The 1998 Valhall microseismic data set: An integrated study of relocated sources, seismic multiplets, and S-wave splitting

Geophysics ◽  
2009 ◽  
Vol 74 (5) ◽  
pp. B183-B195 ◽  
Author(s):  
K. De Meersman ◽  
J.-M. Kendall ◽  
M. van der Baan
Keyword(s):  
Seismic Anisotropy ◽  
Amplitude Ratio ◽  
Temporal Variations ◽  
Oil Field ◽  
P Wave ◽  
Wave Form ◽  
S Wave ◽  
Data Set ◽  
Wave Splitting ◽  
Source Mechanisms

We relocate 303 microseismic events recorded in 1998 by sensors in a single borehole in the North Sea Valhall oil field. A semiautomated array analysis method repicks the P- and S-wave arrival times and P-wave polarizations, which are needed to locate these events. The relocated sources are confined predominantly to a [Formula: see text]-thick zone just above the reservoir, and location uncertainties are half those of previous efforts. Multiplet analysis identifies 40 multiplet groups, which include 208 of the 303 events. The largest group contains 24 events, and five groups contain 10 or more events. Within each multiplet group, we further improve arrival-time picking through crosscorrelation, which enhances the relative accuracy of the relocated events and reveals that more than 99% of the seismic activity lies spatially in three distinct clusters. The spatial distribution of events and wave-form similarities reveal two faultlike structures that match well with north-northwest–south-southeast-trending fault planes interpreted from 3D surface seismic data. Most waveform differences between multiplet groups located on these faults can be attributed to S-wave phase content and polarity or P-to-S amplitude ratio. The range in P-to-S amplitude ratios observed on the faults is explained best in terms of varying source mechanisms. We also find a correlation between multiplet groups and temporal variations in seismic anisotropy, as revealed by S-wave splitting analysis. We explain these findings in the context of a cyclic recharge and dissipation of cap-rock stresses in response to production-driven compaction of the underlying oil reservoir. The cyclic nature of this mechanism drives the short-term variations in seismic anisotropy and the reactivation of microseismic source mechanisms over time.

scholarly journals Deriving micro- to macro-scale seismic velocities from ice-core <i>c</i> axis orientations

2018 ◽  
Vol 12 (5) ◽  
pp. 1715-1734 ◽  
Author(s):  
Johanna Kerch ◽  
Anja Diez ◽  
Ilka Weikusat ◽  
Olaf Eisen
Keyword(s):  
Shear Wave ◽  
Seismic Anisotropy ◽  
Ice Core ◽  
Shear Wave Splitting ◽  
P Wave ◽  
Seismic Velocities ◽  
Polar Ice ◽  
S Wave ◽  
Crystal Anisotropy ◽  
Wave Splitting

Abstract. One of the great challenges in glaciology is the ability to estimate the bulk ice anisotropy in ice sheets and glaciers, which is needed to improve our understanding of ice-sheet dynamics. We investigate the effect of crystal anisotropy on seismic velocities in glacier ice and revisit the framework which is based on fabric eigenvalues to derive approximate seismic velocities by exploiting the assumed symmetry. In contrast to previous studies, we calculate the seismic velocities using the exact c axis angles describing the orientations of the crystal ensemble in an ice-core sample. We apply this approach to fabric data sets from an alpine and a polar ice core. Our results provide a quantitative evaluation of the earlier approximative eigenvalue framework. For near-vertical incidence our results differ by up to 135 m s−1 for P-wave and 200 m s−1 for S-wave velocity compared to the earlier framework (estimated 1 % difference in average P-wave velocity at the bedrock for the short alpine ice core). We quantify the influence of shear-wave splitting at the bedrock as 45 m s−1 for the alpine ice core and 59 m s−1 for the polar ice core. At non-vertical incidence we obtain differences of up to 185 m s−1 for P-wave and 280 m s−1 for S-wave velocities. Additionally, our findings highlight the variation in seismic velocity at non-vertical incidence as a function of the horizontal azimuth of the seismic plane, which can be significant for non-symmetric orientation distributions and results in a strong azimuth-dependent shear-wave splitting of max. 281 m s−1 at some depths. For a given incidence angle and depth we estimated changes in phase velocity of almost 200 m s−1 for P wave and more than 200 m s−1 for S wave and shear-wave splitting under a rotating seismic plane. We assess for the first time the change in seismic anisotropy that can be expected on a short spatial (vertical) scale in a glacier due to strong variability in crystal-orientation fabric (±50 m s−1 per 10 cm). Our investigation of seismic anisotropy based on ice-core data contributes to advancing the interpretation of seismic data, with respect to extracting bulk information about crystal anisotropy, without having to drill an ice core and with special regard to future applications employing ultrasonic sounding.

