scholarly journals Use of Local Seismic Network in Analysis of Volcano-Tectonic (VT) Events Preceding the 2017 Agung Volcano Eruption (Bali, Indonesia)

2021 ◽  
Vol 9 ◽  
Author(s):  
David P. Sahara ◽  
Puput P. Rahsetyo ◽  
Andri Dian Nugraha ◽  
Devy Kamil Syahbana ◽  
Sri Widiyantoro ◽  
...  
Keyword(s):  
Velocity Model ◽  
Fracture Network ◽  
Double Difference ◽  
S Wave ◽  
Magma Intrusion ◽  
Eruption Forecasting ◽  
Volcano Eruption ◽  
Geological Conditions ◽  
Stress Changes ◽  
Seismic Crisis

This study provides an attempt to analyze the pre-eruptive seismicity events for volcano eruption forecasting. After more than 50 years of slumber, Agung volcano on Bali Island erupted explosively, starting on November 21, 2017. The eruption was preceded by almost 2 months of significant increase of recorded seismicity, herein defined as “seismic crisis.” Our study provides the first analysis of VT events using data from eight local seismic stations deployed by the Center for Volcanology and Geological Hazard Mitigation of Indonesia (CVGHM) to monitor the Agung Volcano activity. In total, 2,726 Volcano-Tectonic (VT) events, with 13,023 P waves and 11,823 S wave phases, were successfully identified between October 18 and November 30, 2017. We increased the accuracy of the hypocenter locations of these VT events using a double-difference (DD) relative relocation and a new velocity model appropriate to the subsurface geological conditions of Agung volcano. We found two types of seismicity during the recording period that represent the VT events relating to fracture network reactivation due to stress changes (during the seismic crisis) and magma intrusion (after the seismic crisis). The characteristics of each event type are discussed in terms of Vp/Vs values, phase delay times, seismic cluster shapes, and waveform similarity. We interpret that the upward migrating magma reached a barrier (probably a stiff layer) which prohibited further ascent. Consequently, magma pressurized the zone above the magma chamber and beneath the barrier, reactivated the fracture zone between Agung and Batur volcanoes, and caused the seismic crisis since September 2017. In early November 2017, the barrier was finally intruded, and magma and seismicity propagated toward the Agung summit. This reconstruction provides a better depth constraint as to the previous conceptual models and explains the long delay (∼10 weeks) between the onset of the seismic crisis and the eruption. The distinction between the fracture reactivation and magma intrusion VT events observed in this study is significant for eruption forecasting and understanding the subsurface structure of the magmatic system. Based on the results obtained in this study, we emphasize the importance of prompt analysis (location and basic seismic characteristics) of the seismic crisis preceding the Agung eruption.

Joint microseismic event location and anisotropic velocity inversion with the cross double-difference method using downhole microseismic data

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. KS63-KS73
Author(s):  
Yangyang Ma ◽  
Congcong Yuan ◽  
Jie Zhang
Keyword(s):  
Arrival Time ◽  
Velocity Model ◽  
P Wave ◽  
Double Difference ◽  
S Wave ◽  
Arrival Times ◽  
Monitoring Well ◽  
The Cross ◽  
Microseismic Event ◽  
Wave Arrival

We have applied the cross double-difference (CDD) method to simultaneously determine the microseismic event locations and five Thomsen parameters in vertically layered transversely isotropic media using data from a single vertical monitoring well. Different from the double-difference (DD) method, the CDD method uses the cross-traveltime difference between the S-wave arrival time of one event and the P-wave arrival time of another event. The CDD method can improve the accuracy of the absolute locations and maintain the accuracy of the relative locations because it contains more absolute information than the DD method. We calculate the arrival times of the qP, qSV, and SH waves with a horizontal slowness shooting algorithm. The sensitivities of the arrival times with respect to the five Thomsen parameters are derived using the slowness components. The derivations are analytical, without any weak anisotropic approximation. The input data include the cross-differential traveltimes and absolute arrival times, providing better constraints on the anisotropic parameters and event locations. The synthetic example indicates that the method can produce better event locations and anisotropic velocity model. We apply this method to the field data set acquired from a single vertical monitoring well during a hydraulic fracturing process. We further validate the anisotropic velocity model and microseismic event locations by comparing the modeled and observed waveforms. The observed S-wave splitting also supports the inverted anisotropic results.

