Probabilistic Moment Tensor Inversion for Hydrocarbon-Induced Seismicity in the Groningen Gas Field, The Netherlands, Part 1: Testing

2020 ◽  
Vol 110 (5) ◽  
pp. 2095-2111 ◽  
Author(s):  
Daniela Kühn ◽  
Sebastian Heimann ◽  
Marius P. Isken ◽  
Elmer Ruigrok ◽  
Bernard Dost
Keyword(s):  
Input Data ◽  
Moment Tensor ◽  
Good Practice ◽  
Velocity Model ◽  
Moment Tensor Inversion ◽  
Phase Identification ◽  
Moment Tensors ◽  
Velocity Models ◽  
3D Velocity Model ◽  
1D Velocity Model

ABSTRACT Since 1991, induced earthquakes have been observed and linked to gas production in the Groningen field. Recorded waveforms are complex, resulting partly from a Zechstein salt layer overlying the reservoir and partly from free-surface reverberations, internal multiples, interface conversions, guided waves, and waves diving below the reservoir. Therefore, picking of polarities or amplitudes for use in moment tensor inversion is problematic, whereas phase identification may be circumvented employing full waveform techniques. Although moment tensors have become a basic tool to analyze earthquake sources, their uncertainties are rarely reported. We introduce a method for probabilistic moment tensor estimation and demonstrate its use on the basis of a single event within the Groningen field, concentrating on detailed tests of input data and inversion parameters to derive rules of good practice for moment tensor estimation of events recorded in the Groningen field. In addition to the moment tensor, event locations are provided. Hypocenters estimated simultaneously with moment tensors are often less sensitive to uncertainties in crustal structure, which is pertinent for the application to the Groningen field, because the task of relating earthquakes to specific faults hitherto suffers from a limited resolution of earthquake locations. Because of the probabilistic approach, parameter trade-offs, uncertainties, and ambiguities are mapped. In addition, the implemented bootstrap method implicitly accounts for modeling errors affecting every station and phase differently. A local 1D velocity model extracted from a full 3D velocity model yields more consistent results than other models applied previously. For all velocity models and combinations of input data tested, a shift in location of 1 km to the south is observed for the test event compared to the public catalog. A full moment tensor computed employing the local 1D velocity model features negative isotropic components and may be interpreted as normal fault and collapse at reservoir level.

scholarly journals Moving from 1-D to 3-D velocity model: automated waveform-based earthquake moment tensor inversion in the Los Angeles region

2019 ◽  
Vol 220 (1) ◽  
pp. 218-234 ◽  
Author(s):  
Xin Wang ◽  
Zhongwen Zhan
Keyword(s):  
Los Angeles ◽  
Moment Tensor ◽  
Velocity Model ◽  
Primary Control ◽  
Lateral Velocity ◽  
Real Time System ◽  
Moment Tensors ◽  
Velocity Models ◽  
Double Couple ◽  
The Moment

SUMMARY Earthquake focal mechanisms put primary control on the distribution of ground motion, and also bear on the stress state of the crust. Most routine focal mechanism catalogues still use 1-D velocity models in inversions, which may introduce large uncertainties in regions with strong lateral velocity heterogeneities. In this study, we develop an automated waveform-based inversion approach to determine the moment tensors of small-to-medium-sized earthquakes using 3-D velocity models. We apply our approach in the Los Angeles region to produce a new moment tensor catalogue with a completeness of ML ≥ 3.5. The inversions using the Southern California Earthquake Center Community Velocity Model (3D CVM-S4.26) significantly reduces the moment tensor uncertainties, mainly owing to the accuracy of the 3-D velocity model in predicting both the phases and the amplitudes of the observed seismograms. By comparing the full moment tensor solutions obtained using 1-D and 3-D velocity models, we show that the percentages of non-double-couple components decrease dramatically with the usage of 3-D velocity model, suggesting that large fractions of non-double-couple components from 1-D inversions are artifacts caused by unmodelled 3-D velocity structures. The new catalogue also features more accurate focal depths and moment magnitudes. Our highly accurate, efficient and automatic inversion approach can be expanded in other regions, and can be easily implemented in near real-time system.

