--> ABSTRACT: Reducing Uncertainty in Burial And Thermal History Modeling of The Colville Basin, Alaska North Slope, by Burns, W. Matthew, Daniel O. Hayba, Elisabeth L. Rowan, David W. Houseknecht; #90026 (2004)

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Burns, W. Matthew1, Daniel O. Hayba1, Elisabeth L. Rowan1, David W. Houseknecht1
(1) U.S. Geological Survey, Reston, VA

ABSTRACT: Reducing Uncertainty in Burial And Thermal History Modeling of The Colville Basin, Alaska North Slope

Sources of error in burial/thermal history modeling include: (1) uncertainty in model inputs (e.g. basin stratigraphy, matrix properties, basal heat flow), (2) the ability of model algorithms to reproduce basin evolution, and (3) uncertainty in calibration data (e.g. rock properties, measured temperatures, vitrinite reflectance data) used to assess model validity. For modeling the Colville basin of the Alaska North Slope, the focus has been on reducing error in model inputs to ensure that the available algorithms provide the highest accuracy results.
The largest potential sources of error for the burial/thermal history model of the Colville basin are: (1) poor chronostratigraphic resolution in the clastic foreland-type strata, whose deposition initiated source rock maturation and (2) uncertainty in the amount of exhumation since maximum burial. Application of sequence stratigraphic analysis reduces uncertainty in stratigraphic ages used in modeling by as much as 50% for the foreland strata. Furthermore, improved estimates of exhumation, derived from porosity-depth trends, reduce uncertainty in maximum burial depth to +/-500 feet for most wells, as opposed to 1000s of feet when using exhumation estimates derived from vitrinite reflectance data.
Error derived from parameterization of matrix properties was addressed by integrating geophysical logs with lithologic and petrophysical data, thereby defining the physical behavior (e.g. change in porosity, permeability, thermal conductivity) of modeled strata as functions of lithology and depth. Compared to results from software defaults or parameters from the literature, our preferred parameters significantly enhance agreement between rock property and fluid pressure predictions and the calibration data.

 

AAPG Search and Discovery Article #90026©2004 AAPG Annual Meeting, Dallas, Texas, April 18-21, 2004.