Tracking Induced Seismicity in the Fort Worth Basin: A Summary of the 2008–2018 North Texas Earthquake Study Catalog

Abstract

Since 2008, earthquake sequences within the Fort Worth basin (FWB), north Texas, have been linked to wastewater disposal activities related to unconventional shale‐gas production. The North Texas Earthquake Study (NTXES) catalog (2008–2018), described and included herein, uses a combination of local and regional seismic networks to track significant seismic sequences in the basin. The FWB earthquakes occur along discrete faults that are relatively far apart (>30 km), allowing for more detailed study of individual sequence development. The three largest sequences (magnitude 3.6+) are monitored by local seismic networks (<15 km epicentral distances), whereas basinwide seismicity outside these three sequences is monitored using regional distance stations. A regional 1D velocity model for the FWB reflects basinwide well log, receiver function, and regional crustal structure studies and is modified for the larger individual earthquake sequences using local well‐log and geology data. Here, we present an mb_Lg relationship appropriate for Texas and a basin‐specific ML relationship, both calculated using attenuation curves developed with the NTXES catalog. Analysis of the catalog reveals that the earthquakes generally occur within the Precambrian basement formation along steeply dipping normal faults, and although overall seismicity rates have decreased since 2016, new faults have become active. Between 2006 and 2018, more than 2 billion barrels of fluids were injected into the Ellenburger formation within the FWB. We observe strong spatial and temporal correlations between the earthquake locations and wastewater disposal well locations and injection volumes, implying that fluid injection activities may be the main driving force of seismicity in the basin. In addition, we observe seismicity occurring at greater distances from injection wells (>10 km) over time, implying that far‐field stress changes associated with fluid injection activities may be an important component to understanding the seismic hazard of induced seismicity sequences.

Full text

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Tracking Induced Seismicity in the Fort Worth Basin: A Summary
of the 2008–2018 North Texas Earthquake Study Catalog
by Louis Quinones, Heather R. DeShon, SeongJu Jeong, Paul Ogwari,
Oner Sufri, Monique M. Holt, and Kevin B. Kwong
Abstract Since 2008, earthquake sequences within the Fort Worth basin (FWB),
north Texas, have been linked to wastewater disposal activities related to unconven-
tional shale-gas production. The North Texas Earthquake Study (NTXES) catalog
(2008–2018), described and included herein, uses a combination of local and regional
seismic networks to track significant seismic sequences in the basin. The FWB earth-
quakes occur along discrete faults that are relatively far apart (>30 km), allowing for
more detailed study of individual sequence development. The three largest sequences
(magnitude 3.6+) are monitored by local seismic networks (<15 km epicentral dis-
tances), whereas basinwide seismicity outside these three sequences is monitored
using regional distance stations. A regional 1D velocity model for the FWB reflects
basinwide well log, receiver function, and regional crustal structure studies and is
modified for the larger individual earthquake sequences using local well-log and geol-
ogy data. Here, we present an mbLg relationship appropriate for Texas and a basin-
specific MLrelationship, both calculated using attenuation curves developed with the
NTXES catalog. Analysis of the catalog reveals that the earthquakes generally occur
within the Precambrian basement formation along steeply dipping normal faults, and
although overall seismicity rates have decreased since 2016, new faults have become
active. Between 2006 and 2018, more than 2 billion barrels of fluids were injected into
the Ellenburger formation within the FWB. We observe strong spatial and temporal
correlations between the earthquake locations and wastewater disposal well locations
and injection volumes, implying that fluid injection activities may be the main driving
force of seismicity in the basin. In addition, we observe seismicity occurring at greater
distances from injection wells (>10 km) over time, implying that far-field stress
changes associated with fluid injection activities may be an important component
to understanding the seismic hazard of induced seismicity sequences.
Supplemental Content: Velocity models used to locate the North Texas
Earthquake Study (NTXES) catalog earthquakes, magnitude differences across cata-
logs of seismicity in the Fort Worth basin (FWB), the strike distribution of the 68%
confidence interval error ellipsoids reported in the NTXES catalog, the differences in
earthquake locations from previously published versions of the NTXES catalog, and
the history of injection activities in the FWB. The digital version of the NTXES cata-
log is also included.
