Time-reverse imaging with limited S-wave velocity model information

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. MA33-MA40 ◽  
Author(s):  
Brian Steiner ◽  
Erik H. Saenger ◽  
Stefan M. Schmalholz
Keyword(s):  
Energy Density ◽  
Wave Velocity ◽  
Wave Energy ◽  
Velocity Model ◽  
Body Waves ◽  
P Wave ◽  
S Wave ◽  
Velocity Models ◽  
Wave Energy Density ◽  
Wavefield Extrapolation

Time-reverse imaging is a wave propagation algorithm for locating sources. Signals recorded by synchronized receivers are reversed in time and propagated back to the source location by elastic wavefield extrapolation. Elastic wavefield extrapolation requires a P-wave as well as an S-wave velocity model. The velocity models available from standard reflection seismic methods are usually restricted to only P-waves. In this study, we use synthetically produced time signals to investigate the accuracy of seismic source localization by means of time-reverse imaging with the correct P-wave and a perturbed S-wave velocity model. The studies reveal that perturbed S-wave velocity models strongly influence the intensity and position of the focus. Imaging the results with the individual maximum energy density for both body wave types instead of mixed modes allows individual analysis of the two body waves. P-wave energy density images render stable focuses in case of a correct P-wave and incorrect S-wave velocity model. Thus, P-wave energy density seems to be a more suitable imaging condition in case of a high degree of uncertainty in the S-wave velocity model.

Elastic reflection waveform inversion based on the decomposition of sensitivity kernels

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. R235-R250 ◽  
Author(s):  
Zhiming Ren ◽  
Zhenchun Li ◽  
Bingluo Gu
Keyword(s):  
Wave Velocity ◽  
Waveform Inversion ◽  
Velocity Model ◽  
P Wave ◽  
Background Model ◽  
Reverse Time ◽  
S Wave ◽  
Velocity Models ◽  
Time Migration ◽  
Starting Model

Full-waveform inversion (FWI) has the potential to obtain an accurate velocity model. Nevertheless, it depends strongly on the low-frequency data and the initial model. When the starting model is far from the real model, FWI tends to converge to a local minimum. Based on a scale separation of the model (into the background model and reflectivity model), reflection waveform inversion (RWI) can separate out the tomography term in the conventional FWI kernel and invert for the long-wavelength components of the velocity model by smearing the reflected wave residuals along the transmission (or “rabbit-ear”) paths. We have developed a new elastic RWI method to build the P- and S-wave velocity macromodels. Our method exploits a traveltime-based misfit function to highlight the contribution of tomography terms in the sensitivity kernels and a sensitivity kernel decomposition scheme based on the P- and S-wave separation to suppress the high-wavenumber artifacts caused by the crosstalk of different wave modes. Numerical examples reveal that the gradients of the background models become sufficiently smooth owing to the decomposition of sensitivity kernels and the traveltime-based misfit function. We implement our elastic RWI in an alternating way. At each loop, the reflectivity model is generated by elastic least-squares reverse time migration, and then the background model is updated using the separated traveltime kernels. Our RWI method has been successfully applied in synthetic and real reflection seismic data. Inversion results demonstrate that the proposed method can retrieve preferable low-wavenumber components of the P- and S-wave velocity models, which are reliable to serve as a starting model for conventional elastic FWI. Also, our method with a two-stage inversion workflow, first updating the P-wave velocity using the PP kernels and then updating the S-wave velocity using the PS kernels, is feasible and robust even when P- and S-wave velocities have different structures.

Computing near-surface velocity models for S-wave static corrections using raypath interferometry

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. U23-U34
Author(s):  
Raul Cova ◽  
David Henley ◽  
Kristopher A. Innanen
Keyword(s):  
Wave Velocity ◽  
Velocity Model ◽  
P Wave ◽  
Surface Velocity ◽  
S Wave ◽  
Converted Wave ◽  
Near Surface ◽  
Velocity Models ◽  
Consistent Solution ◽  
Static Corrections

