scholarly journals Analysis of Tsunami Inundation due in Pangandaran Tsunami Earthquake in South Java Area Based on Finite Faults Solutions Model

2020 ◽  
Vol 10 (2) ◽  
pp. 114
Author(s):  
Ramadhan Priadi ◽  
Dede Yunus ◽  
Berlian Yonanda ◽  
Relly Margiono
Keyword(s):  
Fault Plane ◽  
Body Wave ◽  
Scaling Law ◽  
Source Mechanism ◽  
Inversion Method ◽  
Tsunami Modeling ◽  
Residential Areas ◽  
North West ◽  
Wave Inversion ◽  
Run Up

On July 17, 2006 an earthquake with a magnitude of  7.7 triggered a tsunami that struck 500 km of the coast in the south of the island of Java. The tsunami generated is classified as an earthquake tsunami because the waves generated were quite large compared to the strength of the earthquake. The difference in the strength of the earthquake and the resulting tsunami requires a tsunami modeling study with an estimated fault area in addition to using aftershock and scaling law. The purpose of this study is to validate tsunamis that occur based on the estimation of the source mechanism and the area of earthquake faults. Determination of earthquake source mechanism parameters using the Teleseismic Body-Wave Inversion method that uses teleseismic waveforms with the distance recorded waveform from the source between  Whereas, tsunami modeling is carried out using the Community Model Interface for Tsunami (commit) method. Fault plane parameters that obtained were strike , dip , and rake  with dominant slip pointing up to north-north-west with a maximum value of 1.7 m. The fault plane is estimated to have a length of 280 km in the strike direction and a width of 102 km in the dip direction. From the results of the tsunami modeling, the maximum inundation area is 0.32 km2 in residential areas flanked by Pangandaran bays and the maximum run-up of 380.96 cm in Pasir Putih beach area. The tsunami modeling results in much smaller inundation and run-up from field observations, it was assumed that the fault plane segmentation had occurred due to the greater energy released than the one from the fault area, causing waves much larger than the modeling results.

scholarly journals Slip distribution effect in spatial coulomb stress analysis (Case study: Palu earthquake on September 28, 2018)

2021 ◽  
Vol 873 (1) ◽  
pp. 012033
Author(s):  
Kevin Hanyu Clinton Wulur ◽  
Iman Suardi ◽  
Sesar Prabu Dwi Sriyanto ◽  
Yusuf Hadi Perdana
Keyword(s):  
Fault Plane ◽  
Body Wave ◽  
Slip Distribution ◽  
Inversion Method ◽  
Coulomb Stress ◽  
The North ◽  
Wave Inversion ◽  
Dip Angle ◽  
Coulomb Stress Analysis

Abstract On September 28, 2018, the Palu-Koro fault released the accumulated stress that caused the earthquake. An earthquake with magnitude 7.5 caused large and massive damage around Palu. There were many aftershocks along the Palu-Koro fault. This research aims to calculate a model of spatial Coulomb stress based on this event to find a correlation between mainshock and the aftershocks. The slip distribution was used as an input of the spatial stress Coulomb modeling to increase the accuracy. We use the Teleseismic Body-Wave Inversion method to calculate slip distribution along the fault plane. As a result, this earthquake was generated by the Palu-Koro fault movement with Mw 7.48, strike 350°, dip angle 67°, and rake -9°. There are three asperity zones along the fault plane located in the north and southern parts of the fault plane. The location of the most energy discharge is in the south asperity zone of the fault plane model with a maximum slip value of 1.65 meters. The spatial Coulomb stress change of this event shows that aftershocks concentration are in areas experiencing increased stress after the earthquake.

scholarly journals Imaging the subsurface using induced seismicity and ambient noise: 3-D tomographic Monte Carlo joint inversion of earthquake body wave traveltimes and surface wave dispersion

