Locating microseismic events using both head and direct waves traveling in vertical transverse isotropic media

2020 ◽  
Author(s):  
Dowan Kim ◽  
Joongmoo Byun ◽  
Soon Jee Seol
Keyword(s):  
Transverse Isotropy ◽  
Microseismic Monitoring ◽  
Head Wave ◽  
Hydraulic Fractures ◽  
Path Diversity ◽  
Isotropic Media ◽  
Transverse Isotropic ◽  
Microseismic Events ◽  
Vertical Transverse Isotropy ◽  
The Waves

Summary Microseismic monitoring is widely used to detect hydraulic fractures. Accurate mapping of microseismic events is essential to detect such fractures enhancing productivity. The eikonal solver is an efficient forward-modeling method used to map microseismic events. However, traditional eikonal solvers do not distinguish between head and direct waves, computing only the traveltimes of the waves that arrive first. We developed a new eikonal solver that computes the traveltimes of direct waves by imposing new constraints on the conventional, vertical transverse isotropy (VTI) solver. We then performed numerical experiments exploiting the traveltimes of direct waves. We used the traveltimes of only the first arrivals, and those of both first and direct arrivals, when performing inverted event mapping. The results showed that the uncertainties of event locations were minimized when both head and direct waves were analyzed due to the increased both the number of available data and the traveling path diversity. Also, we found that the use of only direct-arrival traveltimes was valuable when head-wave first arrivals were difficult to detect because the signal-to-noise (S/N) ratio was low.

Results of the downhole microseismic monitoring at a pilot hydraulic fracturing site in Poland — Part 1: Event location and stimulation performance

2018 ◽  
Vol 6 (3) ◽  
pp. SH39-SH48 ◽  
Author(s):  
Wojciech Gajek ◽  
Jacek Trojanowski ◽  
Michał Malinowski ◽  
Marek Jarosiński ◽  
Marko Riedel
Keyword(s):  
Hydraulic Fracturing ◽  
Seismic Anisotropy ◽  
Transverse Isotropy ◽  
Velocity Model ◽  
Microseismic Monitoring ◽  
Baltic Basin ◽  
Hydraulic Stimulation ◽  
Lower Paleozoic ◽  
Event Location ◽  
Microseismic Events

A precise velocity model is necessary to obtain reliable locations of microseismic events, which provide information about the effectiveness of the hydraulic stimulation. Seismic anisotropy plays an important role in microseismic event location by imposing the dependency between wave velocities and its propagation direction. Building an anisotropic velocity model that accounts for that effect allows for more accurate location of microseismic events. We have used downhole microseismic records from a pilot hydraulic fracturing experiment in Lower-Paleozoic shale gas play in the Baltic Basin, Northern Poland, to obtain accurate microseismic events locations. We have developed a workflow for a vertical transverse isotropy velocity model construction when facing a challenging absence of horizontally polarized S-waves in perforation shot data, which carry information about Thomsen’s [Formula: see text] parameter and provide valuable constraints for locating microseismic events. We extract effective [Formula: see text], [Formula: see text] and [Formula: see text], [Formula: see text] for each layer from the P- and SV-wave arrivals of perforation shots, whereas the unresolved [Formula: see text] is retrieved afterward from the SH-SV-wave delay time of selected microseismic events. An inverted velocity model provides more reliable location of microseismic events, which then becomes an essential input for evaluating the hydraulic stimulation job effectiveness in the geomechanical context. We evaluate the influence of the preexisting fracture sets and obliquity between the borehole trajectory and principal horizontal stress direction on the hydraulic treatment performance. The fracturing fluid migrates to previously fractured zones, while the growth of the microseismic volume in consecutive stages is caused by increased penetration of the above-lying lithologic formations.

