Microseismic and Induced Seismicity Monitoring and Tomography of the Changning-Zhaotong shale gas play in China using dense nodal arrays

2020 ◽  
Author(s):  
Wen Yang ◽  
Junlun Li ◽  
Yuyang Tan ◽  
Yaxing Li ◽  
Jiawei Qian ◽  
...  
Keyword(s):  
Hydraulic Fracturing ◽  
Shale Gas ◽  
Velocity Structure ◽  
Double Difference ◽  
Steady Increase ◽  
S Wave ◽  
Two Phase ◽  
Arrival Times ◽  
Seismicity Monitoring ◽  
Tomography Method

<p>With the development of shale gas in the Changning-Zhaotong play in the southern Sichuan basin of China, which is the largest shale gas prospect in China, the frequency and magnitude of earthquakes in this region have increased significantly in recent years. For example, a M5.7 earthquake occurred on December 16, 2018, and a M5.3 earthquake on January 6, 2019 in addition to many M4.0+ earthquakes in this area. Some studies argue the large magnitude earthquakes are triggered by hydraulic fracturing in for the local shale gas development, which commenced in 2011. The frequency of the earthquake occurrence has been on steady increase in the past few years that local residents often reported felt quakes. To further understand the correlation between the shale gas development and local seismic activity, we conducted a two-phase dense array seismic monitoring with about 200 Zland 3C and SmartSolo 3C 5 Hz seismic nodes, from late February to early May, 2019 for a period of 70 days. The survey consists of roughly 340 deployments at 240 sites, with an average interstation distance of 1.5 km, covering 500 km<sup>2</sup> in total. We have processed seismic records from late February to early April, 2019 (phase I), and picked some 600,000 P- and S-wave arrival times from 4385 detected local earthquakes. The earthquake hypocenters and the subsurface velocity structure of the Changning-Zhaotong area are inverted for using the double-difference tomography method. The relocation results show that the majority of hypocenters were located at depths ranging from 1.0km to 4.0km, in the proximity of the horizontal hydraulic fracturing wells. The tomographic results (< 3 km) correlate well with the known surface geological units, and most earthquakes occurred along the velocity discontinuities, likely characterizing a large hidden fault which, interestingly, is where the January 2019 M5.3 occurred. Our study is very important for understanding the seismic potentials in this area, and should provide useful information for the shale gas development in this region and other areas in China with similar geological, tectonic and stress conditions.</p>

Tuning S-Wave Velocity Structure of Deep Sedimentary Layers in the Shimousa Region of the Kanto Basin, Japan, Using Autocorrelation of Strong-Motion Records

2020 ◽  
Vol 110 (6) ◽  
pp. 2882-2891
Author(s):  
Kosuke Chimoto ◽  
Hiroaki Yamanaka
Keyword(s):  
Wave Velocity ◽  
Velocity Structure ◽  
Strong Motion ◽  
S Wave ◽  
Reflected Waves ◽  
Arrival Times ◽  
Strong Motion Records ◽  
Kanto Basin ◽  
Determination Of Parameters

ABSTRACT The autocorrelation of ambient noise is used to capture reflected waves for crustal and sedimentary structures. We applied autocorrelation to strong-motion records to capture the reflected waves from sedimentary layers and used them for tuning the S-wave velocity structure of these layers. Because a sedimentary-layered structure is complicated and generates many reflected waves, it is important to identify the boundary layer from which the waves reflected. We used spectral whitening during autocorrelation analysis to capture the reflected waves from the seismic bedrock with an appropriate smoothing band, which controls the wave arrival from the desired layer boundary. The effect of whitening was confirmed by the undulation frequency observed in the transfer function of the sedimentary layers. After careful determination of parameters for spectral whitening, we applied data processing to the strong-motion records observed at the stations in the Shimousa region of the Kanto Basin, Japan, to estimate the arrival times of the reflected waves. The arrival times of the reflected waves were found to be fast in the northern part of the Shimousa region and slow in the western and southern parts. These arrival times are consistent with those obtained using existing models. Because we observed a slight difference in the arrival times, the autocorrelation function at each station was used for tuning the S-wave velocity structure model of the sedimentary layers using the inversion technique. The tuned models perfectly match the autocorrelation functions in terms of the arrival time of the reflected waves from the seismic bedrock.

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.