2020 ◽  
Vol 222 (3) ◽  
pp. 1639-1655
Author(s):  
Xin Zhang ◽  
Corinna Roy ◽  
Andrew Curtis ◽  
Andy Nowacki ◽  
Brian Baptie
Keyword(s):  
Surface Wave ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Joint Inversion ◽  
Body Wave ◽  
Source Parameters ◽  
Wave Dispersion ◽  
Inversion Method ◽  
Surface Wave Dispersion ◽  
Wave Data

SUMMARY Seismic body wave traveltime tomography and surface wave dispersion tomography have been used widely to characterize earthquakes and to study the subsurface structure of the Earth. Since these types of problem are often significantly non-linear and have non-unique solutions, Markov chain Monte Carlo methods have been used to find probabilistic solutions. Body and surface wave data are usually inverted separately to produce independent velocity models. However, body wave tomography is generally sensitive to structure around the subvolume in which earthquakes occur and produces limited resolution in the shallower Earth, whereas surface wave tomography is often sensitive to shallower structure. To better estimate subsurface properties, we therefore jointly invert for the seismic velocity structure and earthquake locations using body and surface wave data simultaneously. We apply the new joint inversion method to a mining site in the United Kingdom at which induced seismicity occurred and was recorded on a small local network of stations, and where ambient noise recordings are available from the same stations. The ambient noise is processed to obtain inter-receiver surface wave dispersion measurements which are inverted jointly with body wave arrival times from local earthquakes. The results show that by using both types of data, the earthquake source parameters and the velocity structure can be better constrained than in independent inversions. To further understand and interpret the results, we conduct synthetic tests to compare the results from body wave inversion and joint inversion. The results show that trade-offs between source parameters and velocities appear to bias results if only body wave data are used, but this issue is largely resolved by using the joint inversion method. Thus the use of ambient seismic noise and our fully non-linear inversion provides a valuable, improved method to image the subsurface velocity and seismicity.

The 4 December 2015 Mw 7.1 Normal-Faulting Antarctic Plate Earthquake and Its Seismotectonic Implications

2020 ◽  
Vol 110 (3) ◽  
pp. 1090-1100
Author(s):  
Ronia Andrews ◽  
Kusala Rajendran ◽  
N. Purnachandra Rao
Keyword(s):  
Body Wave ◽  
Focal Depth ◽  
Normal Fault ◽  
Normal Faults ◽  
Oceanic Plate ◽  
Normal Faulting ◽  
Transform Faults ◽  
Wave Inversion ◽  
Spreading Ridges ◽  
Southeast Indian Ridge

ABSTRACT Oceanic plate seismicity is generally dominated by normal and strike-slip faulting associated with active spreading ridges and transform faults. Fossil structural fabrics inherited from spreading ridges also host earthquakes. The Indian Oceanic plate, considered quite active seismically, has hosted earthquakes both on its active and fossil fault systems. The 4 December 2015 Mw 7.1 normal-faulting earthquake, located ∼700  km south of the southeast Indian ridge in the southern Indian Ocean, is a rarity due to its location away from the ridge, lack of association with any mapped faults and its focal depth close to the 800°C isotherm. We present results of teleseismic body-wave inversion that suggest that the earthquake occurred on a north-northwest–south-southeast-striking normal fault at a depth of 34 km. The rupture propagated at 2.7  km/s with compact slip over an area of 48×48  km2 around the hypocenter. Our analysis of the background tectonics suggests that our chosen fault plane is in the same direction as the mapped normal faults on the eastern flanks of the Kerguelen plateau. We propose that these buried normal faults, possibly the relics of the ancient rifting might have been reactivated, leading to the 2015 midplate earthquake.