Transverse isotropy of the upper mantle in the vicinity of Pacific fracture zones

1969 ◽  
Vol 59 (1) ◽  
pp. 59-72
Author(s):  
Robert S. Crosson ◽  
Nikolas I. Christensen
Keyword(s):  
Upper Mantle ◽  
Symmetry Axis ◽  
Transverse Isotropy ◽  
Transversely Isotropic ◽  
Seismic Wave Propagation ◽  
Fracture Zones ◽  
Mantle Material ◽  
Transversely Isotropic Media ◽  
Horizontal Symmetry ◽  
Isotropic Media

Abstract Several recent investigations suggest that portions of the Earth's upper mantle behave anisotropically to seismic wave propagation. Since several types of anisotropy can produce azimuthal variations in Pn velocities, it is of particular geophysical interest to provide a framework for the recognition of the form or forms of anisotropy most likely to be manifest in the upper mantle. In this paper upper mantle material is assumed to possess the elastic properties of transversely isotropic media. Equations are presented which relate azimuthal variations in Pn velocities to the direction and angle of tilt of the symmetry axis of a transversely isotropic upper mantle. It is shown that the velocity data of Raitt and Shor taken near the Mendocino and Molokai fracture zones can be adequately explained by the assumption of transverse isotropy with a nearly horizontal symmetry axis.

Normal moveout from dipping reflectors in anisotropic media

Geophysics ◽  
1995 ◽  
Vol 60 (1) ◽  
pp. 268-284 ◽  
Author(s):  
Ilya Tsvankin
Keyword(s):  
Symmetry Axis ◽  
Transverse Isotropy ◽  
Transversely Isotropic ◽  
Anisotropic Media ◽  
Weak Anisotropy ◽  
Anisotropic Models ◽  
Transversely Isotropic Media ◽  
Wide Range ◽  
Isotropic Media ◽  
The Difference

Description of reflection moveout from dipping interfaces is important in developing seismic processing methods for anisotropic media, as well as in the inversion of reflection data. Here, I present a concise analytic expression for normal‐moveout (NMO) velocities valid for a wide range of homogeneous anisotropic models including transverse isotropy with a tilted in‐plane symmetry axis and symmetry planes in orthorhombic media. In transversely isotropic media, NMO velocity for quasi‐P‐waves may deviate substantially from the isotropic cosine‐of‐dip dependence used in conventional constant‐velocity dip‐moveout (DMO) algorithms. However, numerical studies of NMO velocities have revealed no apparent correlation between the conventional measures of anisotropy and errors in the cosine‐of‐dip DMO correction (“DMO errors”). The analytic treatment developed here shows that for transverse isotropy with a vertical symmetry axis, the magnitude of DMO errors is dependent primarily on the difference between Thomsen parameters ε and δ. For the most common case, ε − δ > 0, the cosine‐of‐dip–corrected moveout velocity remains significantly larger than the moveout velocity for a horizontal reflector. DMO errors at a dip of 45 degrees may exceed 20–25 percent, even for weak anisotropy. By comparing analytically derived NMO velocities with moveout velocities calculated on finite spreads, I analyze anisotropy‐induced deviations from hyperbolic moveout for dipping reflectors. For transversely isotropic media with a vertical velocity gradient and typical (positive) values of the difference ε − δ, inhomogeneity tends to reduce (sometimes significantly) the influence of anisotropy on the dip dependence of moveout velocity.

Arrival-time picking of microseismic events based on MSNet

Geophysics ◽  
2021 ◽  
pp. 1-66
Author(s):  
Guanqun Sheng ◽  
Shuangyu Yang ◽  
Xiaolong Guo ◽  
Xingong Tang
Keyword(s):  
Arrival Time ◽  
Spatial Information ◽  
Synthetic Data ◽  
Microseismic Monitoring ◽  
Monitoring Data ◽  
Convolutional Network ◽  
Low Snr ◽  
Microseismic Data ◽  
Microseismic Events ◽  
Arrival Time Picking