Hypocenter Analysis of Aftershocks Data of the Mw 6.3, 27 May 2006 Yogyakarta Earthquake Using Oct-Tree Importance Sampling Method

2018 ◽  
Vol 881 ◽  
pp. 89-97 ◽  
Author(s):  
Asri Wulandari ◽  
Ade Anggraini ◽  
Wiwit Suryanto
Keyword(s):  
Importance Sampling ◽  
Sampling Method ◽  
Velocity Model ◽  
Fault Scarp ◽  
P Wave ◽  
Double Difference ◽  
S Wave ◽  
Maximum Probability ◽  
Importance Sampling Method ◽  
Dip Angle

Yogyakarta earthquake, Mw 6.3, 27 May 2006 had killed 5,571 victims and destroyed more than 1 million buildings. This incident became the most destructive earthquake disaster over the last 11 years in Indonesia. Earthquake mitigation plan in the area has been carried out by understands the location of the fault. The location of the fault is still unclear among geoscientists until now. In this case, analysis of the aftershocks using oct-tree importance sampling method was applied to support the location of the fault that responsible for the 2006 Yogyakarta earthquake. Oct-tree importance sampling is a method that is recursively subdividing the solution domain into exactly eight children for estimating properties of a particular distribution. The final result of the subdividing process is a cell that has a maximum Probability Density Function (PDF) and identified as the location of the hypocenter. Input data consists of the arrival time of the P wave and S wave of the aftershocks catalog from 3-7 June 2006 and the coordinate of the 12 seismometers, and 1D velocity model of the study area. Based on the hypocenter distribution of the aftershocks data with the proposed method show a clearer trend of the fault compared with the aftershocks distribution calculated with theHypo71program. The fault trend has a strike orientation of N 42° E with a dip angle of 80° parallel with the fault scarp along the Opak River at the distance of about 15 km to the east. This fault trend is similar with the fault orientation obtained using the Double Difference Algorithm.

Complex magmatic-tectonic interactions during the 2020 Makushin Volcano, Alaska, earthquake swarm

2021 ◽  
Author(s):  
Diana Roman ◽  
Federica Lanza ◽  
John Power ◽  
Cliff Thurber ◽  
Thomas Hudson
Keyword(s):  
Earthquake Swarm ◽  
Velocity Model ◽  
Aftershock Sequence ◽  
Double Difference ◽  
Magma Intrusion ◽  
Fault Plane Solutions ◽  
3D Velocity Model ◽  
Double Couple ◽  
Seismic Swarms ◽  
Lower Magnitude

<p>We investigate the processes driving<strong> </strong>a significant earthquake swarm that occurred between June and December 2020 on Unalaska Island, Alaska, ~12 km southeast of the summit of Makushin Volcano. The swarm was energetic, with two M>4 events that were widely felt by the population in Dutch Harbor, ~ 15 km west of the epicenters. This is the strongest seismic activity ever recorded at Makushin since instrumental monitoring began in 1996. To date, no eruptive activity or other surface changes have been observed at the volcano in satellite views, webcam images, GPS or InSAR. Seismic swarms close to volcanoes are often associated with the onset of unrest that can lead to eruption. However, determining whether they reflect magmatic rather than tectonic stresses is challenging. Here, we integrate information from space-time patterns of the hypocenters of the swarm earthquakes with their double-couple fault-plane solutions (FPS). We relocate swarm events using double-difference relocation techniques and a 3D velocity model. We find that most of the events cluster into two perpendicular lineaments with NW-SE and SW-NE orientations, but no apparent migration in time towards a preferred fault. On the one hand, the lack of temporal migration (with both faults slipping concurrently), and FPS for M3+ events consistent with regional stresses, seem to indicate a tectonic driving process. On the other hand, FPS for the lower-magnitude earthquakes have 90°-rotated P-axes perpendicular to the regional principal stress orientation, providing strong evidence for dike inflation/magma intrusion. Coulomb stress modeling indicates that the rotated FPS are best explained by an inflating dike to the SW of the swarm epicenters, in a zone of long-term elevated seismicity. This complex overlapping of regional and magmatic stresses is also evident in the statistical analysis of the sequence, which started as a main-shock/aftershock sequence with the first event having the largest magnitude, and evolved into a swarm sequence indicative of a more pronounced role of magmatic processes.</p>

