Summary
Well-log and core information, seismic surveys, outcrop studies, and
pressure-transient tests are usually insufficient to generate representative 3D
fracture-network maps individually. Any combination of these sources of data
could potentially be used for accurate preparation of static models.
Our previous attempts showed that there exists a strong correlation between
the statistical and fractal parameters of 2D fracture networks and their
permeability (Jafari and Babadagli 2009). We extend this work to
fracture-network permeability estimation using the statistical and fractal
properties data conditioned to well-test information. For this purpose, 3D
fracture models of 19 natural-fracture patterns with all known fracture-network
parameters were generated initially. It is assumed that 2D fracture traces on
the top of these models and 1D data from imaginary wells that penetrated the
whole thickness of the cubic models were available, as well as
pressure-transient tests of different kinds. The 1D and 2D data include
statistical parameters and fractal characteristics of different features of the
fracture system. Next, the permeability of each 3D fracture-network model was
measured and then converted to a grid-based permeability map for drawdown
well-test simulations using commercial software packages.
Finally, an extensive multivariable-regression analysis (MRA) using the
statistical and fractal properties and well-test permeability as independent
variables was performed to obtain a correlation for equivalent fracture-network
permeability. The equations were derived using different
natural-fracture-network patterns. The cases requiring well (logs and cores)
and reservoir (pressure-transient tests) data were identified. It was found
that an equation honoring all types of data [i.e., outcrop (2D), wellbore data
(1D), and well-test analysis (3D)] can accurately predict the actual
permeability of the fracture system. For certain fracture-network types,
reliable correlations can be obtained without 2D data, which are relatively
difficult to obtain. These types of patterns were identified.
© 2011. Society of Petroleum Engineers
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History
- Original manuscript received:
16 September 2009
- Meeting paper published:
20 October 2009
- Revised manuscript received:
12 October 2010
- Manuscript approved:
13 October 2010
- Published online:
29 March 2011
- Version of record:
6 April 2011
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