scholarly journals Applicability of On-Site P-Wave Earthquake Early Warning to Seismic Data Observed During the 2011 Off the Pacific Coast of Tohoku Earthquake, Japan

2021 ◽  
Vol 9 ◽  
Author(s):  
Seiji Tsuno
Keyword(s):  
Seismic Data ◽  
Time Window ◽  
Seismic Station ◽  
Tohoku Earthquake ◽  
Spectral Ratio ◽  
P Wave ◽  
S Wave ◽  
Site Specific ◽  
Source Effects ◽  
The Pacific

In this study, the on-site P-wave earthquake early warning (EEW) based on the site-specific spectral ratio of S-wave to P-wave to efficiently incorporate the site characteristics, which can potentially issue the earthquake warning by the time of Ts-p, was developed. The spectral ratio of S-wave to P-wave that are related to the source effects, the path effects, and the site effects are significantly affected by the site effects contrast to the source effects and the path effects in practical. At first, the on-site P-wave EEW method which multiplies a site-specific spectral ratio of S-wave to P-wave prepared in advance by P-wave observed in the real-time at seismic stations is applied to seismic data for moderate-sized earthquakes with a magnitude (Mj) of 5.0–6.0, occurred in the eastern Japan, observed at both the sedimentary basin site and the rock site. As a result, this method predicted well the observed S-wave in the single indicator of SI within the logarithmic standard deviation of 0.25 as well as in the frequency of more than 0.5 Hz. It is, also, confirmed that the site-specific spectral ratio of S-wave to P-wave at a seismic station was stably retrieved from 20 data samples at least. To investigate the applicability of this method to earthquake ground motions induced by a large-scaled earthquake, finally, this method is applied to seismic data during the 2011 off the Pacific coast of Tohoku earthquake, Japan (Mw 9.0). The prediction of S-wave using a time-window of 10 s after P-wave arrived, could not reproduce the observation with the underestimation; however, the prediction of S-wave using a time-window of more than 20 s containing P-wave propagated from an area generating strong motions in the fault, could reproduce the observation. Even in the case of the large-scaled earthquake, the on-site P-wave EEW method based on the site-specific spectral ratio of S-wave to P-wave at a seismic station availably works by using the gradually increasing time-windows after P-wave arrived in the single indicator of SI as well as in the frequency content, avoiding the mixture of S-wave into a part of P-wave.

Spectral ratio comparison between translation and rotational records from induced seismic events.

2021 ◽  
Author(s):  
Dariusz Nawrocki ◽  
Maciej Mendecki ◽  
Lesław Teper
Keyword(s):  
Seismic Data ◽  
Seismic Station ◽  
Spectral Ratio ◽  
Numerical Differentiation ◽  
Vertical Axis ◽  
Frequency Range ◽  
Signal Ratio ◽  
Seismic Waveforms ◽  
Seismic Tests ◽  
Rotation Spectrum

<p>The seismic observations of the rotational signals are a field of seismology that is constantly developed. The recent research concerns sensors technology and its potential application in seismic tests. This study presents the results of a comparative analysis of rotational and translational seismic records using the horizontal-to-vertical spectral ratio (HVSR) method. In terms of transitional signal ratio, we have used the name of HVSR, but in terms of rotational component spectra, we have introduced a torsion-to-rocking spectral ratio (TRSR) which corresponds to horizontal rotation spectrum to vertical rotation spectrum. It has to be noticed that rotation in the horizontal axes has a vertical character and rotation in the vertical axis has a horizontal character.</p><p>The comparison was carried out between velocity signals of translational and rotational records, as well as, between acceleration signals respectively. All seismic data were recorded by two independent sensors: the rotational seismometer and translational accelerometer at the Imielin station, located in the Upper Silesia Coal Basin (USCB), Poland. The seismic data composed of three-component seismic waveforms related to 56 recorded tremors which were located up to 1,5 km from the seismic station and they resulted from the coal extractions carried out in the neighboring coal mines. The rotational acceleration was obtained by numerical differentiation and the translational velocity was produced by numerical integration.</p><p>The conducted spectral analyses allowed to estimate the range of frequency in which the rotational HVSR and the corresponded translational HVSR are comparable. The analysis of HVSR/TRSR curves (in the selected frequency range of 1Hz to 10Hz) showed a strong correlation between the spectral ratios for the velocity signals (translational and rotational) in the frequency range of 1Hz to 2Hz. Respectively, the comparison of the accelerometer signals indicated the correlation between HVSR/TRSR curves in the frequency range of 1Hz to 3Hz. Moreover, both of the TRSR (for velocity and acceleration) showed additional maxima in the same frequency range of 3Hz to 5Hz. These relatively high-frequency maxima did not correspond to translational spectra.  </p>

