Generating 3D Permeability Map of Fracture Networks Using Well, Outcrop, and Pressure-Transient Data

Abstract

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 welltest 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.