.

Part of the reason, he explained, is that in the early development of the Eagle Ford, Permian, and some core parts of the Williston, either the original wells didn’t produce large volumes of water or the existing infrastructure around conventional plays was sufficient to handle it. But with field evolution and changing completion designs, water has become a critical issue.