The objective of this study is to better understand the impact of mineralogy, in-situ stress and natural fractures on hydraulically-induced fracture system geometry within horizontal organic shale wells. Vertical heterogeneity within organic shale occurs at a much smaller scale than that in the lateral direction. Previous studies involving borehole image analyses suggest that the lateral variability observed in most horizontal shale wells is the result of the wellbore traversing multiple layers of different rock properties (i.e., vertical heterogeneity). Results have shown that a more efficient and effective hydraulic fracture stimulation is possible when this variability is addressed in the completion design.

Borehole micro -resistivity image data from horizontal wells in multiple U.S. shale basins are analyzed and compared to borehole -based micro -seismic data. Natural and drilling-induced fracture type, spacing and orientation are analyzed in order to reveal their impact on hydraulic fracture initiation and geometry. Natural fracture orientation relative to the maximum horizontal stress has been shown to influence hydraulically-induced fracture system geometry. Drilling-induced fractures are essentially miniature hydraulic fractures and provide information about near wellbore in-situ stresses that can be used to predict relative hydraulically -induced fracture initiation pressures and geometry. Previous studies have shown that fracture initiation pressure is directly proportional to clay content within organic shale reservoirs.

This study provides an improved understanding of factors that ultimately control the economics of horizontal shale wells. Horizontal measurements collected during drilling or post-drill allow for (i) understanding where the wellbore is in section (i.e., well placement), (ii) visualization of how the reservoir characteristics are changing along the lateral wellbore (i.e., heterogeneity) and, (iii) planning the stimulation accordingly (i.e., treatment design). These data allow operators to predict how certain reservoir properties impact reservoir stimulation. Such correlations should lead to improved operational efficiency and better well performance, thereby increasing return on investment.

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