AAPG Bulletin, Vol.95, No.6, 899-923, 2011
Static connectivity of fluvial sandstones in a lower coastal-plain setting: An example from the Upper Cretaceous lower Williams Fork Formation, Piceance Basin, Colorado
This study addresses the field-scale architecture and static connectivity of fluvial sandstones of the lower Williams Fork Formation through analysis and reservoir modeling of analogous outcrop data from Coal Canyon, Piceance Basin, Colorado. The Upper Cretaceous lower Williams Fork Formation is a relatively low net-to-gross ratio (commonly <30%) succession of fluvial channel sandstones, crevasse splays, flood-plain mudstones, and coals that were deposited by meandering river systems within a coastal-plain setting. The lower Williams Fork outcrops serve as proximal reservoir analogs because the strata dip gently eastward into the Piceance Basin where they form natural gas reservoirs. Three-dimensional architectural-element models (3-D reservoir models) of the lower Williams Fork Formation that are constrained to outcrop-derived data (e.g., sandstone body types, dimensions, stratigraphic position) from Coal Canyon show how static sandstone body connectivity is sensitive to sandstone body width and varies with net-to-gross ratio and well spacing. With a low well density (e.g., 160-ac well spacing), connectivity is low for net-to-gross ratios less than 20%, connectivity increases between net-to-gross ratios of 20 to 30%, and levels off above a net-to-gross ratio of 30%. As well density increases, static connectivity increases more linearly with an increasing net-to-gross ratio. For a 20-ac well spacing, static connectivity can range from approximately 35 to 75% and 45 to 80% for net-to-gross ratios of 10 and 15%, respectively, depending on sandstone body width. Given the lower net-to-gross ratio and continuity of lower Williams Fork deposits, this underscores the importance of representative sandstone body statistics (e.g., sandstone body type, dimensions) to aid in subsurface correlation and mapping and to constrain reservoir models.