A fall in P-wave velocity before the Gisborne, New Zealand, earthquake of 1966

1974 ◽  
Vol 64 (5) ◽  
pp. 1501-1507 ◽  
Author(s):  
D. J. Sutton
Keyword(s):  
New Zealand ◽  
Wave Velocity ◽  
Significant Variation ◽  
Arrival Time ◽  
P Wave ◽  
Time Interval ◽  
P Waves ◽  
Arrival Times ◽  
P Wave Velocity ◽  
Seismograph Station

Abstract A fall in P-wave velocity before the Gisborne earthquake of March 4, 1966 is indicated by arrival-time residuals of P waves from distant earthquakes recorded at the Gisborne seismograph station. Residuals were averaged over 6-month intervals from 1964 to 1968 and showed an increase of about 0.5 sec, implying later arrival times. The change began about 480 days before the earthquake. This precursory time interval is about that expected for an earthquake of this magnitude (ML = 6.2), but unlike most other reported instances, there was no obvious delay between the return of the velocity to normal and the occurrence of the earthquake. Similar analyses were carried out over the same period for two other New Zealand seismograph stations; at Karapiro there was no significant variation in mean residuals, and at Wellington the scatter was too large for the results to be meaningful. The Gisborne earthquake had a focus in the lower crust, about 25 km deep and was deeper than other events for which such precursory drops in P-wave velocity have been reported.

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 Technique for solving for microseismic source location parameters based on adaptive particle swarm optimization

2019 ◽  
Author(s):  
Hong-Mei Sun ◽  
Jian-Zhi Yu ◽  
Xing-Li Zhang ◽  
Bing-Guo Wang ◽  
Rui-Sheng Jia
Keyword(s):  
Particle Swarm Optimization ◽  
Wave Velocity ◽  
Least Squares Method ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
P Wave ◽  
Origin Time ◽  
Swarm Optimization ◽  
Arrival Times ◽  
P Wave Velocity

Abstract. An intelligent method is presented for locating microseismic source based on particle swarm optimization (PSO) concept. It eliminates microseismic source locating errors caused by inaccurate velocity model of the earth medium. The method uses as the target of PSO a global minimum of the sum of squared discrepancies between modeled arrival times and measured arrival times. The discrepancies are calculated for all pairs of detectors of a seismic monitoring system, Then, the adaptive PSO algorithm is applied to locate the microseismic source and obtain optimal value of the P-wave velocity. The PSO algorithm adjusts inertia weight, accelerating constants, the maximum flight velocity of particles, and other parameters to avoid the PSO algorithm trapping by local optima during the solution process. The origin time of the microseismic event is estimated by minimizing the sum of squared discrepancies between the modeled arrival times and the measured arrival times. This Sum is calculated using the obtained estimates of the microseismic source coordinates and P-wave velocity. The effectiveness of the PSO algorithm was verified through inversion of a theoretical model and two analyses of actual data from mine blasts in different locations. Compared with the classic least squares method, the PSO algorithm displays faster convergence and higher accuracy of microseismic source positioning. Moreover, there is no need to measure the microseismic wave velocity in advance: the PSO algorithm eliminates the adverse effects caused by error in the P-wave velocity when locating a microseismic source using traditional methods.

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

No description supplied

scholarly journals Estimation of Geodynamic Properties using Seismic Techniques at a Steel Rolling Factory, Northwestern Gulf of Suez, Egypt

2020 ◽  
Vol 8 (6) ◽  
pp. 1785-1794
Keyword(s):  
Wave Velocity ◽  
Seismic Waves ◽  
Seismic Refraction ◽  
Industrial Area ◽  
P Wave ◽  
Gulf Of Suez ◽  
S Wave ◽  
P Waves ◽  
Steel Rolling ◽  
P Wave Velocity

The objective of the current investigations is to estimate the dynamic geotechnical properties necessary for evaluating the conditions of the subsurface in order to make better decisions for economic and safe designs of the proposed structures at a Steel Rolling Factory, Ataqa Industrial Area, Northwestern Gulf of Suez, Egypt. To achieve this purpose, four seismic refraction profiles were conducted to measure the velocity of primary seismic waves (P-waves) and four profiles were conducted using Multichannel Analysis of Surface Waves (MASW) technique in the same locations of refraction profiles to measure the velocity of shear waves (S-waves). SeisImager/2D Software Package was used in the analysis of the measured data. Data processing and interpretation reflect that the subsurface section in the study area consists of two layers, the first layer is a thin surface layer ranges in thickness from 1 to 4 meters with P-wave velocity ranges from 924 m/s to 1247 m/s and S-wave velocity ranges from 530 m/s to 745 m/s. The second layer has a P-wave velocity ranges from 1277 m/s to 1573 m/s and the S-wave velocity ranges from 684 m/s to 853 m/s. Geotechnical parameters were calculated for both layers. Since elastic moduli such as Poisson’s ratio, shear modulus, Young’s modulus, and bulk’s modulus were calculated. Competence scales such as material index, stress ratio, concentration index, and density gradient were calculated also. In addition, the ultimate and allowable bearing capacities

scholarly journals A Simple Method for P-waves Velocity Estimation Using Pore Attributes Shape Factor and Tortuosity

2020 ◽  
Vol 9 (2) ◽  
pp. 83-89
Author(s):  
Muhammad Burhannudinnur ◽  
Suryo Prakoso
Keyword(s):  
Wave Velocity ◽  
Shape Factor ◽  
Empirical Relationship ◽  
Velocity Estimation ◽  
P Wave ◽  
Simple Relationship ◽  
P Waves ◽  
Simple Method ◽  
P Wave Velocity ◽  
Relationship Of

