Bureau of Economic Geology, The University of Texas at Austin (www.beg.utexas.edu).
West Texas Geological Society Fall Symposium, Midland, Texas, October 25-26, 2001
Fracture Evaluation and Image Log Calibration,
Stephen E. Laubach1, Jon Olson2, and Randall A. Marrett3
Ongoing research is
aimed at enhancing exploration and production for fractured reservoirs
by development and integration of emerging and existing technologies for
the observation, prediction, and fluid-flow modeling of natural fractures.
Macroscopic fractures produce the largest impact on fluid flow through
fractured rock, however they are orders of magnitude less abundant than
microscopic fractures. Macro-fractures in subsurface reservoirs typically
are poorly represented by data acquired with conventional techniques.
Due to the abundance of microfractures, they can be well studied even
in small samples from the subsurface. We are exploring the hypotheses
that micro- and macro-fractures are different size fractions of the same
fracture sets, and that microfractures can be used to predict the critical
characteristics (in terms of fluid flow) of associated macro-fractures.
Microfractures are sufficiently abundant in the numerous fractured units we have studied that the size distributions can be readily quantified. Under special circumstances, the sizes (i.e., mechanical apertures and/or lengths) of both micro- and macro-fractures can be reliably measured in the same fractured rock volume. The spatial frequency of fractures, as a function of fracture size, follows power-law distributions over at least 4 to 5 orders of magnitude in these cases. This confirms that microfracture sizes can be used to quantitatively predict spatial frequencies of associated macro-fractures.
The orientations, time of formation relative to diagenetic minerals, and sizes of macro-fractures are the most important factors for understanding fluid flow in fractured rock. Although discrete-fracture modeling provides the most realistic portrayal of fluid flow through fractured rock, this technique is computationally infeasible for simulation of the large volumes in a fractured hydrocarbon field. Dual-porosity simulation is the dominant technique for this reason. We are developing a blended approach to simulation that is both cost effective and grounded on local fracture observation.
On a bed-by-bed basis, microfracture observations are used to make statistical predictions of the key macro-fracture attributes. From these predictions, multiple discrete-fracture models are generated for each bed, representing volumes comparable to those of the cells in dual-porosity simulations. Fluid-flow simulations in the discrete-fracture models provide a quantitative, observation-based understanding of the fluid-flow characteristics and spatial heterogeneity for each bed. These results can then be used to construct a dual-porosity simulation for large regions in the subsurface. Quantitative testing of this approach with subsurface flow data is ongoing.
Examples will be provided of application of this method to oil and gas fields in West Texas sandstone plays.
of Economic Geology, The University of Texas at Austin
E. Laubach, Senior Research Scientist