scholarly journals The 30 June 2017 North Sea Earthquake: Location, Characteristics, and Context

2020 ◽  
Vol 110 (2) ◽  
pp. 937-952
Author(s):  
Annie E. Jerkins ◽  
Hasbi Ash Shiddiqi ◽  
Tormod Kværna ◽  
Steven J. Gibbons ◽  
Johannes Schweitzer ◽  
...  
Keyword(s):  
North Sea ◽  
Moment Tensor ◽  
P Wave ◽  
Double Difference ◽  
High Signal ◽  
Seismic Events ◽  
S Wave ◽  
Surface Reflection ◽  
Moment Tensor Solution ◽  
Seismicity Pattern

ABSTRACT The Mw 4.5 southern Viking graben earthquake on 30 June 2017 was one of the largest seismic events in the Norwegian part of the North Sea during the last century. It was well recorded on surrounding broadband seismic stations at regional distances, and it generated high signal-to-noise ratio teleseismic P arrivals at up to 90° with good azimuthal coverage. Here, the teleseismic signals provide a unique opportunity to constrain the event hypocenter. Depth phases are visible globally and indicate a surface reflection in the P-wave coda some 4 s after the initial P arrival, giving a much better depth constraint than regional S-P time differences provide. Moment tensor inversion results in a reverse thrust faulting mechanism. The fit between synthetic and observed surface waves at regional distances is improved by including a sedimentary layer. Synthetic teleseismic waveforms generated based on the moment tensor solution, and a near-source 1D velocity model indicates a depth of 7 km. Correlation detectors using the S-wave coda from the main event were run on almost 30 yr of continuous multichannel seismic data searching for repeating signals. In addition to a magnitude 1.9 aftershock 33 min later, and a few magnitude ∼1 events in the following days, a magnitude 2.5 earthquake on 13 November 2016 was the only event found to match the 30 June 2017 event well. Using double-difference techniques, we find that the two largest events are located within 1 km of the main event. We present a Bayesloc probabilistic multiple event location including the 30 June event and all additional seismic events in the region well recorded on the regional networks. The Bayesloc relocation gave a more consistent seismicity pattern and moved several of the events more toward the west. The results of this study are also discussed within the regional seismotectonic frame of reference.

An exact anelastic model for the free-surface relfection of P and S-I waves

1989 ◽  
Vol 79 (3) ◽  
pp. 842-859
Author(s):  
R. D. Borcherdt ◽  
G. Glassmoyer
Keyword(s):  
Free Surface ◽  
Volumetric Strain ◽  
Major Axis ◽  
P Wave ◽  
Reflection Coefficients ◽  
S Wave ◽  
Low Loss ◽  
Surface Reflection ◽  
Pierre Shale ◽  
Homogeneous Wave

Abstract Exact anelastic solutions incorporating inhomogeneous waves are used to model numerically S-I and P waves incident on the free surface of a low-loss anelastic half-space. Anelastic free-surface reflection coefficients are computed for the volumetric strain and displacement components of inhomogeneous wave fields. For the problem of an incident homogeneous S-I wave in Pierre shale, the largest strain and displacement amplitudes for the reflected P wave occur at angles of incidence for which the particle motion for the reflected inhomogeneous P wave is elliptical (minor/major axis = 0.6), the specific absorption (QP−1) is greater (300 per cent) and the velocity is less (25 per cent) than those for a corresponding homogeneous P wave, the direction of phase propagation is not parallel to the free surface, and the amplitude of the wave shows a significant increase with depth (6 per cent in one wavelength). Energy reflection coefficients computed for this low-loss anelastic model show that energy flow due to interaction of the incident and reflected waves reach maxima (30 per cent of the incident energy) near large but nongrazing angles of incidence. For the problem of an incident homogeneous P wave in Pierre shale, the inhomogeneity of the reflected S wave is shown not to contribute to significant variations in wave field characteristics over those that would be expected for a homogeneous wave.

Shear‐wave velocity and density estimation from PS-wave AVO analysis: Application to an OBS dataset from the North Sea

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1446-1454 ◽  
Author(s):  
Side Jin ◽  
G. Cambois ◽  
C. Vuillermoz
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Random Noise ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Avo Analysis ◽  
The North ◽  
Avo Inversion ◽  
The North Sea

S-wave velocity and density information is crucial for hydrocarbon detection, because they help in the discrimination of pore filling fluids. Unfortunately, these two parameters cannot be accurately resolved from conventional P-wave marine data. Recent developments in ocean‐bottom seismic (OBS) technology make it possible to acquire high quality S-wave data in marine environments. The use of (S)-waves for amplitude variation with offset (AVO) analysis can give better estimates of S-wave velocity and density contrasts. Like P-wave AVO, S-wave AVO is sensitive to various types of noise. We investigate numerically and analytically the sensitivity of AVO inversion to random noise and errors in angles of incidence. Synthetic examples show that random noise and angle errors can strongly bias the parameter estimation. The use of singular value decomposition offers a simple stabilization scheme to solve for the elastic parameters. The AVO inversion is applied to an OBS data set from the North Sea. Special prestack processing techniques are required for the success of S-wave AVO inversion. The derived S-wave velocity and density contrasts help in detecting the fluid contacts and delineating the extent of the reservoir sand.

