Study on Shear Fracture Performance of Subsea Test Tree Under Emergency Conditions in the Deepwater Oil and Gas Completion Testing

The relation between stimulated shear fractures and production in the Barnett Shale: Implications for unconventional oil and gas reservoirs

Geophysics ◽

10.1190/geo2018-0545.1 ◽

2019 ◽

Vol 84 (6) ◽

pp. B461-B469 ◽

Cited By ~ 2

Author(s):

Alex Hakso ◽

Mark Zoback

Keyword(s):

Hydraulic Fracturing ◽

Oil And Gas ◽

Shear Fracture ◽

Fracture Network ◽

Early Years ◽

Barnett Shale ◽

Hydraulic Fractures ◽

Low Permeability ◽

Distributed Temperature Sensing ◽

Fracture Planes

Economic production from extremely low permeability unconventional reservoirs is accomplished through multistage slick water hydraulic fracturing, which generates opening-mode hydraulic fractures and induces shear slip on preexisting fractures in the surrounding formation. We have addressed the critical contribution of the stimulated shear fracture network on production. We found production decline curves from tens of thousands of wells in four unconventional plays in the U.S. (two oil and two gas). These data indicate that during the early years of production: (1) Production is dominated by linear flow from the extremely low permeability matrix into much more permeable fracture planes, (2) the rapid decrease in production rates is a natural consequence of pressure depletion in the matrix within several meters of the more permeable planes, and (3) the cumulative area of permeable fracture planes created during stimulation is an important factor affecting cumulative production. Using data from two case studies in the Barnett Shale, we estimate the area of the fracture network from the microseismicity generated during hydraulic fracturing operations. The data from one study demonstrates that the cumulative area of the shear fracture network is needed to match production data. With data from the other case study, we demonstrate that the relative fracture area created during each stage correlates well with the relative stage-by-stage production determined from distributed temperature sensing.

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