Comparison of surface and borehole locations of induced seismicity

Eisner, Leo; Hulsey, B.J.; Duncan, P. Martin; Jurick, Dana; Werner, Heigl; Keller, William R.

doi:10.1111/j.1365-2478.2010.00867.x

Cited by 181 publications

(80 citation statements)

References 15 publications

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“…Attempts were made to select common events detected during this period by both (deep and shallow) networks for a joint location analysis, however, due to clock synchronization problems and difference in sensor frequency bands between the two networks, the common events could not be identified, and hence the task could not be accomplished. Some research indicated that by carefully identifying the largest events in different networks, synchronization between networks sometimes can be achieved by shifting the origin times in one network with a constant time (Eisner et al, 2010). The similar strategy will be adopted in the future.…”

Section: Induced Microearthquake Datasetmentioning

confidence: 99%

Focal mechanism determination of induced microearthquakes in an oil field using full waveforms from shallow and deep seismic networks

Küleli

Zhang

et al. 2011

GEOPHYSICS

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A new, high frequency, full waveform matching method is used to study the focal mechanisms of small, local earthquakes induced in an oil field, which are monitored by a sparse near-surface network and a deep borehole network. The determined source properties are helpful for understanding the local stress regime in this field. During the waveform inversion, we maximize both the phase and amplitude matching between the observed and modeled waveforms. We also use the polarities of the first P-wave arrivals and the average S/P amplitude ratios to better constrain the matching. An objective function is constructed to include all four criteria. For different hypocenters and source types, comprehensive synthetic tests show that our method is robust to determine the focal mechanisms under the current array geometries, even when there is considerable velocity inaccuracy. The application to several tens of induced microseismic events showed satisfactory waveform matching between modeled and observed seismograms. The majority of the events have a strike direction parallel with the major NE-SW faults in the region, and some events trend parallel with the NW-SE conjugate faults. The results are consistent with the in-situ well breakout measurements and the current knowledge on the stress direction of this region. The source mechanisms of the studied events together with the hypocenter distribution indicate that the microearthquakes are caused by the reactivation of preexisting faults. We observed that the faulting mechanism varies with depth, from strike-slip dominance at shallower depth to normal faulting dominance at greater depth.

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Section: Induced Microearthquake Datasetmentioning

confidence: 99%

Focal mechanism determination of induced microearthquakes in an oil field using full waveforms from shallow and deep seismic networks

Küleli

Zhang

et al. 2011

GEOPHYSICS

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“…The spatial search range and grid size are selected based on the location uncertainty. The location uncertainty in the downhole monitoring scenario is estimated from the standard deviations of P-and S-wave arrival times and P-wave polarization angles (Eisner et al, 2010). For the dual-array data set used in this study, we calculate standard deviations and obtain 4.6 m (15 ft) in the radial direction, 7.6 m (25 ft) in the vertical direction and 2°in P-wave derived event back-azimuths constrained by two geophone arrays.…”

Section: Devmentioning

confidence: 99%

Full-waveform based microseismic source mechanism studies in the Barnett Shale: Linking microseismicity to reservoir geomechanics

2014

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Seismic moment tensors (MTs) of microearthquakes contain important information on the reservoir and fracturing mechanisms. Difficulties arise when attempting to retrieve complete MT with conventional amplitude inversion methods if only one well is available. With the full-waveform approach, nearfield information and nondirect waves (i.e., refracted/reflected waves) help stabilize the inversion and retrieve complete MT from the single-well data set. However, for events which are at far field from the monitoring well, a multiple-well data set is required. In this study, we perform the inversion with a dual-array data set from a hydrofracture stimulation in the Barnett Shale. Determining source mechanisms from the inverted MTs requires the use of a source model, which in this case is the tensile earthquake model. The source information derived includes the fault plane solution, slip direction, V P /V S ratio in the focal area and seismic moment. The primary challenge of extracting source parameters from MT is to distinguish the fracture plane from auxiliary plane. We analyze the microseismicity using geomechanical analysis to determine the fracture plane. Furthermore, we investigate the significance of non-DC components by F-test. We also study the influence of velocity model errors, event mislocations, and data noise using synthetic data. The results of source mechanism analysis are presented for the events with good signal-to-noise ratios and low condition numbers. Some events have fracture planes with similar orientations to natural fractures delineated by core analysis, suggesting reactivation of natural fractures. Other events occur as predominantly tensile events along the unperturbed maximum horizontal principal stress direction, indicating an opening mode failure on hydraulic fractures. Microseismic source mechanisms not only reveal important information about fracturing mechanisms, but also allow fracture characterization away from the wellbore, providing critical constraints for understanding fractured reservoirs.

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“…Traditionally, events are located individually, for example, from variants of Geiger's method by ray tracing them from receiver locations using their respective arrival time and polarization estimates. It has been shown (Richards et al, 2006;Hulsey et al, 2009;Eisner et al, 2010;Kummerow, 2010) that this approach ignores important information that couples data from different events and thus ties them together.…”

Section: Introductionmentioning

confidence: 99%

Joint location of microseismic events in the presence of velocity uncertainty

et al. 2014

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The locations of seismic events are used to infer reservoir properties and to guide future production activity, as well as to determine and understand the stress field. Thus, locating seismic events with uncertainty quantification remains an important problem. Using Bayesian analysis, a joint probability density function of all event locations was constructed from prior information about picking errors in kinematic data and explicitly quantified velocity model uncertainty. Simultaneous location of all seismic events captured the absolute event locations and the relative locations of some events with respect to others, along with their associated uncertainties. We found that the influence of an uncertain velocity model on location uncertainty under many realistic scenarios can be significantly reduced by jointly locating events. Many quantities of interest that are estimated from multiple event locations, such as fault sizes and fracture spacing or orientation, can be better estimated in practice using the proposed approach.

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Comparison of surface and borehole locations of induced seismicity

Cited by 181 publications

References 15 publications

Focal mechanism determination of induced microearthquakes in an oil field using full waveforms from shallow and deep seismic networks

Focal mechanism determination of induced microearthquakes in an oil field using full waveforms from shallow and deep seismic networks

Full-waveform based microseismic source mechanism studies in the Barnett Shale: Linking microseismicity to reservoir geomechanics

Joint location of microseismic events in the presence of velocity uncertainty

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