Seismicity and Casing Failures Due to Steam Stimulation in Oil Sands

Talebi, Shahriar; Nechtschein, S.; Boone, T.J.

doi:10.1007/978-3-0348-8804-2_13

Cited by 8 publications

(12 citation statements)

References 7 publications

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“…From formation stress test measurements at wells at Cold Lake, the stress field in and above the reservoir is known. In the overburden, the maximum principal stress direction is along N30E-S30W, and the minimum principal stress direction is vertical and along N60W-S60E above and in the reservoir, respectively ͑e.g., Dusseault, 1980;Talebi et al, 1998c͒.…”

Section: Stress Analysismentioning

confidence: 99%

“…The CSS process produces microearthquakes or microseismic events ͑henceforth referred to as events͒ in the overburden and possibly in the reservoir as well. Boone ͑1998͒ andTalebi et al ͑1998a;1998b;1998c͒ studied the seismicity and casing failure in the production wells at Cold Lake, and theoretically analyzed the possible failure mechanisms. More recently, McGillivray ͑2005͒ used induced microearthquake data to monitor steam-front diffusion in the Peace River deposit.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of microearthquake data at Cold Lake and its applications to reservoir monitoring

et al. 2008

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More than four months of continuously recorded microearthquake data acquired at Cold Lake, Canada, was analyzed using advanced algorithms for microearthquake location and subsurface tomography. Robust determination of the spatial, temporal, and magnitude distribution of seismicity is the first step toward understanding the relationship between the stress perturbations caused by the cyclic steam stimulation ͑CSS͒ process and seismicity. Acquisition geometry was constrained because the receivers were located in a single vertical borehole. Despite this constraint, we were successful in improving event locations by use of the double-difference method, which highlights several tight event clusters. The deep cluster at a depth of 400 m, just above the oil reservoir, shows very high seismicity during the CSS processes. A second cluster is observed at shallower depths in the successive steam cycle. This suggests that repeated steaming causes the deformation to spread to shallower depths. The number of events, however, decreases in the second steam cycle. Even though some of the largest events occur below the Clearwater reservoir, we observed few events in the reservoir itself, indicating that the reservoir may be an aseismic region. The size and distribution of seismicity during the first cycle agrees with a Mohr's circle analysis using simple geomechanical modeling.

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Section: Stress Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of microearthquake data at Cold Lake and its applications to reservoir monitoring

et al. 2008

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“…The left-hand side is the area under the displacement pulse corrected for spreading, radiation pattern and source constants. This equation provides a procedure for the determination of seismic moment from far-field displacement signals in the time domain (see TALEBI et al, 1998b).…”

Section: Displacement Fieldmentioning

confidence: 99%

“…To realise this potential, it is necessary to understand the seismic radiation due to this process. This paper presents a seismic model that has been successfully applied to in situ seismic data from the Cold Lake oil field (TALEBI et al, 1998b).…”

Section: Introductionmentioning

confidence: 99%

A Seismic Model of Casing Failure in Oil Fields

Talebi¹,

Boone

Nechtschein

1998

Pure and Applied Geophysics

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We develop a seismic model that characterises the sudden tensional failure of oil-well casings. The energy released by the rupture of a well casing is transformed into heat and seismic energy. The upper bound of the seismic efficiency of this process is estimated at about 3%. The static situation at the completion of a casing failure episode is modelled by calculating the static displacement field generated by two opposing forces separated by an arm. The azimuthal patterns of these displacements and the change in the strain and stress fields caused by the force couple are described. The dynamics of the failure episode are modelled as a dipole with a seismic moment equivalent to the product of the average drop in shear stress, the failure surface, and an arm. The radiated P and S waves have mean-square radiation pattern coefficients of 1/5 for P waves and 2/15 for S waves. The displacement field as a function of time during rupture and the spectral properties in the far field are derived. The most promising seismic parameters that can be used for distinguishing between casing failure events and other possible events are polarisation properties of S waves and S/P amplitude ratios. S-wave polarisation distinguishes between shear events and casing failure events. S/P amplitude ratios distinguish between tensile events and casing failure events.

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“…Thus microseismic monitoring can be used to satisfy environmental concerns, meet regulatory requirements and assess the development of induced fracturing within the reservoir. In addition, the microseismic monitoring systems have been successful in identifying and locating casing failures due to steam stimulation in oil sands (TALEBI et al, 1998).…”

Section: Introductionmentioning

confidence: 99%

Application of Kalman Filtering Techniques for Microseismic Event Detection

Baziw

Weir-Jones

2002

Pure appl. geophys.

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Ð Microseismic monitoring systems are generally installed in areas of induced seismicity caused by human activity. Induced seismicity results from changes in the state of stress which may occur as a result of excavation within the rock mass in mining (i.e., rockbursts), and changes in hydrostatic pressures and rock temperatures (e.g., during¯uid injection or extraction) in oil exploitation, dam construction or¯uid disposal. Microseismic monitoring systems determine event locations and important source parameters such as attenuation, seismic moment, source radius, static stress drop, peak particle velocity and seismic energy. An essential part of the operation of a microseismic monitoring system is the reliable detection of microseismic events. In the absence of reliable, automated picking techniques, operators rely upon manual picking. This is time-consuming, costly and, in the presence of background noise, very prone to error. The techniques described in this paper not only permit the reliable identi®cation of events in cluttered signal environments they have also enabled the authors to develop reliable automated event picking procedures. This opens the way to use microseismic monitoring as a cost-eective production/operations procedure. It has been the experience of the authors that in certain noisy environments, the seismic monitoring system may trigger on and subsequently acquire substantial quantities of erroneous data, due to the high energy content of the ambient noise. Digital ®ltering techniques need to be applied on the microseismic data so that the ambient noise is removed and event detection simpli®ed. The monitoring of seismic acoustic emissions is a continuous, real-time process and it is desirable to implement digital ®lters which can also be designed in the time domain and in real-time such as the Kalman Filter. This paper presents a real-time Kalman Filter which removes the statistically describable background noise from the recorded seismic traces.

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Seismicity and Casing Failures Due to Steam Stimulation in Oil Sands

Cited by 8 publications

References 7 publications

Analysis of microearthquake data at Cold Lake and its applications to reservoir monitoring

Analysis of microearthquake data at Cold Lake and its applications to reservoir monitoring

A Seismic Model of Casing Failure in Oil Fields

Application of Kalman Filtering Techniques for Microseismic Event Detection

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