Seismic vertical transversely isotropic parameter inversion from P- and S-wave cross-borehole measurements in an aquifer environment

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. D101-D116
Author(s):  
Julius K. von Ketelhodt ◽  
Musa S. D. Manzi ◽  
Raymond J. Durrheim ◽  
Thomas Fechner
Keyword(s):  
Transversely Isotropic ◽  
P Wave ◽  
Perturbation Equation ◽  
S Wave ◽  
P Waves ◽  
Data Set ◽  
Near Surface ◽  
S Waves ◽  
Wave Measurements ◽  
Wave Splitting

Joint P- and S-wave measurements for tomographic cross-borehole analysis can offer more reliable interpretational insight concerning lithologic and geotechnical parameter variations compared with P-wave measurements on their own. However, anisotropy can have a large influence on S-wave measurements, with the S-wave splitting into two modes. We have developed an inversion for parameters of transversely isotropic with a vertical symmetry axis (VTI) media. Our inversion is based on the traveltime perturbation equation, using cross-gradient constraints to ensure structural similarity for the resulting VTI parameters. We first determine the inversion on a synthetic data set consisting of P-waves and vertically and horizontally polarized S-waves. Subsequently, we evaluate inversion results for a data set comprising jointly measured P-waves and vertically and horizontally polarized S-waves that were acquired in a near-surface ([Formula: see text]) aquifer environment (the Safira research site, Germany). The inverted models indicate that the anisotropy parameters [Formula: see text] and [Formula: see text] are close to zero, with no P-wave anisotropy present. A high [Formula: see text] ratio of up to nine causes considerable SV-wave anisotropy despite the low magnitudes for [Formula: see text] and [Formula: see text]. The SH-wave anisotropy parameter [Formula: see text] is estimated to be between 0.05 and 0.15 in the clay and lignite seams. The S-wave splitting is confirmed by polarization analysis prior to the inversion. The results suggest that S-wave anisotropy may be more severe than P-wave anisotropy in near-surface environments and should be taken into account when interpreting cross-borehole S-wave data.

Premonitory seismic-wave phenomena before earthquakes near Fairview Peak, Nevada

1975 ◽  
Vol 65 (2) ◽  
pp. 425-437 ◽  
Author(s):  
Indra N. Gupta
Keyword(s):  
Vertical Component ◽  
Temporal Variations ◽  
Stress Axis ◽  
Wave Form ◽  
S Wave ◽  
Upward Migration ◽  
Compression Direction ◽  
Wave Splitting ◽  
First Motion ◽  
Precursory Phenomena

abstract Anomalous variations in three different seismic processes have been observed before an earthquake of magnitude 4 on May 14, 1971 in the Fairview Peak region of central Nevada. The data used are the three-component seismograms from Tonopah (TNP) and Battle Mountain (BMN) as well as the vertical-component seismograms from several other seismographic stations. The observed precursory phenomena are (1) reorientation of the compressive stress axis: evidence for this is based on clear reversals of first motion of Pg at certain stations together with reversal of wave form of the SV component of Sg at BMN; (2) vertical migration of hypocenters: the PmP phase is often distinctly observed in central Nevada and the observed temporal variations in t(PmP)−t(Pg) at TNP indicate generally upward migration of foci before the main event; (3) changes in the extent of S-wave splitting: a large precursory increase is observed along the tensile stress direction and a small premonitory decrease along the compression direction. Similar but unidentical results have been obtained before another earthquake of magnitude 4 whereas all events of magnitude 3.5 or larger have been preceded by anomalous S-wave splitting along the tension direction. The various observed pre-earthquake processes appear to be interrelated and may be explained in terms of recent laboratory and theoretical results when applied to the tectonics of central Nevada. It seems highly desirable to attempt simultaneous observations of anomalous changes in more than one seismic process.

