Do spatial and/or temporal b-value variations exist within the Groningen induced earthquake catalogue?

2021 ◽  
Author(s):  
Annemarie Muntendam-Bos ◽  
Nilgün Güdük
Keyword(s):  
Spatial Analysis ◽  
B Value ◽  
Northern Region ◽  
Earthquake Catalogue ◽  
Magnitude Of Completeness ◽  
Gas Field ◽  
B Values ◽  
Induced Earthquake ◽  
The Difference ◽  
Groningen Gas Field

<p>We present a data-driven analysis to derive whether statistically significant spatial and/or temporal Gutenberg-Richter b-value variations exist within the induced earthquake catalogue of the Groningen gas field. We utilize the method developed by Kamer and Hiemer (2015; J. Geophys. Res. Solid Earth, 120, doi:10.1002/2014JB011510 ) which is based on optimal partitioning using Voronoi tessellation, penalized likelihood, and wisdom of the crowd philosophy. Our implementation derives both the magnitude of completeness and the b-values simultaneously. The magnitude of completeness is computed with the maximum curvature method with a correction applied to avoid bias due to catalogue incompleteness. Finally, following Marzocchi et al. (2020; Geophys. J. Int. 220, doi: 10.1093/gji/ggz541) the b-values computed are corrected for bin size and small sample sizes.</p><p>In a first step we have limited the analysis to spatial variations in the b-values. A significant advantage of the approach taken is that it is feasible to also derive b-values in regions of very low data density. We will show that a statistically significant variation in b-values is obtained. Very low b-values (b<0.8) are observed in the central-northern part of the gas field. However, in the west near the production cluster Eemskanaal (EKL) and in the east near the city of Delfzijl significantly higher b-values (b>1.1) are observed. A Kolmogorov-Smirnov test of frequency-magnitude distributions for the two areas obtains a p-value of 1.5 10-13 and 2.3 10-12 for the EKL region and Delfzijl regions, respectively, rendering the difference more than statistically significant at the 99% confidence level.</p><p>In a second step we extended the spatial analysis to a spatial-temporal analysis. The results of the analysis show that the Groningen earthquake database is too small to derive meaningful spatial results for the full Groningen gas field based on multiple random temporal nodes.  We divided the dataset in two almost equal datasets: both containing roughly 50% of the data and of comparable spatial resolution. Spatial analysis of these two subsets of the catalogue shows a significant decrease of the b-values in the central and southern regions. Particularly in the western EKL region the b-value decreases from 1.2 to 0.92. The decrease is close to significant at the 90% confidence level. The northern region exhibits comparable low b-values in both periods. As the data in the first decade is primarily concentrated in the northern region, we have attempted to assess the spatial b-value here in the period prior to 2005. We find the high b-value area is significantly smaller and the minimum value is higher (b = 0.96 pre-2005 versus b = 0.88 post-2012). The difference is significant only at the interquartile level, but the model resolution is low.</p><p>Based on our results, we could conclude a spatial and temporal variation in b-value is observed. However, despite our efforts to limit bias in the derivation, variations could still result from the presence of a truncation. Hence, we will extend the current analysis by a comparable analysis assuming a constant b-value and estimating the corner magnitude of a taper truncation.</p>

Mapping b-Value Anomalies Along the Indonesian Island Chain: Implications for Upcoming Earthquakes

2014 ◽  
Vol 08 (04) ◽  
pp. 1450010 ◽  
Author(s):  
Santi Pailoplee
Keyword(s):  
Spatial Relationship ◽  
B Value ◽  
Fixed Number ◽  
Earthquake Catalogue ◽  
Suitable Assumption ◽  
B Values ◽  
Magnitude Distribution ◽  
Risk Areas ◽  
Frequency Magnitude Distribution ◽  
Frequency Magnitude

In this study, the geospatial frequency–magnitude distribution (FMD) b-value images of the prospect sources of upcoming earthquakes were investigated along the Indonesian Sunda Margin (ISM) that strikes parallel to and near the Indonesian Island chain. After enhancing the completeness and stability of the earthquake catalogue, the seismicity data were separated according to their seismotectonic setting into shallow crustal and Intraslab earthquakes. In order to verify the spatial relationship between the b-values and the occurrence of subsequent major earthquakes, the complete shallow crustal seismicity dataset (1980–2005) was truncated into the 1980–2000 sub-dataset. Utilizing the suitable assumption of fixed-number of earthquakes, retrospective tests of both the complete and truncated datasets supported that areas of comparatively low b-values could reasonably be expected to predict likely hypocenters of future earthquakes. As a result, the present-day distributions of b-values derived from the complete (1980–2005) shallow crustal and Intraslab seismicity datasets revealed eight and six earthquake-prone areas, respectively, along the ISM. Since most of these high risk areas proposed here are quite close to the major cities of Indonesia, attention should be paid and mitigation plans should be developed for both seismic and tsunami hazards.

