SEISMIC EXPERIMENTS WITH VERTICAL ARRAYS

Geophysics ◽  
1968 ◽  
Vol 33 (2) ◽  
pp. 270-284 ◽  
Author(s):  
Robert B. Roden
Keyword(s):  
Ambient Noise ◽  
Vertical Component ◽  
P Wave ◽  
Signal Interference ◽  
Vertical Array ◽  
Reflected Waves ◽  
Deep Well ◽  
Vertical Arrays ◽  
Multichannel Filtering ◽  
Selection Of

Experiments with vertical arrays of seismometers were conducted from 1963 to 1965. Data of exceptionally high quality were obtained through the use of special 1‐cps, deep‐well seismometers and direct digital recording techniques. Arrays studied experimentally contained up to 7 vertical‐component seismometers and extended to depths as great as 3.1 km. P‐wave signals observed at depth are generally distorted because of interference between incident and surface‐reflected waves. It is shown that the outputs of two or more deep‐well instruments can be combined to reconstruct signal waveforms. Small additional improvements were obtained through the application of optimum multichannel filtering to vertical array outputs, but the best signal‐to‐noise ratios obtained were never more than 6 db above those available from single deep‐well seismometers located at points of constructive signal interference. Results obtained from analysis of experimental data support the hypothesis that severe attenuation of seismic noise with depth is a characteristic only of sites where ambient noise is very intense at the surface. It is concluded that improvements in record quality which can be obtained through the application of vertical array processing at noisy sites are probably not greater than the improvements which would result from careful selection of a quiet site.

SOME DATA PROCESSING RESULTS FOR A VERTICAL ARRAY OF TRIAXIAL SEISMOMETERS

Geophysics ◽  
1970 ◽  
Vol 35 (2) ◽  
pp. 337-343 ◽  
Author(s):  
Zoltan A. Der
Keyword(s):  
Data Processing ◽  
Signal To Noise Ratio ◽  
Vertical Component ◽  
Poor Performance ◽  
P Wave ◽  
Oil Well ◽  
Vertical Array ◽  
Signal To Noise ◽  
Vertical Arrays ◽  
Three Components

A vertical array of three component (triaxial) seismometers was operated in an abandoned oil well near Grapevine, Texas. The experiment was designed to investigate the effectiveness of teleseismic P‐wave enhancement by utilization of all three components of motion at various depths within the well. Previous experiments with vertical arrays which only recorded the vertical component of motion showed that optimum processors did not significantly improve the signal‐to‐noise ratio (Roden, 1968). The reason for this poor performance was found to be a similarity in the changes of signal and noise properties with depth.

WIDE‐BAND EXTRACTION OF MANTLE P WAVES FROM AMBIENT NOISE

Geophysics ◽  
1964 ◽  
Vol 29 (5) ◽  
pp. 672-692 ◽  
Author(s):  
Milo Backus ◽  
John Burg ◽  
Dick Baldwin ◽  
Ed Bryan
Keyword(s):  
Ambient Noise ◽  
Wide Band ◽  
P Wave ◽  
Cumberland Plateau ◽  
P Waves ◽  
Single Output ◽  
Short Period ◽  
Multichannel Filtering ◽  
On Line ◽  
Element Array

The spatial correlation characteristics of ambient short‐period (0.5 to 5 cps) noise at Ft. Sill, Oklahoma, and on the Cumberland Plateau in Tennessee were investigated on “permanent” arrays with 3–4 kilometer diameter. Dominant ambient noise at the two locations is spatially organized, and to first order may be treated as a combination of seismic propagating wave trains. At the Tennessee location noise energy above one cps is dominantly propagating with velocities from 3.5 to 4.5 km/sec, and must be carried in deeply trapped, high‐order modes. Generalized multichannel filtering (Burg) can be used to preserve a large class of mantle P‐wave signals, wide‐band, in a single output trace, while at the same time specifically rejecting ambient noise on the basis of its organization. Results of generalized multichannel filtering applied on‐line at the nineteen‐element array in Tennessee and applied off‐line are discussed.

scholarly journals Crustal structure beneath Tierra del Fuego, Argentina, inferred from seismic P-wave receiver functions and ambient noise autocorrelations

2019 ◽  
Vol 751 ◽  
pp. 41-53 ◽  
Author(s):  
Carolina Buffoni ◽  
Martin Schimmel ◽  
Nora Cristina Sabbione ◽  
María Laura Rosa ◽  
Gerardo Connon
Keyword(s):  
Crustal Structure ◽  
Ambient Noise ◽  
Receiver Functions ◽  
Tierra Del Fuego ◽  
P Wave