Cross double-difference inversion for microseismic event location using data from a single monitoring well

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. KS183-KS194 ◽  
Author(s):  
Xiao Tian ◽  
Wei Zhang ◽  
Jie Zhang
Keyword(s):  
Velocity Model ◽  
P Wave ◽  
Double Difference ◽  
Separate Analysis ◽  
S Wave ◽  
Monitoring Wells ◽  
Monitoring Well ◽  
Single Well ◽  
Microseismic Events ◽  
Wave Arrival

The double-difference (DD) location method has long been applied for locating a cluster of earthquakes with data recorded at surface seismic stations. This method has also been used for locating microseismic events with multiple monitoring wells during hydraulic fracturing. We first extended the approach for locating a cluster of microseismic events with data recorded from a single well. To do this, we have reduced the 3D location problem to 2D by projecting all of the events onto a vertical ([Formula: see text]) plane, with a vertical [Formula: see text]-axis and a horizontal [Formula: see text]-axis representing the distance to the monitoring well, considering the symmetric character of the 1D velocity model and the vertical monitoring well. We then performed a 2D location inversion and projected the results back to 3D using the event azimuths, which were determined from a separate analysis of the initial P-wave polarizations. However, although the DD method could determine relative locations of events reasonably well, it yielded poor absolute locations. We have developed a cross DD (CDD) approach using the cross traveltime difference between the P-wave arrival of one event and the S-wave arrival of another event for inversion instead of the arrival-time differences of the same phases as in the DD method. The CDD method contains more information on absolute locations than the DD method, resulting in a much more stable absolute location determination. The synthetic and field data tests indicated that the CDD method could improve the accuracy of relative and absolute event locations in microseismic clusters.

The 25 October, 2018 Zakynthos (Greece) earthquake: seismic activity at the transition between a transform fault and a subduction zone.

2020 ◽  
Author(s):  
P Papadimitriou ◽  
V Kapetanidis ◽  
A Karakonstantis ◽  
I Spingos ◽  
K Pavlou ◽  
...  
Keyword(s):  
Spatial Clustering ◽  
Accretionary Prism ◽  
Velocity Model ◽  
Strike Slip ◽  
Double Difference ◽  
Strain Partitioning ◽  
Transform Fault ◽  
Fault Plane Solutions ◽  
The North ◽  
Waveform Modelling

Summary The properties of the Mw = 6.7 earthquake that took place on 25 October 2018, 22:54:51 UTC, ∼50 km SW of the Zakynthos Island, Greece, are thoroughly examined. The main rupture occurred on a dextral strike-slip, low-angle, east-dipping fault at a depth of 12 km, as determined by teleseismic waveform modelling. Over 4000 aftershocks were manually analysed for a period of 158 days. The events were initially located with an optimal 1D velocity model and then relocated with the double-difference method to reveal details of their spatial distribution. The latter spreads in an area spanning 80 km NNW-SSE and ∼55 km WSW-ENE. Certain parts of the aftershock zone present strong spatial clustering, mainly to the north, close to Zakynthos Island, and at the southernmost edge of the sequence. Focal mechanisms were determined for 61 significant aftershocks using regional waveform modelling. The results revealed characteristics similar to the mainshock, with few aftershocks exhibiting strike-slip faulting at steeper dip angles, possibly related to splay faults on the accretionary prism. The slip vectors that correspond to the east-dipping planes are compatible with the long-term plate convergence and with the direction of coseismic displacement on the Zakynthos Island. Fault-plane solutions in the broader study area were inverted for the determination of the regional stress-field. The results revealed a nearly horizontal, SW-NE to E-W-trending S1 and a more variable S3 axis, favouring transpressional tectonics. Spatial clusters at the northern and southern ends of the aftershock zone coincide with the SW extension of sub-vertical along-dip faults of the segmented subducting slab. The mainshock occurred in an area where strike-slip tectonics, related to the Cephalonia Transform Fault and the NW Peloponnese region, gradually converts into reverse faulting at the western edge of the Hellenic subduction. Plausible scenarios for the 2018 Zakynthos earthquake sequence include a rupture on the subduction interface, provided the slab is tilted eastwards in that area, or the reactivation of an older east-dipping thrust as a low-angle strike-slip fault that contributes to strain partitioning.

