CHARACTERISING FRACTURE PATTERNS IN A FOLD-AND-THRUST BELT; AN ANALOGUE FOR A FRACTURED TIGHT SANDSTONE RESERVOIR

Open or partially open fractures may be important for enhancing reservoir quality, especially where primary porosity and permeability is low. In order for productivity to be enhanced, fractures must be well connected, a factor influenced by fracture orientation, length, fill, distribution and intensity. We explore how these fracture attributes vary as a function of structural position in a fold-and-thrust belt. We use a workflow involving systematic grid sampling and transect sampling to characterise heterogeneous strain at outcrop. At each sampling site fracture attribute data is collected using a combination of linear scan line, circular scan line and areal sampling techniques, in order to capture variability in fracture patterns.

Our analysis suggests there are two main structural controls on fractures; fold curvature and deformation history. Regions of high curvatures, or that have undergone long deformation histories (high strain), exhibit consistent fracture attributes across large areas, indicating that fracturing is controlled by strain. Low curvature regions and younger folds (lower strain) exhibit variable fracture patterns that are inconsistent across small areas, indicating fracture formation is influenced by lithology.

Well connected, predictable fracture networks in high strain regions make these zones ideal fractured reservoir targets. However, where curvature is highest fractures are quartz filled, meaning these regions would make poor fractured reservoirs. Connectivity is lower in low strain regions, meaning fractured reservoir quality prediction is difficult. Fractures in low strain regions are generally open, meaning that although fractures are unpredictable, these regions would make better fractured reservoirs than high strain regions. The systematic quantification of fracture patterns and fracture attributes as a function of structural position can provide useful insights into predicting reservoir quality in regions of heterogeneous strain.