scholarly journals The 11 October 2010 Novaya Zemlya Earthquake: Implications for Velocity Models and Regional Event Location

2017 ◽  
Author(s):  
Steven Gibbons ◽  
Galina Antonovskaya ◽  
Vladimir Asming ◽  
Yana Konechnaya ◽  
Lene Kremenetskaya ◽  
...  
Keyword(s):  
Novaya Zemlya ◽  
Velocity Models ◽  
Event Location

scholarly journals The 11 October 2010 Novaya Zemlya Earthquake: Implications for Velocity Models and Regional Event Location

2016 ◽  
Vol 106 (4) ◽  
pp. 1470-1481 ◽  
Author(s):  
S. J. Gibbons ◽  
G. Antonovskaya ◽  
V. Asming ◽  
Y. V. Konechnaya ◽  
E. Kremenetskaya ◽  
...  
Keyword(s):  
Novaya Zemlya ◽  
Velocity Models ◽  
Event Location

scholarly journals Sensitivity analysis of the backprojection imaging method for seismic event location

2021 ◽  
Vol 11 (1) ◽  
pp. 21-32
Author(s):  
Cristian Alexis Murillo Martínez ◽  
William Mauricio Agudelo
Keyword(s):  
Sensitivity Analysis ◽  
Signal To Noise Ratio ◽  
Synthetic Data ◽  
Spatial Location ◽  
Noise Removal ◽  
Image Resolution ◽  
Imaging Method ◽  
Velocity Models ◽  
Event Location ◽  
Location Methods

Accuracy of earthquake location methods is dependent upon the quality of input data. In the real world, several sources of uncertainty, such as incorrect velocity models, low Signal to Noise Ratio (SNR), and poor coverage, affect the solution. Furthermore, some complex seismic signals exist without distinguishable phases for which conventional location methods are not applicable. In this work, we conducted a sensitivity analysis of Back-Projection Imaging (BPI), which is a technique suitable for location of conventional seismicity, induced seismicity, and tremor-like signals. We performed a study where synthetic data is modelled as fixed spectrum explosive sources. The purpose of using such simplified signals is to fully understand the mechanics of the location method in controlled scenarios, where each parameter can be freely perturbed to ensure that their individual effects are shown separately on the outcome. The results suggest the need for data conditioning such as noise removal to improve image resolution and minimize artifacts. Processing lower frequency signal increases stability, while higher frequencies improve accuracy. In addition, a good azimuthal coverage reduces the spatial location error of seismic events, where, according to our findings, depth is the most sensitive spatial coordinate to velocity and geometry changes.

Waveform inversion for microseismic velocity analysis and event location in VTI media

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. WA95-WA103 ◽  
Author(s):  
Oscar Jarillo Michel ◽  
Ilya Tsvankin
Keyword(s):  
Moment Tensor ◽  
Source Parameters ◽  
Waveform Inversion ◽  
Transversely Isotropic ◽  
Velocity Analysis ◽  
Origin Time ◽  
Velocity Models ◽  
Trade Offs ◽  
Receiver Array ◽  
Event Location

Waveform inversion (WI), which has been extensively used in reflection seismology, could provide improved velocity models and event locations for microseismic surveys. Here, we develop an elastic WI algorithm for anisotropic media designed to estimate the 2D velocity field along with the source parameters (location, origin time, and moment tensor) from microseismic data. The gradient of the objective function is obtained with the adjoint-state method, which requires just two modeling simulations at each iteration. In the current implementation the source coordinates and velocity parameters are estimated sequentially at each stage of the inversion to minimize trade-offs and improve the convergence. Synthetic examples illustrate the accuracy of the inversion for layered VTI (transversely isotropic with a vertical symmetry axis) media, as well as the sensitivity of the velocity-analysis results to noise, the length of the receiver array, errors in the initial model, and variability in the moment tensor of the recorded events.

