Energies (Sep 2018)

Characterization and Prediction of Complex Natural Fractures in the Tight Conglomerate Reservoirs: A Fractal Method

  • Lei Gong,
  • Xiaofei Fu,
  • Shuai Gao,
  • Peiqiang Zhao,
  • Qingyong Luo,
  • Lianbo Zeng,
  • Wenting Yue,
  • Benjian Zhang,
  • Bo Liu

DOI
https://doi.org/10.3390/en11092311
Journal volume & issue
Vol. 11, no. 9
p. 2311

Abstract

Read online

Using the conventional fracture parameters is difficult to characterize and predict the complex natural fractures in the tight conglomerate reservoirs. In order to quantify the fracture behaviors, a fractal method was presented in this work. Firstly, the characteristics of fractures were depicted, then the fracture fractal dimensions were calculated using the box-counting method, and finally the geological significance of the fractal method was discussed. Three types of fractures were identified, including intra-gravel fractures, gravel edge fractures and trans-gravel fractures. The calculations show that the fracture fractal dimensions distribute between 1.20 and 1.50 with correlation coefficients being above 0.98. The fracture fractal dimension has exponential correlation with the fracture areal density, porosity and permeability and can therefore be used to quantify the fracture intensity. The apertures of micro-fractures are distributed between 10 μm and 100 μm, while the apertures of macro-fractures are distributed between 50 μm and 200 μm. The areal densities of fractures are distributed between 20.0 m·m−2 and 50.0 m·m−2, with an average of 31.42 m·m−2. The cumulative frequency distribution of both fracture apertures and areal densities follow power law distribution. The fracture parameters at different scales can be predicted by extrapolating these power law distributions.

Keywords