Modeling guided waves to constrain the velocity structure of the oceanic crust in the subduction zone of eastern Alaska

2020 ◽  
Author(s):  
Xiaoyu Guan ◽  
Yuanze Zhou ◽  
Takashi Furumura
Keyword(s):  
Subduction Zone ◽  
Oceanic Crust ◽  
High Frequency ◽  
Subduction Zones ◽  
Guided Waves ◽  
Velocity Structure ◽  
Guided Wave ◽  
S Wave ◽  
Arrival Times ◽  
Velocity Models

<p>Fitting subduction zone guided waves with synthetics is an ideal choice for studying the velocity structure of the oceanic crust. After an earthquake occurs in subduction zones, seismic waves can be trapped in the low-velocity oceanic crust and propagated as guided waves. The arrival time and frequency characteristics of the guided waves can be used to image the velocity structure of the oceanic crust. The analysis and modeling based on guided wave observations provide a rare opportunity to understand the velocity structure of the oceanic crust and the variations in oceanic crustal materials during the subduction process.</p><p>High-frequency guided waves have been observed in the subduction zone of eastern Alaska. On several sections, observed seismograms recorded by seismic stations show low-frequency (<2Hz) onsets ahead of the main high-frequency (>2Hz) guided waves. Differences in the arrival times and dispersion characteristics of seismic phases are related to the velocity structure of the oceanic crust, and the characteristics of coda waves are related to the distribution of elongated scatters in the oceanic crust. Through fitting the observed broadband waveforms and synthetics modeled with the 2-D FDM (Finite Difference Method), we obtain the preferred oceanic crustal velocity models for several sections in the subduction zone of eastern Alaska. The preferred models can explain the seismic phase arrival times, dispersions, and coda characteristics in the observed waveforms. With the obtained P- and S- wave models of velocity structures on several sections, the material compositions they represent are deduced, and the variations of oceanic crustal materials during subducting can be understood. This provides new evidence for studying the details of the subduction process in the subduction zone of eastern Alaska.</p>

scholarly journals Velocity structure and the role of fluids in the West Bohemia Seismic Zone

2014 ◽  
Vol 6 (1) ◽  
pp. 511-534
Author(s):  
C. Alexandrakis ◽  
M. Calò ◽  
F. Bouchaala ◽  
V. Vavryčuk
Keyword(s):  
Velocity Structure ◽  
Weighted Average ◽  
Tectonic Stress ◽  
Double Difference ◽  
Seismic Zone ◽  
The West ◽  
Fluid Concentration ◽  
West Bohemia ◽  
Basic Characteristics ◽  
Tomography Method

Abstract. In this study, we apply the double-difference tomography method to investigate the detailed 3-D structure within and around the Nový Kostel seismic zone, an area in the Czech Republic known for frequent occurrences of earthquake swarms. We use data from the extensively analyzed 2008 swarm, which has known focal mechanisms, principal faults, tectonic stress, source migration and other basic characteristics. We selected about 500 microearthquakes recorded at 22 local seismic stations of the West Bohemia Network (WEBNET). Applying double-difference tomography, combined with Weighted Average Model post-processing to correct for parameter dependence effects, we produce and interpret 3-D models of the Vp-to-Vs ratio (Vp/Vs) in and around the focal zone. The modeled Vp-to-Vs ratio shows several distinct structures, namely an area of high Vp-to-Vs ratio correlating with the microearthquakes, and a layer of low values directly above it. These structures may reflect changes in lithology and/or fluid concentration. The overlaying low Vp-to-Vs ratio layer coincides with high density metamorphic unit associated with the Fichtelgebirge (Smrčiny) granitic intrusion. It is possible that the base of the layer acts as a fluid trap, resulting in the observed periodic swarms.

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).

Double-difference tomography of P- and S-wave velocity structure beneath the western part of Java, Indonesia

2019 ◽  
Vol 32 (1) ◽  
pp. 12-25 ◽  
Author(s):  
Shindy Rosalia ◽  
◽  
Sri Widiyantoro ◽  
Andri Dian Nugraha ◽  
Pepen Supendi ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Velocity Structure ◽  
Double Difference ◽  
S Wave

scholarly journals Seismic Imaging and Seismicity Analysis in Beijing-Tianjin-Tangshan Region

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Xiangwei Yu ◽  
Wenbo Zhang ◽  
Yun-tai Chen
Keyword(s):  
Focal Depth ◽  
Velocity Model ◽  
Double Difference ◽  
Low Velocity ◽  
Arrival Times ◽  
Velocity Anomaly ◽  
The North ◽  
Tomographic Method ◽  
Vertical Slice ◽  
Tomography Method

