Estimation of SH-Wave Amplification in the Bandung Basin Using Haskellâs Method

The Bandung basin is a large basin in Indonesia surrounded by mountains that are associated with faults. There is the possibility of earthquakes generated by these faults shaking populated areas in the basin. The consequences will be worse because the shaking is amplified by the sediment layer of the basin. We have estimated the amplification of SH-waves generated by the Lembang fault using Haskell's method for multilayer models. The pattern of amplification is a decreasing value with increasing distance from the Lembang fault. This pattern is valid for low-frequency incident waves. For higher-frequency incident waves, the pattern looks more complicated. Fortunately, there are many areas with low amplification values. Hopefully, this result will help the local government in making decisions regarding construction planning in this region. Of course, the final objective is to reduce earthquake risks

Estimation of SH-Wave Amplification in the Bandung Basin Using Haskell\u27s Method

The Bandung basin is a large basin in Indonesia surrounded by mountains that are associated with faults. There is the possibility of earthquakes generated by these faults shaking populated areas in the basin. The consequences will be worse because the shaking is amplified by the sediment layer of the basin. We have estimated the amplification of SH-waves generated by the Lembang fault using Haskell\u27s method for multilayer models. The pattern of amplification is a decreasing value with increasing distance from the Lembang fault. This pattern is valid for low-frequency incident waves. For higher-frequency incident waves, the pattern looks more complicated. Fortunately, there are many areas with low amplification values. Hopefully, this result will help the local government in making decisions regarding construction planning in this region. Of course, the final objective is to reduce earthquake risks

Development of an Inversion Method for Low Velocity Medium

The main problem with the inversion of a low velocity medium is the application of an appropriate ray tracing method after choosing a suitable model parameterization. Block parameterization is not suitable, because it is not capable of representing the velocity model well. A large amount of blocks with a small grid size are needed to express the model well, but in that case, a ray coverage problem will be encountered. A knot-point parameterization model is better suited than a block model, because it can express the velocity model well, while the number of variables is much smaller. Ray calculation using the pseudo-bending method is not appropriate for the velocity model because of an instability problem at high velocity gradients. The crucial problem of this method involves the initial ray-path that is optimized in order to obtain the "true" ray, but does not satisfy the Fermat principle. These problems can be solved by applying the eikonal-solver method, because this can handle high-velocity gradients and does not need an initial ray path. Using a suitable model parameterization and appropriate ray tracing method, the inversion can obtain good results that fit the desired output. Applying a block model and the pseudo-bending method will not produce the desired output

Source Processes of the March 2007 Singkarak Earthquakes Inferred from Teleseismic Data

The rupture processes of two sequentialearthquakes have been inverted from teleseismic data. The first event released a total seismic moment of 7.9×1018 Nm (Mw 6.5) and the slip distribution shows three asperities, 1.5 m at the shallowside, 0.7 m at the rightsouth-east deep side and 0.5 m atthe north-west deep side. The second event had one asperity with 1.7 m slip and released a seismic moment of 7.5×1018 Nm (Mw 6.5). In both cases, maximum slip occurred above the hypocenter which was responsible for the surface displacement pattern

Estimation of S-wave Velocity Structures by Using Microtremor Array Measurements for Subsurface Modeling in Jakarta

Jakarta  is located on  a  thick sedimentary  layer that  potentially has a very  high  seismic  wave  amplification.  However,  the  available information concerning the  subsurface model and bedrock depth  is insufficient  for a seismic hazard  analysis.  In  this  study,  a  microtremor  array  method  was  applied  to estimate the geometry and S-wave velocity of the sedimentary layer. The spatial autocorrelation  (SPAC)  method  was  applied  to  estimate  the  dispersion  curve, while  the S-wave  velocity  was  estimated  using  a  genetic  algorithm  approach. The  analysis  of  the  1D  and  2D  S-wave  velocity  profiles  shows  that  along  a north-south  line,  the  sedimentary  layer  is  thicker  towards  the  north.  It  has  a positive  correlation  with  a  geological  cross section  derived  from  a borehole down to  a depth of  about 300 m. The SPT data from  the  BMKG site  were used to  verify  the  1D  S-wave  velocity  profile.  They  show  a  good agreement. The microtremor analysis  reached  the engineering bedrock  in a  range from 359  to 608  m  as  depicted by a  cross section  in  the  north-south  direction. The site class was also estimated at each site, based on the average S-wave velocity until 30 m depth. The sites UI to ISTN belong to class  D (medium soil),  while BMKG and ANCL belong to class E (soft soil)