Arrival-time picking of microseismic events is a critical procedure in microseismic data processing. However, as field monitoring data contain many microseismic events with low signal-to-noise ratios (SNRs), traditional arrival-time picking methods based on the instantaneous characteristics of seismic signals cannot meet the picking accuracy and efficiency requirements of microseismic monitoring owing to the large volume of monitoring data. Conversely, methods based on deep neural networks can significantly improve arrival-time picking accuracy and efficiency in low-SNR environments. Therefore, we propose a deep convolutional network that combines the U-net and DenseNet approaches to pick arrival times automatically. This novel network, called MSNet not only retains the spatial information of any input signal or profile based on the U-net, but also extracts and integrates more essential features of events and non-events through dense blocks, thereby further improving the picking accuracy and efficiency. An effective workflow is developed to verify the superiority of the proposed method. First, we describe the structure of MSNet and the workflow of the proposed picking method. Then, datasets are constructed using variable microseismic traces from field microseismic monitoring records and from the finite-difference forward modeling of microseismic data to train the network. Subsequently, hyperparameter tuning is conducted to optimize the MSNet. Finally, we test the MSNet using modeled signals with different SNRs and field microseismic data from different monitoring areas. By comparing the picking results of the proposed method with the results of U-net and short-term average and long-term average (STA/LTA) methods, the effectiveness of the proposed method is verified. The arrival picking results of synthetic data and microseismic field data show that the proposed network has increased adaptability and can achieve high accuracy for picking the arrival-time of microseismic events.

scholarly journals Automatic Classification of Microseismic Signals Based on MFCC and GMM-HMM in Underground Mines

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Pingan Peng ◽  
Zhengxiang He ◽  
Liguan Wang
Keyword(s):  
Rock Mass ◽  
Gaussian Mixture ◽  
Automatic Classification ◽  
Microseismic Monitoring ◽  
Underground Mines ◽  
Basic Step ◽  
Microseismic Data ◽  
Safety Risks ◽  
Microseismic Events

In order to mitigate economic and safety risks during mine life, a microseismic monitoring system is installed in a number of underground mines. The basic step for successfully analyzing those microseismic data is the correct detection of various event types, especially the rock mass rupture events. The visual scanning process is a time-consuming task and requires experience. Therefore, here we present a new method for automatic classification of microseismic signals based on the Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) by using only Mel-frequency cepstral coefficient (MFCC) features extracted from the waveform. The detailed implementation of our proposed method is described. The performance of this method is tested by its application to microseismic events selected from the Dongguashan Copper Mine (China). A dataset that contains a representative set of different microseismic events including rock mass rupture, blasting vibration, mechanical drilling, and electromagnetic noise is collected for training and testing. The results show that our proposed method obtains an accuracy of 92.46%, which demonstrates the effectiveness of the method for automatic classification of microseismic data in underground mines.

scholarly journals Microseismic monitoring using a fibre-optic Distributed Acoustic Sensor (DAS) array

Geophysics ◽  
2020 ◽  
pp. 1-48
Author(s):  
James P. Verdon ◽  
Steve A. Horne ◽  
Andrew Clarke ◽  
Anna L. Stork ◽  
Alan F. Baird ◽  
...  
Keyword(s):  
Time Windows ◽  
Microseismic Monitoring ◽  
P Wave ◽  
Hydraulic Fractures ◽  
Fibre Optic ◽  
S Wave ◽  
Simple Method ◽  
Waveform Data ◽  
Zero Offset ◽  
Optic Array

We present a case study demonstrating the use of an “L”-shaped downhole fibre-optic array to monitor microseismicity. We use a relatively simple method to detect events from continuous waveform data, and develop a workflow for manual event location. Locations are defined with a cylindrical coordinate system, with the horizontal axis of the DAS cable being the axis of symmetry. Events are located using three manual “picks”, constraining (1) the zero-offset “broadside” channel to the event (2) the P-S wave arrival time difference at the broadside channel, and (3) the angle, ? of the event from the array. Because the one-component DAS array is unable to record P-wave energy on the broadside channel, the P-wave pick is made indirectly by ensuring that the modeled P- and S-wave moveout curves match the observed data. The ? angle requires that signal is observed on the vertical part of the array, in our case this is possible because an engineered fiber, rather than standard telecommunications fiber, provided a significant reduction in the noise level. Because only three picks need to be made, our manual approach is significantly more efficient than equivalent manual processing of downhole geophone data, where picks for P- and S-waves must be made for each receiver. We find that the located events define a tight cluster around the injection interval, indicating that this approach provides relatively precise and accurate event locations. A surface microseismic array was also used at this site, which detected significantly fewer events, the locations of which had significantly greater scatter than the DAS array locations. We conclude by examining some other aspects of the DAS microseismic data, including the presence of multiple events within very short time windows, and the presence of converted phases that appear to represent scattering of energy from the hydraulic fractures themselves.

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