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.

scholarly journals Preliminary Results of Receiver Function Forward Velocity Modelling at Merapi Volcano

2021 ◽  
Vol 873 (1) ◽  
pp. 012056
Author(s):  
M F R Auly ◽  
A K Ilahi ◽  
I Madrinovella ◽  
S Widyanti ◽  
S K Suhardja ◽  
...  
Keyword(s):  
Receiver Function ◽  
Tectonic Setting ◽  
Vertical Component ◽  
P Wave ◽  
Function Technique ◽  
Boundary Current ◽  
Low Velocity ◽  
Mantle Boundary ◽  
Velocity Models ◽  
Synthetic Model

Abstract The tectonic setting of Java island, located at southwestern edge of the Eurasia continent, is dominated by the subduction of Indo-Australia plate. One of the characteristics of active subduction is active seismicity, the generation of arc magmatism and volcanic activity. Mt. Merapi is one example of active volcano related with the subduction process. It is one of the most active volcanoes with location close to high population area. To better understand this area, we employed the Receiver Function technique, a method to image sub surface structure by removing the vertical component from horizontal component. First, we collected high magnitude events and processed RF with water level deconvolution method. Then, we constructed synthetic model with initial velocity input from previous tomography model. Note that we used reflectivity method in generating synthetic model with input parameters matched with parameters from real data processing. Next, we adjusted velocity inputs mainly on tops sediments (1-3 km) to include sediment layers and volcanic rocks, mid-depth low velocity zone that may be related with magma chamber and depth of crust-mantle boundary. Current forward velocity models show a relatively good agreement from 3 stations (ME25, ME32 and ME36). We estimate a thin layer of sediments followed a zone of velocity layer at a depth of 10-15 km and crust-mantle boundary ranging from 26-29 km. In this study, simulated that the signal of sediments layer and low velocity layers interfere main crust mantle boundary that supposed to be highest signal after the P wave in the typical receiver function study.

Multiple geophysical investigations to characterize massive slope failure deposits: application to the Balta rockslide, Carpathians

2021 ◽  
Vol 225 (2) ◽  
pp. 1032-1047
Author(s):  
A-S Mreyen ◽  
L Cauchie ◽  
M Micu ◽  
A Onaca ◽  
H-B Havenith
Keyword(s):  
Surface Wave ◽  
Ambient Noise ◽  
Slope Failure ◽  
Seismic Refraction ◽  
P Wave ◽  
Surface Wave Dispersion ◽  
Seismic Region ◽  
Valley Bottom ◽  
Single Station ◽  
Landslide Body

SUMMARY Origins of ancient rockslides in seismic regions can be controversial and must not necessarily be seismic. Certain slope morphologies hint at a possible coseismic development, though further analyses are required to better comprehend their failure history, such as modelling the slope in its pre-failure state and failure development in static and dynamic conditions. To this effect, a geophysical characterization of the landslide body is crucial to estimate the possible failure history of the slope. The Balta rockslide analysed in this paper is located in the seismic region of Vrancea-Buzau, Romanian Carpathian Mountains and presents a deep detachment scarp as well as a massive body of landslide deposits. We applied several geophysical techniques on the landslide body, as well as on the mountain crest above the detachment scarp, in order to characterize the fractured rock material as well as the dimension of failure. Electrical resistivity measurements revealed a possible trend of increasing fragmentation of rockslide material towards the valley bottom, accompanied by increasing soil moisture. Several seismic refraction surveys were performed on the deposits and analysed in form of P-wave refraction tomographies as well as surface waves, allowing to quantify elastic parameters of rock. In addition, a seismic array was installed close to the detachment scarp to analyse the surface wave dispersion properties from seismic ambient noise; the latter was analysed together with a colocated active surface wave analysis survey. Single-station ambient noise measurements completed all over the slope and deposits were used to further reveal impedance contrasts of the fragmented material over in situ rock, representing an important parameter to estimate the depth of the shearing horizon at several locations of the study area. The combined methods allowed the detection of a profound contrast of 70–90 m, supposedly associated with the maximum landslide material thickness. The entirety of geophysical results was used as basis to build up a geomodel of the rockslide, allowing to estimate the geometry and volume of the failed mass, that is, approximately 28.5–33.5 million m3.