Aftershocks of the February 21, 1973 Point Mugu, California earthquake

1976 ◽  
Vol 66 (6) ◽  
pp. 1931-1952
Author(s):  
Donald J. Stierman ◽  
William L. Ellsworth
Keyword(s):  
Fault Zone ◽  
Main Shock ◽  
Fault Plane ◽  
Body Wave ◽  
P Wave ◽  
Fault System ◽  
Wave Radiation ◽  
Fault Plane Solutions ◽  
Complex Deformation ◽  
Transverse Ranges

abstract The ML 6.0 Point Mugu, California earthquake of February 21, 1973 and its aftershocks occurred within the complex fault system that bounds the southern front of the Transverse Ranges province of southern California. P-wave fault plane solutions for 51 events include reverse, strike slip and normal faulting mechanisms, indicating complex deformation within the 10-km broad fault zone. Hypocenters of 141 aftershocks fail to delineate any single fault plane clearly associated with the main shock rupture. Most aftershocks cluster in a region 5 km in diameter centered 5 km from the main shock hypocenter and well beyond the extent of fault rupture estimated from analysis of body-wave radiation. Strain release within the imbricate fault zone was controlled by slip on preexisting planes of weakness under the influence of a NE-SW compressive stress.

REAL-TIME 2.5D INVERSION OF LWD RESISTIVITY MEASUREMENTS USING DEEP LEARNING FOR GEOSTEERING APPLICATIONS ACROSS FAULTED FORMATIONS

2021 ◽  
Author(s):  
Kyubo Noh ◽  
◽  
Carlos Torres-Verdín ◽  
David Pardo ◽  
◽  
...  
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Fault Plane ◽  
Synthetic Data ◽  
Field Measurements ◽  
Geological Structure ◽  
Inversion Method ◽  
Adaptive Finite Element ◽  
Resistivity Measurements ◽  
Lwd Resistivity

We develop a Deep Learning (DL) inversion method for the interpretation of 2.5-dimensional (2.5D) borehole resistivity measurements that requires negligible online computational costs. The method is successfully verified with the inversion of triaxial LWD resistivity measurements acquired across faulted and anisotropic formations. Our DL inversion workflow employs four independent DL architectures. The first one identifies the type of geological structure among several predefined types. Subsequently, the second, third, and fourth architectures estimate the corresponding spatial resistivity distributions that are parameterized (1) without the crossings of bed boundaries or fault plane, (2) with the crossing of a bed boundary but without the crossing of a fault plane, and (3) with the crossing of the fault plane, respectively. Each DL architecture employs convolutional layers and is trained with synthetic data obtained from an accurate high-order, mesh-adaptive finite-element forward numerical simulator. Numerical results confirm the importance of using multi-component resistivity measurements -specifically cross-coupling resistivity components- for the successful reconstruction of 2.5D resistivity distributions adjacent to the well trajectory. The feasibility and effectiveness of the developed inversion workflow is assessed with two synthetic examples inspired by actual field measurements. Results confirm that the proposed DL method successfully reconstructs 2.5D resistivity distributions, location and dip angles of bed boundaries, and the location of the fault plane, and is therefore reliable for real-time well geosteering applications.

Seismic wave energy inferred from long-period body wave inversion

1988 ◽  
Vol 78 (5) ◽  
pp. 1707-1724
Author(s):  
Masayuki Kikuchi ◽  
Yoshio Fukao
Keyword(s):  
Seismic Wave ◽  
Wave Energy ◽  
Body Wave ◽  
Empirical Relation ◽  
P Waves ◽  
Average Value ◽  
Long Period ◽  
Wave Inversion ◽  
Moment Ratio ◽  
Order Of Magnitude

Abstract The seismic wave energy is evaluated for 35 large earthquakes by inverting far-field long-period P waves into the multiple-shock sequence. The results show that the seismic wave energy thus obtained is systematically less than that inferred from the Gutenberg-Richter's formula with the seismic magnitude. The difference amounts to one order of magnitude. The results also show that the energy-moment ratio is well confined to a narrow range: 10−6 < ES/Mo < 10−5 with the average of ∼5 × 10−6. This average value is exactly one order of magnitude as small as the energy-moment ratio inferred from the Gutenberg-Richter's formula using the moment magnitude. Comparing the energy-moment ratio with Δσo/2μ, where Δσo and μ are the stress drop and the rigidity, we obtain an empirical relation: ES/Mo ∼ 0.1 × Δσ0/2μ. Such a relation can be interpreted in terms of a subsonic rupture where the energy loss due to cohesion is not negligible to the seismic wave energy.

