New modeling methods for unconventional reservoirs could help oil & gas producers optimize well production. A recent article in The American Oil & Gas Reporter highlights some of Battelle’s work in this area.
Using data from 476 horizontal wells in the Wolfcamp Shale play in the Delaware Basin, researchers analyzed the factors that impact well performance. The analysis was used to develop predictive models and decision rules to help operators identify the wells with the most production potential and make effective decisions to maximize overall production.
Data-driven statistical modeling can be used to predict well performance and improve results from Enhanced Oil Recovery (EOR) efforts. Statistical models take less time to develop than mechanistic models such as physics-based simulators, allowing operators to extract important trends and information with less time and effort. However, choosing and applying the right algorithm is critical in order to extract meaningful results. This has been especially challenging for unconventional reservoirs. The Wolfcamp Shale study is helping to inform development of more robust models with better predictive power for complex unconventional reservoirs.
The study was conducted by Battelle researchers Jared Schuetter and Srikanta Mishra, along with Ming Zhong of Shell and Randy LaFollette of Baker Hughes. The complete article can be found in the April 2016 Special Report on Drilling Technology for The American Oil & Gas Reporter.