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The AAPG/Datapages Combined Publications Database
AAPG Bulletin
Abstract
AAPG Bulletin, V.
2012. The American Association of Petroleum Geologists. All rights reserved.
DOI:10.1306/05231110192
Stratigraphic uncertainty in sparse versus rich data sets in a fluvial-deltaic outcrop analog: Ferron Notom delta in the Henry Mountains region, southern Utah
Weiguo Li,1 Janok P. Bhattacharya,2 Yijie Zhu3
1BP America Incorporated, Houston, Texas 77079; [email protected]
2Department of Earth and Atmospheric Sciences, University of Houston, Houston, Texas 77204; [email protected]
3Department of Earth and Atmospheric Sciences, University of Houston, Houston, Texas 77204; [email protected]
ABSTRACT
The Turonian Notom delta is one of the Ferron fluvial-deltaic wedges deposited in the Cretaceous foreland basin of North America and is well
exposed in the Henry Mountains region, Utah. This article uses variable sampling of measured sections of the fluvial-deltaic wedge along a 19-mi (30-km) outcrop belt to address correlation uncertainties in sparse data sets, such as are common in subsurface studies.
A high-resolution sequence
-stratigraphic
analysis
based on 58 measured sections, extensive walking out of beds, and field photomosaics shows that the wedge is composed of 43 parasequences, 18 parasequence sets, and six depositional sequences. Resampling the outcrop belt with 13 sections provides a sparse data set. Correlations using the data set show considerable uncertainties. Fluvial complexity is greatly underestimated, and in the extreme case, only 40% of the fluvial bodies are identified. Overcorrelation results in as much as 400% exaggeration of sandstone width and thickness. Some of the uncertainties can be reduced by incorporating nonmarine
sequence
-stratigraphic models and various techniques that allow a more reasonable evaluation of fluvial body geometry.
With sparse data, uncertainties also arise in marine successions. A key challenge is to identify and correlate the small-scale units, particularly forced regressive deposits. Many of their diagnostic features that can be easily recognized from outcrops and cores may not be as easily detected from well
logs and on seismic data. In subsurface studies where sparse data are observed, integrating detailed facies
analysis
cores and
sequence
-stratigraphic concepts is critical to predict the occurrence and understand the architecture of such deposits.
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