Moment tensor inversion of microseisms from the B-sand propped hydrofracture, M-site, Colorado

Nolen‐Hoeksema, Richard; Ruff, Larry J.

doi:10.1016/s0040-1951(01)00100-7

Cited by 100 publications

(44 citation statements)

References 30 publications

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“…Hence the variability of the mechanisms we observe must be due to additional factors. Nolen-Hoeksema and Ruff (2001) proposed three mechanisms that may produce seismicity during hydrofracturing: (1) tensile fracturing at the tip of the propagating fracture, (2) pressure leak-off into pre-existing fractures that intersect the propagating hydrofracture, resulting in their weakening and shear failure (e.g., Rutledge et al, 2004), or (3) slip along pre-existing fractures near the fracture tip induced by stress perturbations associated with fracture propagation (Martínez-Garzón et al, 2013;Warpinski and Branagan, 1989). In our case, pure tensile fracturing (mechanism 1) can be excluded for the observed double-couple events.…”

Section: Comparison To Overcoring Stress Measurementsmentioning

confidence: 99%

On the link between stress field and small-scale hydraulic fracture growth in anisotropic rock derived from microseismicity

et al. 2018

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Abstract. To characterize the stress field at the Grimsel Test Site (GTS) underground rock laboratory, a series of hydrofracturing and overcoring tests were performed. Hydrofracturing was accompanied by seismic monitoring using a network of highly sensitive piezosensors and accelerometers that were able to record small seismic events associated with metre-sized fractures. Due to potential discrepancies between the hydrofracture orientation and stress field estimates from overcoring, it was essential to obtain highprecision hypocentre locations that reliably illuminate fracture growth. Absolute locations were improved using a transverse isotropic P-wave velocity model and by applying joint hypocentre determination that allowed for the computation of station corrections. We further exploited the high degree of waveform similarity of events by applying cluster analysis and relative relocation. Resulting clouds of absolute and relative located seismicity showed a consistent east-west strike and 70 • dip for all hydrofractures. The fracture growth direction from microseismicity is consistent with the principal stress orientations from the overcoring stress tests, provided that an anisotropic elastic model for the rock mass is used in the data inversions. The σ 1 stress is significantly larger than the other two principal stresses and has a reasonably welldefined orientation that is subparallel to the fracture plane; σ 2 and σ 3 are almost equal in magnitude and thus lie on a circle defined by the standard errors of the solutions. The poles of the microseismicity planes also lie on this circle towards the north. Analysis of P-wave polarizations suggested double-couple focal mechanisms with both thrust and normal faulting mechanisms present, whereas strike-slip and thrust mechanisms would be expected from the overcoring-derived stress solution. The reasons for these discrepancies can be explained by pressure leak-off, but possibly may also involve stress field rotation around the propagating hydrofracture. Our study demonstrates that microseismicity monitoring along with high-resolution event locations provides valuable information for interpreting stress characterization measurements.

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Section: Comparison To Overcoring Stress Measurementsmentioning

confidence: 99%

On the link between stress field and small-scale hydraulic fracture growth in anisotropic rock derived from microseismicity

et al. 2018

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“…For this second group of potential microseismic events, the regional tectonic in situ stress state controls the direction of hydraulic fracture growth in the unperturbed rock formation (e.g. Nolen-Hoeksema & Ruff 2001;Zang & Stephansson 2010). The knowledge about the orientation of the maximum horizontal compressive stress (S Hmax ) is thus vital to establish possible candidate geometries for the expected focal mechanisms.…”

Section: S Y N T H E T I C M I C Ro S E I S M I C C Ata L O G U Ementioning

confidence: 99%

“…The second category uses the network distribution to estimate M c : this is either done through the analysis of diurnal variations (Rydelek & Sacks 1989), the comparison of amplitude-distance curves and the signal-to-noise ratio (SNR, Sereno & Bratt 1989), seismic threshold monitoring (Gomberg 1991;Kvaerna & Ringdahl 1999;Kvaerna et al 2002), numerical simulation (D'Alessandro et al 2011aD'Alessandro & Stickney 2012), Bayesian statistics (Mignan et al 2011;Kraft et al 2013;Mignan & Chouliaras 2014) and detection probability estimates for each seismic station (Schorlemmer & Woessner 2008;Nanjo et al 2010;Plenkers et al 2011;Maghsoudi et al 2013Maghsoudi et al , 2015. Furthermore, understanding the microseismic source mechanisms and stress state has gained more interest recently and should be considered in an appropriate estimation of the detection performance (Nolen-Hoeksema & Ruff 2001;Baig & Urbancic 2010).…”