MAPPING ASPERITIES ALONG THE SAGAING FAULT ZONE, MYANMAR USING b-VALUE ANOMALIES

2013 ◽  
Vol 07 (05) ◽  
pp. 1371001 ◽  
Author(s):  
SANTI PAILOPLEE
Keyword(s):  
Fault Zone ◽  
Cross Section ◽  
B Value ◽  
Earthquake Catalogue ◽  
Adjacent Area ◽  
Southwestern Part ◽  
B Values ◽  
Earthquake Sources ◽  
Frequency Magnitude ◽  
Section Dimension

In this study, the b-values of frequency-magnitude earthquake distributions were mapped spatially along the sagaing fault zone (SFZ), central Myanmar. Three sub-datasets of the complete earthquake catalogue were tested in order to ensure the applied assumption. Using the present-day dataset (1980–2010), two areas of low b-values, which are prospective potential earthquake sources, were identified at the Naypyidaw-Mandalay and southwestern part of Myitkyina in the central and northern part of the SFZ, respectively. To assess the possible earthquake magnitudes, the b-values were mapped in the cross-section dimension along the SFZ. The obtained areas of low b-values, referred to as the fault asperity regions, conformed to those illustrated in the surface map. The asperity's sizes, examined from specific low b-values of ≤ 0.65 and ≤ 0.060 were quantitatively estimated and empirically converted to the potential earthquake magnitudes. This analysis revealed three prospective areas surrounding the Myitkyina regions capable of generating earthquakes in the future with a possible magnitude of 8.6 Richter. The contribution of effective mitigation plans are, therefore, urgently needed for Myanmar and the adjacent area.

scholarly journals Seismic slip‐pulse experiments simulate induced earthquake rupture in the Groningen gas field

2021 ◽  
Author(s):  
Luuk B. Hunfeld ◽  
Jianye Chen ◽  
André R. Niemeijer ◽  
Shengli Ma ◽  
Christopher J. Spiers
Keyword(s):  
Earthquake Rupture ◽  
Gas Field ◽  
Seismic Slip ◽  
Induced Earthquake ◽  
Slip Pulse ◽  
Groningen Gas Field

scholarly journals Relocation of clustered earthquakes in the Groningen gas field

2017 ◽  
Vol 96 (5) ◽  
pp. s163-s173 ◽  
Author(s):  
Lisanne Jagt ◽  
Elmer Ruigrok ◽  
Hanneke Paulssen
Keyword(s):  
S Wave ◽  
Gas Field ◽  
Single Station ◽  
Source Mechanisms ◽  
The Difference ◽  
Multiplet Analysis ◽  
Using Data ◽  
Groningen Gas Field ◽  
Master Event ◽  
Improved Accuracy

AbstractPrevious locations of earthquakes induced by depletion of the Groningen gas field were not accurate enough to infer which faults in the reservoir are reactivated. A multiplet analysis is performed to identify clusters of earthquakes that have similar waveforms, representing repeating rupture on the same or nearby faults. The multiplet analysis is based on the cross-correlation of seismograms to assess the degree of similarity. Using data of a single station, six earthquake clusters within the limits of the Groningen field were identified for the period 2010 to mid-2014. Four of these clusters were suitable for a relocation method that is based on the difference in travel time between the P- and the S-wave. Events within a cluster can be relocated relative to a master event with improved accuracy by cross-correlating first arrivals. By choosing master events located with a new dense seismic network, the relocated events likely not only have better relative, but also improved absolute locations. For a few clusters with sufficient signal-to-noise detections, we show that the relocation method is successful in assigning clusters to specific faults at the reservoir level. Overall, about 90% of the events did not show clustering, despite choosing low correlation thresholds of 0.5 and 0.6. This suggests that different faults and/or fault segments with likely varying source mechanisms are active in reservoir sub-regions of a few square kilometres.

scholarly journals Spatial Analysis of b-value Variability in Armutlu Peninsula (NW Turkey)

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Tekin Yeken
Keyword(s):  
Spatial Analysis ◽  
B Value ◽  
Spatial Variations ◽  
B Values ◽  
Nw Turkey