Using Seismic Data to Predict Shale Pore Pressure and Overpressure Sweet Spots: A Case Study from the Lower Silurian Longmaxi Formation in Sichuan Basin, China

2021 ◽  
Author(s):  
Sheng Chen ◽  
Qingcai Zeng ◽  
Xiujiao Wang ◽  
Qing Yang ◽  
Chunmeng Dai ◽  
...  
Keyword(s):  
Prediction Model ◽  
Wave Velocity ◽  
Shale Gas ◽  
Seismic Data ◽  
P Wave ◽  
Formation Pressure ◽  
S Wave ◽  
P Wave Velocity ◽  
New Formation ◽  
Sweet Spots

Abstract Practices of marine shale gas exploration and development in south China have proved that formation overpressure is the main controlling factor of shale gas enrichment and an indicator of good preservation condition. Accurate prediction of formation pressure before drilling is necessary for drilling safety and important for sweet spots predicting and horizontal wells deploying. However, the existing prediction methods of formation pore pressures all have defects, the prediction accuracy unsatisfactory for shale gas development. By means of rock mechanics analysis and related formulas, we derived a formula for calculating formation pore pressures. Through regional rock physical analysis, we determined and optimized the relevant parameters in the formula, and established a new formation pressure prediction model considering P-wave velocity, S-wave velocity and density. Based on regional exploration wells and 3D seismic data, we carried out pre-stack seismic inversion to obtain high-precision P-wave velocity, S-wave velocity and density data volumes. We utilized the new formation pressure prediction model to predict the pressure and the spatial distribution of overpressure sweet spots. Then, we applied the measured pressure data of three new wells to verify the predicted formation pressure by seismic data. The result shows that the new method has a higher accuracy. This method is qualified for safe drilling and prediction of overpressure sweet spots for shale gas development, so it is worthy of promotion.

Three-component analysis of regional seismograms

1990 ◽  
Vol 80 (6B) ◽  
pp. 2032-2052 ◽  
Author(s):  
D. C. Jepsen ◽  
B. L. N. Kennett
Keyword(s):  
Free Surface ◽  
Time Window ◽  
Seismic Station ◽  
P Wave ◽  
Sh Waves ◽  
Near Surface ◽  
Source Discrimination ◽  
Decomposition Scheme ◽  
Phased Array Techniques ◽  
The Stability

Abstract Both phased array techniques for single-component sensors and vectorial analysis of three-component recordings can provide estimates of the azimuth and slowness of seismic phases. However, a combination of these approaches provides a more powerful tool to estimate the propagation characteristics of different seismic phases at regional distances. Conventional approaches to the analysis of three-component seismic records endeavor to exploit the apparent angles of propagation in horizontal and vertical planes as well as the polarization of the waves. The basic assumption is that for a given time window there is a dominant wavetype (e.g., a P wave) traveling in a particular direction arriving at the seismic station. By testing a range of characteristics of the three-component records, a set of rules can be established for classifying much of the seismogram in terms of wavetype and direction. It is, however, difficult to recognize SH waves in the presence of other wavetypes. Problems also arise when more than one signal (in either wavetype or direction) arrive in the same window. The stability and robustness of the classification scheme is much improved when records from an array of three-component sensors are combined. For a set of three-component instruments forming part of a larger array, it is possible to estimate the slowness and azimuth of arrivals from the main array and then extract the relative proportions of the current P-, SV-, and SH-wave contributions to the seismogram. This form of wavetype decomposition depends on a model of near-surface propagation. A convenient choice for hard-rock sites is to include just the effect of the free surface, which generates a frequency-independent operation on the three-component seismograms and which is not very sensitive to surface velocities. This approach generates good estimates of the character of the S wavefield, because the phase distortion of SV induced by the free surface can be removed. The method has been successfully applied to regional seismograms recorded at the medium aperture Warramunga array in northern Australia, and the two small arrays NORESS and ARCESS in Norway, which were designed for studies of regional phases. The new wavefield decomposition scheme provides results in which the relative proportions of P, SV, and SH waves as a function of time can be compared without the distortion imposed by free surface amplification. Such information can provide a useful adjunct to existing measures of signal character used in source discrimination.