Two-parameter scaling of source spectra: Love waves from deep-focus Bonin Islands earthquakes

1977 ◽  
Vol 67 (2) ◽  
pp. 285-300
Author(s):  
R. James Brown
Keyword(s):  
Body Wave ◽  
Scaling Law ◽  
Spectral Ratio ◽  
Love Waves ◽  
Corner Frequency ◽  
Spectral Ratios ◽  
Bonin Islands ◽  
Deep Focus ◽  
Two Parameter ◽  
Fault Length

Abstract Starting with the one-parameter scaling law of Aki, a two-parameter expression is developed to model the source factor of the far-field spectrum from a dislocation fault source for both ω−2 and ω−3 high-frequency asymptotic types. Aki's assumption of similarity is relaxed in two respects: it is neither here assumed that wD0 ∞ L2 (L = fault length, w = fault width, D0 = average dislocation) nor that kT = v kL (kT−1 = correlation time, kL−1 = correlation length, v = velocity of rupture propagation), the latter being equivalent to allowing for Brune's fractional stress drop. From this two-parameter model a four-parameter model of spectral ratio is obtained and fitted to observed spectral ratios by computer optimization of the four parameters. Observed spectral ratios have been determined from the Love waves recorded at NORSAR from six deep-focus Bonin Islands earthquakes using a common-path method. From the optimal values of the four parameters, values are determined for corner frequency (f ≈ 0.2 Hz for m 6.0; f ≈ 0.3 Hz for m = 5.3; m = PDE body-wave magnitude), relative fault length, relative seismic moment (and magnitudes), and p, the slope of the corner-frequency locus. Values found for p are all greater than 3 and such p, in combination with an ω−3 scaling law, can yield a reasonable m:M relation, i.e., with no ceiling imposed on m. A slightly better fit is obtained by starting with an ω−3 model than with ω−2.

Rapid earthquake source characterization in the context of tsunami early warning

2021 ◽  
Author(s):  
Alberto Armigliato ◽  
Martina Zanetti ◽  
Stefano Tinti ◽  
Filippo Zaniboni ◽  
Glauco Gallotti ◽  
...  
Keyword(s):  
Focal Mechanism ◽  
Early Warning ◽  
Fault Plane ◽  
Early Warning Systems ◽  
Slip Distribution ◽  
Generation Process ◽  
Tsunami Early Warning ◽  
Earthquake Focal Mechanism ◽  
Run Up ◽  
Seismic Networks

