摘要：Natural fracture network characteristics can be establishes from high-resolutionoutcrop images acquired from drone and photogrammetry. Such images mightalso be good analogues of subsurface naturally fractured reservoirs and canbe used to make predictions of the fracture geometry and efficiency atdepth. However, even when supplementing fractured reservoir models withoutcrop data, gaps will remain in the model and fracture networkextrapolation methods are required. In this paper we used fracture networksinterpreted from two outcrops from the Apodi area, Brazil, to present arevised and innovative method of fracture network geometry prediction usingthe multiple-point statistics (MPS) method.The MPS method presented in this article uses a series of small synthetictraining images (TIs) representing the geological variability of fractureparameters observed locally in the field. The TIs contain the statisticalcharacteristics of the network (i.e. orientation, spacing, length/height andtopology) and allow for the representation of a complex arrangement of fracture networks.These images are flexible, as they can be simply sketched by the user.We proposed to simultaneously use a set of training images in specificelementary zones of the Apodi outcrops in order to best replicate thenon-stationarity of the reference network. A sensitivity analysis wasconducted to emphasise the influence of the conditioning data, thesimulation parameters and the training images used. Fracture densitycomputations were performed on selected realisations and compared to thereference outcrop fracture interpretation to qualitatively evaluate theaccuracy of our simulations. The method proposed here is adaptable in termsof training images and probability maps to ensure that the geological complexityin the simulation process is accounted for. It can be used on any type ofrock containing natural fractures in any kind of tectonic context. Thisworkflow can also be applied to the subsurface to predict the fracturearrangement and fluid flow efficiency in water, geothermal or hydrocarbonfractured reservoirs.
