From Bureau of Economic Geology, The University of Texas at Austin (www.beg.utexas.edu).
For more information, please contact the author.

 

West Texas Geological Society Fall Symposium, Midland, Texas, October 25-26, 2001

Quantitative Fracture Evaluation and Image Log Calibration,
West Texas Sandstones

Stephen E. Laubach1, Jon Olson2, and Randall A. Marrett3

ABSTRACT

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.
Previously invisible microfractures are readily observed and characterized when their cathodoluminescence is imaged using scanning electron microscopy. This facilitates determination of the orientations, timing (relative to diagenetic events), and sizes of the numerous microfractures typically present in prospective fractured reservoirs. These observations may be made systematically on a bed-by-bed basis. Orientations and timing of microfractures commonly compare favorably with those of associated conductive 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.

 

1Bureau of Economic Geology, The University of Texas at Austin
2Department of Petroleum and Geosystems Engineering, The University of Texas at Austin
3Department of Geological Sciences, The University of Texas at Austin

Dr. Stephen E. Laubach, Senior Research Scientist
Bureau of Economic Geology
The University of Texas at Austin
Box X, University Station, Austin, TX 78713-8972
Phone: (512) 471-6303; Fax 512-471-0140
E-mail: steve.laubach@beg.utexas.edu