scholarly journals A Multi-Channel Approach for Automatic Microseismic Event Association using RANSAC-based Arrival Time Event Clustering (RATEC)

2021 ◽  
pp. 100008
Author(s):  
Lijun Zhu ◽  
Lindsay Chuang ◽  
James H. McClellan ◽  
Entao Liu ◽  
Zhigang Peng
Keyword(s):  
Arrival Time ◽  
Event Clustering ◽  
Microseismic Event

Joint microseismic event location and anisotropic velocity inversion with the cross double-difference method using downhole microseismic data

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. KS63-KS73
Author(s):  
Yangyang Ma ◽  
Congcong Yuan ◽  
Jie Zhang
Keyword(s):  
Arrival Time ◽  
Velocity Model ◽  
P Wave ◽  
Double Difference ◽  
S Wave ◽  
Arrival Times ◽  
Monitoring Well ◽  
The Cross ◽  
Microseismic Event ◽  
Wave Arrival

We have applied the cross double-difference (CDD) method to simultaneously determine the microseismic event locations and five Thomsen parameters in vertically layered transversely isotropic media using data from a single vertical monitoring well. Different from the double-difference (DD) method, the CDD method uses the cross-traveltime difference between the S-wave arrival time of one event and the P-wave arrival time of another event. The CDD method can improve the accuracy of the absolute locations and maintain the accuracy of the relative locations because it contains more absolute information than the DD method. We calculate the arrival times of the qP, qSV, and SH waves with a horizontal slowness shooting algorithm. The sensitivities of the arrival times with respect to the five Thomsen parameters are derived using the slowness components. The derivations are analytical, without any weak anisotropic approximation. The input data include the cross-differential traveltimes and absolute arrival times, providing better constraints on the anisotropic parameters and event locations. The synthetic example indicates that the method can produce better event locations and anisotropic velocity model. We apply this method to the field data set acquired from a single vertical monitoring well during a hydraulic fracturing process. We further validate the anisotropic velocity model and microseismic event locations by comparing the modeled and observed waveforms. The observed S-wave splitting also supports the inverted anisotropic results.

scholarly journals Estimation of the Relative Arrival Time of Microseismic Events Based on Phase-Only Correlation

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2527 ◽  
Author(s):  
Peng Wang ◽  
Xu Chang ◽  
Xiyan Zhou
Keyword(s):  
Arrival Time ◽  
Linear Equations ◽  
Time Lag ◽  
Synthetic Data ◽  
Information Criterion ◽  
Peak Position ◽  
Arrival Times ◽  
Time Frequency ◽  
Microseismic Events ◽  
Microseismic Event

The arrival time of a microseismic event is an important piece of information for microseismic monitoring. The accuracy and efficiency of arrival time identification is affected by many factors, such as the low signal-to-noise ratio (SNR) of the records, the vast amount of real-time monitoring records, and the abnormal situations of monitoring equipment. In order to eliminate the interference of these factors, we propose a method based on phase-only correlation (POC) to estimate the relative arrival times of microseismic events. The proposed method includes three main steps: (1) The SNR of the records is improved via time-frequency transform, which is used to obtain the time-frequency representation of each trace of a microseismic event. (2) The POC functions of all pairs of time-frequency representations are calculated. The peak value of the POC function indicates the similarity of the traces, and the peak position in the time lag axis indicates the relative arrival times between the traces. (3) Using the peak values as weighting coefficients of the linear equations, consistency processing is used to exclude any abnormal situations and obtain the optimal relative arrival times. We used synthetic data and field data to validate the proposed method. Comparing with Akaike information criterion (AIC) and cross-correlation, the proposed method is more robust at estimating the relative arrival time and excluding the influence of abnormal situations.

scholarly journals Microseismic Event Location by Considering the Influence of the Empty Area in an Excavated Tunnel

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 574 ◽  
Author(s):  
Pingan Peng ◽  
Yuanjian Jiang ◽  
Liguan Wang ◽  
Zhengxiang He
Keyword(s):  
Arrival Time ◽  
Velocity Model ◽  
Microseismic Monitoring ◽  
Fast Marching Method ◽  
Fast Marching ◽  
Working Face ◽  
Event Location ◽  
Microseismic Event Location ◽  
Microseismic Event ◽  
Empty Area

The velocity model is a key factor that affects the accuracy of microseismic event location around tunnels. In this paper, we consider the effect of the empty area on the microseismic event location and present a 3D heterogeneous velocity model for excavated tunnels. The grid-based heterogeneous velocity model can describe a 3D arbitrarily complex velocity model, where the microseismic monitoring areas are divided into many blocks. The residual between the theoretical arrival time calculated by the fast marching method (FMM) and the observed arrival time is used to identify the block with the smallest residual. Particle swarm optimization (PSO) is used to improve the location accuracy in this block. Synthetic tests show that the accuracy of the microseismic event location based on the heterogeneous velocity model was higher than that based on the single velocity model, independent of whether an arrival time error was considered. We used the heterogeneous velocity model to locate 7 blasting events and 44 microseismic events with a good waveform quality in the Qinling No. 4 tunnel of the Yinhanjiwei project from 6 June 2017 to 13 June 2017 and compared the location results of the heterogeneous-velocity model with those of the single-velocity model. The results of this case study show that the events located by the heterogeneous velocity model were concentrated around the working face, which matched the actual conditions of the project, while the events located by the single-velocity model were scattered and far from the working face.

An Arrival Time and Duration Estimation of a Signal

2000 ◽  
Vol 54 (8-9) ◽  
pp. 122-133
Author(s):  
Andrey Pavlovich Trifonov ◽  
Yurii Eduardovich Korchagin
Keyword(s):  
Arrival Time ◽  
Duration Estimation

The Prediction of Rainfall and the Direction of Rainfall by a Narrow Area Radar Rain Gauge

1993 ◽  
Vol 28 (11-12) ◽  
pp. 79-85
Author(s):  
Shinichi Kondo
Keyword(s):  
Small Area ◽  
Arrival Time ◽  
Rain Gauge ◽  
Rain Gauges ◽  
Sewage Plant ◽  
Future Prediction ◽  
Near Future ◽  
Narrow Area

Narrow area radar rain gauges are currently used for measuring rainfall. These radar gauges can measure rainfall accurately in a small area. In sewage plants it is important to predict stormwater. To calculate predicted stormwater the results of rainfall and a prediction of the near future are necessary. Recently urbanization has made the arrival time of flooding to the sewage plant much shorter. This paper deals with system technologies for the near future prediction of radar rain gauge rainfall. The method of prediction of rainfall, calculation of results and other considerations are described.

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