scholarly journals Time–frequency windowing in multiparameter elastic FWI of shallow seismic wavefield

2020 ◽  
Vol 222 (2) ◽  
pp. 1164-1177
Author(s):  
Nikolaos Athanasopoulos ◽  
Edgar Manukyan ◽  
Thomas Bohlen ◽  
Hansruedi Maurer
Keyword(s):  
Wave Velocity ◽  
Time Window ◽  
Mass Density ◽  
Waveform Inversion ◽  
P Wave ◽  
S Wave ◽  
Time Frequency ◽  
Full Waveform ◽  
Shallow Seismic ◽  
P Wave Velocity

SUMMARY Full-waveform inversion of shallow seismic wavefields is a promising method to infer multiparameter models of elastic material properties (S-wave velocity, P-wave velocity and mass density) of the shallow subsurface with high resolution. Previous studies used either the refracted Pwaves to reconstructed models of P-wave velocity or the high-amplitude Rayleigh waves to infer the S-wave velocity structure. In this work, we propose a combination of both wavefields using continuous time–frequency windowing. We start with the contribution of refracted P waves and gradually increase the time window to account for scattered body waves, higher mode Rayleigh waves and finally the fundamental Rayleigh wave mode. The opening of the time window is combined with opening the frequency bandwidth of input signals to avoid cycle skipping. Synthetic reconstruction tests revealed that the reconstruction of P-wave velocity model and mass density can be improved. The S-wave velocity reconstruction is still accurate and robust and is slightly benefitted by time–frequency windowing. In a field data application, we observed that time–frequency windowing improves the consistency of multiparameter models. The inferred models are in good agreement with independent geophysical information obtained from ground-penetrating radar and full-waveform inversion of SH waves.

On plane‐wave decomposition: Alias removal

Geophysics ◽  
1989 ◽  
Vol 54 (10) ◽  
pp. 1339-1343 ◽  
Author(s):  
S. C. Singh ◽  
G. F. West ◽  
C. H. Chapman
Keyword(s):  
Plane Wave ◽  
Seismic Data ◽  
P Wave ◽  
S Wave ◽  
Plane Wave Decomposition ◽  
Time Migration ◽  
Time Distance ◽  
P Domain ◽  
Wave Decomposition ◽  
Rapid Modeling

The delay‐time (τ‐p) parameterization, which is also known as the plane‐wave decomposition (PWD) of seismic data, has several advantages over the more traditional time‐distance (t‐x) representation (Schultz and Claerbout, 1978). Plane‐wave seismograms in the (τ, p) domain can be used for obtaining subsurface elastic properties (P‐wave and S‐wave velocities and density as functions of depth) from inversion of the observed oblique‐incidence seismic data (e.g., Yagle and Levy, 1985; Carazzone, 1986; Carrion, 1986; Singh et al., 1989). Treitel et al. (1982) performed time migration of plane‐wave seismograms. Diebold and Stoffa (1981) used plane‐wave seismograms to derive a velocity‐depth function. Decomposing seismic data also allows more rapid modeling, since it is faster to compute synthetic seismograms in the (τ, p) than in the (t, x) domain. Unfortunately, the transformation of seismic data from the (t, x) to the (τ, p) domain may produce artifacts, such as those caused by discrete sampling, of the data in space.

