Seismic b-value within the Montney Play of Northeast British Columbia, Canada

2021 ◽  
Author(s):  
Alireza Babaie Mahani
Keyword(s):  
British Columbia ◽  
Hydraulic Fracturing ◽  
Induced Seismicity ◽  
B Value ◽  
Systematic Difference ◽  
Magnitude Distribution ◽  
Seismicity Rate ◽  
Northern Area ◽  
Seismicity Rates ◽  
Frequency Magnitude Distribution

Critical analysis of induced earthquake occurrences requires comprehensive datasets obtained by dense seismographic networks. In this study, using such datasets, I take a detailed investigation into induced seismicity that occurred in the Montney play of northeast British Columbia, mostly caused by hydraulic fracturing. The frequency-magnitude distribution (FMD) of earthquakes in several temporal and spatial clusters, show fundamental discrepancies between seismicity in the southern Montney play (2014-2018) and the northern area (2014-2016). In both regions, FMDs follow the linear Gutenberg-Richter (G-R) relationship for magnitudes up to 2-3. While in the southern Montney, within the Fort St. John graben complex, the number of earthquakes at larger magnitudes falls off rapidly below the G-R line, within the northern area with a dominant compressional regime, the number of events increases above the G-R line. This systematic difference may have important implications with regard to seismic hazard assessments from induced seismicity in the two regions, although caution in the interpretation is warranted due to local variabilities. While for most clusters within the southern Montney area, the linear or truncated G-R relationship provide reliable seismicity rates for events below magnitude 4, the G-R relationship underestimates the seismicity rate for magnitudes above 3 in northern Montney. Using a well-located dataset of earthquakes in southern Montney, one can observe generally that 1) seismic productivity correlates well with the injected volume during hydraulic fracturing and 2) there is a clear depth dependence for the G-R b-value; clusters with deeper median depths show lower b-values than those with shallower depths.

Risk from Oklahoma’s Induced Earthquakes: The Cost of Declustering

2020 ◽  
Author(s):  
Jeremy Maurer ◽  
Deborah Kane ◽  
Marleen Nyst ◽  
Jessica Velasquez
Keyword(s):  
Financial Risk ◽  
B Value ◽  
Earthquake Risk ◽  
Eastern United States ◽  
Induced Earthquakes ◽  
Magnitude Distribution ◽  
Seismicity Rate ◽  
Seismicity Rates ◽  
Tectonic Earthquakes ◽  
Frequency Magnitude

ABSTRACT The U.S. Geological Survey (USGS) has for each year 2016–2018 released a one-year seismic hazard map for the central and eastern United States (CEUS) to address the problem of induced and triggered seismicity (ITS) in the region. ITS in areas with historically low rates of earthquakes provides both challenges and opportunities to learn about crustal conditions, but few scientific studies have considered the financial risk implications of damage caused by ITS. We directly address this issue by modeling earthquake risk in the CEUS using the 1 yr hazard model from the USGS and the RiskLink software package developed by Risk Management Solutions, Inc. We explore the sensitivity of risk to declustering and b-value, and consider whether declustering methods developed for tectonic earthquakes are suitable for ITS. In particular, the Gardner and Knopoff (1974) declustering algorithm has been used in every USGS hazard forecast, including the recent 1 yr forecasts, but leads to the counterintuitive result that earthquake risk in Oklahoma is at its highest level in 2018, even though there were one-fifth as many earthquakes as occurred in 2016. Our analysis shows that this is a result of (1) the peculiar characteristics of the declustering algorithm with space-varying and time-varying seismicity rates, (2) the fact that the frequency–magnitude distribution of earthquakes in Oklahoma is not well described by a single b-value, and (3) at later times, seismicity is more spatially diffuse and seismicity rate increases are closer to more populated areas. ITS in Oklahoma may include a combination of swarm-like events with tectonic-style events, which have different frequency–magnitude and aftershock distributions. New algorithms for hazard estimation need to be developed to account for these unique characteristics of ITS.