A near-surface velocity model is one of the typical products generated when computing static corrections, particularly in the processing of PP data. Critically refracted waves are the input usually needed for this process. In addition, for the converted PS mode, S-wave near-surface corrections must be applied at the receiver locations. In this case, however, critically refracted S-waves are difficult to identify when using P-wave energy sources. We use the [Formula: see text]-[Formula: see text] representation of the converted-wave data to capture the intercept-time differences between receiver locations. These [Formula: see text]-differences are then used in the inversion of a near-surface S-wave velocity model. Our processing workflow provides not only a set of raypath-dependent S-wave static corrections, but also a velocity model that is based on those corrections. Our computed near-surface S-wave velocity model can be used for building migration velocity models or to initialize elastic full-waveform inversions. Our tests on synthetic and field data provided superior results to those obtained by using a surface-consistent solution.

scholarly journals The Local Earthquake Tomography of Erzurum (Turkey) Geothermal Area

2019 ◽  
Vol 23 (3) ◽  
pp. 209-223 ◽  
Author(s):  
Caglar Ozer ◽  
Mehmet Ozyazicioglu
Keyword(s):  
Wave Velocity ◽  
Seismic Velocity ◽  
Three Dimensional ◽  
P Wave ◽  
Geothermal Area ◽  
S Wave ◽  
Velocity Models ◽  
Local Earthquake Tomography ◽  
P Wave Velocity ◽  
Local Earthquake

Erzurum and its surroundings are one of the seismically active and hydrothermal areas in the Eastern part of Turkey. This study is the first approach to characterize the crust by seismic features by using the local earthquake tomography method. The earthquake source location and the three dimensional seismic velocity structures are solved simultaneously by an iterative tomographic algorithm, LOTOS-12. Data from a combined permanent network comprising comprises of 59 seismometers which was installed by Ataturk University-Earthquake Research Center and Earthquake Department of the Disaster and Emergency Management Authority  to monitor the seismic activity in the Eastern Anatolia, In this paper, three-dimensional Vp and Vp/Vs characteristics of Erzurum geothermal area were investigated down to 30 km by using 1685 well-located earthquakes with 29.894 arrival times, consisting of 17.298 P- wave and 12.596 S- wave arrivals. We develop new high-resolution depth-cross sections through Erzurum and its surroundings to provide the subsurface geological structure of seismogenic layers and geothermal areas. We applied various size horizontal and vertical checkerboard resolution tests to determine the quality of our inversion process. The basin models are traceable down to 3 km depth, in terms of P-wave velocity models. The higher P-wave velocity areas in surface layers are related to the metamorphic and magmatic compact materials. We report that the low Vp and high Vp/Vs values are observed in Yedisu, Kaynarpinar, Askale, Cimenozu, Kaplica, Ovacik, Yigitler, E part of Icmeler, Koprukoy, Uzunahmet, Budakli, Soylemez, Koprukoy, Gunduzu, Karayazi, Icmesu, E part of Horasan and Kaynak regions indicated geothermal reservoir.

scholarly journals The potential of seismic cross-hole tomography for geotechnical site investigation

2019 ◽  
Vol 92 ◽  
pp. 18006
Author(s):  
Yannick Choy Hing Ng ◽  
William Danovan ◽  
Taeseo Ku
Keyword(s):  
Wave Velocity ◽  
Site Investigation ◽  
Velocity Model ◽  
P Wave ◽  
Reconstruction Technique ◽  
Sufficient Information ◽  
Eastern Region ◽  
S Wave ◽  
Near Surface ◽  
Soil Layers

Seismic cross-hole tomography has been commonly used in oil and gas exploration and the mining industry for the detection of precious resources. For near-surface geotechnical site investigation, this geophysical method is relatively new and can be used to supplement traditional methods such as the standard penetration test, coring and sampling, thus improving the effectiveness of site characterization. This paper presents a case study which was carried out on a reclaimed land in the Eastern region of Singapore. A seismic cross-hole test was performed by generating both compressional waves and shear waves into the ground. The signals were interpreted by using first-arrival travel time wave tomography and the arrival times were subsequently inverted using Simultaneous Iterative Reconstruction Technique (SIRT). A comparison with the borehole logging data indicated that P-wave velocity model cannot provide sufficient information about the soil layers, especially when the ground water table is near the surface. The S-wave velocity model seemed to agree quite well with the variation in the SPT-N value and could identify to a certain extent the interface between the different soil layers. Finally, P-wave and S-wave velocities are used to compute the Poisson's ratio distribution which gave a good indication of the degree of saturation of the soil.