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.

scholarly journals Closing crack earthquakes within the Krafla caldera, North Iceland

2016 ◽  
Vol 207 (2) ◽  
pp. 1137-1141 ◽  
Author(s):  
Zoë K. Mildon ◽  
David J. Pugh ◽  
Jon Tarasewicz ◽  
Robert S. White ◽  
Bryndís Brandsdóttir
Keyword(s):  
Signal To Noise Ratio ◽  
Moment Tensor ◽  
Full Range ◽  
P Wave ◽  
High Signal ◽  
Closing Crack ◽  
Double Couple ◽  
Moment Tensor Analysis ◽  
First Arrival ◽  
Microseismic Activity

Abstract Moment tensor analysis with a Bayesian approach was used to analyse a non-double-couple (non-DC) earthquake (Mw ∼ 1) with a high isotropic (implosive) component within the Krafla caldera, Iceland. We deduce that the earthquake was generated by a closing crack at depth. The event is well located, with high signal-to-noise ratio and shows dilatational P-wave first arrivals at all stations where the first arrival can be picked with confidence. Coverage of the focal sphere is comprehensive and the source mechanism stable across the full range of uncertainties. The non-DC event lies within a cluster of microseismic activity including many DC events. Hence, we conclude that it is a true non-DC closing crack earthquake as a result of geothermal utilization and observed magma chamber deflation in the region at present.

Downhole seismic logging for high‐resolution reflection surveying in unconsolidated overburden

Geophysics ◽  
1998 ◽  
Vol 63 (4) ◽  
pp. 1371-1384 ◽  
Author(s):  
J. A. Hunter ◽  
S. E. Pullan ◽  
R. A. Burns ◽  
R. L. Good ◽  
J. B. Harris ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Velocity ◽  
P Wave ◽  
Unconsolidated Sediments ◽  
Dynamic Shear Modulus ◽  
S Wave ◽  
Interface Shear ◽  
Similar Frequency ◽  
Surface Reflection ◽  
First Arrival

Downhole seismic velocity logging techniques have been developed and applied in support of high‐resolution reflection seismic surveys. For shallow high‐resolution reflection surveying within unconsolidated overburden, velocity‐depth control can sometimes be difficult to achieve; as well, unambiguous correlation of reflections with overburden stratigraphy is often problematic. Data obtained from downhole seismic logging can provide accurate velocity‐depth functions and directly correlate seismic reflections to depth. The methodologies described in this paper are designed for slimhole applications in plastic‐cased boreholes (minimum ID of 50 mm) and with source and detector arrays that yield similar frequency ranges and vertical depth resolutions as the surface reflection surveys. Compressional- (P-) wave logging uses a multichannel hydrophone array with 0.5-m detector spacings in a fluid‐filled borehole and a high‐frequency, in‐hole shotgun source at the surface. Overlapping array positions downhole results in redundant first‐arrival data (picked using interactive computer techniques), which can be processed to provide accurate interval velocities. The data also can be displayed as a record suite, showing reflections and directly correlating reflection events with depths. Example applications include identification of gas zones, lithological boundaries within unconsolidated sediments, and the overburden‐bedrock interface. Shear- (S-) wave logging uses a slimhole, well‐locked, three‐component (3-C) geophone pod and a horizontally polarized, hammer‐and‐loaded‐plate source at ground surface. The pod is moved in successive 0.5- or 1-m intervals downhole with no redundancy of overlapping data as in the P-wave method. First‐arrival data can be obtained by picking the crossover onset of polarized energy or by closely examining particle‐motion plots using all three components of motion. In unconsolidated sediments, shear‐wave velocity contrasts can be associated with changes in material density or dynamic shear modulus, which in turn can be related to consolidation. Example applications include identification of a lithological boundary for earthquake hazard applications and mapping massive ice within permafrost materials.

scholarly journals Inferring microseismic source mechanisms and in situ stresses during triaxial deformation of a North-Sea-analogue sandstone

2019 ◽  
Vol 49 ◽  
pp. 85-93
Author(s):  
Luke Griffiths ◽  
Jérémie Dautriat ◽  
Ismael Vera Rodriguez ◽  
Kamran Iranpour ◽  
Guillaume Sauvin ◽  
...  
Keyword(s):  
North Sea ◽  
Acoustic Emissions ◽  
Stress Conditions ◽  
P Wave ◽  
Co2 Injection ◽  
Fracture Mechanisms ◽  
High Signal ◽  
In Situ Stresses ◽  
Microseismic Activity

