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A Data-Driven Proppant-Filled Fracture Model for Comparing Sliding Sleeve and Plug and Perf Completion Styles


Microseismicity can be used as a diagnostic tool to identify the nature of the hydraulic fracture stimulation associated with different completion styles and determine which style most effectively stimulates the targeted zone of interest. We coupled a proppant-filled Discrete Facture Network (DFN) model with treatment information (slurry volume and proppant concentration) to compare fracture growth and proppant distribution between two wells targeting the Niobrara Formation. One well was completed with twenty-seven sliding-sleeve stages while the other well was treated with thirty-two plug and perf stages. Differences in slurry volumes (93%) and treating pressures (88%) between wells were small and unlike the other wells in the eleven-well pad treatment they were not zipper-fraced. We extend our proppant-filled DFN model (McKenna and Toohey, 2013) by calibrating the model on the entire pad and employ a data-driven proppant-filling algorithm to account for stress anisotropy. By assuming all fractures are fluid filled at the end of the pad treatment, we avoid differentiating rock-stress from fluid-induced microseisms and set the total fracture volume equal to the product of injected slurry volume and fluid efficiency (to account for leakoff). Distal fractures (stage center reference) located near untreated stages likely accommodate injected fluid from those stages. The calibrated fracture model is filled with proppant volumes stage-by-stage outwards from the stage center. The major stress azimuth (θ) is calculated using a spatial-temporal correlation using chronologically-occurring hypocenters (assuming microseismicity occurring close in times reflects displacement along the same failure plane) which is verified by focal mechanism strike. Proppant fills the DFN elliptically to mimic the shape of the microseismic cloud. The major and semi-minor axes of the microseismic cloud is calculated by stacking fractures from all stages and measuring the distance parallel to θ, perpendicular to θ, and vertically. Plug and perf stages show tight, long trends that continue to increase length while pumping, vertical distribution is skewed toward shallower depths, and energy release rate is more constant during the entire treatment. Sliding sleeve stages show broad, short trends resulting in more near-wellbore complexity, vertical distribution is symmetric about the wellbore, and energy release rate reduces as treatment progresses.