High-resolution passive seismic tomography for 3D velocity, Poisson’s ratio ν, and P-wave quality QP in the Delvina hydrocarbon field, southern Albania

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. B89-B112 ◽  
Author(s):  
G-Akis Tselentis ◽  
Nikolaos Martakis ◽  
Paraskevas Paraskevopoulos ◽  
Athanasios Lois
Keyword(s):  
Wave Velocity ◽  
Seismic Tomography ◽  
Oil Field ◽  
P Wave ◽  
S Wave ◽  
Gas Field ◽  
Data Set ◽  
Geophysical Surveys ◽  
Passive Seismic ◽  
Hydrocarbon Field

We have studied using traveltimes of P- and S-waves and initial seismic-pulse rise-time measurements from natural microearthquakes to derive 3D P-wave velocity VP information (mostly structural) as well as P- and S-wave velocity VP/VS and P-wave quality factor QP information (mostly lithologic) in a known hydrocarbon field in southern Albania. During a 12-month monitoring period, 1860 microearthquakes were located at a 50-station seismic network and were used to obtain the above parameters. The data set included earthquakes with magnitudes ranging from –0.1 to 3.0 R (Richter scale) and focal depths typically occurring between 2 and 10 km. Kohonen neural networks were implemented to facilitate the lithological classification of the passive seismic tomography (PST) results. The obtained results, which agreed with data from nearby wells, helped delineate the structure of the reservoir. Two subregions of the investigated area, one corresponding to an oil field and one to a gas field, were correlated with the PST results. This experiment showed that PST is a powerful new geophysical technique for exploring regions that present seismic penetration problems, difficult topographies, and complicated geologies, such as thrust-belt regions. The method is economical and environmentally friendly, and it can be used to investigate very large regions for the optimal design of planned 2D or 3D conventional geophysical surveys.

Shear‐wave velocity and density estimation from PS-wave AVO analysis: Application to an OBS dataset from the North Sea

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1446-1454 ◽  
Author(s):  
Side Jin ◽  
G. Cambois ◽  
C. Vuillermoz
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Random Noise ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Avo Analysis ◽  
The North ◽  
Avo Inversion ◽  
The North Sea

S-wave velocity and density information is crucial for hydrocarbon detection, because they help in the discrimination of pore filling fluids. Unfortunately, these two parameters cannot be accurately resolved from conventional P-wave marine data. Recent developments in ocean‐bottom seismic (OBS) technology make it possible to acquire high quality S-wave data in marine environments. The use of (S)-waves for amplitude variation with offset (AVO) analysis can give better estimates of S-wave velocity and density contrasts. Like P-wave AVO, S-wave AVO is sensitive to various types of noise. We investigate numerically and analytically the sensitivity of AVO inversion to random noise and errors in angles of incidence. Synthetic examples show that random noise and angle errors can strongly bias the parameter estimation. The use of singular value decomposition offers a simple stabilization scheme to solve for the elastic parameters. The AVO inversion is applied to an OBS data set from the North Sea. Special prestack processing techniques are required for the success of S-wave AVO inversion. The derived S-wave velocity and density contrasts help in detecting the fluid contacts and delineating the extent of the reservoir sand.