Aftershock Analysis of the 2018 Mw 7.1 Anchorage, Alaska, Earthquake: Relocations and Regional Moment Tensors

2019 ◽  
Vol 91 (1) ◽  
pp. 114-125 ◽  
Author(s):  
Natalia A. Ruppert ◽  
Avinash Nayak ◽  
Clifford Thurber ◽  
Cole Richards
Keyword(s):  
Moment Tensor ◽  
Hanging Wall ◽  
Velocity Model ◽  
Aftershock Sequence ◽  
Fault Rupture ◽  
Moment Tensors ◽  
3D Velocity Model ◽  
The Moment ◽  
The Relationship ◽  
Alaska Earthquake

Abstract The 30 November 2018 magnitude 7.1 Anchorage earthquake occurred as a result of normal faulting within the lithosphere of subducted Yakutat slab. It was followed by a vigorous aftershock sequence with over 10,000 aftershocks reported through the end of July 2019. The Alaska Earthquake Center produced a reviewed aftershock catalog with a magnitude of completeness of 1.3. This well‐recorded dataset provides a rare opportunity to study the relationship between the aftershocks and fault rupture of a major intraslab event. We use tomoDD algorithm to relocate 2038 M≥2 aftershocks with a regional 3D velocity model. The relocated aftershocks extend over a 20 km long zone between 47 and 57 km depth and are primarily confined to a high VP/VS region. Aftershocks form two clusters, a diffuse southern cluster and a steeply west‐dipping northern cluster with a gap in between where maximum slip has been inferred. We compute moment tensors for the Mw>4 aftershocks using a cut‐and‐paste method and careful selection of regional broadband stations. The moment tensor solutions do not exhibit significant variability or systematic differences between the northern and southern clusters and, on average, agree well with the mainshock fault‐plane parameters. We propose that the mainshock rupture initiated in the Yakutat lower crust or uppermost mantle and propagated both upward into the crust to near its top and downward into the mantle. The majority of the aftershocks are confined to the seismically active Yakutat crust and located both on and in the hanging wall of the mainshock fault rupture.

scholarly journals Seismic Moment Tensor Solutions from GeoNet Data to Provide a Moment Magnitude Scale for New Zealand

2021 ◽  
Author(s):  
◽  
Elizabeth de Joux Robertson
Keyword(s):  
New Zealand ◽  
Seismic Moment ◽  
Moment Tensor ◽  
Velocity Model ◽  
Moment Tensor Inversion ◽  
Moment Magnitude ◽  
Seismic Moment Tensor ◽  
Waveform Data ◽  
Moment Tensors ◽  
The Moment

<p>The aim of this project is to enable accurate earthquake magnitudes (moment magnitude, MW) to be calculated routinely and in near real-time for New Zealand earthquakes. This would be done by inversion of waveform data to obtain seismic moment tensors. Seismic moment tensors also provide information on fault-type. I use a well-established seismic moment tensor inversion method, the Time-Domain [seismic] Moment Tensor Inversion algorithm (TDMT_INVC) and apply it to GeoNet broadband waveform data to generate moment tensor solutions for New Zealand earthquakes. Some modifications to this software were made. A velocity model can now be automatically used to calculate Green's functions without having a pseudolayer boundary at the source depth. Green's functions can be calculated for multiple depths in a single step, and data are detrended and a suitable data window is selected. The seismic moment tensor solution that has either the maximum variance reduction or the maximum double-couple component is automatically selected for each depth. Seismic moment tensors were calculated for 24 New Zealand earthquakes from 2000 to 2005. The Global CMT project has calculated CMT solutions for 22 of these, and the Global CMT project solutions are compared to the solutions obtained in this project to test the accuracy of the solutions obtained using the TDMT_INVC code. The moment magnitude values are close to the Global CMT values for all earthquakes. The focal mechanisms could only be determined for a few of the earthquakes studied. The value of the moment magnitude appears to be less sensitive to the velocity model and earthquake location (epicentre and depth) than the focal mechanism. Distinguishing legitimate seismic signal from background seismic noise is likely to be the biggest problem in routine inversions.</p>

