2021
DOI: 10.3390/en14227727
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The Effect of Hydraulic Fracture Geometry on Well Productivity in Shale Oil Plays with High Pore Pressure

Abstract: We propose three idealized hydraulic fracture geometries (“fracture scenarios”) likely to occur in shale oil reservoirs characterized by high pore pressure and low differential in situ stresses. We integrate these geometries into a commercial reservoir simulator (CMG-IMEX) and examine their effect on reservoir fluids production. Our first, reference fracture scenario includes only vertical, planar hydraulic fractures. The second scenario has stimulated vertical natural fractures oriented perpendicularly to the… Show more

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Cited by 10 publications
(2 citation statements)
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“…So it is necessary to pay attention to minimize the differential stress due to the greater bottom hole pressure. Then, pore pressure becomes an important part of hydraulic fracturing to control the final stimulation of the fracture geometry (Arias Ortiz et al, 2021). b) Biot Coefficient One of the parameters to determine and minimize geomechanical effects during the process fracturing job is the biot's coefficient.…”
Section: Geomechanicmentioning
confidence: 99%
“…So it is necessary to pay attention to minimize the differential stress due to the greater bottom hole pressure. Then, pore pressure becomes an important part of hydraulic fracturing to control the final stimulation of the fracture geometry (Arias Ortiz et al, 2021). b) Biot Coefficient One of the parameters to determine and minimize geomechanical effects during the process fracturing job is the biot's coefficient.…”
Section: Geomechanicmentioning
confidence: 99%
“…The proposed methodology combines numerical simulation of gas production and stochastic simulation of the gas price based on historical data. Through computational fluid dynamics, we obtain the decline curves of gas production for different combinations of porosity (ϕ), induced permeability or EPV permeability (k EPV ), and EPV geometry values (AR) [50][51][52]. Using historical gas price data and applying the bootstrapping statistical re-sampling technique [53], we obtain the drift and volatility of the stochastic process of gas price evolution over time [54].…”
Section: Introductionmentioning
confidence: 99%