LATERAL DELINEATION OF SANDSTONE BODIES GUIDED BY SEISMIC AND PETROPHYSICAL DATA USING GEOCELLULAR MODEL: CAÑADÓN SECO FORMATION, SAN JORGE BASIN, ARGENTINA. SPE 69487
Language: Inglés Series: Guerberoff, David ; Publication details: Dallas, Texas Society of Petroleum Engineers 2001Online resources: Summary: The studied area is characterized by sandstone-shale complexes vertically arranged in a column of approximately 200 m. Conventional well correlations provide high uncertainty in sandstone prediction because of the high variability and small lateral extension of the bodies. We rely on geo-statistical techniques of interpolation of the petrophysical variables supported by seismic derived attributes. Seismic-petrophysical matrixes and cross plots were constructed to high correlation coefficients. Having the linear correspondence between the variables, an adjusted function allow us to find the unknown values (petrophysical) from the seismic data using geo-statistical methods such as Krigging and Co-Krigging. The grids of petrophysical values feed a geocellular model where they are volumetrically interpolated. This static model can be used through "up scaling" in a future dynamic model for reservoir simulation.| Current library | Status | Barcode | |
|---|---|---|---|
| Biblioteca virtual | Not for loan | 200003054 |
The studied area is characterized by sandstone-shale complexes vertically arranged in a column of approximately 200 m. Conventional well correlations provide high uncertainty in sandstone prediction because of the high variability and small lateral extension of the bodies. We rely on geo-statistical techniques of interpolation of the petrophysical variables supported by seismic derived attributes. Seismic-petrophysical matrixes and cross plots were constructed to high correlation coefficients. Having the linear correspondence between the variables, an adjusted function allow us to find the unknown values (petrophysical) from the seismic data using geo-statistical methods such as Krigging and Co-Krigging. The grids of petrophysical values feed a geocellular model where they are volumetrically interpolated. This static model can be used through "up scaling" in a future dynamic model for reservoir simulation.