A Retrospective Analysis of b-Value Changes Preceding Strong Earthquakes

2021 ◽  
Author(s):  
Nicolas D. DeSalvio ◽  
Maxwell L. Rudolph
Keyword(s):  
B Value ◽  
Earthquake Precursors ◽  
Earthquake Catalog ◽  
Traffic Light ◽  
Magnitude Distribution ◽  
Parameter Combination ◽  
Definition Of ◽  
Value Changes ◽  
Frequency Magnitude Distribution ◽  
Optimal Set

Abstract Earthquake precursors have long been sought as a means to predict earthquakes with very limited success. Recently, it has been suggested that a decrease in the Gutenberg–Richter b-value after a magnitude 6 earthquake is predictive of an imminent mainshock of larger magnitude, and a three-level traffic-light system has been proposed. However, this method is dependent on parameters that must be chosen by an expert. We systematically explore the parameter space to find an optimal set of parameters based on the Matthews correlation coefficient. For each parameter combination, we analyze the temporal changes in the frequency–magnitude distribution for every M ≥ 6 earthquake sequence in the U.S. Geological Survey Comprehensive Earthquake Catalog for western North America. We then consider smaller events, those with a foreshock magnitude as small as 5, and repeat the analysis to assess its performance for events that modify stresses over smaller spatial regions. We analyze 25 M ≥ 6 events and 88 M 5–6 events. We find that no perfect parameter combination exists. Although the method generates correct retrodictions for some M 5 events, the predictions are dependent on the retrospectively selected parameters. About 80%–95% of magnitude 5–6 events have too little data to generate a result. Predictions are time dependent and have large uncertainties. Without a precise definition of precursory b-value changes, this and similar prediction schemes are incompatible with the IASPEI criteria for evaluating earthquake precursors. If limitations on measuring precursory changes in seismicity and relating them to the state of stress in the crust can be overcome, real-time forecasting of mainshocks could reduce the loss of lives.

Well-Log-Based Velocity and Density Models for the Montney Unconventional Resource Play in Northeast British Columbia, Canada, Applicable to Induced Seismicity Monitoring and Research

2020 ◽  
Author(s):  
Alireza Babaie Mahani ◽  
Dmytro Malytskyy ◽  
Ryan Visser ◽  
Mark Hayes ◽  
Michelle Gaucher ◽  
...  
Keyword(s):  
British Columbia ◽  
Hydraulic Fracturing ◽  
Cross Sections ◽  
Induced Seismicity ◽  
Focal Depth ◽  
Depth Resolution ◽  
Velocity Model ◽  
The North ◽  
Seismicity Monitoring ◽  
Unconventional Resource

Abstract We present detailed velocity and density models for the Montney unconventional resource play in northeast British Columbia, Canada. The new models are specifically essential for robust hypocenter determination in the areas undergoing multistage hydraulic-fracturing operations and for detailed analysis of induced seismicity processes in the region. For the upper 4 km of the sedimentary structure, we review hundreds of well logs and select sonic and density logs from 19 locations to build the representative models. For depths below 4 km, we extend our models using data from the southern Alberta refraction experiment (Clowes et al., 2002). We provide one set of models for the entire Montney play along with two separated sets for the southern and northern areas. Specifically, the models for the southern and northern Montney play are based on logs located in and around the Kiskatinaw Seismic Monitoring and Mitigation Area and the North Peace Ground Motion Monitoring area, respectively. To demonstrate the usefulness of our detailed velocity model, we compare the hypocenter location of earthquakes that occurred within the Montney play as determined with our model and the simple two-layered model (CN01) routinely used by Natural Resources Canada. Locations obtained by our velocity model cluster more tightly with the majority of events having root mean square residual of <0.2  s compared with that of <0.4  s when the CN01 model is used. Cross sections of seismicity versus depth across the area also show significant improvements in the determination of focal depths. Our model results in a reasonable median focal depth of ∼2  km for events in this area, which is consistent with the completion depths of hydraulic-fracturing operations. In comparison, most solutions determined with the CN01 model have fixed focal depths (0 km) due to the lack of depth resolution.