Introduction
Starting in late 2008, earthquakes within the Fort Worth
basin (FWB), Texas, contributed to the central United States
increased seismicity rates after the late-2000s (Frohlich
et al., 2010,2016;Ellsworth, 2013;Weingarten et al.,
2015). Studies of individual earthquake sequences in the basin
link activity, with varying degrees of certainty, to wastewater
injection activities associated with unconventional shale-gas
development (Frohlich et al., 2010,2011;Frohlich, 2012;
Reiter et al., 2012;Justinic et al.,2013;Hornbach et al.,
2015;Scales et al., 2017;Ogwari et al.,2018). Seismogenic
faults in the basin are steeply dipping, basement-seeded,
northeast–southwest-trending normal faults (Magnani et al.,
2017;Quinones et al.,2018;Fig.1b) and have deformation
limited to >300 Ma resolved using formation offset in seismic
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Bulletin of the Seismological Society of America, Vol. 109, No. 4, pp. 1203–1216, August 2019, doi: 10.1785/0120190057
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reflection data (Magnani et al., 2017). Some, but not all, of the
larger magnitude earthquakes occur near wastewater disposal
wells. Compilations of injection data and estimates of regional
pore-pressure changes in the FWB (i.e., Gono et al., 2015;
Hornbach et al, 2016), however, need to be linked to a more
complete documentation in time and space of earthquakes to
holistically understand the evolution of the subsurface system.
In addition, the Dallas–Fort Worth (DFW) metropolitan area
(population >6million) overlies the eastern seismogenic
FWB, and a comprehensive catalog (ComCat) of FWB earth-
quakes provides better data for hazard and risk assessment and
regulatory decisions.
The FWB is a foreland basin with a history of oil and gas
production activity dating back to the early twentieth century
(Pollastro et al., 2007; Fig. 1). The majority of faults within
the basin that have been interpreted from drilling and seismic
reflection data have strikes that align well with the strikes of
the major basin boundaries (e.g., Ewing, 1990;Pollastro
et al., 2007;Magnani et al., 2017; P. H. Hennings et al.,
unpublished manuscript, 2019; see Data and Resources).
Earthquakes are limited to the northeast portion of the
FWB (Fig. 1a). Here, the Barnett Shale formation has served
as the primary shale-gas producing unit since 2004 (Pollastro
et al., 2007), and wastewater associated with this production
is primarily injected into the underlying Ellenburger dolo-
mitic limestone formation (Hornbach et al., 2016). The
Ellenburger lies in unconformity atop the crystalline
Precambrian basement (Fig. 2a). A complete mapping of
basement-seeded faults remains data limited; faults shown
in this article come from recent updated compilation by
P. H. Hennings et al. (unpublished manuscript, 2019; see
Data and Resources).
Five hypocenter catalogs provide information on earth-
quakes in the FWB. The catalog of record, the U.S.
Advanced National Seismic System (ANSS) ComCat,
reports midmagnitude (M ≥3) earthquakes consistently
through time after 1973, but uncertainty in space can be
on the order of 5–15 km. The Frohlich et al. (2016) historic
Texas earthquake catalog provides information before
1973. Neither of these catalogs contains reliable reported
(a) (b)
arch
arch
Ouachita thrust front
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ip
p
c
m
w
Ouachita thrust front
Figure 1. (a) Map view showing the locations of the North Texas Earthquake Study (NTXES) earthquakes as circles shaded by the time of
their occurrence along with the locations of wastewater wells (arrows) in the basin that were active during the period of observation. County
names (italics) and important well locations such as the Bond Ranch (BR), Briar Well (BW), Trigg Well (TW), and A1MD well are also labeled.
(b) Map view showing the locations of all stations that were used to locate the NTXES earthquakes shaded by their network codes and the
symbols of which represent the station’s sensor type. The locations of the NTXES earthquakes (light gray circles) are also shown. Faults
interpreted from proprietary seismic reflection data (P. H. Hennings et al., unpublished manuscript, 2019; see Data and Resources).
(c) General map view showing the locations of regional United States and Transportable Array (TA) stations used to locate some NTXES
catalog earthquakes along with the highlighted study area (box). The color version of this figure is available only in the electronic edition.
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earthquakes in the FWB east of the Bend Arch before
October 2008. Frohlich (2012) reported small-magnitude
earthquakes (M <3) in the basin using the Earthscope
Transportable Array (TA) from 2009 to 2011. Between
2008 and 2019, Southern Methodist University (SMU) oper-
ated three temporary seismic networks deployed more than
five named seismic sequences in the basin (Frohlich et al.,
2011;Justinic et al., 2013;DeShon et al., 2018) but focused
publication of individual earthquake sequence catalogs over
discrete time periods. The North Texas Earthquake Study
(NTXES) catalog presented herein and included within
ⒺDataset S1 (available in the supplemental content to this
article) reports all seismicity recorded by the temporary net-
works operated by SMU during the 2008–2018 period.
