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Mondal, Satyajit, 2010

Stochastic connectivity analysis of low sinuosity streams and statistical analysis of representative petrographic data from tertiary tight gas sands, Cook Inlet, Alaska

Bibliographic Reference

Mondal, Satyajit, 2010, Stochastic connectivity analysis of low sinuosity streams and statistical analysis of representative petrographic data from tertiary tight gas sands, Cook Inlet, Alaska: University of Alaska Fairbanks, M.S. thesis, xvii, 200 p., illust., maps.

Abstract

Tight gas sands present a considerable development challenge due to reservoir heterogeneity and poor permeability. Successful exploitation of tight gas reservoirs requires an understanding of the factors controlling their porosity and permeability (P&P) as well as the geologic factors influencing the distribution of key facies. Initial statistical analysis of published petrographic data of Cook Inlet tight gas prospects reconfirmed the effect of mechanical compaction on porosity. A suitable correlation between porosity and depth for very-fine- to fine- (VF-F) grain tight gas sandstone was developed. Though permeability was weakly correlated with porosity, the positive effect of macropore (>20 microns across) percentage on permeability was evident. Thus, a suitable permeability-macropore correlation was developed for non-cemented, VF-F grain, and fine-medium to medium grain sandstone samples. These results help clarify the factors that control the porosity and permeability of Cook Inlet tight gas prospects. Static connectivity and effective static connectivity analysis of stochastic channel facies model representing low sinuosity river deposits, as found in the Cook Inlet Region in Alaska, shows the high uncertainty involved in static connectivity analysis at lower channel facies volume percentage. However, channel deposits of sinuosity 1.1 show best static connectivity with a drainage area of 50 acres. Above 70-75% of channel volume, the role of channel dimension in static connectivity is limited and 100% static connectivity is achievable. This facies modeling assists in predicting the factors that control the static connectivity of low-sinuosity tight gas reservoirs in Kenai Group formations. Moreover, this static connectivity analysis will help determine recommended well spacing and well type, orientation, and suitable completion techniques to enhance recovery efficiency in Cook Inlet tight gas sands

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