Microseismic design studies

Zimmer, Ulrich

doi:10.1190/geo2011-0004.1

Cited by 36 publications

(16 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Head wave is common in microseismic survey in shale (Maxwell, 2010;Zimmer, 2010;Zimmer, 2011). We consider a parallel horizontal wells pair configuration ( Figure 1), which is common in this kind of Marcellus shale formation.…”

Section: Theory and Methods Head Wavementioning

confidence: 99%

“…Due to shale's low velocity nature, head wave is very common in crosswell seismic (Dong and Toksöz, 1995;Parra et al, 2002;Parra et al, 2006) and microseismic survey (Maxwell, 2010;Zimmer, 2010;Zimmer, 2011) in shale operation. When the distance between geophones and source is relatively large, the head wave arrival can precede direct arrival.…”

Section: Introductionmentioning

confidence: 99%

“…Due to its weakness, head wave has been commonly regarded as the contamination of direct arrival. Some preliminary research on making use of head wave has been conducted but mainly on synthetic example of simplified situations (Zimmer, 2010;Zimmer, 2011). No publication on field data and rigorous analysis on the improvement due to head wave is available.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Microseismic Event Location Using Multiple Arrivals: Demonstration of Uncertainty Reduction

Zhang¹,

Rector²,

Nava³

2015

Proceedings of the 3rd Unconventional Resources Technology Conference

View full text Add to dashboard Cite

SummaryEvent location is the basis of hydraulic fracture characterization using microseismic data. However, the traditional method of using direct arrival times and Pwave polarizations leads to increased error due to the large uncertainty in polarization. Due to shale's low velocity nature and the configuration of horizontal stimulation and monitoring wells, the head wave can often be the first arrival rather than the direct arrival.Finite difference modeling was used to validate the character of head waves in field data gathered from the Marcellus shale and the situations under which a head wave can be the first arrival were carefully analyzed. With careful processing, we reveal the presence of high number of head waves in the Marcellus Shale. Head wave and direct arrivals were used instead of the conventional Pwave polarization to estimate microseismic event location. A Bayesian inference program was also developed for joint event location and velocity model calibration. Validation of the developed method was performed on perforation shots and shows that using head waves instead of polarization can achieve much better resolution in microseismic event location. The application of the developed method on field data shows a more reasonable result than that provided by contractor.Our results show that the head wave can be a contributor instead of a detractor in the process of accurate event location. This will eliminate the necessity for polarization which has large uncertainty due to poor geophoneborehole coupling, multiple arrivals, and low signal to noise ratio. The developed method can effectively improve the accuracy of microseismic event location and proposes a better acquisition geometry and strategy to reduce microseismic monitoring cost and improve event location accuracy.

show abstract

Section: Theory and Methods Head Wavementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Microseismic Event Location Using Multiple Arrivals: Demonstration of Uncertainty Reduction

Zhang¹,

Rector²,

Nava³

2015

Proceedings of the 3rd Unconventional Resources Technology Conference

View full text Add to dashboard Cite

show abstract

“…Once the calibrated velocity model is gained, the travel time based source location method can be applied to estimate the microseismic source positions. The implementation of this location method generally consists of two steps: the first step is to determine the source azimuth based on P-wave polarization, and the second step is to search for the source position by minimizing the discrepancy between the observed and predicted arrival times (Drew et al, 2008;Bardainne et al, 2009;Eisner et al, 2009;Maxwell, 2009;Zimmer, 2011). This kind of source location method nowadays has been widely used in microseismic date processing, however, its application in location of the low SNR microseismic events is not satisfactory.…”