AbstractSpatial variations of b values were studied by means of 2376 earthquakes with a magnitude completeness of 2.7 in the Armutlu Peninsula (NW Turkey) during a 15-year period following the destructive earthquake on August 17, 1999 in Kocaeli. The

scholarly journals Field-wide reservoir compressibility estimation through inversion of subsidence data above the Groningen gas field

2017 ◽  
Vol 96 (5) ◽  
pp. s117-s129 ◽  
Author(s):  
Rob M.H.E. van Eijs ◽  
Onno van der Wal
Keyword(s):  
Induced Seismicity ◽  
Surface Deformation ◽  
Gas Production ◽  
Potential Threat ◽  
Gas Field ◽  
Reservoir Compaction ◽  
The Difference ◽  
Seismological Model ◽  
Groningen Gas Field ◽  
Deformation Measurements

AbstractNot long after discovery of the Groningen field, gas-production-induced compaction and consequent land subsidence was recognised to be a potential threat to groundwater management in the province of Groningen, in addition to the fact that parts of the province lie below sea level. More recently, NAM's seismological model also pointed to a correlation between reservoir compaction and the observed induced seismicity above the field. In addition to the already existing requirement for accurate subsidence predictions, this demanded a more accurate description of the expected spatial and temporal development of compaction.Since the start of production in 1963, multiple levelling campaigns have gathered a unique set of deformation measurements used to calibrate geomechanical models. In this paper we present a methodology to model compaction and subsidence, combining results from rock mechanics experiments and surface deformation measurements. Besides the optical spirit-levelling data, InSAR data are also used for inversion to compaction and calibration of compaction models. Residual analysis, i.e. analysis of the difference between measurement and model output, provides confidence in the model results used for subsidence forecasting and as input to seismological models.

b-VALUE ANOMALIES ALONG THE NORTHERN SEGMENT OF THE SUMATRA–ANDAMAN SUBDUCTION ZONE: IMPLICATIONS FOR UPCOMING EARTHQUAKES

2013 ◽  
Vol 07 (04) ◽  
pp. 1350030 ◽  
Author(s):  
SANTI PAILOPLEE ◽  
PEERASIT SURAKIATCHAI ◽  
PUNYA CHARUSIRI
Keyword(s):  
Subduction Zone ◽  
B Value ◽  
Earthquake Catalogue ◽  
B Values ◽  
Magnitude Distribution ◽  
Nicobar Islands ◽  
Spatial Investigation ◽  
Frequency Magnitude Distribution ◽  
Northern Segment ◽  
Frequency Magnitude

The potential areas of upcoming earthquakes were investigated along the Northern segment of the Sumatra–Andaman Subduction Zone according to the b-value of the frequency-magnitude distribution. After enhancing the completeness of the earthquake catalogue, two datasets, those recorded during (i) 1980–1994 and (ii) 1980–2003, were tested in order to verify the effective correlation between precursory b-values and the location of subsequent earthquakes. The results confirmed that areas with low b-values agreed well with the locations of the subsequent earthquakes in that region. Accordingly, the present-day dataset from 1980–2010 was carefully evaluated to determine the b-values across the region. Within this spatial investigation, three areas of low b-values and so potential hazards were found. These consisted of the (i) West coast of Myanmar, and (ii) North and (iii) South of the Nicobar Islands. From 2010–2012, a major earthquake with magnitude 7.5 mb was recorded as being generated in the region South of the Nicobar Islands. Thus, attention should be paid to the remaining two until now quiescent areas, and mitigation plans should be raised for both seismic and tsunami hazards.

scholarly journals Central Asia earthquake catalogue from ancient time to 2009

2015 ◽  
Vol 58 (1) ◽  
Author(s):  
Natalya N. Mikhailova ◽  
Aidyn S. Mukambayev ◽  
Irina L. Aristova ◽  
Galina Kulikova ◽  
Shahid Ullah ◽  
...  
Keyword(s):  
Surface Waves ◽  
Central Asia ◽  
B Value ◽  
Earthquake Catalogue ◽  
Magnitude Of Completeness ◽  
Ancient Time ◽  
Seismic Catalogue ◽  
Earthquake Model ◽  
Former Ussr

