scholarly journals Studi Automatic Picking Waktu Tiba Gelombang P dan S dengan Menggunakan Spektogram pada Obspy Python

2020 ◽  
Vol 8 (1) ◽  
pp. 77-82
Author(s):  
Indriati Retno Palupi ◽  
◽  
Wiji Raharjo ◽  
Keyword(s):  
Frequency Analysis ◽  
Arrival Time ◽  
Dominant Frequency ◽  
S Wave ◽  
Important Thing ◽  
Automatic Picking ◽  
Wave Arrival

One of important thing in locating hypocenter process is determine P and S arrival time of the seismogram. Beside that, frequency analysis by FFT method is needed to know the character of the seismogram, like dominant frequency. For further analysis, FFT method can be a good tools in determine P and S wave arrival time in the spectogram form. This process is called automatic picking.

scholarly journals The Study of Automatic Picking of P and S Wave Arrival and Identification of Earthquake Sequence Pattern using Scalogram in Obspy (Python)

2021 ◽  
Vol 873 (1) ◽  
pp. 012014
Author(s):  
Sri Kiswanti ◽  
Indriati Retno Palupi ◽  
Wiji Raharjo ◽  
Faricha Yuna Arwa ◽  
Nela Elisa Dwiyanti
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Arrival Time ◽  
Continuous Wavelet ◽  
S Wave ◽  
S Waves ◽  
Automatic Picking ◽  
Earthquake Record ◽  
Initial Identification ◽  
Wave Arrival

Abstract Initial identification on an earthquake record (seismogram) is something that needs to be done precisely and accurately. Moreover, the discovery of a series of unexpected successive earthquake events has caused unpreparedness for the community and related agencies in tackling these events. Determining the arrival time of the P and S waves becomes an important parameter to finding the location of the earthquake source (hypocenter) as well as further information related to the earthquake event. However, manual steps that are currently often used are considered to be less effective, because it requires a lot of time in the process. Continuous Wavelet Transform (CWT) analysis can be a solution for this problem. With further CWT analysis in the form of a scalogram, can help to determine the arrival time of P and S waves automatically (automatic picking) becomes simpler. In addition, further CWT analysis can also be utilized to help identify the sequence of earthquake events (foreshock, mainshock, aftershock) through the resulting scalogram pattern.

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.

Automatic algorithm for triaxial hodogram source location in downhole acoustic emission measurement

Geophysics ◽  
1989 ◽  
Vol 54 (4) ◽  
pp. 508-513 ◽  
Author(s):  
K. Nagano ◽  
H. Niitsuma ◽  
N. Chubachi
Keyword(s):  
Acoustic Emission ◽  
Arrival Time ◽  
Field Measurements ◽  
Source Location ◽  
P Wave ◽  
Likelihood Method ◽  
Emission Measurement ◽  
Wave Direction ◽  
S Wave ◽  
Wave Arrival

An automatic acoustic emission (AE) source location algorithm has been developed for downhole AE measurement of subsurface cracks by using the triaxial hodogram method. The P-wave arrival time is detected by analyzing crosscorrelation coefficients among three components of AE signal energy; the P-wave direction is determined by the method of least squares. For detection of S-wave arrival time, a maximum‐likelihood method analyzes a distribution of instantaneous values of the SH-wave component amplitude. This algorithm can locate an AE source as accurately as human analysis. For field measurements, it takes less than 4 s to locate an AE source using a 16-bit personal computer with a program in C language. Automatic AE source location by the triaxial hodogram method has been realized with this algorithm.

New Methods for Data Stacking and P‐ and S‐wave Arrival Time Determination Using the Deep Moonquake Apollo Recordings

2021 ◽  
Vol 126 (2) ◽  
Author(s):  
Yuefeng Yuan ◽  
Edward J. Garnero ◽  
Peimin Zhu ◽  
Pei‐ying Lin ◽  
Renee C. Weber ◽  
...  
Keyword(s):  
Arrival Time ◽  
S Wave ◽  
New Methods ◽  
Time Determination ◽  
Wave Arrival

Dominant frequency analysis of EEG reveals brain's response during injury and recovery

1996 ◽  
Vol 43 (11) ◽  
pp. 1083-1092 ◽  
Author(s):  
V. Goel ◽  
A.M. Brambrink ◽  
A. Baykal ◽  
R.C. Koehler ◽  
D.F. Hanley ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Dominant Frequency ◽  
Dominant Frequency Analysis

scholarly journals Metode Seismik dalam Pemodelan Fisis Letusan Gunung Lumpur Bledug Kuwu

2019 ◽  
Vol 2 (2) ◽  
pp. 61-66
Author(s):  
Ahmad Fauzi Pohan ◽  
Rusnoviandi Rusnoviandi
Keyword(s):  
Wave Velocity ◽  
Physical Modeling ◽  
Vertical Component ◽  
Dominant Frequency ◽  
P Wave ◽  
Physical Parameters ◽  
S Wave ◽  
Interesting Phenomenon ◽  
Central Java ◽  
P Wave Velocity

Aktivitas gunung lumpur Bledug Kuwu di Jawa  Tengah merupakan fenomena yang menarik dikaji menggunakan pemodelan fisis. Tujuan penelitian ini adalah mengetahui parameter dari medium gunung lumpur Bledug Kuwu. Adapun pemodelan fisis yang dilakukan dengan menggunakan media fisis akuarium berukuran 59 × 59 × 37,3 cm yang diisi material dari lumpur Bledug Kuwu. Sumber letusan dihasilkan dari tekanan kompresor yang dapat diatur kedalaman (10.5, 13, dan 15.5 cm) dan sudut (30o, 45o dan 60o) sumbernya. Sensor yang digunakan geophone komponen vertikal sebanyak 3 buah dengan durasi perekaman selama 5 dan 2,5 detik. Data diambil dengan frekuensi sampel 2 dan 4 kHz untuk masing-masing durasi perekaman. Konfigurasi sumber dan geophone dibuat sesuai dengan pemodelan fisisnya. Pengukuran desnsitas lumpur menunjukkan angka sebesar 1200 kg/m3. Berdasarkan hasil analisis seismogram model fisis diperoleh kecepatan perambatan gelombang-P pada medium lumpur Bledug Kuwu adalah sebesar 48,74 m/s,dan gelombang-S sebesar 28,14 m/s dengan frekuensi dominan antara 20 sampai 25 Hz.   Bledug Kuwu mud volcano activity in Central Java is an interesting phenomenon to be studied using both physical  modeling. The objective of this study was to determine the physical parameters of the medium of Bledug Kuwu. The Physical model was an aquarium with a dimension of 59 × 59 × 37.3 cm filled with Bledug Kuwu’s mud. The eruption source is generated by a compressor pressure that can be controled both the depth(10.5, 13, and 15.5 cm) and the angel of the source (30o, 45o and 60o). The resulting seismic signals were recorded by using 3 vertical component geophones for 10 and 5 seconds durations at a frequency of 2 and 4 kHz respectivel, mud density 1200 kg/m3 . The physical modeling shows that the P-wave velocity of the Bledug Kuwu’s medium is 48.7 m/s, S-wave velocity of Bledug Kuwu’s is 28,14 m/s  with a dominant frequency of 20 to 25 Hz.

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