Determination of the time-dependent moment tensor using time-reverse imaging

Geophysics ◽  
2020 ◽  
pp. 1-61
Author(s):  
Claudia Finger ◽  
Erik Saenger
Keyword(s):  
Moment Tensor ◽  
Back Propagation ◽  
Velocity Model ◽  
Source Location ◽  
Geothermal Field ◽  
Time Dependent ◽  
Signal To Noise ◽  
Origin Time ◽  
Moment Tensors ◽  
Velocity Models

An approach is presented to determine the time-dependent moment tensor and the origin time in addition to commonly derived locations of seismic events using time-reverse imaging (TRI). It is crucial to locate and characterize the occurring micro-seismicity without making a priori assumptions about the sources to fully understand the subsurface processes inducing seismicity. Low signal-to-noise ratios often force standard methods to make assumptions about sources or only characterize selected larger-magnitude events. In TRI, micro-earthquakes are located by back propagating the full recorded time-reversed wavefield through a velocity model until it ideally convergences on the source location. Therefore, it is less affected by low signal-to-noise ratios and potentially locates and characterizes most of the events. After distinguishing artificial convergence locations from source locations, the quality of the source location and the moment tensors are derived by recording the stress at the determined source locations during the back propagation of the time-reversed wavefield. A robust workflow is derived using synthetic test cases in a realistic scenario with velocity models that only approximate the true velocity model and/or noisy displacement traces. The influence of a rudimentary velocity model on the source-location accuracy and characterisation is significant. The proposed workflow handles these less-than optimal station distributions and velocity models. Finally, the derived workflow is successfully applied to field data recorded at the geothermal field of Los Humeros, Mexico. Although only a one-dimensional velocity model is currently available, source locations and (time-dependent) moment tensors could be determined for selected events.

scholarly journals Seismic Moment Tensor Solutions from GeoNet Data to Provide a Moment Magnitude Scale for New Zealand

2021 ◽  
Author(s):  
◽  
Elizabeth de Joux Robertson
Keyword(s):  
New Zealand ◽  
Seismic Moment ◽  
Moment Tensor ◽  
Velocity Model ◽  
Moment Tensor Inversion ◽  
Moment Magnitude ◽  
Seismic Moment Tensor ◽  
Waveform Data ◽  
Moment Tensors ◽  
The Moment

<p>The aim of this project is to enable accurate earthquake magnitudes (moment magnitude, MW) to be calculated routinely and in near real-time for New Zealand earthquakes. This would be done by inversion of waveform data to obtain seismic moment tensors. Seismic moment tensors also provide information on fault-type. I use a well-established seismic moment tensor inversion method, the Time-Domain [seismic] Moment Tensor Inversion algorithm (TDMT_INVC) and apply it to GeoNet broadband waveform data to generate moment tensor solutions for New Zealand earthquakes. Some modifications to this software were made. A velocity model can now be automatically used to calculate Green's functions without having a pseudolayer boundary at the source depth. Green's functions can be calculated for multiple depths in a single step, and data are detrended and a suitable data window is selected. The seismic moment tensor solution that has either the maximum variance reduction or the maximum double-couple component is automatically selected for each depth. Seismic moment tensors were calculated for 24 New Zealand earthquakes from 2000 to 2005. The Global CMT project has calculated CMT solutions for 22 of these, and the Global CMT project solutions are compared to the solutions obtained in this project to test the accuracy of the solutions obtained using the TDMT_INVC code. The moment magnitude values are close to the Global CMT values for all earthquakes. The focal mechanisms could only be determined for a few of the earthquakes studied. The value of the moment magnitude appears to be less sensitive to the velocity model and earthquake location (epicentre and depth) than the focal mechanism. Distinguishing legitimate seismic signal from background seismic noise is likely to be the biggest problem in routine inversions.</p>

scholarly journals The waveform inversion of mainshock and aftershock data of the 2006 M6.3 Yogyakarta earthquake