scholarly journals A benchmark case study for seismic event relative location

2020 ◽  
Vol 223 (2) ◽  
pp. 1313-1326
Author(s):  
S J Gibbons ◽  
T Kværna ◽  
T Tiira ◽  
E Kozlovskaya
Keyword(s):  
Time Delay ◽  
Signal To Noise Ratio ◽  
Source Region ◽  
Ground Truth ◽  
Double Difference ◽  
High Signal ◽  
Relative Location ◽  
Data Set ◽  
Velocity Models ◽  
Event Location

Summary ‘Precision seismology’ encompasses a set of methods which use differential measurements of time-delays to estimate the relative locations of earthquakes and explosions. Delay-times estimated from signal correlations often allow far more accurate estimates of one event location relative to another than is possible using classical hypocentre determination techniques. Many different algorithms and software implementations have been developed and different assumptions and procedures can often result in significant variability between different relative event location estimates. We present a Ground Truth (GT) dataset of 55 military surface explosions in northern Finland in 2007 that all took place within 300 m of each other. The explosions were recorded with a high signal-to-noise ratio to distances of about 2°, and the exceptional waveform similarity between the signals from the different explosions allows for accurate correlation-based time-delay measurements. With exact coordinates for the explosions, we are able to assess the fidelity of relative location estimates made using any location algorithm or implementation. Applying double-difference calculations using two different 1-D velocity models for the region results in hypocentre-to-hypocentre distances which are too short and it is clear that the wavefield leaving the source region is more complicated than predicted by the models. Using the GT event coordinates, we are able to measure the slowness vectors associated with each outgoing ray from the source region. We demonstrate that, had such corrections been available, a significant improvement in the relative location estimates would have resulted. In practice we would of course need to solve for event hypocentres and slowness corrections simultaneously, and significant work will be needed to upgrade relative location algorithms to accommodate uncertainty in the form of the outgoing wavefield. We present this data set, together with GT coordinates, raw waveforms for all events on six regional stations, and tables of time-delay measurements, as a reference benchmark by which relative location algorithms and software can be evaluated.

A Seismic Event Relative Location Benchmark Case Study

2020 ◽  
Author(s):  
Tormod Kvaerna ◽  
Steven J. Gibbons ◽  
Timo Tiira ◽  
Elena Kozlovskaya
Keyword(s):  
Time Delay ◽  
Signal To Noise Ratio ◽  
Source Region ◽  
Ground Truth ◽  
Double Difference ◽  
High Signal ◽  
Relative Location ◽  
Hypocenter Determination ◽  
Velocity Models ◽  
Event Location

<p>"Precision seismology'' encompasses a set of methods which use differential measurements of time-delays to estimate the relative locations of earthquakes and explosions.  Delay-times estimated from signal correlations often allow far more accurate estimates of one event location relative to another than is possible using classical hypocenter determination techniques.  Many different algorithms and software implementations have been developed and different assumptions and procedures can often result in significant variability between different relative event location estimates.  We present a Ground Truth (GT) database of 55 military surface explosions in northern Finland in 2007 that all took place within 300 meters of each other.  The explosions were recorded with a high signal-to-noise ratio to distances of about 2 degrees, and the exceptional waveform similarity between the signals from the different explosions allows for accurate correlation-based time-delay measurements.  With exact coordinates for the explosions, we can assess the fidelity of relative location estimates made using any location algorithm or implementation.  Applying double-difference calculations using two different 1-d velocity models for the region results in hypocenter-to-hypocenter distances which are too short and the wavefield leaving the source region is more complicated than predicted by the models.  Using the GT event coordinates, we can measure the slowness vectors associated with each outgoing ray from the source region. We demonstrate that, had such corrections been available, a significant improvement in the relative location estimates would have resulted.  In practice we would of course need to solve for event hypocenters and slowness corrections simultaneously, and significant work will be needed to upgrade relative location algorithms to accommodate uncertainty in the form of the outgoing wavefield.  We present this dataset, together with GT coordinates, raw waveforms for all events on six regional stations, and tables of time-delay measurements, as a reference benchmark by which relative location algorithms and software can be evaluated.</p>

scholarly journals Locating Mine Microseismic Events in a 3D Velocity Model through the Gaussian Beam Reverse-Time Migration Technique

