Fracture distribution in a fold and thrust belt is commonly thought to vary depending on structural position, strain, lithology and mechanical stratigraphy. The distribution, geometry, orientation, intensity, connectivity and fill of fractures in a reservoir are all important influences on fractured reservoir quality. The presence of fractures is particularly beneficial in reservoirs that contain little matrix porosity or permeability, for example tight sandstones. In these examples fractures provide essential secondary porosity and permeability that enhance reservoir production. To predict how reservoir quality may fluctuate spatially, it is important to understand how fracture attributes may vary, and what controls them. This research aims to investigate the influence of structural position on fracture attribute variations. Detailed fracture data collection is undertaken on folded sandstone outcrops. 2D forward modelling and 3D model restorations are used to predict strain distribution in the fold-and-thrust belt. Relationships between fracture attributes and predicted strain are determined. Discrete Fracture Network (DFN) modelling is then undertaken to predict fracture attribute variations. DFN modelling results are compared with field fracture data to determine how well fractured reservoir quality can be predicted. Field data suggests strain is a major controlling factor on fracture formation. Fractures become more organised and predictable as strain increases. For example in high strain forelimb regions, fracture intensity and connectivity are high, and fracture orientations are consistent. In lower strain regions, fracture attributes are much more variable and unpredictable. Fracture variations often do not correspond to strain fluctuations, and correlations can be seen between fracture intensity and lithology. Reservoir quality is likely to be much more variable in low strain regions than high strain regions. DFN modelling is also challenging because fracture attribute variations in low strain regions do not correspond to strain, and therefore cannot be predicted.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:659072 |
| Date | January 2015 |
| Creators | Watkins, Hannah E. |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=227123 |
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