Section: Joint Inversion Of Velocity Model and Source Positionmentioning

confidence: 98%

Detection and Location of Microseismic Events with Low Signal-to-Noise Ratios

Tan

Hou

et al. 2014

All Days

View full text Add to dashboard Cite

Microseismic monitoring of hydraulic fractures is the process of monitoring the small earthquakes induced by fluid injection during hydraulic fracture stimulation. The primary goal of microseismic monitoring is to map the source positions of microseismic events. However, in actual cases, location of the microseismic events could become problematic because a considerable part of the microseismic events show a low signal-to-noise ratio (SNR) and conventional event detection and location techniques tend to omit these events even though they may provide useful information for delineation of the hydraulic fractures. To address this problem, several improved methods are proposed in this study to increase the detectability and location accuracy of microseismic events with low signal-to-noise ratios.It has been well known that microseismic data processing generally composes of several critical steps, such as event detection, arrival picking, velocity modeling and source location. As for the event detection process, we develop a multi-channel semblance coefficient based method to identify the low SNR microseismic events. Our method utilizes a semblance coefficient to quantitatively determine the waveform similarity of windowed record segments after moveout correction, and uses it as a detector of the presence of a microseismic event. After identifying the events, a robust method is employed to pick their P-and S-wave arrival times. This method, referred to as SLPEA algorithm, is developed by integrating the differences in amplitude, polarization and statistic properties between seismic signal and ambient noise. Once the arrival times are gained, a simulated annealing (SA) based joint inversion algorithm is adopted to invert the velocity models and microseismic source positions. Innovations in this method include the use of a probability distribution function for determination of the source azimuth and a joint objective function for inversion of the velocity model and source position. The performance of the proposed methods is illustrated using field dataset recorded during an 11-stage hydraulic fracture treatment. 521 locatable microseismic events are detected from this dataset and nearly one third of them show a low signal-to-noise ratio. The source positions of these events are successfully gained through using the proposed methods, and analysis of the location results indicates that the low SNR microseismic events can reveal more details about the hydraulic fractures.

show abstract

“…The lack of events in the vicinity of the perforation intervals does not indicate that no microseismicity occurred. The ability of a downhole array of microseismic sensors with a given sensitivity to detect a microseismic event largely depends on the magnitude of the event, ambient noise, and observational distance (Zimmer ). The decay of detectability with distance is shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Consistency of stress state, locations and source mechanisms of events induced by hydraulic fracturing: downhole monitoring

Jechumtálová

Chu

et al. 2018

Geophysical Prospecting

View full text Add to dashboard Cite

We present results of processed microseismic events induced by hydraulic fracturing and detected using dual downhole monitoring arrays. The results provide valuable insight into hydraulic fracturing. For our study, we detected and located microseismic events and determined their magnitudes, source mechanisms and inverted stress field orientation. Event locations formed a distinct linear trend above the stimulated intervals. Source mechanisms were only computed for high‐quality events detected on a sufficient number of receivers. All the detected source mechanisms were dip‐slip mechanisms with steep and nearly horizontal nodal planes. The source mechanisms represented shear events and the non‐double‐couple components were very small. Such small, non‐double‐couple components are consistent with a noise level in the data and velocity model uncertainties. Strikes of inverted mechanisms corresponding to the nearly vertical fault plane are (within the error of measurements) identical with the strike of the location trend. Ambient principal stress directions were inverted from the source mechanisms. The least principal stress, σ3, was determined perpendicular to the strike of the trend of the locations, indicating that the hydraulic fracture propagated in the direction of maximum horizontal stress. Our analysis indicated that the source mechanisms observed using downhole instruments are consistent with the source mechanisms observed in microseismic monitoring arrays in other locations. Furthermore, the orientation of the inverted principal components of the ambient stress field is in agreement with the orientation of the known regional stress, implying that microseismic events induced by hydraulic fracturing are controlled by the regional stress field.

show abstract

Microseismic design studies

Cited by 36 publications

References 25 publications

Microseismic Event Location Using Multiple Arrivals: Demonstration of Uncertainty Reduction

Microseismic Event Location Using Multiple Arrivals: Demonstration of Uncertainty Reduction

Detection and Location of Microseismic Events with Low Signal-to-Noise Ratios

Consistency of stress state, locations and source mechanisms of events induced by hydraulic fracturing: downhole monitoring

Contact Info

Product

Resources

About