Paper No. 3
Presentation Time: 9:30 AM


ZHOU, Wendy and MINNICK, Matthew, Geology and Geological Engineering, Colorado School of Mines, 1516 Illinois Street, Golden, CO 80401,

Subsurface geology, the geologic features beneath the land or sea-floor surface, is an object that can never been fully seen or investigated. Geologists try to represent the subsurface geology through three-dimensional (3D) geological modeling. A 3D geological model represents an interpolation of what could occur between the data points based on certain assumptions. In order to ensure engineers and general end user to proper use the geological model, it is necessary to validate the model and to quantify the uncertainties associated with the model creation. The validation of the model can be done in many traditional ways such as testing model output against a known dataset, cross-validation of interpolation between disparate datasets, and incorporating new points taken in the field and checking for degrees of changes of the interpolation. These methods are not always available or practical especially in modeling the subsurface and dealing with a limited dataset and complex geological conditions. Due to these limitations it has become increasingly important to be able to quantify uncertainty in the model interpolation.

The uncertainty of geological modeling can result from a variety of issues (Lelliott et al. 2009), such as the inherent natural variability that exists in geologic objects and parameters; measurement uncertainty caused be limitations of equipment and human error; sampling uncertainty caused by the ability to characterize the subsurface at only specific points; and modeling uncertainty that exists with data processing and interpolation. Assessment of these uncertainties relied heavily on geostatistical models traditionally. However, less statistical-intensive methods have been developed and used recently (such as Lelliott et al., 2009; Keefer et al., 2011; MacCormack and Eyles, 2012) in uncertainty assessment of geological modeling. This presentation provides examples of uncertainty assessments and discussions of various uncertainty assessment issues. It is not the authors’ intention to exhaust the uncertainty assessment meth­ods, but to provide case study in which uncertainty has been addressed for 3D geological modeling application.