Machine learning for predicting stochastic fluid and mineral volumes in complex unconventional reservoirs
Machine learning for predicting stochastic fluid and mineral volumes in complex unconventional reservoirs A machine learning workflow can quickly, and accurately, predict mineralogy, porosity and saturation in multiple wells to better understand productive layers in unconventional oil reservoirs. Fred Jenson, Chiranjith Ranganathan, Shi Xiuping, Ted Holden, CGG Determination of mineralogy is a critical step in the petrophysical analysis of many types of reservoirs. Changes in volumes of minerals indicate changes in geological deposition, diagenesis, reservoir quality a...
Source: worldoil.com