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The AAPG/Datapages Combined Publications Database
AAPG Bulletin
Abstract
AAPG Bulletin, V.
DOI:10.1306/07220909081
Multivariate fracture intensity prediction: Application to Oil Mountain anticline, Wyoming
Jason A. McLennan1, Patricia F. Allwardt2, Peter H. Hennings3, Helen E. Farrell4
1ConocoPhillips, 600 North Dairy Ashford, Houston, Texas 77079; [email protected]
2ConocoPhillips, 600 North Dairy Ashford, Houston, Texas 77079; [email protected]
3ConocoPhillips, 600 North Dairy Ashford, Houston, Texas 77079; [email protected]
4ConocoPhillips, 600 North Dairy Ashford, Houston, Texas 77079; [email protected]
ABSTRACT
The geometric characteristics of natural fractures significantly impact the hydraulic behavior of fractured reservoirs. Prediction of fracture geometry is therefore important for reservoir development decisions and production forecasting. Although many geometric, kinematic, mechanical, geomechanical, petrophysical, sedimentary, and geophysical attributes correlate to fracture intensity, typically, only the attribute with the highest absolute value correlation is chosen to be carried forward to influence prediction. We employ a geostatistical Bayesian updating approach that quantitatively accounts for multiple important attributes together impacting fracture geometry prediction. The resulting models are more representative of the true geological complexity. This methodology is applied to the Oil Mountain anticline outcrop near Casper, Wyoming.
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