Basin modeling: identifying and quantifying significant uncertainties

This article is under construction

Basin Modeling: New Horizons in Research and Applications
120px
Series	Hedberg
Chapter	Identifying and Quantifying Significant Uncertainties in Basin Modeling
Author	P. J. Hicks Jr., C. M. Fraticelli, J. D. Shosa, M. J. Hardy, and M. B. Townsley
Link	Web page
Store	AAPG Store

Basin modeling is an increasingly important element of exploration, development, and production workflows. Problems addressed with basin models typically include questions regarding burial history, source maturation, hydrocarbon yields (timing and volume), hydrocarbon migration, hydrocarbon type and quality, reservoir quality, and reservoir pressure and temperature prediction for pre–drill analysis. As computing power and software capabilities increase, the size and complexity of basin models also increase. These larger, more complex models address multiple scales (well to basin) and problems of variable intricacy, making it more important than ever to understand how the uncertainties in input parameters affect model results.

Increasingly complex basin models require an ever-increasing number of input parameters with values that are likely to vary both spatially and temporally. Some of the input parameters that are commonly used in basin models and their potential effect on model results are listed in Table 1. For a basin model to be successful, the modeler must not only determine the most appropriate estimate for the value for each input parameter, but must also understand the range of uncertainty associated with these estimates and the uncertainties related to the assumptions, approximations, and mathematical limitations of the software. This second type of uncertainty may involve fundamental physics that are not adequately modeled by the software and/or the numerical schemes used to solve the underlying partial differential equations. Although these issues are not addressed in this article or by the proposed workflow, basin modelers should be aware of these issues and consider them in any final recommendations or conclusions.

Table 1 Some of the input parameters commonly used in basin models and their potential effects on model results.

Property	Effect
Depths (or isopachs)	Thickness of each unit controls the relative amount of each rock type (see bulk rock properties) and controls the depth and, therefore, temperature and maturity of each stratigraphic unit.
Ages	Ages of each surface and event control timing and thereby control the transient behavior in the model.
Bulk rock properties Stratigraphy/lithology Compaction curves Thermal conductivity Density, heat capacity Radiogenic contribution	The bulk rock properties control the thermal and fluid transport properties (thermal conductivity, density, heat capacity, radiogenic heat, and permeability) that control thermal and pressure evolution in the model.
Missing section (erosion)	The amount of missing section controls the burial history of sediments below the associated unconformity. The burial history controls bulk rock properties (primarily thorugh the compaction history) and the temperature and pressure through time.
Fluid properties	Fluid properties control bulk rock properties in the porous rocks, migration rates, and affect seal capacity.
Source properties Thickness, original total organic carbon and hydrogen index Kinetics, retention/expulsion model	Source properties control the timing, rate, and fluid type for hydrocarbon generation and expulsion from the source rocks.
asdf

External links

find literature about Basin modeling: identifying and quantifying significant uncertainties

• Original content in Datapages
• Find the book in the AAPG Store