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.

scholarly journals Unprecedented quiescence in resource development area allows detection of long-lived latent seismicity

Solid Earth ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 765-783
Author(s):  
Rebecca O. Salvage ◽  
David W. Eaton
Keyword(s):  
British Columbia ◽  
Hydraulic Fracturing ◽  
Pore Pressure ◽  
Stock Prices ◽  
Oil And Gas ◽  
Economic Market ◽  
Oil And Gas Development ◽  
Seismicity Rate ◽  
North East ◽  
Correlation Prior

Abstract. Recent seismicity in Alberta and north-east British Columbia has been attributed to ongoing oil and gas development in the area, due to its temporal and spatial correlation. Prior to such development, the area was seismically quiescent. Here, we show evidence that latent seismicity may occur in areas where previous operations have occurred, even during a shutdown in operations. The global COVID-19 pandemic furnished the unique opportunity to study seismicity during a long period of anthropogenic quiescence. Within the Kiskatinaw area of British Columbia, 389 events were detected from April to August 2020, which encompasses a period with very little hydraulic fracturing operations. This reduction in operations was the result of a government-imposed lockdown severely restricting the movement of people as well as a downturn in the economic market causing industry stock prices to collapse. Except for a reduction in the seismicity rate and a lack of temporal clustering that is often characteristic of hydraulic fracturing induced sequences, the general characteristics of the observed seismicity were similar to the preceding time period of active operations. During the period of relative quiescence, event magnitudes were observed between ML −0.7 and ML 1.2, which is consistent with previous event magnitudes in the area. Hypocentres occurred in a corridor orientated NW–SE, just as seismicity had done in previous years, and were located at depths associated with the target Montney formation or shallower (<2.5 km). A maximum of 21 % of the detected events during lockdown may be attributable to natural seismicity, with a further 8 % potentially attributed to dynamic triggering of seismicity from teleseismic events and 6 % related to ongoing saltwater disposal and a single operational well pad. However, this leaves ∼65 % of the seismicity detected during lockdown being unattributable to primary activation mechanisms. This seismicity is unlikely to be the result of direct pore pressure increases (as very little direct injection of fluids was occurring at the time) and we see no patterns of temporal or spatial migration in the seismicity as would be expected from direct pore pressure increases. Instead, we suggest that this latent seismicity may be generated by aseismic slip as fluids (resulting from previous hydraulic fracturing injection) become trapped within permeable formations at depth, keeping pore pressures in the area elevated and consequently allowing the generation of seismicity. Alternatively, this seismicity may be the result of fault and fracture weakening in response to previous fluid injection. This is the first time that this latent seismicity has been observed in this area of British Columbia and, as such, this may now represent the new normal background seismicity rate within the Kiskatinaw area.

A grid-based b-value approximation through Southern and Northern Norway: preliminary results 

2021 ◽  
Author(s):  
Rodrigo Estay ◽  
Claudia Pavez
Keyword(s):  
B Value ◽  
Seismic Events ◽  
Online Database ◽  
Magnitude Of Completeness ◽  
Stress Regime ◽  
Magnitude Distribution ◽  
The Mean ◽  
Frequency Magnitude Distribution ◽  
Frequency Magnitude ◽  
Grid Based