Several researchers have arranged an approach to estimating the P-wave velocity, but none of them specifically relates to the pore attribute. Pore attributes are one of the main factors that affect pore complexity and rock quality. If P-wave velocity is influenced by the pore complexity, then it should be possible to arrange a simple relationship of P-wave velocity with the pore attribute. This study is intended to construct an empirical relationship of P-wave velocity with a combination of pore attributes, shape factor, and tortuosity (Fsτ) so that the P-wave velocity can be easily estimated. This study used two sandstone datasets from 2 different basins, which are the northern part of the West Java basin and the Kutai basin. This research shows that a simple empirical equation can be arranged to relate the P-wave velocity with Fsτ. This relationship provides a good correlation coefficient. It offers an easy and straightforward approach to estimating P-wave

scholarly journals The adaptive particle swarm optimization technique for solving microseismic source location parameters

2019 ◽  
Vol 26 (3) ◽  
pp. 163-173 ◽  
Author(s):  
Hong-Mei Sun ◽  
Jian-Zhi Yu ◽  
Xing-Li Zhang ◽  
Bin-Guo Wang ◽  
Rui-Sheng Jia
Keyword(s):  
Particle Swarm Optimization ◽  
Wave Velocity ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Source Location ◽  
P Wave ◽  
Swarm Optimization ◽  
Arrival Times ◽  
P Wave Velocity ◽  
Microseismic Source Location

Abstract. An intelligent method is presented for locating a microseismic source based on the particle swarm optimization (PSO) concept. It eliminates microseismic source locating errors caused by the inaccurate velocity model of the earth medium. The method uses, as the target of PSO, a global minimum of the sum of squared discrepancies between differences of modeled arrival times and differences of measured arrival times. The discrepancies are calculated for all pairs of detectors of a seismic monitoring system. Then, the adaptive PSO algorithm is applied to locate the microseismic source and obtain optimal value of the P-wave velocity. The PSO algorithm adjusts inertia weight, accelerating constants, the maximum flight velocity of particles, and other parameters to avoid the PSO algorithm trapping by local optima during the solution process. The origin time of the microseismic event is estimated by minimizing the sum of squared discrepancies between the modeled arrival times and the measured arrival times. This sum is calculated using the obtained estimates of the microseismic source coordinates and P-wave velocity. The effectiveness of the PSO algorithm was verified through inversion of a theoretical model and two analyses of actual data from mine blasts in different locations. Compared with the classic least squares method (LSM), the PSO algorithm displays faster convergence and higher accuracy of microseismic source location. Moreover, there is no need to measure the microseismic wave velocity in advance: the PSO algorithm eliminates the adverse effects caused by error in the P-wave velocity when locating a microseismic source using traditional methods.

ATTENUATION MEASUREMENTS IN THE FIELD

Geophysics ◽  
1966 ◽  
Vol 31 (3) ◽  
pp. 562-569 ◽  
Author(s):  
J. Cl. De Bremaecker ◽  
Richard H. Godson ◽  
Joel S. Watkins
Keyword(s):  
Wave Velocity ◽  
Reasonable Agreement ◽  
P Wave ◽  
Head Wave ◽  
Published Data ◽  
Complex Shear Modulus ◽  
P Waves ◽  
P Wave Velocity ◽  
Complex Shear ◽  
Aa Lava

The amplitudes of the P head wave were measured on an aa lava flow, on unconsolidated cinders, and on compact limestone. The data are satisfied by the equation [Formula: see text], where A is the amplitude, d the distance, [Formula: see text] the attenuation coefficient for P waves, ν the frequency, and α the P wave velocity. By assuming a complex shear modulus μ* but a real λ one finds [Formula: see text], where β is the shear wave velocity. This formula is in reasonable agreement with published data.

Arrival times of P waves and upper mantle structure

1964 ◽  
Vol 54 (2) ◽  
pp. 727-736
Author(s):  
Eysteinn Tryggvason
Keyword(s):  
Standard Error ◽  
Upper Mantle ◽  
P Wave ◽  
P Waves ◽  
Arrival Times ◽  
P Wave Velocity ◽  
Upper Mantle Structure ◽  
The Mean ◽  
The Difference ◽  
Mantle Velocity

ABSTRACT Residuals of arrival times of P waves, as given in the International Seismological Summary for Kiruna, Sweden, Reykjavik, Iceland, and Scoresbysund, Greenland, were studied in order to detect upper mantle anomalies. The Kiruna arrivals were systematically too early, with a mean residual of −1.4 seconds, while the mean Reykjavik residual was +1.3 seconds. The difference in mean residual was 2.7 seconds with a standard error of about 0.5 second. The mean residual at Scoresbysund was −0.4 second. It is assumed that there is a depth D below which the mantle is homogeneous. The difference in mean residuals at the stations is assumed to be caused by different wave velocities at depths less than D in the vicinities of the stations. If it is assumed that the P-wave velocity in the upper mantle is constant down to a depth D below each station, this depth can be computed. This velocity is known from other data to be 8.36 km/sec below Kiruna and 7.4 km./sec. below Reykjavik. If only earthquakes at distances from 20° to 39° were used, D is determined to be 246 ± 36 km. (standard error). Earthquakes at distances 40° to 59° give D = 177 ± 25 km., at distances 60° to 79° give D = 234 ± 14 km., and at distances 80° to 99° give D = 281 ± 20 km. The most probable value of D is thus about 240 km. below the earth's surface, with a standard error of about 40 km. In the vicinity of Scoresbysund the upper mantle velocity is found to be about 8.0 km./sec., using the same assumption.

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