Sectional velocity model for microseismic source location in tunnels

2015 ◽  
Vol 45 ◽  
pp. 73-83 ◽  
Author(s):  
Guang-Liang Feng ◽  
Xia-Ting Feng ◽  
Bing-Rui Chen ◽  
Ya-Xun Xiao ◽  
Quan Jiang
Keyword(s):  
Velocity Model ◽  
Source Location ◽  
Microseismic Source Location

Microseismic velocity model inversion and source location: The use of neighborhood algorithm and master station method

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. KS49-KS63 ◽  
Author(s):  
Yuyang Tan ◽  
Chuan He ◽  
Zhonghua Mao
Keyword(s):  
Velocity Model ◽  
Source Location ◽  
Model Inversion ◽  
Tuning Parameters ◽  
Velocity Models ◽  
Systematic Methodology ◽  
Microseismic Source Location ◽  
Microseismic Events ◽  
Master Station ◽  
Half Length

The accuracy of the velocity model strongly affects the accuracy of microseismic source location and hence the reliability of fracture imaging. We have developed a systematic methodology for microseismic velocity model inversion and source location. A new misfit function is used for both problems, which yields more reliable result than the conventional ones. Using the same measure of misfit, the location errors resulting from the use of different misfit functions are eliminated. The neighborhood algorithm and master station method (MSM) are adopted for calculating the velocity model and source location, respectively. The reason for using the neighborhood algorithm is that it has fewer tuning parameters and is easy to be tuned, whereas the advantage of the MSM is that it can automatically remove the mispicks. The performance of the proposed methods is illustrated using the ball-hit events with known locations, and the validity of the inversion results is verified by the relocations of these events. We also used the inverted velocity models to locate the microseismic events detected from the monitoring data. The location result indicates that the fractures have an average half-length of 280 m and height of 55 m and the fracture azimuth is approximately N77°W.

A Compact Program for 3D Passive Seismic Source-Location Imaging

2021 ◽  
Author(s):  
Yangkang Chen ◽  
Omar M. Saad ◽  
Min Bai ◽  
Xingye Liu ◽  
Sergey Fomel
Keyword(s):  
Open Source ◽  
Seismic Source ◽  
Velocity Model ◽  
Source Location ◽  
Imaging Method ◽  
Python Script ◽  
Passive Seismic ◽  
Synthetic Test ◽  
Microseismic Source Location ◽  
C Program

Abstract Microseismic source-location imaging is important for inferring the dynamic status of reservoirs during hydraulic fracturing. The accuracy and resolution of the located microseismic sources are closely related to the imaging technique. We present an open-source program for high-fidelity and high-resolution 3D microseismic source-location imaging. The presented code is compact in the sense that all required subroutines are included in one single C program, based on which seismic wavefields can be propagated either forward during a synthetic test or backward during a real time-reversal imaging process. The compact C program is accompanied by a Python script known as the SConstruct file in the Madagascar open-source platform to compile and run the C program. The velocity model and recorded microseismic data can be input using the Python script. This compact program is useful for educational purposes and for future algorithm development. We introduce the basics of the imaging method used in the presented package and present one representative synthetic example and a field data example. The results show that the presented program can be reliably used to locate source locations using a passive seismic dataset.

Interpretation of physical status of arrival picks for microseismic source location

1990 ◽  
Vol 80 (6A) ◽  
pp. 1643-1660
Author(s):  
Maochen Ge ◽  
P. K. Kaiser
Keyword(s):  
Time Window ◽  
Velocity Model ◽  
Source Location ◽  
Physical Status ◽  
Voltage Level ◽  
Window Current ◽  
Unique Approach ◽  
Microseismic Source Location ◽  
Event Based ◽  
Microseismic Event

Abstract The automatic recognition of a microseismic event usually relies on two criteria: threshold voltage level and event recognition time window. Current microseismic source location techniques are severaly limited because the physical status of an arrival pick is not known. This paper presents a theory for the identification of the physical status of an arrival pick. It consists of an arrival time difference analysis and a residual analysis. The theory can be used to discriminate various types of arrival picks critical for microseismic source location. An event-based velocity model can then be established and used to determine the source location more accurately. The theory provides a unique approach that may be utilized in various automatic acoustic/seismic processing systems.

Microseismic source location method based on a velocity model database and statistical analysis

2021 ◽  
Vol 14 (19) ◽  
Author(s):  
Bing-Rui Chen ◽  
Tao Li ◽  
Xin-Hao Zhu ◽  
Fan-Bo Wei ◽  
Xu Wang ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Velocity Model ◽  
Source Location ◽  
Location Method ◽  
Microseismic Source Location ◽  
Model Database

scholarly journals Rapid estimation of earthquake locations using waveform traveltimes

2019 ◽  
Vol 217 (3) ◽  
pp. 1727-1741 ◽  
Author(s):  
D W Vasco ◽  
Seiji Nakagawa ◽  
Petr Petrov ◽  
Greg Newman
Keyword(s):  
Standard Error ◽  
Random Noise ◽  
Grid Point ◽  
Synthetic Data ◽  
Velocity Model ◽  
Source Location ◽  
Model Errors ◽  
Average Deviation ◽  
Origin Time ◽  
Data Set

SUMMARY We introduce a new approach for locating earthquakes using arrival times derived from waveforms. The most costly computational step of the algorithm scales as the number of stations in the active seismographic network. In this approach, a variation on existing grid search methods, a series of full waveform simulations are conducted for all receiver locations, with sources positioned successively at each station. The traveltime field over the region of interest is calculated by applying a phase picking algorithm to the numerical wavefields produced from each simulation. An event is located by subtracting the stored traveltime field from the arrival time at each station. This provides a shifted and time-reversed traveltime field for each station. The shifted and time-reversed fields all approach the origin time of the event at the source location. The mean or median value at the source location thus approximates the event origin time. Measures of dispersion about this mean or median time at each grid point, such as the sample standard error and the average deviation, are minimized at the correct source position. Uncertainty in the event position is provided by the contours of standard error defined over the grid. An application of this technique to a synthetic data set indicates that the approach provides stable locations even when the traveltimes are contaminated by additive random noise containing a significant number of outliers and velocity model errors. It is found that the waveform-based method out-performs one based upon the eikonal equation for a velocity model with rapid spatial variations in properties due to layering. A comparison with conventional location algorithms in both a laboratory and field setting demonstrates that the technique performs at least as well as existing techniques.

scholarly journals Research Developments and Prospects on Microseismic Source Location in Mines

Engineering ◽  
2018 ◽  
Vol 4 (5) ◽  
pp. 653-660 ◽  
Author(s):  
Jiulong Cheng ◽  
Guangdong Song ◽  
Xiaoyun Sun ◽  
Laifu Wen ◽  
Fei Li
Keyword(s):  
Source Location ◽  
Microseismic Source Location
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