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2676 ◽  
Author(s):  
Yi Wang ◽  
Xueyi Shang ◽  
Kang Peng
Keyword(s):  
Gaussian Beam ◽  
Back Propagation ◽  
Velocity Model ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Location Method ◽  
Velocity Models ◽  
Time Migration ◽  
3D Velocity Model ◽  
Event Location

Microseismic (MS) source location is a fundamental and critical task in mine MS monitoring. The traditional ray tracing-based location method can be easily affected by many factors, such as multi-ray path effects, waveform focusing and defocusing of wavefield propagation, and low picking precision of seismic phase arrival. By contrast, the Gaussian beam reverse-time migration (GBRTM) location method can effectively and correctly model the influences of multi-path effects and wavefield focusing and defocusing in complex 3D media, and it takes advantages of the maximum energy focusing point as the source location with the autocorrelation imaging condition, which drastically reduces the requirements of signal-to-noise ratio (SNR) and picking accuracy of P-wave arrival. The Gaussian beam technique has been successfully applied in locating natural earthquake events and hydraulic fracturing-induced MS events in one-dimensional (1D) or simple two-dimensional (2D) velocity models. The novelty of this study is that we attempted to introduce the GBRTM technique into a mine MS event location application and considered utilizing a high-resolution tomographic 3D velocity model for wavefield back propagation. Firstly, in the synthetic test, the GBRTM location results using the correct 2D velocity model and different homogeneous velocity models are compared to show the importance of velocity model accuracy. Then, it was applied and verified by eight location premeasured blasting events. The synthetic results show that the spectrum characteristics of the recorded blasting waveforms are more complicated than those generated by the ideal Ricker wavelet, which provides a pragmatic way to evaluate the effectiveness and robustness of the MS event location method. The GBRTM location method does not need a highly accurate picking of phase arrival, just a simple detection criterion that the first arrival waveform can meet the windowing requirements of wavefield back propagation, which is beneficial for highly accurate and automatic MS event location. The GBRTM location accuracy using an appropriate 3D velocity model is much higher than that of using a homogeneous or 1D velocity model, emphasizing that a high-resolution velocity model is very critical to the GBRTM location method. The average location error of the GBRTM location method for the eight blasting events is just 17.0 m, which is better than that of the ray tracing method using the same 3D velocity model (26.2 m).

Image-domain velocity inversion and event location for microseismic monitoring

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. KS71-KS83 ◽  
Author(s):  
Ben Witten ◽  
Jeffrey Shragge
Keyword(s):  
Oil And Gas ◽  
Random Noise ◽  
Microseismic Monitoring ◽  
Seismic Events ◽  
S Wave ◽  
Origin Time ◽  
Image Domain ◽  
Velocity Inversion ◽  
Velocity Models ◽  
Event Location

Microseismic event locations obtained from seismic monitoring data sets are often a primary means of determining the success of fluid-injection programs, such as hydraulic fracturing for oil and gas extraction, geothermal projects, and wastewater injection. Event locations help the decision makers to evaluate whether operations conform to expectations or parameters need to be changed and may be used to help assess and reduce the risk of induced seismicity. However, obtaining accurate event location estimates requires an accurate velocity model, which is not available at most injection sites. Common velocity updating techniques require picking arrivals on individual seismograms. This can be problematic in microseismic monitoring, particularly for surface acquisition, due to the low signal-to-noise ratio of the arrivals. We have developed a full-wavefield adjoint-state method for locating seismic events while inverting for P- and S-wave velocity models that optimally focus multiple complementary images of recorded seismic events. This method requires neither picking nor initial estimates of event location or origin time. Because the inversion relies on (image domain) residuals that satisfy the differential semblance criterion, there is no requirement that the starting model be close to the true velocity. We determine synthetic results derived from a model with conditions similar to a field-acquisition scenario in terms of the number and spatial sampling of receivers and recorded coherent and random noise levels. The results indicate the effectiveness of the methodology by demonstrating a significantly enhanced focusing of event images and a reduction of 95% in event location error from a reasonable initial model.