scholarly journals Structure-controlled asperities of the 1920 Haiyuan M8.5 and 1927 Gulang M8 earthquakes, NE Tibet, China, revealed by high-resolution seismic tomography

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Quan Sun ◽  
Shunping Pei ◽  
Zhongxiong Cui ◽  
Yongshun John Chen ◽  
Yanbing Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Tomography ◽  
High Velocity ◽  
Three Dimensional ◽  
Large Earthquake ◽  
Velocity Model ◽  
Tectonic Stress ◽  
Double Difference ◽  
Source Regions ◽  
Large Earthquakes

AbstractDetailed crustal structure of large earthquake source regions is of great significance for understanding the earthquake generation mechanism. Numerous large earthquakes have occurred in the NE Tibetan Plateau, including the 1920 Haiyuan M8.5 and 1927 Gulang M8 earthquakes. In this paper, we obtained a high-resolution three-dimensional crustal velocity model around the source regions of these two large earthquakes using an improved double-difference seismic tomography method. High-velocity anomalies encompassing the seismogenic faults are observed to extend to depths of 15 km, suggesting the asperity (high-velocity area) plays an important role in the preparation process of large earthquakes. Asperities are strong in mechanical strength and could accumulate tectonic stress more easily in long frictional locking periods, large earthquakes are therefore prone to generate in these areas. If the close relationship between the aperity and high-velocity bodies is valid for most of the large earthquakes, it can be used to predict potential large earthquakes and estimate the seismogenic capability of faults in light of structure studies.

Rayleigh Wave Dispersion Curve Inversion with the Artificial Bee Colony Algorithm

2021 ◽  
Vol 26 (2) ◽  
pp. 99-110
Author(s):  
Xin Wang ◽  
Hongyan Shen ◽  
Xinxin Li ◽  
Qin Li ◽  
Daoyuan Wang
Keyword(s):  
Rayleigh Wave ◽  
Dispersion Curve ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Wave Dispersion ◽  
Velocity Model ◽  
S Wave ◽  
Bee Colony ◽  
Search Optimization ◽  
Rayleigh Wave Dispersion

Rayleigh wave dispersion curve inversion is a non-linear iterative optimization process with multi-parameter and multi-extrema. It is difficult to carry out inversion and reconstruction of stratigraphic parameters quickly and accurately with a single linear or non-linear inversion for the data processing of Rayleigh waves with complex seismic geological conditions. We proposed a new method that combines artificial bee colony algorithm (ABC) and damped least squares algorithm (DLS) to invert Rayleigh wave dispersion curve. First, food sources are initialized in a large scale of the model based on the prior geological information. Then, after three kinds of bee operators (employed bees, onlooker bees and scout bees) transform each other and perform search optimization with several iterations, the targets are converged near the optimal solution to obtain an initial S-wave velocity model. Finally, the final S-wave velocity model is obtained by local optimization of DLS inversion with fast convergence and strong stability. The correctness of the method has been verified by one high-velocity interlayer model, and it was further applied to a real Rayleigh wave dataset. The results show that our method not only absorbs the advantages of ABC global search optimization and strong adaptability, but also makes full use of the advantages of DLS inversion, such as high accuracy and fast convergence speed. The inversion strategy can effectively suppress the inversion falling into local extrema, get rid of the dependence on an initial model, enhance the inversion stability, further improve the convergence speed and inversion accuracy, while has good anti-noise ability.