Elastic reflectivity vectors and the geometry of intercept-gradient crossplots

2019 ◽  
Vol 38 (10) ◽  
pp. 762-769
Author(s):  
Patrick Connolly
Keyword(s):  
Elastic Property ◽  
Elastic Properties ◽  
Wave Velocity ◽  
Seismic Data ◽  
Measurement Errors ◽  
Rock Physics ◽  
P Wave ◽  
S Wave ◽  
P Wave Velocity ◽  
Well Log Analysis

Reflectivities of elastic properties can be expressed as a sum of the reflectivities of P-wave velocity, S-wave velocity, and density, as can the amplitude-variation-with-offset (AVO) parameters, intercept, gradient, and curvature. This common format allows elastic property reflectivities to be expressed as a sum of AVO parameters. Most AVO studies are conducted using a two-term approximation, so it is helpful to reduce the three-term expressions for elastic reflectivities to two by assuming a relationship between P-wave velocity and density. Reduced to two AVO components, elastic property reflectivities can be represented as vectors on intercept-gradient crossplots. Normalizing the lengths of the vectors allows them to serve as basis vectors such that the position of any point in intercept-gradient space can be inferred directly from changes in elastic properties. This provides a direct link between properties commonly used in rock physics and attributes that can be measured from seismic data. The theory is best exploited by constructing new seismic data sets from combinations of intercept and gradient data at various projection angles. Elastic property reflectivity theory can be transferred to the impedance domain to aid in the analysis of well data to help inform the choice of projection angles. Because of the effects of gradient measurement errors, seismic projection angles are unlikely to be the same as theoretical angles or angles derived from well-log analysis, so seismic data will need to be scanned through a range of angles to find the optimum.

scholarly journals Anisotropy extraction using a deviated well in the Mahanadi Basin, East Coast of India

2019 ◽  
Vol 10 (3) ◽  
pp. 911-918
Author(s):  
Biplab Kumar Mukherjee ◽  
G. Karthikeyan ◽  
Karanpal Rawat ◽  
Hari Srivastava
Keyword(s):  
Seismic Data ◽  
East Coast ◽  
Velocity Model ◽  
P Wave ◽  
S Wave ◽  
Gardner Equation ◽  
East Coast Of India ◽  
Nonlinear Fitting ◽  
Sonic Log ◽  
Mahanadi Basin

Abstract Shale is the primary rock type in the shallow marine section of the Mahanadi Basin, East Coast of India. Shale, being intrinsically anisotropic, always affects the seismic data. Anisotropy derived from seismic and VSP has lower resolution and mostly based on P wave. The workflow discussed here uses Gardner equation to derive vertical velocity and uses a nonlinear fitting to extract the Thomsen’s parameters using both the P wave and S wave data. These parameters are used to correct the sonic log of a deviated well as well as anisotropic AVO response of the reservoir. The presence of negative delta was observed, which is believed to be affected by the presence of chloride and illite in the rock matrix. This correction can be used to update the velocity model for time–depth conversion and pore pressure modelling.

Prestack 2D parsimonious Kirchhoff depth migration of elastic seismic data

Geophysics ◽  
2011 ◽  
Vol 76 (4) ◽  
pp. S157-S164 ◽  
Author(s):  
Robert Sun ◽  
George A. McMechan
Keyword(s):  
Seismic Data ◽  
Velocity Model ◽  
P Wave ◽  
P Value ◽  
Common Source ◽  
S Wave ◽  
P Values ◽  
Depth Migration ◽  
Reflector Surface ◽  
Kirchhoff Depth Migration