Transdimensional simultaneous inversion of velocity structure and event locations in downhole microseismic monitoring

Geophysics ◽  
2021 ◽  
pp. 1-92
Author(s):  
Xingda Jiang ◽  
Wei Zhang ◽  
Hui Yang ◽  
Chaofeng Zhao ◽  
Zixuan Wang
Keyword(s):  
Hydraulic Fracturing ◽  
Velocity Structure ◽  
Velocity Model ◽  
Microseismic Monitoring ◽  
Location Accuracy ◽  
Simultaneous Inversion ◽  
Velocity Models ◽  
Effective Velocity ◽  
Number Of Layers ◽  
Event Location

In downhole microseismic monitoring, the velocity model plays a vital role in accurate mapping of the hydraulic fracturing image. For velocity model uncertainties in the number of layers or interface depths, the conventional velocity calibration method has been shown to effectively locate the perforation shots; however, it introduces non-negligible location errors for microseismic events, especially for complex geological formations with inclinations. To improve the event location accuracy, we exploit the advantages of the reversible jump Markov chain Monte Carlo (rjMCMC) approach in generating different dimensions of velocity models and propose a transdimensional Bayesian simultaneous inversion framework for obtaining the effective velocity structure and event locations simultaneously. The transdimensional inversion changes the number of layers during the inversion process and selects the optimal interface depths and velocity values to improve the event location accuracy. The confidence intervals of the simultaneous inversion event locations estimated by Bayesian inference enable us to evaluate the location uncertainties in the horizontal and vertical directions. Two synthetic examples and a field test are presented to illustrate the performance of our methodology, and the event location accuracy is shown to be higher than that obtained using the conventional methods. With less dependence on prior information, the proposed transdimensional simultaneous inversion method can be used to obtain an effective velocity structure for facilitating highly accurate hydraulic fracturing mapping.

Microseismic image-domain velocity inversion: Marcellus Shale case study

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. KS99-KS112 ◽  
Author(s):  
Ben Witten ◽  
Jeffrey Shragge
Keyword(s):  
Marcellus Shale ◽  
Velocity Variation ◽  
Signal To Noise ◽  
Injection Wells ◽  
Hydraulic Stimulation ◽  
Image Domain ◽  
Velocity Inversion ◽  
Velocity Models ◽  
Adjoint State ◽  
Event Location

Seismic monitoring at injection wells relies on generating accurate location estimates of detected (micro-) seismicity. Event location estimates assist in optimizing well and stage spacings, assessing potential hazards, and establishing causation of larger events. The largest impediment to generating accurate location estimates is an accurate velocity model. For surface-based monitoring, the model should capture 3D velocity variation, yet rarely is the laterally heterogeneous nature of the velocity field captured. Another complication for surface monitoring is that the data often suffer from low signal-to-noise levels, making velocity updating with established techniques difficult due to uncertainties in the arrival picks. We use surface-monitored field data to demonstrate that a new method requiring no arrival picking can improve microseismic locations by jointly locating events and updating 3D P- and S-wave velocity models through image-domain adjoint-state tomography. This approach creates a complementary set of images for each chosen event through wave-equation propagation and correlating combinations of P- and S-wavefield energy. The method updates the velocity models to optimize the focal consistency of the images through adjoint-state inversion. We have determined the functionality of the method using a surface array of 192 3C geophones over a hydraulic stimulation in the Marcellus Shale. Applying the proposed joint location and velocity-inversion approach significantly improves the estimated locations. To assess the event location accuracy, we have developed a new measure of inconsistency derived from the complementary images. By this measure, the location inconsistency decreases by 75%. The method has implications for improving the reliability of microseismic interpretation with low signal-to-noise data, which may increase hydrocarbon extraction efficiency and improve risk assessment from injection-related seismicity.

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