High-Resolution 3D P-Wave Velocity Model for the East Ventura-San Fernando Basin, California, and Relocation of Events in the Northridge and San Fernando Aftershock Sequences

2006 ◽  
Vol 96 (6) ◽  
pp. 2269-2280 ◽  
Author(s):  
J. Pujol ◽  
K. Mueller ◽  
P. Shen ◽  
V. Chitupolu
Keyword(s):  
High Resolution ◽  
Wave Velocity ◽  
Velocity Model ◽  
P Wave ◽  
P Wave Velocity ◽  
Aftershock Sequences ◽  
San Fernando

Reconnaissance seismic refraction-reflection surveys in northwestern New Mexico

1984 ◽  
Vol 74 (4) ◽  
pp. 1263-1274
Author(s):  
Lawrence H. Jaksha ◽  
David H. Evans
Keyword(s):  
New Mexico ◽  
Wave Velocity ◽  
Lower Crust ◽  
Seismic Waves ◽  
Seismic Refraction ◽  
Velocity Model ◽  
P Wave ◽  
Uppermost Mantle ◽  
P Wave Velocity ◽  
Crustal Thinning

Abstract A velocity model of the crust in northwestern New Mexico has been constructed from an interpretation of direct, refracted, and reflected seismic waves. The model suggests a sedimentary section about 3 km thick with an average P-wave velocity of 3.6 km/sec. The crystalline upper crust is 28 km thick and has a P-wave velocity of 6.1 km/sec. The lower crust below the Conrad discontinuity has an average P-wave velocity of about 7.0 km/sec and a thickness near 17 km. Some evidence suggests that velocity in both the upper and lower crust increases with depth. The P-wave velocity in the uppermost mantle is 7.95 ± 0.15 km/sec. The total crustal thickness near Farmington, New Mexico, is about 48 km (datum = 1.6 km above sea level), and there is evidence for crustal thinning to the southeast.

scholarly journals P-wave velocity and density structure beneath Mt. Vesuvius: a magma body in the upper edifice?

2013 ◽  
Vol 56 (4) ◽  
Author(s):  
Paolo Capuano ◽  
Guido Russo ◽  
Roberto Scarpa
Keyword(s):  
High Resolution ◽  
Wave Velocity ◽  
Gravity Data ◽  
High Energy ◽  
P Wave ◽  
Gravity Inversion ◽  
Density Structure ◽  
Resolution Image ◽  
High Resolution Image ◽  
P Wave Velocity

<p>A high-resolution image of the compressional wave velocity and density structure in the shallow edifice of Mount Vesuvius has been derived from simultaneous inversion of travel times and hypocentral parameters of local earthquakes and from gravity inversion. The robustness of the tomography solution has been improved by adding to the earthquake data a set of land based shots, used for constraining the travel time residuals. The results give a high resolution image of the P-wave velocity structure with details down to 300-500 m. The relocated local seismicity appears to extend down to 5 km depth below the central crater, distributed into two clusters, and separated by an anomalously high Vp region positioned at around 1 km depth. A zone with high Vp/Vs ratio in the upper layers is interpreted as produced by the presence of intense fluid circulation alternatively to the interpretation in terms of a small magma chamber inferred by petrologic studies. In this shallower zone the seismicity has the minimum energy, whilst most of the high-energy quakes (up to Magnitude 3.6) occur in the cluster located at greater depth. The seismicity appears to be located along almost vertical cracks, delimited by a high velocity body located along past intrusive body, corresponding to remnants of Mt. Somma. In this framework a gravity data inversion has been performed to study the shallower part of the volcano. Gravity data have been inverted using a method suitable for the application to scattered data in presence of relevant topography based on a discretization of the investigated medium performed by establishing an approximation of the topography by a triangular mesh. The tomography results, the retrieved density distribution, and the pattern of relocated seismicity exclude the presence of significant shallow magma reservoirs close to the central conduit. These should be located at depth higher than that of the base of the hypocenter volume, as evidenced by previous studies.</p>

Multi-parameter model building for the Qiuyue structure using four-component ocean-bottom seismometer data

Geophysics ◽  
2021 ◽  
pp. 1-52
Author(s):  
Yuzhu Liu ◽  
Xinquan Huang ◽  
Jizhong Yang ◽  
Xueyi Liu ◽  
Bin Li ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Waveform Inversion ◽  
Velocity Model ◽  
P Wave ◽  
Velocity Analysis ◽  
Full Waveform Inversion ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Full Waveform ◽  
P Wave Velocity