Nodal Seismograph Recordings of the 2019 Ridgecrest Earthquake Sequence

2020 ◽  
Vol 91 (6) ◽  
pp. 3622-3633
Author(s):  
Rufus D. Catchings ◽  
Mark R. Goldman ◽  
Jamison H. Steidl ◽  
Joanne H. Chan ◽  
Amir A. Allam ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Large Volume ◽  
Ambient Noise ◽  
Temporal Variations ◽  
Earthquake Sequence ◽  
S Wave ◽  
Data Set ◽  
Fault Structure ◽  
Nodal Data ◽  
Dense Arrays

Abstract The 2019 Ridgecrest, California, earthquake sequence included Mw 6.4 and 7.1 earthquakes that occurred on successive days beginning on 4 July 2019. These two largest earthquakes of the sequence occurred on orthogonal faults that ruptured the Earth’s surface. To better evaluate the 3D subsurface fault structure, (P- and S-wave) velocity, 3D and temporal variations in seismicity, and other important aspects of the earthquake sequence, we recorded aftershocks and ambient noise using up to 461 three-component nodal seismographs for about two months, beginning about one day after the Mw 7.1 mainshock. The ∼30,000Mw≥1 earthquakes that were recorded on the dense arrays provide an unusually large volume of data with which to evaluate the earthquake sequence. This report describes the recording arrays and is intended to provide metadata for researchers interested in evaluating various aspects of the 2019 Ridgecrest earthquake sequence using the nodal data set.

Near-surface scattering phenomena and implications for tunnel detection

2015 ◽  
Vol 3 (1) ◽  
pp. SF43-SF54 ◽  
Author(s):  
Shelby L. Peterie ◽  
Richard D. Miller
Keyword(s):  
Synthetic Data ◽  
P Wave ◽  
S Wave ◽  
Seismic Line ◽  
Data Set ◽  
Near Surface ◽  
Tunnel Detection ◽  
Impedance Contrast ◽  
Diffraction Imaging ◽  
Imaging Algorithms

Tunnel locations are accurately interpreted from diffraction sections of focused mode converted P- to S-wave diffractions from a perpendicular tunnel and P-wave diffractions from a nonperpendicular (oblique) tunnel. Near-surface tunnels are ideal candidates for diffraction imaging due to their small size relative to the seismic wavelength and large acoustic impedance contrast at the tunnel interface. Diffraction imaging algorithms generally assume that the velocities of the primary wave and the diffracted wave are approximately equal, and that the diffraction apex is recorded directly above the scatterpoint. Scattering phenomena from shallow tunnels with kinematic properties that violate these assumptions were observed in one field data set and one synthetic data set. We developed the traveltime equations for mode-converted and oblique diffractions and demonstrated a diffraction imaging algorithm designed for the roll-along style of acquisition. Potential processing and interpretation pitfalls specific to these diffraction types were identified. Based on our observations, recommendations were made to recognize and image mode-converted and oblique diffractions and accurately interpret tunnel depth, horizontal location, and azimuth with respect to the seismic line.

Amplitude-based misfit functions in viscoelastic full-waveform inversion applied to walk-away vertical seismic profile data

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. B335-B351 ◽  
Author(s):  
Wenyong Pan ◽  
Kristopher A. Innanen
Keyword(s):  
Amplitude Ratio ◽  
Waveform Inversion ◽  
Seismic Profile ◽  
P Wave ◽  
Western Canada ◽  
Full Waveform Inversion ◽  
Walk Away ◽  
Profile Data ◽  
S Wave ◽  
Full Waveform