Finally, beginning in 2017, SMU operations were combined
with the Texas Seismic Network (TexNet) such that the
NTXES catalog overlaps in time and space with the state-
wide publicly available catalog (Savvaidis et al., 2019).
The NTXES catalog uses a combination of local and
regional stations within the basin and a standardized
approach to earthquake location and magnitude calculations.
The NTXES catalog is composed of autodetected and man-
ually reviewed earthquakes located using the GENLOC loca-
tion algorithm (Pavlis et al., 2004) in conjunction with local
and regional 1D velocity models generated using data from
well logs collected from within the FWB. We report formal
uncertainties for all earthquakes in the catalog. A new
regional attenuation curve constrains the local magnitudes
reported in the NTXES catalog. The NTXES catalog is com-
bined with the more temporally complete ComCat to inves-
tigate the relationship between earthquakes, faults, and
wastewater injection in the FWB and explore magnitude–
time relationships along individual faults and within the
basin. Finally, we examine the relationship between injected
wastewater rates and seismicity and discuss far-field versus
near-source triggering effects of fluid injection in the basin
(a) (b) (c) (d)
Figure 2. (a) Stratigraphic column created using data collected from the Trigg Well site. (b) Interval velocity models created using data
collected from the Trigg and Briar Well sites. (c) 1D local P- (solid lines) and S-wave (dashed lines) velocity models used to locate earth-
quakes within the Azle, Irving–Dallas, and Venus sequences. (d) 1D regional P- (solid lines) and S-wave (dashed lines) velocity models used
to locate earthquakes within the Fort Worth basin (FWB) that occur outside the three previously mentioned sequences. The upper 5 km of the
regional velocity models, which is similar to the local 1D velocity models, is highlighted (gray area). The color version of this figure is
available only in the electronic edition.
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and the possible role fluid injection activities had on the
Irving–Dallas sequence, the primary cause of which is still
under investigation.
Methodology for the NTXES Catalog
SMU has operated temporary seismic stations in the
FWB since 2008 (Frohlich et al., 2011;Justinic et al., 2013)
and since 2013 the local networks appear under the auspice
of the NTXES, as summarized by DeShon et al. (2018).
Continuous waveform data from all networks are archived
without embargo or restriction, including currently operating
stations in near-real time (see Data and Resources). The net-
works consist of a mix of short-period, broadband, and
strong-motion stations and station locations reflect the com-
plex history of deployment in rapid response mode (DeShon
et al., 2018; Fig. 1b). The resolution in time and space of the
resulting NTXES hypocenter catalog reflects this complex-
ity. Early studies using the SMU temporary networks in
2008–2010 used different location methodologies and veloc-
ity models (Frohlich et al., 2010,2011;Janská and Eisner,
2012;Reiter et al., 2012;Justinic et al.,2013) than later stud-
ies, which focused on stations deployed in and after 2013
(Hornbach et al.,2015;Scales et al., 2017;Ogwari et al.,
2018;Quinones et al.,2018). In total, there are five well-
studied earthquake sequences, here referred to by year and
place name of significant first or largest event: 2008 DFW
Airport (Frohlich et al., 2010,2011;Janská and Eisner, 2012;
Rieter et al., 2012;Ogwari et al., 2018), 2009 Cleburne
(Justinic et al.,2013), 2013 Azle–Reno (Hornbach et al.,
2015;Quinones et al., 2018), 2015 Dallas–Irving (Magnani
et al.,2017;Quinones et al., 2018), and 2015 Venus
(Magnani et al.,2017;Scales et al., 2017;Quinones et al.,
2018). Here, we joined all data into a single data processing
stream to ensure methodological consistency and additionally
report all earthquakes rather than only low-uncertainty events
associated with specific earthquake sequences.
Hypocenter Determination
We use Antelope Environmental Monitoring software
and underlying relational database for archiving and analysis
of the temporary seismic network data. Analysis uses the
offline batch-processing mode, and no real-time analysis
operations were implemented. The 2008–2011 networks
were not telemetered, and although stations post-2013 were,
SMU did not have the staff capabilities or reporting authority
to provide real-time earthquake catalogs.