&lt;p&gt;The Gutenberg &amp;#8211; Richter&amp;#8217;s b-value is commonly used to analyze the frequency-magnitude distribution of earthquakes, describing the proportion of small and large seismic events as the first estimation of seismic hazard. Additionally, the b-value has been used as a stress meter, giving some insights into the stress regime in different regions around the world. In this research, a grid-based spatial distribution for the b &amp;#8211; value was estimated in three different areas of Norway: northern (74&amp;#176;-81&amp;#176; N/ 12&amp;#176;-26&amp;#176; E), southern (57&amp;#176;-64&amp;#176;N/3&amp;#176;-12&amp;#176; E), and the ridge zones of Mohns and Knipovich. For this, we used a complete catalog from the years 2000 to 2019, which was obtained from the Norwegian National Seismic Network online database. The magnitude of completeness was estimated separately for each zone both in time and space, covering a total area of ~425,000 km&lt;sup&gt;2&lt;/sup&gt;. Our results show a regional variation of the mean b-value for northern (b&lt;sub&gt;north&lt;/sub&gt; = 0.79) and southern (b&lt;sub&gt;south&lt;/sub&gt; = 1.03) Norway, and the Ridge (b&lt;sub&gt;ridge&lt;/sub&gt; = 0.73), which can be interpreted in terms of the predominant stress regime in the different zones. So far, a few calculations regarding the b-value were previously done in Norway to analyze local intraplate sequences. Then, according to our knowledge, this research corresponds to the first estimation of a regional spatial variation of the b &amp;#8211; value in the country.&lt;/p&gt;

The St. Elias, Alaska, earthquake of February 28, 1979: Regional recording of aftershocks and short-term, pre-earthquake seismicity

1980 ◽  
Vol 70 (5) ◽  
pp. 1607-1633
Author(s):  
Christopher D. Stephens ◽  
John C. Lahr ◽  
Kent A. Fogleman ◽  
Robert B. Horner
Keyword(s):  
Main Shock ◽  
B Value ◽  
High Gain ◽  
Yukon Territory ◽  
P Wave ◽  
Magnitude Distribution ◽  
Regional Seismicity ◽  
Inverse Power Law ◽  
Frequency Magnitude Distribution ◽  
Alaska Earthquake

abstract The St. Elias, Alaska, earthquake (Ms 7.1) of February 28, 1979 occurred beneath the Chugach and St. Elias Mountains of southeastern Alaska and southwestern Yukon Territory. The main shock and aftershocks were recorded at regional high-gain, high-frequency seismographs operated by the U.S. and Canada. Hypocenters and magnitudes are presented for 308 aftershocks that occurred between February 28 and March 31, 1979. These data contain a nearly complete record of events of magnitude 3.5 and larger starting about 20 min after the main shock. The largest aftershock has a poorly determined magnitude slightly above 5, and the frequency-magnitude distribution has a b value of 1.36. A t−p inverse power law with an unusually low value of 0.93 for p adequately describes the decay with time in the frequency of occurrence of large aftershocks. The aftershocks occurred in a broad zone that extends about 115 km southeast from the epicenter of the main shock. Events tend to form clusters within this zone. One of the most remarkable features in the distribution of epicenters is that relatively few aftershocks were located near the epicenter of the main shock, and the highest rate of activity was centered about 50 km southeast of the epicenter of the main shock. Within the accuracy of the data, the depths of the aftershocks are all less than about 20 km. In the few areas where good depth control is available, the seismicity appears not to extend to the Earth's surface. Additional data from temporary stations operated in the aftershock zone during July and August 1979 indicate that the seismicity in some areas may be confined to a zone less than 6 km in vertical thickness. Focal mechanisms determined from p-wave first motions for some of the larger aftershocks all indicate northward-directed compression, which is consistent with the focal mechanism of the main shock. A review of the regional seismicity during the 6-month period preceding the St. Elias earthquake indicates that, relative to a comparable 6-month period 1 yr earlier, there was a 45 per cent increase in the rate of activity for events of magnitude 1.8 and larger, and possibly a decrease in the b value during the same period. Also, a prominent cluster of events with magnitudes less than 3.3 occurred at the southeast corner of the aftershock zone during the 6 months prior to the earthquake. The seismic record from the USGS network since 1974 is not yet complete in time, so it is not possible to determine how unusual the seismic activity preceding this earthquake has been.

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