Section: Introductionmentioning

confidence: 99%

Monitoring performance using synthetic data for induced microseismicity by hydrofracking at the Wysin site (Poland)

López‐Comino

Cesca

Kriegerowski

et al. 2017

Geophysical Journal International

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S U M M A R YIdeally, the performance of a dedicated seismic monitoring installation should be assessed prior to the observation of target seismicity. This work is focused on a hydrofracking experiment monitored at Wysin, NE Poland. A microseismic synthetic catalogue is generated to assess the monitoring performance during the pre-operational phase, where seismic information only concerns the noise conditions and the potential background seismicity. Full waveform, accounting for the expected spatial, magnitude and focal mechanism distributions and a realistic local crustal model, are combined with real noise recording to produce either event based or continuous synthetic waveforms. The network detection performance is assessed in terms of the magnitude of completeness (M c ) through two different techniques. First, we use an amplitude threshold, taking into the ratio among the maximal amplitude of synthetic waveforms and station-dependent noise levels, for different values of signal-to-noise ratio. The detection probability at each station is estimated for the whole data set and extrapolated to a broader range of magnitude and distances. We estimate an M c of about 0.55, when considering the distributed network, and can further decrease M c to 0.45 using arrays techniques. The second approach, taking advantage on an automatic, coherence-based detection algorithm, can lower M c to ∼ 0.1, at the cost of an increase of false detections. M c experiences significant changes during day hours, in consequence of strongly varying noise conditions. Moreover, due to the radiation patterns and network geometry, double-couple like sources are better detected than tensile cracks, which may be induced during fracking.

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“…Microseismic moment (M o ) is usually determined from the recorded event's parameters using various methods such as the simple method introduced by Brune in 1970 [9] and more sophisticated methods based on moment tensor inversion that require at least two monitoring wells [10]. In Brune method, the moment (M o ) and radius (r o ) of the event is calculated from following equations Equation;…”

Section: Theorymentioning

confidence: 99%

Microseismic Imaging of Hydraulically Induced-Fractures in Gas Reservoirs: A Case Study in Barnett Shale Gas Reservoir, Texas, USA

Abdulaziz¹

2013

OJG

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Microseismic technology has been proven to be a practical approach for in-situ monitoring of fracture growth during hydraulic fracture stimulations. Microseismic monitoring has rapidly evolved in acquisition methodology, data processing, and in this paper, we evaluate the progression of this technology with emphasis on their applications in Barnett shale gas reservoir. Microseismic data analysis indicates a direct proportion between microseismic moment magnitude and depth, yet no relation between microseismic activity and either injection rate or injection volume has been observed. However, large microseismic magnitudes have been recorded where hydraulic fracturing stimulation approaches a fault and therefore the geologic framework should be integrated in such programs. In addition, the geometry of fracture growth resulted by proppant interactions with naturally fractured formations follows unpredictable fashion due to redirecting the injection fluids along flow paths associated with the pre-existing fault network in the reservoir. While microseismic imaging is incredibly useful in revealing the fracture geometry and the way the fracture evolves, recently several concerns have been raised regarding the capability of microseismic data to provide the fracture dimensional parameters and the fracture mechanism that could provide detailed information for reservoir characterization.

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Moment tensor inversion of microseisms from the B-sand propped hydrofracture, M-site, Colorado

Cited by 100 publications

References 30 publications

On the link between stress field and small-scale hydraulic fracture growth in anisotropic rock derived from microseismicity

On the link between stress field and small-scale hydraulic fracture growth in anisotropic rock derived from microseismicity

Monitoring performance using synthetic data for induced microseismicity by hydrofracking at the Wysin site (Poland)

Microseismic Imaging of Hydraulically Induced-Fractures in Gas Reservoirs: A Case Study in Barnett Shale Gas Reservoir, Texas, USA

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