Abstract. Monitoring microseismic activity provides a window through which to observe reservoir deformation during hydrocarbon and geothermal energy production, or CO2 injection and storage. Specifically, microseismic monitoring may help constrain geomechanical models through an improved understanding of the location and geometry of faults, and the stress conditions local to them. Such techniques can be assessed in the laboratory, where fault geometries and stress conditions are well constrained. We carried out a triaxial test on a sample of Red Wildmoor sandstone, an analogue to a weak North Sea reservoir sandstone. The sample was coupled with an array of piezo-transducers, to measure ultrasonic wave velocities and monitor acoustic emissions (AE) – sample-scale microseismic activity associated with micro-cracking. We calculated the rate of AE, localised the AE events, and inferred their moment tensor from P-wave first motion polarities and amplitudes. We applied a biaxial decomposition to the resulting moment tensors of the high signal-to-noise ratio events, to provide nodal planes, slip vectors, and displacement vectors for each event. These attributes were then used to infer local stress directions and their relative magnitudes. Both the AE fracture mechanisms and the inferred stress conditions correspond to the sample-scale fracturing and applied stresses. This workflow, which considers fracture models relevant to the subsurface, can be applied to large-scale geoengineering applications to obtain fracture mechanisms and in-situ stresses from recorded microseismic data.

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.

Development on Seismic Sensor System with MEMS Technology for Elevator’s Seismic Condition

2015 ◽  
Vol 713-715 ◽  
pp. 1009-1014
Author(s):  
Zhi Qun Luo ◽  
Shao Lun Huang ◽  
Jian Ru Wan
Keyword(s):  
Practical Problem ◽  
Hardware Design ◽  
P Wave ◽  
Sensor System ◽  
Seismic Events ◽  
Design Consideration ◽  
Seismic Evaluation ◽  
S Wave ◽  
Mems Technology ◽  
Evaluation Algorithm

A large amount of elevators ruined in seismic events since sudden vibrations are bursting when elevator’s cars or counterweights are running. To solve this practical problem, this paper prospered a seismic sensor system with MEMS technology specializing for elevators. The fatal parts are discussed detailed including hardware design consideration, software improvement of sensor accuracy and seismic evaluation algorithm. Finally, two parts of experiments about P-wave and S-wave were verified successfully. To some extents, it’s reliable, suitable and affordable for domestic elevator’s safety on earthquake abrupt occurrence.

Hypocenter and Magnitude Analysis of Aftershocks of the 2018 Lombok, Indonesia, Earthquakes Using Local Seismographic Networks

2020 ◽  
Vol 91 (4) ◽  
pp. 2152-2162 ◽  
Author(s):  
Annisa Trisnia Sasmi ◽  
Andri Dian Nugraha ◽  
Muzli Muzli ◽  
Sri Widiyantoro ◽  
Zulfakriza Zulfakriza ◽  
...  
Keyword(s):  
Elevated Temperatures ◽  
Detection Threshold ◽  
Double Difference ◽  
Type Model ◽  
Northwestern Part ◽  
S Wave ◽  
Waveform Data ◽  
Arrival Times ◽  
Seismicity Pattern ◽  
Rupture Area

Abstract The island of Lombok in Indonesia is located between the Indo-Australian and Eurasian subduction trenches and the Flores back-arc thrust, making it vulnerable to earthquakes. On 29 July 2018, a significant earthquake Mw 6.4 shook this region and was followed by series of major earthquakes (Mw>5.8) on 5, 9, and 19 August, which led to severe damage in the northern Lombok area. In this study, we attempt to reveal the possible cause of the sequences of the 2018 Lombok earthquakes based on aftershock monitoring data. Twenty stations were deployed to record earthquake waveform data from 4 August to 9 September 2018. In total, 3259 events were identified using 28,728 P- and 20,713 S-wave arrival times during the monitoring. The aftershock hypocenters were determined using a nonlinear approach and relocated using double-difference method. The moment magnitude (Mw) of each event was determined by fitting the displacement spectrum amplitude using a Brune-type model. The magnitudes of the aftershocks range from Mw 1.7 to 6.7. The seismicity pattern reveals three clusters located in the Flores oceanic crust, which fit well with the occurrences of the four events with Mw>6. We interpret these events as the main rupture area of the 2018 Lombok earthquake sequence. Furthermore, an aseismic zone in the vicinity of Rinjani extending toward the northwestern part of Lombok was observed. We propose that the crust in this area has elevated temperatures and is highly fractured thus inhibiting the generation of large earthquakes. The aseismic nature is therefore an artifact of the detection threshold of our network (Mw 4.6).

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