Viscoelastic full-waveform inversion is applied to walk-away vertical seismic profile data acquired at a producing heavy-oil field in Western Canada for the determination of subsurface velocity models (P-wave velocity [Formula: see text] and S-wave velocity [Formula: see text]) and attenuation models (P-wave quality factor [Formula: see text] and S-wave quality factor [Formula: see text]). To mitigate strong velocity-attenuation trade-offs, a two-stage approach is adopted. In Stage I, [Formula: see text] and [Formula: see text] models are first inverted using a standard waveform-difference (WD) misfit function. Following this, in Stage II, different amplitude-based misfit functions are used to estimate the [Formula: see text] and [Formula: see text] models. Compared to the traditional WD misfit function, the amplitude-based misfit functions exhibit stronger sensitivity to attenuation anomalies and appear to be able to invert [Formula: see text] and [Formula: see text] models more reliably in the presence of velocity errors. Overall, the root-mean-square amplitude-ratio and spectral amplitude-ratio misfit functions outperform other misfit function choices. In the final outputs of our inversion, significant drops in the [Formula: see text] to [Formula: see text] ratio (~1.6) and Poisson’s ratio (~0.23) are apparent within the Clearwater Formation (depth ~0.45–0.50 km) of the Mannville Group in the Western Canada Sedimentary Basin. Strong [Formula: see text] (~20) and [Formula: see text] (~15) anomalies are also evident in this zone. These observations provide information to help identify the target attenuative reservoir saturated with heavy-oil resources.

Real-time monitoring of seismic moment and radiated energy

2020 ◽  
Author(s):  
Davide Scafidi ◽  
Daniele Spallarossa ◽  
Matteo Picozzi ◽  
Dino Bindi
Keyword(s):  
Real Time ◽  
Seismic Moment ◽  
P Wave ◽  
Calibration Data ◽  
S Wave ◽  
Data Set ◽  
Local Networks ◽  
Radiated Energy ◽  
The Impact ◽  
Large Earthquakes

&lt;p&gt;Understanding the dynamics of faulting is a crucial target in earthquake source physics (Yoo et al., 2010). To study earthquake dynamics it is indeed necessary to look at the source complexity from different perspectives; in this regard, useful information is provided by the seismic moment (M0), which is a static measure of the earthquake size, and the seismic radiated energy (ER), which is connected to the rupture kinematics and dynamics (e.g. Bormann &amp; Di Giacomo 2011a). Studying spatial and temporal evolution of scaling relations between scaled energy (i.e., e = ER/M0) versus the static measure of source dimension (M0) can provide valuable indications for understanding the earthquake generation processes, single out precursors of stress concentrations, foreshocks and the nucleation of large earthquakes (Picozzi et al., 2019). In the last ten years, seismology has undergone a terrific development. Evolution in data telemetry opened the new research field of real-time seismology (Kanamori 2005), which targets are the rapid determination of earthquake location and size, the timely implementation of emergency plans and, under favourable conditions, earthquake early warning. On the other hand, the availability of denser and high quality seismic networks deployed near faults made possible to observe very large numbers of micro-to-small earthquakes, which is pushing the seismological community to look for novel big data analysis strategies. Large earthquakes in Italy have the peculiar characteristic of being followed within seconds to months by large aftershocks of magnitude similar to the initial quake or even larger, demonstrating the complexity of the Apennines&amp;#8217; faults system (Gentili and Giovanbattista, 2017). Picozzi et al. (2017) estimated the radiated seismic energy and seismic moment from P-wave signals for almost forty earthquakes with the largest magnitude of the 2016-2017 Central Italy seismic sequence. Focusing on S-wave signals recorded by local networks, Bindi et al. (2018) analysed more than 1400 earthquakes in the magnitude ranges 2.5 &amp;#8804; Mw &amp;#8804; 6.5 of the same region occurred from 2008 to 2017 and estimated both ER and M0, from which were derived the energy magnitude (Me) and Mw for investigating the impact of different magnitude scales on the aleatory variability associated with ground motion prediction equations. In this work, exploiting first steps made in this direction by Picozzi et al. (2017) and Bindi et al. (2018), we derived a novel approach for the real-time, robust estimation of seismic moment and radiated energy of small to large magnitude earthquakes recorded at local scales. In the first part of the work, we describe the procedure for extracting from the S-wave signals robust estimates of the peak displacement (PDS) and the cumulative squared velocity (IV2S). Then, exploiting a calibration data set of about 6000 earthquakes for which well-constrained M0 and theoretical ER values were available, we describe the calibration of empirical attenuation models. The coefficients and parameters obtained by calibration were then used for determining ER and M0 of a testing dataset&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document