This paper presents a novel approach in statistical analysis of well performance of multi-stage fractured wells completed in specific part of Montney. For the first time, both geological and hydraulic fracture parameters were considered in analysis with objective of finding most influential parameters that impact deliverability of wells. Results from single point statistical analysis were further extended to unsupervised discrete classification using neural-network to bin the reservoir. Binning classification was then used to design and optimize hydraulic fracture parameters.

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