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hijrah Saputra ◽  
Wahyudi Wahyudi ◽  
Iman Suardi ◽  
Ade Anggraini ◽  
Wiwit Suryanto
Keyword(s):  
Joint Inversion ◽  
Body Wave ◽  
Moment Tensor ◽  
Near Field ◽  
Source Parameters ◽  
Waveform Inversion ◽  
Moment Tensor Inversion ◽  
Slip Distribution ◽  
Aftershock Distribution ◽  
Velocity Models

AbstractThis study comprehensively investigates the source mechanisms associated with the mainshock and aftershocks of the Mw = 6.3 Yogyakarta earthquake which occurred on May 27, 2006. The process involved using moment tensor inversion to determine the fault plane parameters and joint inversion which were further applied to understand the spatial and temporal slip distributions during the earthquake. Moreover, coseismal slip distribution was overlaid with the relocated aftershock distribution to determine the stress field variations around the tectonic area. Meanwhile, the moment tensor inversion made use of near-field data and its Green’s function was calculated using the extended reflectivity method while the joint inversion used near-field and teleseismic body wave data which were computed using the Kikuchi and Kanamori methods. These data were filtered through a trial-and-error method using a bandpass filter with frequency pairs and velocity models from several previous studies. Furthermore, the Akaike Bayesian Information Criterion (ABIC) method was applied to obtain more stable inversion results and different fault types were discovered. Strike–slip and dip-normal were recorded for the mainshock and similar types were recorded for the 8th aftershock while the 9th and 16th June were strike slips. However, the fault slip distribution from the joint inversion showed two asperities. The maximum slip was 0.78 m with the first asperity observed at 10 km south/north of the mainshock hypocenter. The source parameters discovered include total seismic moment M0 = 0.4311E + 19 (Nm) or Mw = 6.4 with a depth of 12 km and a duration of 28 s. The slip distribution overlaid with the aftershock distribution showed the tendency of the aftershock to occur around the asperities zone while a normal oblique focus mechanism was found using the joint inversion.

scholarly journals Supplemental Material: Is the Eastern Denali fault still active?

2021 ◽  
Author(s):  
Minhee Choi ◽  
David W. Eaton ◽  
et al.
Keyword(s):  
Hierarchical Clustering ◽  
Moment Tensor ◽  
Velocity Model ◽  
Coulomb Stress ◽  
Stress Inversion ◽  
Moment Tensors ◽  
Stress Calculation ◽  
Denali Fault

Catalog of relocated seismicity, table of moment tensor parameters, detailed methodology of the velocity model, hierarchical clustering, moment tensors, stress inversion, Coulomb stress calculation, and Figures S1–S12.<br>

scholarly journals Accuracy of the moment-tensor inversion of far-field P waves

2019 ◽  
Vol 220 (1) ◽  
pp. 248-256 ◽  
Author(s):  
Yue Kong ◽  
Min Li ◽  
Weimin Chen ◽  
Boqi Kang
Keyword(s):  
Moment Tensor ◽  
Near Field ◽  
Radial Component ◽  
Moment Tensor Inversion ◽  
Far Field ◽  
Field Range ◽  
P Waves ◽  
Moment Tensors ◽  
Nodal Lines ◽  
The Moment

SUMMARY The far-field assumption is widely used and suitable for the moment-tensor inversion in which the source–receiver distance is quite long. However, the description of far field is uncertain and an explicit far-field range is missing. In this study, the explicit far-field range is determined and the errors of moment-tensor solutions produced by the far-field approximation are analysed. The distance, for which the far-field assumption is satisfied and the effect of the near-field term can be ignored, is directionally dependent. For the shear dislocation, in the directions near the nodal lines of the far-field P waves, the far-field distance is heavily dependent on the displacement component used to invert moment tensors. The radial component of displacement, which is parallel to the wave propagation direction, is recommended for the inversion and the corresponding far-field distance is quite short. In the directions far from the nodal lines, the selection of displacement components has little influence on the far-field distance. The maximum far-field distance appears in the directions of the pressure and tensile axes of the source and the value is about 30 wavelengths of radiated waves. Using more receivers (>6) in the moment-tensor inversion can shorten the far-field distance. The effect of the near-field term on the moment-tensor inversion for tensile dislocations and isotropic sources (explosion or implosion) can be ignored. The conclusions obtained in this study are helpful for determining the positions of receivers and evaluating the accuracy of moment-tensor solutions, with far-field assumption being applied in the inversion.