We have extended prestack parsimonious Kirchhoff depth migration for 2D, two-component, reflected elastic seismic data for a P-wave source recorded at the earth’s surface. First, we separated the P-to-P reflected (PP-) waves and P-to-S converted (PS-) waves in an elastic common-source gather into P-wave and S-wave seismograms. Next, we estimated source-ray parameters (source p values) and receiver-ray parameters (receiver p values) for the peaks and troughs above a threshold amplitude in separated P- and S-wavefields. For each PP and PS reflection, we traced (1) a source ray in the P-velocity model in the direction of the emitted ray angle (determined by the source p value) and (2) a receiver ray in the P- or S-velocity model back in the direction of the emergent PP- or PS-wave ray angle (determined by the PP- or PS-wave receiver p value), respectively. The image-point position was adjusted from the intersection of the source and receiver rays to the point where the sum of the source time and receiver-ray time equaled the two-way traveltime. The orientation of the reflector surface was determined to satisfy Snell’s law at the intersection point. The amplitude of a P-wave (or an S-wave) was distributed over the first Fresnel zone along the reflector surface in the P- (or S-) image. Stacking over all P-images of the PP-wave common-source gathers gave the stacked P-image, and stacking over all S-images of the PS-wave common-source gathers gave the stacked S-image. Synthetic examples showed acceptable migration quality; however, the images were less complete than those produced by scalar reverse-time migration (RTM). The computing time for the 2D examples used was about 1/30 of that for scalar RTM of the same data.

Supercritical reflections observed in P- and S- wave data

Geophysics ◽  
1985 ◽  
Vol 50 (2) ◽  
pp. 185-195 ◽  
Author(s):  
D. F. Winterstein ◽  
J. B. Hanten
Keyword(s):  
Seismic Data ◽  
Critical Angle ◽  
Plane Waves ◽  
Critical Distance ◽  
P Wave ◽  
S Wave ◽  
Sh Waves ◽  
Midland Basin ◽  
Head Waves ◽  
Sonic Logs

We have observed a conspicuous example of supercritical reflection in both P- and SH- wave seismic data. Data were recorded in the Midland Basin (Texas) Project of the Conoco Shear Wave Group Shoot in 1977–1978. P- and S- wave critical angle phenomena, as observed in the data, are remarkably similar. Event amplitudes are small or undetectable at offsets out to about 2 000 ft, but at offsets from 2 500 to 3 600 ft amplitudes are higher than those of any other event. Head waves originating at the critical distance are weak but detectable. Long path multiplies of the supercritical parts of P and SH events appear at expected times and offsets. Constant velocity moveout corrections helped identify them. Sonic logs in combination with a knowledge of the lithology made it possible to model P- wave critical angle phenomena. Agreement of model results with the data was good when we assumed cylindrical wavefronts. As expected, modeling based on plane waves was unable to match observed phase and amplitude behavior. A number of potential uses for supercritical reflections in exploration and data processing readily come to mind, many of them related to the recording of relatively high amplitudes at distances where source noise is low. Observed rise in amplitude near the critical offset was very abrupt, particularly for SH-waves. This suggests that variations in the onset of high amplitudes may be useful for monitoring changes in velocity contrast at the reflecting interface.

Accuracy Comparison of Elastic Impedance Formula

2012 ◽  
Vol 466-467 ◽  
pp. 400-404
Author(s):  
Jin Zhang ◽  
Huai Shan Liu ◽  
Si You Tong ◽  
Lin Fei Wang ◽  
Bing Xu
Keyword(s):  
Seismic Data ◽  
Poisson Ratio ◽  
Seismic Inversion ◽  
P Wave ◽  
S Wave ◽  
Elastic Parameters ◽  
Accuracy Comparison ◽  
Elastic Impedance ◽  
Prestack Seismic Inversion ◽  
Lamé Coefficients

Elastic impedance (EI) inversion is one of the prestack seismic inversion methods, which can obtain P-wave and S-wave velocity, density, Poisson ratio, Lame coefficients and other elastic parameters. But there have been many EI formulas nowadays, so which formula should be used in inversion is an urgent problem. This paper divides these formulas into two categories, and use several forward modeling to test the accuracy of these EI formulas. It shows that using the first kind of EI formulas in near offset seismic data can get high precision results.

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