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Microseismic Monitoring of Hydraulic Fracturing - Data Interpretation Methodology With an Example from Pomerania

Microseismic monitoring is a method for localizing fractures induced by hydraulic fracturing in search for shell gas. The data is collected from an array of geophones deployed on the surface or underground. Ground vibrations are recorded and analysed for fracture location, magnitude and breakage mechanism. For successful microseismic monitoring one need a velocity model of underlying formations. The model is further tuned with signal from perforation shots of known location. Imaging of calibration events is done using software MicSeis developed by Seismik s.r.o. MicSeis utilizes diffraction stacking of waveforms from multiple stations and is intended to image microseismic events with low signal-to-noise ratio (SNR). Imaging means detection of events in time on the seismogram records (determination of arrivals and amplitudes at each receiver), location of the event hypocenters in subsurface, determination of their origin time, and characterization (or evaluation) of detected events. The reliability of detection is further enhanced by analysis of semblance of amplitudes of the detected events. The imaging of microseismic events in MicSeis is using a grid search over all possible origin times and expected set of potential source location points in the selected rock volume. Wave propagation times from grid nodes to the geophones are computed using input velocity model. The seismic moment tensors are automatically determined from the amplitudes gathered during the grid search procedure and are used to model polarities of events which then enhance constructive interference of the event amplitudes and reduce noise influence. Function characterizing a maximum stack per time sample is calculated over whole volume and it is analyzed using the STA/LTA algorithm with a predefined threshold. Additionally a semblance value is used to verify the event detection. Once the event is detected in time, location is determined through analysis of the 3D spatial image function.

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DOI
Digital Object Identifier link open in new tab 10.3846/enviro.2017.001
Category
Aktywność konferencyjna
Type
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Language
angielski
Publication year
2017

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