Guidelines for building a detailed elastic depth model

Geophysics ◽  
2000 ◽  
Vol 65 (1) ◽  
pp. 35-45
Author(s):  
Jarrod C. Dunne ◽  
Greg Beresford ◽  
Brian L. N Kennett
Keyword(s):  
Wave Velocity ◽  
Mode Conversion ◽  
Poisson Ratio ◽  
Velocity Model ◽  
P Wave ◽  
Time Interval ◽  
S Wave ◽  
Sea Floor ◽  
P Wave Velocity ◽  
Inelastic Attenuation

We developed guidelines for building a detailed elastic depth model by using an elastic synthetic seismogram that matched both prestack and stacked marine seismic data from the Gippsland Basin (Australia). Recomputing this synthetic for systematic variations upon the depth model provided insight into how each part of the model affected the synthetic. This led to the identification of parameters in the depth model that have only a minor influence upon the synthetic and suggested methods for estimating the parameters that are important. The depth coverage of the logging run is of prime importance because highly reflective layering in the overburden can generate noise events that interfere with deeper events. A depth sampling interval of 1 m for the P-wave velocity model is a useful lower limit for modeling the transmission response and thus maintaining accuracy in the tie over a large time interval. The sea‐floor model has a strong influence on mode conversion and surface multiples and can be built using a checkshot survey or by testing different trend curves. When an S-wave velocity log is unavailable, it can be replaced using the P-wave velocity model and estimates of the Poisson ratio for each significant geological formation. Missing densities can be replaced using Gardner’s equation, although separate substitutions are required for layers known to have exceptionally high or low densities. Linear events in the elastic synthetic are sensitive to the choice of inelastic attenuation values in the water layer and sea‐floor sediments, while a simple inelastic attenuation model for the consolidated sediments is often adequate. The usefulness of a 1-D depth model is limited by misties resulting from complex 3-D structures and the validity of the measurements obtained in the logging run. The importance of such mis‐ties can be judged, and allowed for in an interpretation, by recomputing the elastic synthetic after perturbing the depth model to simulate the key uncertainties. Taking the next step beyond using simplistic modeling techniques requires extra effort to achieve a satisfactory tie to each part of a prestack seismic record. This is rewarded by the greater confidence that can then be held in the stacked synthetic tie and applications such as noise identification, data processing benchmarking, AVO analysis, and inversion.

Mode Conversion Technique Employed in Shear Wave Velocity Studies of Rock Samples Under Axial and Uniform Compression

1967 ◽  
Vol 7 (02) ◽  
pp. 136-148 ◽  
Author(s):  
A.R. Gregory
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Wave Energy ◽  
Pressure Range ◽  
Mode Conversion ◽  
P Wave ◽  
S Wave ◽  
Rock Samples ◽  
Mode Converters