A new 3D velocity model of Central Apennines: insights from 2D/3D geological modelling and earthquake relocation.

2021 ◽  
Author(s):  
Andrea D'Ambrosio ◽  
Eugenio Carminati ◽  
Carlo Doglioni ◽  
Lorenzo Lipparini ◽  
Mario Anselmi ◽  
...  
Keyword(s):  
Seismic Hazard ◽  
Cross Sections ◽  
3D Model ◽  
Velocity Model ◽  
Earthquake Relocation ◽  
Central Apennines ◽  
Seismic Stations ◽  
Velocity Models ◽  
3D Velocity Model ◽  
Seismogenic Faults

&lt;p&gt;The Central Apennines fold-and-thrust belt (Central Italy) is characterized by the presence of several active faults, potentially capable of generating damaging earthquakes. To support seismic hazard studies over the area, a new 3D velocity model was built, integrating a wide range of surface and subsurface data.&lt;/p&gt;&lt;p&gt;The tectonic framework of the area (from Sulmona plain to Maiella Mt), is still debated in literature, also due to the lack of both an adequate geophysical data set and a reliable velocity model at the crustal scale.&lt;/p&gt;&lt;p&gt;In addition, the low number of seismic stations available for the acquisition of Vp/Vs arrival times, and the very low seismicity detected in the study area (the Sulmona and Caramanico Apennine valleys are considered as &amp;#8220;seismic gaps&amp;#8221;), lead to a difficult interpretation of the subsurface tectonic structures.&lt;/p&gt;&lt;p&gt;3D velocity modelling could well represent an important tool to support these deep crustal reconstructions as well earthquake relocation studies and could enhance the definition of seismogenic faults deep geometries, hence supporting a better risk assessment over the area of these potential locked faults.&lt;/p&gt;&lt;p&gt;Using the knowledge developed within the oil&amp;gas industry as well in gas/CO&lt;sub&gt;2&lt;/sub&gt; storage projects for the construction of 3D velocity models, extensively used to obtain subsurface imaging and define the geometry of the reservoirs and traps in the depth domain, a similar methodological approach was implemented over the study area.&lt;/p&gt;&lt;p&gt;The subsurface dataset was partially inherited by the past hydrocarbon exploration activities (e.g. seismic lines, exploration wells and sonic logs) and by the literature (e.g. time/depth regional models). Tomographic sections and relocated earthquake hypocentres were also integrated form geophysical studies. Geological maps (1:50.000 &amp; 1:100.000 scale) represent the surface dataset that we used to create the surface interpretation of the regional geology.&lt;/p&gt;&lt;p&gt;As a first step, 18 2D balanced regional geological cross-sections, dip-oriented (W-E) across the Central Apennine, were built define the structural picture at regional scale. The cross-sections were built using MOVE (Petroleum Experts) and Petrel (Schlumberger) software. The following modelling step was the 3D model construction, in which the surface/subsurface data as well as all the geological sections were integrated in the final 3D structural and geological model.&lt;/p&gt;&lt;p&gt;The main geological layers reconstructed in the 3D model were than populated using the appropriated interval velocity values, building the final 3D velocity model in which the lateral velocity variation due to the presence of different facies/geological domains were considered.&lt;/p&gt;&lt;p&gt;As one of the results, we defined several 1D-velocity models coherent with the regional 3D velocity model, in which the key seismic stations and the earthquakes hypocentres dataset for the most potential seismogenic faults were included. 1D models were characterized by different degree of simplification, in order to test diverse approaches for the earthquake relocation. For this exercise, we used public dataset extracted by the analysis of microseismicity of the Sulmona basin.&lt;/p&gt;&lt;p&gt;We believe that the proposed approach can represents an effective method for combining geological and geophysical data to improve the subsurface and seismogenic faults interpretation, contributing to the seismic hazard assessment.&lt;/p&gt;

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