<p>It is well known that for earthquake-generated tsunamis impacting near-field coastlines the focal mechanism, the position of the fault with respect to the coastline and the on fault slip distribution are key factors in determining the efficiency of the generation process and the distribution of the maximum run-up and inundation along the nearby coasts. The time needed to obtain the aforementioned information from the analysis of seismic records is usually too long compared to the time required to issue a timely tsunami warning/alert to the nearest coastlines. In the context of tsunami early warning systems, a big challenge is hence to be able to define 1) the relative position of the hypocenter and of the fault and 2) the earthquake focal mechanism, based only on the preliminary earthquake localization and magnitude estimation, which are made available by seismic networks soon after the earthquake occurs.</p><p>In this study, the intrinsic unpredictability of the position of the hypocenter on the fault plane is studied through a probabilistic approach based on the analysis of two finite fault model datasets (SRCMOD and USGS) and by limiting the analysis to moderate-to-large shallow earthquakes (Mw  6 and depth  50 km). After a proper homogenization procedure needed to define a common geometry for all samples in the two datasets, the hypocentral positions are fitted with different probability density functions (PDFs) separately in the along-dip and along-strike directions.</p><p>Regarding the focal mechanism determination, different approaches have been tested: the most successful is restricted to subduction-type earthquakes. It defines average values and uncertainties for strike, dip and rake angles based on a combination of a proper zonation of the main tsunamigenic subduction areas worldwide and of subduction zone geometries available from publicdatabases.</p><p>The general workflow that we propose can be schematically outlined as follows. Once an earthquake occurs and the magnitude and hypocentral solutions are made available by seismic networks, it is possible to assign the focal mechanism by selecting the characteristic values for strike, dip and rake of the zone where the hypocenter falls into. Fault length and width, as well as the slip distribution on the fault plane, are computed through regression laws against magnitude proposed by previous studies. The resulting rectangular fault plane can be discretized into a matrix of subfaults: the position of the center of each subfault can be considered as a “realization” of the hypocenter position, which can then be assigned a probability. In this way, we can define a number of earthquake fault scenarios, each of which is assigned a probability, and we can run tsunami numerical simulations for each scenario to quantify the classical observables, such as water elevation time series in selected offshore/coastal tide-gauges, flow depth, run-up, inundation distance. The final results can be provided as probabilistic distributions of the different observables.</p><p>The general approach, which is still in a proof-of-concept stage, is applied to the 16 September 2015 Illapel (Chile) tsunamigenic earthquake (Mw = 8.2). The comparison with the available tsunami observations is discussed with special attention devoted to the early-warning perspective.</p>

Spatial distribution of high-frequency energy radiation on the fault of the 1995 Hyogo-Ken Nanbu, Japan, earthquake (MW 6.9) on the basis of the seismogram envelope inversion

1999 ◽  
Vol 89 (1) ◽  
pp. 22-35 ◽  
Author(s):  
Hisashi Nakahara ◽  
Haruo Sato ◽  
Masakazu Ohtake ◽  
Takeshi Nishimura
Keyword(s):  
Spatial Distribution ◽  
Wave Energy ◽  
High Frequency ◽  
Fault Plane ◽  
Time Window ◽  
Source Region ◽  
Inversion Method ◽  
S Wave ◽  
Energy Radiation ◽  
Initial Rupture

Abstract We studied the generation and propagation of high-frequency (above 1 Hz) S-wave energy from the 1995 Hyogo-Ken Nanbu (Kobe), Japan, earthquake (MW 6.9) by analyzing seismogram envelopes of the mainshock and aftershocks. We first investigated the propagation characteristics of high-frequency S-wave energy in the heterogeneous lithosphere around the source region. By applying the multiple lapse time window analysis method to aftershock records, we estimated two parameters that quantitatively characterize the heterogeneity of the medium: the total scattering coefficient and the intrinsic absorption of the medium for S waves. Observed envelopes of aftershocks were well reproduced by the envelope Green functions synthesized based on the radiative transfer theory with the obtained parameters. Next, we applied the envelope inversion method to 13 strong-motion records of the mainshock. We divided the mainshock fault plane of 49 × 21 km into 21 subfaults of 7 × 7 km square and estimated the spatial distribution of the high-frequency energy radiation on that plane. The average constant rupture velocity and the duration of energy radiation for each subfault were determined by grid searching to be 3.0 km/sec and 5.0 sec, respectively. Energy radiated from the whole fault plane was estimated as 4.9 × 1014 J for 1 to 2 Hz, 3.3 × 1014 J for 2 to 4 Hz, 1.5 × 1014 J for 4 to 8 Hz, 8.9 × 1012 J for 8 to 16 Hz, and 9.8 × 1014 J in all four frequency bands. We found that strong energy was mainly radiated from three regions on the mainshock fault plane: around the initial rupture point, near the surface at Awaji Island, and a shallow portion beneath Kobe. We interpret that energetic portions were associated with rupture acceleration, a fault surface break, and rupture termination, respectively.

Sign in / Sign up

Export Citation Format

Share Document