Abstract A shear wave velocity laboratory apparatus and techniques for testing rock samples under simulated subsurface conditions have been developed. In the apparatus, two electromechanical transducers operating in the frequency range 0.5 to 5.0 megahertz (MHz: megacycles per second) are mounted in contact with each end of the sample. Liquid-solid interfaces of Drakeol-aluminum are used as mode converters. In the generator transducer, there is total mode conversion from P-wave energy to plain S-wave energy, S-wave energy is converted back to P-wave energy in the motor transducer. Similar transducers without mode converters are used to measure P-wave velocities. The apparatus is designed for testing rock samples under axial or uniform loading in the pressure range 0 to 12,000 psi. The transducers have certain advantages over those used by King,1 and the measurement techniques are influenced less by subjective elements than other methods previously reported. An electronic counter-timer having a resolution of 10 nanoseconds measures the transit time of ultrasonic pulses through the sample; elastic wave velocities of most homogeneous materials can be measured with errors of less than 1 percent. S- and P-wave velocity measurements on Bandera sandstone and Solenhofen limestone are reported for the axial pressure range 0 to 6,000 psi and for the uniform pressure range 0 to 10,000 psi. The influence of liquid pore saturants on P- and S-wave velocity is investigated and found to be in broad agreement with Biot's theory. In specific areas, the measurements do not conform to theory. Velocities of samples measured under axial and uniform loading are compared and, in general, velocities measured under uniform stress are higher than those measured under axial stress. Liquid pore fluids cause increases in Poisson's ratio and the bulk modulus but reduce the rigidity modulus, Young's modulus and the bulk compressibility. INTRODUCTION Ultrasonic pulse methods for measuring the shear wave velocity of rock samples in the laboratory have been gradually improved during the last few years. Early experimental pulse techniques reported by Hughes et al.2, and by Gregory3 were beset by uncertainties in determining the first arrival of the shear wave (S-wave) energy. Much of this ambiguity was caused by the multiple modes propagated by piezoelectric crystals and by boundary conversions in the rock specimens. Shear wave velocity data obtained from the critical angle method, described by Schneider and Burton4 and used later by King and Fatt5 and by Gregory,3,6 are of limited accuracy, and interpreting results is too complicated for routine laboratory work. The mode conversion method described by Jamieson and Hoskins7 was recently used by King1 for measuring the S-wave velocities of dry and liquid-saturated rock samples. Glass-air interfaces acted as mode converters in the apparatus, and much of the compressional (P-wave) energy apparently was eliminated from the desired pure shear mode. A more detailed discussion of the current status of laboratory pulse methods applied to geological specimens is given in a review by Simmons.8

scholarly journals Hypocenter Determination of Volcano-Tectonic (VT) Earthquake around Agung Volcano in Period October-December 2017 Using a Non-Linear Location Method: A Preliminary Result

2021 ◽  
Vol 873 (1) ◽  
pp. 012098
Author(s):  
P P Rahsetyo ◽  
D P Sahara ◽  
A D Nugraha ◽  
D K Syahbana ◽  
Zulfakriza ◽  
...  
Keyword(s):  
Volcanic Eruptions ◽  
Velocity Model ◽  
P Wave ◽  
Significant Activity ◽  
S Wave ◽  
Location Method ◽  
Hypocenter Determination ◽  
Velocity Models ◽  
Central Java ◽  
Non Linear

Abstract Agung is one of active volcanoes in Indonesia, located on island of Bali. Since 1963, Agung has not had significant activity, until in September 2017 the volcano was active again which was marked by increased seismic activity and eruptions in November 2017. Therefore, to analyze the dynamics and processes of active volcanic eruptions requires an understanding of the structure of the volcano, especially the position of the magma reservoir and its path. The depiction of the structure of this volcano can be analyzed by determining the location of the earthquake due to volcanic activity, especially Volcano-Tectonic (VT) earthquake. In this study, we determined the location of the hypocenter around the Agung using the non-linear location method. VT earthquakes have similar characteristics to tectonic earthquakes so this method can be used to determine the initial hypocenter. The data used in this study came from 8 PVMBG seismographs from October to December 2017. We manually picking arrival time of P- and S-waves from the 3948 VT events found. Pair of P and S wave phases with 18741 P-wave phases and 17237 S-wave phases, plotted in a wadati diagram resulting in a vp/vs ratio of 1.7117. We use 1D velocity models derived from Koulakov with the assumption that the geology of the study area is not much different from the volcanoes in Central Java. The resulting hypocenter distribution shows a very random location and has uncertain X, Y, and Z directions from a range of 0 to 91 km. This study limits this uncertainty to 5 km resulting in a more reliable earthquakes distribution of 3050 events. The results indicate 2 clustered events, a swarm of VT events that occur every month at a depth of 8 to 15 km and there are 2 paths that lead to the top of Agung and SW of that swarm. These preliminary results will be used to update 1D velocity model and relocate the events beneath Agung region for further studies.