<p>In this work, we present the seismic catalogue compiled for Central Asia (Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan and Turkmenistan) in the framework of the Earthquake Model Central Asia (EMCA) project. The catalogue from 2000 B.C. to 2009 A.D. is composed by 33,034 earthquakes in the MLH magnitude (magnitude by surface waves on horizontal components widely used in practice of the former USSR countries) range from 1.5 to 8.3. The catalogue includes both macroseimic and instrumental constrained data, with about 32,793 earthquake after 1900 A.D. The main sources and procedure used to compile the catalogues are discussed, and the comparison with the ISC-GEM catalogue presented. Magnitude of completeness analysis shows that the catalogue is complete down to magnitude 4 from 1959 and to magnitude 7 from 1873, whereas the obtained regional b value is 0.805.</p>

Relating spatial-temporal b-value patterns of induced earthquakes of the Groningen gas field to differential stress changes due to reservoir extraction

2021 ◽  
Author(s):  
Nilgün Güdük ◽  
Annemarie Muntendam-Bos ◽  
Jan Dirk Jansen
Keyword(s):  
Pore Pressure ◽  
B Value ◽  
Enhanced Geothermal Systems ◽  
Differential Stress ◽  
Gas Field ◽  
Seismic Slip ◽  
Stress Changes ◽  
Pressure Depletion ◽  
Groningen Gas Field ◽  
Event Magnitude

&lt;p&gt;The Gutenberg-Richter law describes the frequency-magnitude distribution of seismic events where its slope, the 'b-value', is commonly used to describe the relative occurrence of large and small events. Statistically significant b-value variations have been measured in laboratory experiments, mines, and various tectonic regimes (Wiemer &amp; Wyss, 2002). An inversely proportional dependency of the b-value on the differential stress has been observed across different scales (Amitrano, 2003; Schorlemmer et al., 2005). Layland-Bachmann et al. (2012) have shown that this could explain the observed pattern of induced seismicity spatial-temporal b-value variations in Enhanced Geothermal Systems. In our study, we look for a similar relation applied to the Groningen gas field in the Netherlands.&lt;/p&gt;&lt;p&gt;It is well known that the poroelastic changes in differential stress during gas extraction are influenced by the offset of the reservoir layer across the fault. Recently, Jansen et al. (2019) and Lehner (2019) proposed an analytical solution for stress changes on offset faults due to reservoir depletion. In a parallel study, we extended this solution to include the development of aseismic slip under slip weakening and the derivation of the onset of seismic slip.&lt;br&gt;We utilize this formulation to derive the onset of seismic slip on theoretical faults of variable fault offset, dip, and reservoir thickness. Subsequently, we map our theoretical faults onto the pre-existing faults in the Groningen gas field, deriving fault segment-specific depletion levels at which the segment would become seismically active. We then simulate reservoir depletion conditions over time and assign an event magnitude to fault segments that move past their seismic activation depletion. To assign a magnitude, we use the observation that b-values are inversely proportional to differential stress, which is governed by the pore pressure depletion. Hence, we assume a simple inverse linear relation with pore pressure depletion. Each event magnitude is then randomly drawn from the probability density function of the Gutenberg-Richter distribution with the b-value assigned.&lt;br&gt;We aim to compare the obtained catalogue and its b-value distribution both in time and space to the observed event-size distribution of the Groningen gas field as derived by Muntendam-Bos and G&amp;#252;d&amp;#252;k (EGU abstract 2021).&lt;/p&gt;

scholarly journals Inversion of double-difference measurements from optical levelling for the Groningen gas field

2015 ◽  
Vol 372 ◽  
pp. 375-378 ◽  
Author(s):  
P. A. Fokker ◽  
K. Van Thienen-Visser
Keyword(s):  
The Netherlands ◽  
Surface Subsidence ◽  
Double Difference ◽  
Gas Reservoir ◽  
Height Difference ◽  
Linear Inversion ◽  
Gas Field ◽  
Reservoir Compaction ◽  
The Difference ◽  
Groningen Gas Field

Abstract. Hydrocarbon extraction lead to compaction of the gas reservoir which is visible as subsidence on the surface. Subsidence measurements can therefore be used to better estimate reservoir parameters. Total subsidence is derived from the result of the measurement of height differences between optical benchmarks. The procedure from optical height difference measurements to absolute subsidence is an inversion, and the result is often used as an input for consequent inversions on the reservoir. We have used the difference measurements directly to invert for compaction of the Groningen gas reservoir in the Netherlands. We have used a linear inversion exercise to update an already existing reservoir compaction model of the field. This procedure yielded areas of increased and decreased levels of compaction compared to the existing compaction model in agreement with observed discrepancies in porosity and aquifer activity.

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