Anisotropy Effects in Microseismic Monitoring

Warpinski, N.R.; Waltman, Charles; Du, Jing; Ma, Qingyu

doi:10.2118/124208-ms

Cited by 35 publications

(18 citation statements)

References 14 publications

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“…The raypaths are mostly horizontal, with a maximum deviation from the horizontal less than 22° (Warpinski et al, 2009). According to Thomsen (1986), the P-wave velocity variation from the horizontal direction is less than 2%, while the SH velocity variation is less than 1.5%.…”

Section: Field Setupmentioning

confidence: 99%

“…A typical anisotropy parameter for the Barnett Shale is reported as ε ¼ 0.1; Δ ¼ 0.2; γ ¼ 0.1 (note that the Thomsen parameter which controls the near-vertical anisotropic response is denoted as Δ in this paper to avoid the confusion with fracture dip angle δ) (Warpinski et al, 2009). The raypaths are mostly horizontal, with a maximum deviation from the horizontal less than 22° (Warpinski et al, 2009).…”

Section: Field Setupmentioning

confidence: 99%

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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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Section: Field Setupmentioning

confidence: 99%

Section: Field Setupmentioning

confidence: 99%

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

2014

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“…Uncertainty in event hypocenters due to low signal-to-noise ratio and environmental noise were noted as well by Reyes-Montes et al, (2009). Warpinski et al, (2009) investigated uncertainties due to seismic anisotropy of shale reservoirs and methods to build a better velocity model of the reservoir to correct for anisotropic effects.…”

Section: Introductionmentioning

confidence: 98%

Why Monitoring With a Single Downhole Microseismic Array May Not Be Enough: A Case For Multiwell Monitoring of Cyclic Steam in Diatomite

Murer¹,

McNeish²,

Urbancic³

et al. 2010

SPE Annual Technical Conference and Exhibition

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Nine wells were drilled to test cyclic steam stimulation as a recovery mechanism in the diatomite reservoir in the Belridge field. Microseismic monitoring was proposed to evaluate steam chest and fracture growth. A series of models were constructed to determine both microseismic event detectability and locatability. The modeling indicated that poor signal-tonoise ratios would constrain the ability to locate events using a single array. As a result, three monitoring wells were installed. The purpose of this paper is to evaluate the microseismic event location results obtained from the 3-well solution and compare them with the solutions obtained when turning off one or two of the arrays. This first phase of investigation was performed on the sand-propped hydraulic fracture stimulation prior to the cyclic steam operations. This study may be applied to other areas including imaging hydraulic fracture stimulations in shale plays, reservoir steam monitoring, or in any area where location precision in microseismic monitoring is necessary.It has been demonstrated in the field that the monitoring range of a microseismic system can be increased and the potential for locating microseismic events improved by installing multiple arrays having overlapping radii of observation. Innovative system design, deployment techniques and operational procedures, plus advanced multi-well processing strategies have all contributed to creating a growing data set with over 4,000 events recorded during the first 13 months of operation. Results of turning off arrays showed increased location error with two well solutions and a significant increase in error with one-well solutions notwithstanding the reduction in event location count due to lack of multi-phase signals on a single array. Azimuth errors in single microseismic observation well solutions result in disperse interpreted fracture geometry and in misinterpretation.Overall, our observations show that, for both multi-and single-phase events, the observed detection limits and size distribution of the seisms has far exceeded those originally predicted by the earlier modeling.

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“…The interaction between natural fractures and hydraulic fractures (e.g., arresting, crossing, offsetting, etc.) is controlled by the injection rate to a large extent (e.g., [1][2][3][4][5]). Among the many factors that affect the hydraulic fracturing response, the fracturing injection rate is the first critical element to consider [1,6].…”

Section: Introductionmentioning

confidence: 99%

Numerical Modeling of Variable Fluid Injection-Rate Modes on Fracturing Network Evolution in Naturally Fractured Formations

2016

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Abstract:In this study, variable injection-rate technology was numerically investigated in a pre-existing discrete fracture network (DFN) formation, the Tarim Basin in China. A flow-stressdamage (FSD) coupling model has been used in an initial attempt towards how reservoir response to variable injection-rates at different hydraulic fracturing stages. The established numerical model simultaneously considered the macroscopic and microscopic heterogeneity characteristics. Eight numerical cases were studied. Four cases were used to study the variable injection-rate technology, and the other four cases were applied for a constant injection-rate in order to compare with the variable injection-rate technology. The simulation results show that the variable injection-rate technology is a potentially good method to a form complex fracturing networks. The hydraulic fracturing effectiveness when increasing the injection-rate at each stage is the best, also, the total injected fluid is at a minimum. At the initial stage, many under-fracturing points appear around the wellbore with a relatively low injection-rate; the sudden increase of injection rate drives the dynamic propagation of hydraulic fractures along many branching fracturing points. However, the case with decreasing injection rate is the worst. By comparing with constant injection-rate cases, the hydraulic fracturing effectiveness with variable flow rate technology is generally better than those with constant injection-rate technology. This work strongly links the production technology and hydraulic fracturing effectiveness evaluation and aids in the understanding and optimization of hydraulic fracturing simulations in naturally fractured reservoirs.

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Anisotropy Effects in Microseismic Monitoring

Cited by 35 publications

References 14 publications

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

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

Why Monitoring With a Single Downhole Microseismic Array May Not Be Enough: A Case For Multiwell Monitoring of Cyclic Steam in Diatomite

Numerical Modeling of Variable Fluid Injection-Rate Modes on Fracturing Network Evolution in Naturally Fractured Formations

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