Elastic reflection traveltime inversion with decoupled wave equation

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. R463-R474 ◽  
Author(s):  
Guanchao Wang ◽  
Shangxu Wang ◽  
Jianyong Song ◽  
Chunhui Dong ◽  
Mingqiang Zhang
Keyword(s):  
Wave Equation ◽  
Wave Velocity ◽  
Waveform Inversion ◽  
P Wave ◽  
Model Parameters ◽  
Local Minima ◽  
S Wave ◽  
Traveltime Inversion ◽  
Velocity Models ◽  
Elastic Reflection

Elastic full-waveform inversion (FWI) updates high-resolution model parameters by minimizing the residuals of multicomponent seismic records between the field and model data. FWI suffers from the potential to converge to local minima and more serious nonlinearity than acoustic FWI mainly due to the absence of low frequencies in seismograms and the extended model domain (P- and S-velocities). Reflection waveform inversion can relax the nonlinearity by relying on the tomographic components, which can be used to update the low-wavenumber components of the model. Hence, we have developed an elastic reflection traveltime inversion (ERTI) approach to update the low-wavenumber component of the velocity models for the P- and S-waves. In our ERTI algorithm, we took the P- and S-wave impedance perturbations as elastic reflectivity to generate reflections and a weighted crosscorrelation as the misfit function. Moreover, considering the higher wavenumbers (lower velocity value) of the S-wave velocity compared with the P-wave case, optimizing the low-wavenumber components for the S-wave velocity is even more crucial in preventing the elastic FWI from converging to local minima. We have evaluated an equivalent decoupled velocity-stress wave equation to ERTI to reduce the coupling effects of different wave modes and to improve the inversion result of ERTI, especially for the S-wave velocity. The subsequent application on the Sigsbee2A model demonstrates that our ERTI method with the decoupled wave equation can efficiently update the low-wavenumber parts of the model and improve the precision of the S-wave velocity.

Full-waveform matching of VP and VS models from surface waves

2019 ◽  
Vol 218 (3) ◽  
pp. 1873-1891 ◽  
Author(s):  
Farbod Khosro Anjom ◽  
Daniela Teodor ◽  
Cesare Comina ◽  
Romain Brossier ◽  
Jean Virieux ◽  
...  
Keyword(s):  
Surface Waves ◽  
Wave Velocity ◽  
Real Data ◽  
Test Site ◽  
P Wave ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Data Set ◽  
Near Surface ◽  
Velocity Models

SUMMARY The analysis of surface wave dispersion curves (DCs) is widely used for near-surface S-wave velocity (VS) reconstruction. However, a comprehensive characterization of the near-surface requires also the estimation of P-wave velocity (VP). We focus on the estimation of both VS and VP models from surface waves using a direct data transform approach. We estimate a relationship between the wavelength of the fundamental mode of surface waves and the investigation depth and we use it to directly transform the DCs into VS and VP models in laterally varying sites. We apply the workflow to a real data set acquired on a known test site. The accuracy of such reconstruction is validated by a waveform comparison between field data and synthetic data obtained by performing elastic numerical simulations on the estimated VP and VS models. The uncertainties on the estimated velocity models are also computed.

PS Energy Imaging Condition for Microseismic Data - Part 1: Theory and Applications in 3D Isotropic Media

Geophysics ◽  
2020 ◽  
pp. 1-79
Author(s):  
Can Oren ◽  
Jeffrey Shragge
Keyword(s):  
Wave Velocity ◽  
Model Building ◽  
Velocity Model ◽  
Microseismic Monitoring ◽  
Elastic Model ◽  
S Wave ◽  
Imaging Condition ◽  
Velocity Models ◽  
Monitoring Programs ◽  
Imaging Conditions

Accurately estimating event locations is of significant importance in microseismic investigations because this information greatly contributes to the overall success of hydraulic fracturing monitoring programs. Full-wavefield time-reverse imaging (TRI) using one or more wave-equation imaging conditions offers an effective methodology for locating surface-recorded microseismic events. To be most beneficial in microseismic monitoring programs, though, the TRI procedure requires using accurate subsurface models that account for elastic media effects. We develop a novel microseismic (extended) PS energy imaging condition that explicitly incorporates the stiffness tensor and exhibits heightened sensitivity to isotropic elastic model perturbations compared to existing imaging conditions. Numerical experiments demonstrate the sensitivity of microseismic TRI results to perturbations in P- and S-wave velocity models. Zero-lag and extended microseismic source images computed at selected subsurface locations yields useful information about 3D P- and S-wave velocity model accuracy. Thus, we assert that these image volumes potentially can serve as the input into microseismic elastic velocity model building algorithms.

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