Quantitative
Seismic
Geomorphology Study in Fluvial Systems – A New Approach
Lorena Moscardelli1, Denise Woods2, and Lesli Wood1
1 Jackson School of Geosciences The University of Texas at Austin, Austin, TX
2 OXY Occidental Oil and Gas Corporation, Houston, TX
The ongoing development and harvesting of shallow marine and terrestrial reservoir systems demand increasingly comprehensive understanding of how to interpret complex reservoir architecture and how to better utilize 3D
seismic
and dense well databases to improve field development and increase production. This study presents Quantitative
Seismic
Geomorphology as an alternative methodology that intend to gain a better understanding of productive fluvial depositional systems, to improve reservoir characterization and to generate realistic inputs for stochastic modeling through the use of quantitative
data
.
Quantitative
Seismic
Geomorphology (QSG) has been defined as the quantitative analysis of the landforms, imaged in
3-D
seismic
data
, for the purposes of understanding the history, processes and fill architecture of basins. Quantitative
data
was collected in an U.Paleozoic fluvial stratigraphic succession (USA) and it was compared with
data
from Mio-Pleistocene fluvial intervals of the Natuna Basin-Indonesia, the coastal plain of the GOM and the modern Brazos River. Several measurements were collected in channels from different locations and stratigraphic intervals, including channel width, meander wavelength, radius of curvature, meander-belt width and meander-arc distance. Sinuosity values were used to classify channels according to their sediment load and to predict sediment type. Morphometric
data
was also used to evaluate subsurface reservoir dimensions. The
data
shows a huge variability in terms of dimensions and geometries in the GOM and the Indonesia
data
bases. However, the U.Paleozoic succession (USA) shows less variability and the predominance of smaller systems (creeks/distributaries), these differences can be associated with changes in extrinsic factors such as clime, paleogeography and tectonism.