Estimating In-situ, Anisotropic, Principal Stresses from 3D Seismic

Gray, F.D.; Anderson, Paul M.; Logel, John D.; Delbecq, Franck; Schmidt, Darren D.

doi:10.3997/2214-4609.201400910

Cited by 6 publications

(8 citation statements)

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“…In general it is empirically related to the minimum horizontal stress (e.g., Iverson, 1995). Expanding on Gray (2010b), a method for the estimation from seismic data of all three principal stresses, the vertical stress, σ v , the maximum horizontal stress, σ H , and the minimum horizontal stress, σ h , is introduced here. Warpinski and Smith (1989) state that in-situ stresses are clearly the most important factor controlling hydraulic fracturing.…”

Section: Introductionmentioning

confidence: 99%

Estimation of stress and geomechanical properties using 3D seismic data

Gray¹,

Anderson²,

Logel³

et al. 2012

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Principal stresses, that is vertical, maximum horizontal and minimum horizontal stresses, and elastic moduli related to rock brittleness, like Young's modulus and Poisson's ratio, can be estimated from wide-angle, wide-azimuth seismic data. This is established using a small 3D seismic survey over the Colorado shale gas play of Alberta, Canada. It is shown that this information can be used to optimize the placement and direction of horizontal wells and hydraulic fracture stimulations.

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Section: Introductionmentioning

confidence: 99%

Estimation of stress and geomechanical properties using 3D seismic data

Gray¹,

Anderson²,

Logel³

et al. 2012

First Break

Self Cite

128

View full text Add to dashboard Cite

show abstract

“…Therefore, it represents the fundamentals of hydraulic fracturing (that is, the deformation and fracturing of rock is caused by stressing it with hydraulic pressure in the borehole). Gray et al (2010) use linear slip theory following Iverson (2010) to estimate these properties from seismic data. Principal stresses are estimated by combining elastic rock properties derived from seismic inversion with azimuthal velocity and AVO analysis of conventional 3D seismic data (Gray, 2011).…”

Section: Methodsmentioning

confidence: 99%

“…Well-calibrated Young's modulus estimates from prestack seismic inversion are critical to isolate brittle areas within the shale. However, interpretation of Young's modulus alone is insufficient to identify optimum targets for hydraulic fracturing (Gray et al, 2010). It is also necessary to understand stress-field distribution characterized by DHSR.…”

Section: Seismic Analysis and Stress Estimationmentioning

confidence: 99%

Seismic reservoir characterization in resource shale plays: Stress analysis and sweet spot discrimination

et al. 2011

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Surface seismic data have proven to be an invaluable asset for organizations producing hydrocarbons from unconventional resource plays. Initially, a primary benefit of surface seismic was the ability to locate and avoid drilling into zones with faults, fractures, and karsting which adversely affected the ability to complete the well successfully. More recent advances in prestack seismic data analysis yield attributes that appear to be correlated to formation lithology, rock strength, and stress fields. Knowledge and proper utilization of these attributes may prove valuable in the optimization of drilling and completion activities.

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“…Therefore, it represents the fundamentals of hydraulic fracturing, that is, the deformation and fracturing of rock is caused by stressing it with hydraulic pressure in the borehole. Gray et al (2010) uses Linear Slip Theory following Iverson (2010) to estimate these properties from seismic data . Principal stresses are estimated by combining elastic rock properties derived from seismic inversion with azimuthal velocity and AVO analysis of conventional 3D seismic data (Gray 2011).…”

Section: Stress Analysis Methodologymentioning

confidence: 99%

“…An elevated well-calibrated value of Young's Modulus is a key property to isolate brittle areas within the shale. However, interpretation of Young's Modulus alone is insufficient to identify optimum targets for hydraulic fracturing (Gray et al, 2010). It is also necessary to understand stress field distribution characterized by the DHSR.…”

Section: Figure 1: Reservoir Characterization Workflowmentioning

confidence: 99%

Seismic reservoir characterization in resource shale plays: “Sweet spot” discrimination and optimization of horizontal well placement

Sena

Castillo

Chesser

et al. 2011

SEG Technical Program Expanded Abstracts 2011

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Surface seismic data has proven to be an invaluable asset for organizations producing hydrocarbons from unconventional resource plays. Initially, one of the primary benefits of surface seismic was the ability to locate and avoid drilling into zones with faults, fractures and karsting which adversely affected the ability to complete the well successfully. More recent advances in pre-stack seismic data analysis yield attributes that appear to be correlated to formation lithology, rock strength and stress fields. Knowledge and proper utilization of these attributes may prove valuable in the optimization of drilling and completion activities. In this article we show an integrated seismic approach based on pre-stack azimuthal seismic data analysis and well log information to identify "sweet spots", estimate geomechanical properties and in-situ principal stresses.

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Estimating In-situ, Anisotropic, Principal Stresses from 3D Seismic

Cited by 6 publications

References 0 publications

Estimation of stress and geomechanical properties using 3D seismic data

Estimation of stress and geomechanical properties using 3D seismic data

Seismic reservoir characterization in resource shale plays: Stress analysis and sweet spot discrimination

Seismic reservoir characterization in resource shale plays: “Sweet spot” discrimination and optimization of horizontal well placement

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