Crustal and upper mantle velocity structure of the Pannonian Region using Rayleigh wave ambient noise tomography

2021 ◽  
Author(s):  
Máté Timkó ◽  
Lars Wiesenberg ◽  
Amr El-Sharkawy ◽  
Zoltán Wéber ◽  
Thomas Meier ◽  
...  
Keyword(s):  
Rayleigh Wave ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Pannonian Basin ◽  
Vertical Component ◽  
High Heat ◽  
Moho Depth ◽  
Ambient Noise Tomography ◽  
Period Range ◽  
Waveform Data

<p>The Pannonian Basin is located in Central-Europe surrounded by the Alpine, Carpathian, and Dinarides mountain ranges. This is a back-arc basin characterized by shallow Moho depth, updoming mantle and high heat flow. In this study, we present the results of the Rayleigh wave based ambient noise tomography to investigate the velocity structure of the Carpathian-Pannonian region. </p><p>For the ambient noise measurements, we collected the continuous waveform data from more than 1280 seismological stations from the broader Central-Eastern European region. This dataset embraces all the permanent and the temporary (AlpArray, PASSEQ, CBP, SCP) stations from the 9-degree radius of the Pannonian Basin which were operating between the time period between 2005 and 2018. All the possible vertical component noise cross-correlation functions were calculated and all phase velocity curves were determined in the 5-80 s period range using an automated measuring algorithm. </p><p>The collected dispersion measurements were then used to create tomographic images that are characterized by similar velocity anomalies in amplitude, pattern and location that are consistent with the well-known tectonic and geologic structure of the research area and are comparable to previous tomographic models published in the literature.</p>

Common-Reflection-Point-Based Prestack Depth Migration for Imaging Lithosphere in Python: Application to the Dense Warramunga Array in Northern Australia

2020 ◽  
Vol 91 (5) ◽  
pp. 2890-2899 ◽  
Author(s):  
Weijia Sun ◽  
Brian L. N. Kennett
Keyword(s):  
Open Source ◽  
Receiver Function ◽  
Function Analysis ◽  
Vertical Component ◽  
P Wave ◽  
Northern Australia ◽  
Reflection Point ◽  
Prestack Depth Migration ◽  
Depth Migration ◽  
Conversion Point

Abstract We exploit estimates of P-wave reflectivity from autocorrelation of transmitted teleseismic P arrivals and their coda in a common reflection point (CRP) migration technique. The approach employs the same portion of the vertical-component seismogram, as in standard Ps receiver function analysis. This CRP prestack depth migration approach has the potential to image lithospheric structures on scales as fine as 4 km or less. The P-wave autocorrelation process and migration are implemented in open-source software—the autocorrelogram calculation (ACC) package, which builds on the widely used the seismological Obspy toolbox. The ACC package is written in the open-source and free Python programming language (3.0 or newer) and has been extensively tested in an Anaconda Python environment. The package is simple and friendly to use and runs on all major operating systems (e.g., Windows, macOS, and Linux). We utilize Python multiprocessing parallelism to speed up the ACC on a personal computer system, or servers, with multiple cores and threads. The application of the ACC package is illustrated with application to the closely spaced Warramunga array in northern Australia. The results show how fine-scale structures in the lithospheric can be effectively imaged at relatively high frequencies. The Moho ties well with conventional H−κ receiver analysis and deeper structure inferred from stacked autocorrelograms for continuous data. CRP prestack depth migration provides an important complement to common conversion point receiver function stacks, since it is less affected by surface multiples at lithospheric depths.

Scalar reverse‐time depth migration of prestack elastic seismic data

Geophysics ◽  
2001 ◽  
Vol 66 (5) ◽  
pp. 1519-1527 ◽  
Author(s):  
Robert Sun ◽  
George A. McMechan
Keyword(s):  
Seismic Waves ◽  
Velocity Model ◽  
P Wave ◽  
Common Source ◽  
Reverse Time ◽  
S Wave ◽  
Wave Source ◽  
Reflected Waves ◽  
S Waves ◽  
Elastic Data

Reflected P‐to‐P and P‐to‐S converted seismic waves in a two‐component elastic common‐source gather generated with a P‐wave source in a two‐dimensional model can be imaged by two independent scalar reverse‐time depth migrations. The inputs to migration are pure P‐ and S‐waves that are extracted by divergence and curl calculations during (shallow) extrapolation of the elastic data recorded at the earth’s surface. For both P‐to‐P and P‐to‐S converted reflected waves, the imaging time at each point is the P‐wave traveltime from the source to that point. The extracted P‐wave is reverse‐time extrapolated and imaged with a P‐velocity model, using a finite difference solution of the scalar wave equation. The extracted S‐wave is reverse‐time extrapolated and imaged similarly, but with an S‐velocity model. Converted S‐wave data requires a polarity correction prior to migration to ensure constructive interference between data from adjacent sources. Synthetic examples show that the algorithm gives satisfactory results for laterally inhomogeneous models.

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