--> --> ABSTRACT: 3-D Geocellular Oil-Resource Determination in South Texas Frio Fluvial-Deltaic Reservoirs, by M. H. Holtz, J. Yeh, and C. Y. Chang; #90941 (1997).
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ABSTRACT: Previous Hit3-DNext Hit Geocellular Oil-Resource Determination in South Texas Frio Fluvial-Deltaic Reservoirs

HOLTZ, MARK H., J. YEH, C. Y. CHANG

Increased accuracy and possible variability of calculated original oil in place can be achieved by combining information acquired from both geologic and engineering reservoir characteristics into a comprehensive model. Three-dimensional (Previous Hit3-DNext Hit) geocellular computer modeling facilitates this integration. Such an approach allows geologic architecture and engineering fluid-flow trends to be combined in order to delineate the spatial geometry of individual reservoir genetic units. Information from both disciplines can be used to determine the spatial distribution of petrophysical attributes within these genetic units, resulting in increased accuracy in calculating original-oil-in-place (OOIP) volumetrics.

In order to determine original and remaining OOIP in South Texas Frio Fluvial reservoirs, Previous Hit3-DNext Hit geocellular computer modeling was applied. We found that fourth- and fifth-order flooding surfaces define reservoir architecture by constraining depositional units and delineating the spatial distribution of gross sandstone depositional facies. Depositional facies information was then combined with both conventional and special core analyses to generate porosity, permeability, water saturation, and Previous HitresidualNext Hit-oil saturation transforms. Fluid-flow trends, including water:oil and gas:oil ratios, were analyzed to determine the connectivity within each fifth-order genetic unit.

The Previous Hit3-DTop geometry of each genetic unit was modeled as distinct bounding surfaces to constrain petrophysical property interpolation, and various controls on petrophysical interpolation were applied to test their sensitivity. Proportional geocellular layering character resulted in a 20-percent increase in OOIP, as compared with onlapping cells against bounding surfaces. A 6-percent variation in OOIP resulted when we combined onlap with directional interpolation bias as opposed to template weighting.

AAPG Search and Discovery Article #90941©1997 GCAGS 47th Annual Meeting, New Orleans, Louisiana