Estimation of SH-Wave Amplification in the Bandung Basin Using Haskellâs Method

The Bandung basin is a large basin in Indonesia surrounded by mountains that are associated with faults. There is the possibility of earthquakes generated by these faults shaking populated areas in the basin. The consequences will be worse because the shaking is amplified by the sediment layer of the basin. We have estimated the amplification of SH-waves generated by the Lembang fault using Haskell's method for multilayer models. The pattern of amplification is a decreasing value with increasing distance from the Lembang fault. This pattern is valid for low-frequency incident waves. For higher-frequency incident waves, the pattern looks more complicated. Fortunately, there are many areas with low amplification values. Hopefully, this result will help the local government in making decisions regarding construction planning in this region. Of course, the final objective is to reduce earthquake risks

Characteristics of Earthquake-Generated Tsunamis in Indonesia Based on Source Parameter Analysis

We have characterized 27 earthquake-generated tsunamis from 1991 to 2012 in Indonesia, based on source parameter analysis. This includes the focal mechanism derived by W phase inversion analysis, the ratio (Θ) between the seismic energy (E) and the seismic moment (Mo), the moment magnitude (Mw), the rupture duration (To) and the distance of the hypocenter to the trench. Most of the earthquakes (24 events) were tsunamigenic earthquakes with various fault types, a shallow focal depth (12 km ≤ D ≤ 77.8 km), a small to large magnitude (6.6 ≤ Mw ≤ 9.0), a low ratio of seismic energy to seismic moment (-5.8 < Θ < -4.9), a short to long rupture duration (27 s ≤ To ≤ 257 s), a small to large tsunami height (0.1 m ≤ H ≤ 50.9 m) and a short to long distance from the hypocenter to the trench (10 km < HT ≤ 230 km). Three tsunami earthquakes were characterized by a thrust fault mechanism, a very shallow depth (D ≤ 20 km), a moderate magnitude (7.5 ≤ Mw ≤ 7.8), a very low ratio of seismic energy to seismic moment (Θ ≤ -5.8), a long rupture duration (99 s ≤ To ≤ 135 s), a large tsunami height (7.4 m ≤ H ≤ 14 m) and a short distance from the hypocenter to the trench (HT ≤ 20 km)

Characteristics of Earthquake-Generated Tsunamis in Indonesia Based on Source Parameter Analysis

We have characterized 27 earthquake-generated tsunamis from 1991 to 2012 in Indonesia, based on source parameter analysis. This includes the focal mechanism derived by W phase inversion analysis, the ratio (Θ) between the seismic energy (E) and the seismic moment (Mo), the moment magnitude (Mw), the rupture duration (To) and the distance of the hypocenter to the trench. Most of the earthquakes (24 events) were tsunamigenic earthquakes with various fault types, a shallow focal depth (12 km ≤ D ≤ 77.8 km), a small to large magnitude (6.6 ≤ Mw ≤ 9.0), a low ratio of seismic energy to seismic moment (-5.8 < Θ < -4.9), a short to long rupture duration (27 s ≤ To ≤ 257 s), a small to large tsunami height (0.1 m ≤ H ≤ 50.9 m) and a short to long distance from the hypocenter to the trench (10 km < HT ≤ 230 km). Three tsunami earthquakes were characterized by a thrust fault mechanism, a very shallow depth (D ≤ 20 km), a moderate magnitude (7.5 ≤ Mw ≤ 7.8), a very low ratio of seismic energy to seismic moment (Θ ≤ -5.8), a long rupture duration (99 s ≤ To ≤ 135 s), a large tsunami height (7.4 m ≤ H ≤ 14 m) and a short distance from the hypocenter to the trench (HT ≤ 20 km)

Three-dimensional joint inversion of traveltime and gravity data across the Chicxulub impact crater

In 2005 an extensive new seismic refraction data set was acquired over the central part of the Chicxulub impact crater, allowing us to image its structure with much better resolution than before. However, models derived from traveltime data are limited by the available ray coverage and the nonuniqueness that is inherent to all geophysical methods. Therefore, many different models can fit the data equally well. To address these issues, we have developed a new method to simultaneously invert traveltime and gravity data to obtain an integrated model. To convert velocity to density, we use a linear relationship derived from measurements on core from the Chicxulub impact basin, thus providing a reliable conversion equation that is typical for lithologies of the central part of this crater. Prior to utilizing the inversion on the observed data, we have run a suite of tests to establish the optimum weighting between traveltime and gravity constraints, using a synthetic model of central crater structure and the real experimental geometry. These synthetic tests indicate which inversion parameters lead to the best recovery of subsurface structure, as well as which parts of the model are well resolved. We applied the method to all existing gravity data and to seismic refraction data acquired in 1996 and the new, higher-resolution seismic refraction data acquired in 2005. We favor the traveltime model wherever we have sufficient ray coverage and the joint model where we have no ray coverage