In this study a new tomographic method is applied to over 43,400 high-quality absolute direct P arrival times and 200,660 relative P arrival times to determine detailed 3D crustal velocity structures as well as the absolute and relative hypocenter parameters of 2809 seismic events under the Beijing-Tianjin-Tangshan region. The inferred velocity model of the upper crust correlates well with the surface geological and topographic features in the BTT region. In the North China Basin, the depression and uplift areas are imaged as slow and fast velocities, respectively. After relocation, the double-difference tomography method provides a sharp picture of the seismicity in the BTT region, which is concentrated along with the major faults. A broad low-velocity anomaly exists in Tangshan and surrounding area from 20 km down to 30 km depth. Our results suggest that the top boundary of low-velocity anomalies is at about 25.4 km depth. The event relocations inverted from double-difference tomography are clusted tightly along the Tangshan-Dacheng Fault and form three clusters on the vertical slice. The maximum focal depth after relocation is about 25 km depth in the Tangshan area.

scholarly journals Passive seismic tomography using induced seismicity at a petroleum field in Oman

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCB57-WCB69 ◽  
Author(s):  
Haijiang Zhang ◽  
Sudipta Sarkar ◽  
M. Nafi Toksöz ◽  
H. Sadi Kuleli ◽  
Fahad Al-Kindy
Keyword(s):  
Seismic Tomography ◽  
Induced Seismicity ◽  
Gas Content ◽  
Double Difference ◽  
Depth Range ◽  
Arrival Times ◽  
Monitoring Wells ◽  
Passive Seismic ◽  
Petroleum Field ◽  
Tomography Method

A borehole network consisting of five monitoring wells monitored the induced seismicity at a producing petroleum field for about [Formula: see text]. Nearly 5400 microseismic events were analyzed and used to image the reservoir based on a new double-difference (DD) seismic tomography. The DD tomography method simultaneously solved for event locations and [Formula: see text], [Formula: see text], and [Formula: see text] models using absolute and differential P, S, and S-P arrival times. Microseismicity in the field was caused primarily by compaction of the reservoir in and above the gas-bearing formation and was distributed along the two major northeast-southwest faults in the field. The model resolution analysis based on the checkerboard test and the resolution matrix showed that the central part of the model was resolved relatively well for the depth range of [Formula: see text]. Clear velocity contrasts were imaged across most parts of the two northeast-southwest faults. The [Formula: see text] ratio estimates from the tomographic inversion were low [Formula: see text] in the shallow depth range, likely caused by rock type and gas content; but they were large [Formula: see text] in the deeper part of the model, likely because of fluid-saturated formation. Thus, seismic tomography shows great potential for reservoir imaging and property estimation using induced seismicity.

Multidomain Two-Phase Flow Model to Study the Impacts of Hydraulic Fracturing on Shale Gas Production

2020 ◽  
Vol 34 (4) ◽  
pp. 4273-4288 ◽  
Author(s):  
Guanglei Cui ◽  
Yuling Tan ◽  
Tianyu Chen ◽  
Xia-Ting Feng ◽  
Derek Elsworth ◽  
...  
Keyword(s):  
Hydraulic Fracturing ◽  
Shale Gas ◽  
Flow Model ◽  
Two Phase Flow ◽  
Gas Production ◽  
Phase Flow ◽  
Two Phase

scholarly journals A CROSS-CORRELATION TECHNIQUE FOR RELOCATION OF SEISMICITY IN THE WESTERN CORINTH RIFT

2017 ◽  
Vol 43 (4) ◽  
pp. 2015
Author(s):  
V. Kapetanidis ◽  
P. Papadimitriou ◽  
K. Makropoulos
Keyword(s):  
Cross Correlation ◽  
Time Lag ◽  
P Wave ◽  
Double Difference ◽  
Correlation Technique ◽  
S Wave ◽  
Waveform Data ◽  
Arrival Times ◽  
Linkage Algorithm ◽  
Seismogenic Structures

Local seismological networks provide data that allow the location of microearthquakes which otherwise would be dismissed due to low magnitudes and low signal-to-noise ratios of their seismic signals. The Corinth Rift Laboratory (CRL) network, installed in the western Corinth rift, has been providing digital waveform data since 2000. In this work, a semi-automatic picking technique has been applied which exploits the similarity between waveforms of events that have occurred in approximately the same area of an active fault. Similarity is measured by the crosscorrelation maxi-mum of full signals. Events with similar waveforms are grouped in multiplet clusters using the nearest-neighbour linkage algorithm. Manually located events act as masters, while automatically located events of each multiplet cluster act as slaves. By cross-correlating the P-wave or S-wave segments of a master event with the corresponding segments of each of its slave events, after appropriately aligning their offsets, the measured time-lag at the cross-correlation maximum can be subtracted from the arrival-time of the slave event. After the correction of the arrival-times, a double-difference technique is applied to the modified catalogue to further improve the locations of clusters and distinguish the active seismogenic structures in the tectonically complex Western Corinth rift.

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