Passive seismic tomography using recorded microseismicity: Application to mining-induced seismicity

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. B41-B57 ◽  
Author(s):  
Himanshu Barthwal ◽  
Mirko van der Baan
Keyword(s):  
Seismic Tomography ◽  
Velocity Model ◽  
P Wave ◽  
Double Difference ◽  
Lateral Velocity ◽  
Study Region ◽  
Arrival Times ◽  
3D Velocity Model ◽  
Passive Seismic ◽  
Dip Angle

Microseismicity is recorded during an underground mine development by a network of seven boreholes. After an initial preprocessing, 488 events are identified with a minimum of 12 P-wave arrival-time picks per event. We have developed a three-step approach for P-wave passive seismic tomography: (1) a probabilistic grid search algorithm for locating the events, (2) joint inversion for a 1D velocity model and event locations using absolute arrival times, and (3) double-difference tomography using reliable differential arrival times obtained from waveform crosscorrelation. The originally diffusive microseismic-event cloud tightens after tomography between depths of 0.45 and 0.5 km toward the center of the tunnel network. The geometry of the event clusters suggests occurrence on a planar geologic fault. The best-fitting plane has a strike of 164.7° north and dip angle of 55.0° toward the west. The study region has known faults striking in the north-northwest–south-southeast direction with a dip angle of 60°, but the relocated event clusters do not fall along any mapped fault. Based on the cluster geometry and the waveform similarity, we hypothesize that the microseismic events occur due to slips along an unmapped fault facilitated by the mining activity. The 3D velocity model we obtained from double-difference tomography indicates lateral velocity contrasts between depths of 0.4 and 0.5 km. We interpret the lateral velocity contrasts in terms of the altered rock types due to ore deposition. The known geotechnical zones in the mine indicate a good correlation with the inverted velocities. Thus, we conclude that passive seismic tomography using microseismic data could provide information beyond the excavation damaged zones and can act as an effective tool to complement geotechnical evaluations.

Three-dimensional lithospheric S wave velocity model of the NE Tibetan Plateau and western North China Craton

2017 ◽  
Vol 122 (8) ◽  
pp. 6703-6720 ◽  
Author(s):  
Xingchen Wang ◽  
Yonghua Li ◽  
Zhifeng Ding ◽  
Lupei Zhu ◽  
Chunyong Wang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Wave Velocity ◽  
North China Craton ◽  
North China ◽  
Three Dimensional ◽  
Velocity Model ◽  
S Wave ◽  
Ne Tibetan Plateau

scholarly journals Antarctic Upper Mantle Rheology

2021 ◽  
pp. M56-2020-19
Author(s):  
E. R. Ivins ◽  
W. van der Wal ◽  
D. A. Wiens ◽  
A. J. Lloyd ◽  
L. Caron
Keyword(s):  
Wave Velocity ◽  
Upper Mantle ◽  
Effective Viscosity ◽  
Seismic Velocity ◽  
Imaging Techniques ◽  
Three Dimensional ◽  
Velocity Model ◽  
Mantle Flow ◽  
S Wave ◽  
Velocity Changes

AbstractThe Antarctic mantle and lithosphere are known to have large lateral contrasts in seismic velocity and tectonic history. These contrasts suggest differences in the response time scale of mantle flow across the continent, similar to those documented between the northeastern and southwestern upper mantle of North America. Glacial isostatic adjustment and geodynamical modeling rely on independent estimates of lateral variability in effective viscosity. Recent improvements in imaging techniques and the distribution of seismic stations now allow resolution of both lateral and vertical variability of seismic velocity, making detailed inferences about lateral viscosity variations possible. Geodetic and paleo sea-level investigations of Antarctica provide quantitative ways of independently assessing the three-dimensional mantle viscosity structure. While observational and causal connections between inferred lateral viscosity variability and seismic velocity changes are qualitatively reconciled, significant improvements in the quantitative relations between effective viscosity anomalies and those imaged by P- and S-wave tomography have remained elusive. Here we describe several methods for estimating effective viscosity from S-wave velocity. We then present and compare maps of the viscosity variability beneath Antarctica based on the recent S-wave velocity model ANT-20 using three different approaches.

Sign in / Sign up

Export Citation Format

Share Document