Thin sand-mud-coal interbedded layers and multiples caused by shallow water pose great challenges to conventional 3D multi-channel seismic techniques used to detect the deeply buried reservoirs in the Qiuyue field. In 2017, a dense ocean-bottom seismometer (OBS) acquisition program acquired a four-component dataset in East China Sea. To delineate the deep reservoir structures in the Qiuyue field, we applied a full-waveform inversion (FWI) workflow to this dense four-component OBS dataset. After preprocessing, including receiver geometry correction, moveout correction, component rotation, and energy transformation from 3D to 2D, a preconditioned first-arrival traveltime tomography based on an improved scattering integral algorithm is applied to construct an initial P-wave velocity model. To eliminate the influence of the wavelet estimation process, a convolutional-wavefield-based objective function for the preprocessed hydrophone component is used during acoustic FWI. By inverting the waveforms associated with early arrivals, a relatively high-resolution underground P-wave velocity model is obtained, with updates at 2.0 km and 4.7 km depth. Initial S-wave velocity and density models are then constructed based on their prior relationships to the P-wave velocity, accompanied by a reciprocal source-independent elastic full-waveform inversion to refine both velocity models. Compared to a traditional workflow, guided by stacking velocity analysis or migration velocity analysis, and using only the pressure component or other single-component, the workflow presented in this study represents a good approach for inverting the four-component OBS dataset to characterize sub-seafloor velocity structures.

scholarly journals Reference P-wave velocity in coal seams at great depths in Jastrzebie coal mine

2019 ◽  
Vol 133 ◽  
pp. 01011
Author(s):  
Jakub Kokowski ◽  
Zbigniew Szreder ◽  
Elżbieta Pilecka
Keyword(s):  
Wave Velocity ◽  
Coal Mine ◽  
Velocity Model ◽  
P Wave ◽  
Coal Seams ◽  
Data Set ◽  
Seismic Profiling ◽  
Reference Velocity ◽  
P Wave Velocity ◽  
Geological Conditions

In the study, the determining of the reference velocity of the P-wave in coal seams used in seismic profiling to assess increases and decreases in relative stresses at large depths has been presented. The seismic profiling method proposed by Dubinski in 1989 covers a range of depth up to 970 m. At present, coal seams exploitation in Polish coal mines is conducted at greater depths, even exceeding 1200 m, which creates the necessity for a new reference velocity model. The study presents an empirical mathematical model of the change of the P-wave velocity in coal seams in the geological conditions of the Jastrzebie coal mine. A power model analogous to the Dubinski’s one was elaborated with new constants. The calculations included the results from 35 measurements of seismic profiling carried out in various coal seams of the Jastrzebie mine at depths from 640 to 1200 m. The results obtained cause changes in the result of calculations of seismic anomalies. Future validation of the proposed model with larger data set will be required.

High-resolution three-term AVO inversion by means of a Trivariate Cauchy probability distribution

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. R43-R55 ◽  
Author(s):  
Wubshet Alemie ◽  
Mauricio D. Sacchi
Keyword(s):  
High Resolution ◽  
Wave Velocity ◽  
P Wave ◽  
S Wave ◽  
Avo Inversion ◽  
P Wave Velocity ◽  
Multivariate Gaussian ◽  
Density Perturbations ◽  
Gaussian Prior ◽  
Scale Matrix

Three-term AVO inversion can be used to estimate P-wave velocity, S-wave velocity, and density perturbations from reflection seismic data. The density term, however, exhibits little sensitivity to amplitudes and, therefore, its inversion is unstable. One way to stabilize the density term is by including a scale matrix that provides correlation information between the three unknown AVO parameters. We investigate a Bayesian procedure to include sparsity and a scale matrix in the three-term AVO inversion problem. To this end, we model the prior distribution of the AVO parameters via a Trivariate Cauchy distribution. We found an iterative algorithm to solve the Bayesian inversion and, in addition, comparisons are provided with the classical inversion approach that uses a Multivariate Gaussian prior. It is important to point out that the Multivariate Gaussian prior allows us to include the correlation of the AVO parameters in the solution of the inverse problem. The Trivariate Cauchy prior not only permits us to incorporate correlation but also leads to high-resolution (broadband) P-wave velocity, S-wave velocity, and density perturbations.

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.

scholarly journals Seismic P  Wave Velocity Model From 3‐D Surface and Borehole Seismic Data at the Alpine Fault DFDP‐2 Drill Site (Whataroa, New Zealand)

2021 ◽  
Author(s):  
V Lay ◽  
S Buske ◽  
SB Bodenburg ◽  
John Townend ◽  
R Kellett ◽  
...  
Keyword(s):  
New Zealand ◽  
Wave Velocity ◽  
Seismic Data ◽  
Velocity Model ◽  
P Wave ◽  
Alpine Fault ◽  
P Wave Velocity ◽  
Drill Site ◽  
Borehole Seismic

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