From 2013 to present, batch processing 24 hr in arrears
includes autodetection and association of P- and S-wave first
arrivals followed by manual review of associations and raw
waveforms to identify small earthquakes. A multifrequency
short-term average over long-term average autodetector
(dbdetect) tuned to find impulsive local distance earthquakes
feeds into an event associator set to use a spatial grid-search
method with the iasp91 global velocity model (dbgrassoc).
In practice, autodetection and association set to optimize
identification across the network can miss emergent or nodal
arrivals, trigger incorrectly on a prominent P-to-S-converted
phase that mixes with first-arriving Son some stations, and
do not capture all microseismicity (M <1) associated with
swarm activity in some sequences. The network itself exhib-
its high noise levels inherent to rapid installation within a
sedimentary basin and major metropolitan area (discussed
in DeShon et al., 2018). Thus, all continuous data are sub-
sequently manually reviewed by a trained analyst to correct
autodetections and add additional phase onsets. At this stage,
all P-wave first-motion data are entered into the database.
The analyst assigned phase-pick uncertainties associated
with these manually reviewed phases are conservatively
estimated to be within 0.01–0.04 s for P-phase picks and
0.02–0.08 s for S-phase picks depending on factors such
as the impulsiveness of the phase arrivals and the sampling
rates of the observing stations (100 or 200 samples per
second).
Event review takes place within the analyst location
software (dbloc2), and we use GENLOC location algo-
rithms, which is a modified version of the Gauss–Newton
inversion method meant for single-event location applica-
tions (Pavlis et al., 2004). The GENLOC programs allow
for multiple 1D velocity models to be interactively tested
resulting in multiple origin locations and times stored for
a given event. Reported formal uncertainties include origin
time and a 68% confidence error ellipsoid in space and are
derived from the covariance matrix in the inverse solution
(Pavlis et al., 2004). The median standard error of obser-
vation (sdobs) value, which is defined as the sum of the
square of the phase arrival-time residuals divided by the
number of degrees of freedom, is also stored by origin.
For the NTXES catalog, we provide the preferred solution
for each event, discussed in the Velocity Models section,
and the 68% confidence error ellipsoids are provided as
the ellipsoid major axis length and strike, minor axis length,
depth axis length, and origin time error (see the Ⓔsupple-
mental content).
Velocity Models
The 1D velocity structure of the basin is derived from a
combination of available geologic, well-log, and reflection
data. The FWB stratigraphy summarized in Pollastro et al.
(2007) provides the basic geology to inform 1D velocity
model design (Fig. 2a). Figure 2is plotted relative to surface,
with mean elevation of ∼235 m above sea level. Most
significantly, the basin deepens from southwest to the north-
east, as reflected in the top of the Ellenburger occurring
∼1:3km below sea level (bsl) in Parker County to more than
2.7 km under Dallas County (e.g., Pollastro et al., 2007;
Hornbach et al., 2016;Smye et al., 2019; see Fig. 1a for
place names). A recent compilation of interpreted well-log
data across the FWB provides thickness estimates of the
Barnett and Ellenburger formations and estimates for the top
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of the crystalline basement near each earthquake sequence
(Smye et al., 2019). We use sonic logs (Fig. 2b) to constrain
P- and S-wave velocities. The Trigg Well (Geotechnical
Corporation, 1964), located in Tarrant County near the
DFW Airport and Irving–Dallas earthquake sequence, and
the Briar saltwater disposal (SWD) well, located in Wise near
the Azle–Reno sequence, provide sonic logs constraining
compressional wave interval velocity through the basin sedi-
mentary units and are in general agreement (Fig. 2b). The
wells also reflect the basin dip; the western Briar Well has a
significant velocity jump at 2.2 km and the Trigg Well at
∼3km below surface reflecting the top of the Ellenburger
formation. Dipole sonic logs available at the Bond Ranch
SWD well, in western Tarrant County near Azle–Reno,
and the A1MD SWD well, near the DFW Airport, suggest
VP=VSof 1.72 for the Ellenburger and crystalline basement,
ranges of 1.82–1.89 through the sedimentary package, and
a return to 1.73 in the upper 500 m. Not many wells drill
to top of basement, and sonic-log data do not indicate a
significant velocity contrast between the Ellenburger and
crystalline basement. Seismic reflection data in the basin
(e.g., Magnani et al., 2017) and the updated FWB strati-
graphic model (Smye et al., 2019) confirm an Ellenburger
thickness of ∼1km. We use the Briar and Bond Ranch well
data to set a 1D model for the Azle region and use the Trigg
and A1MD data for DFW Airport, Irvi ng–Dallas, Venus, and
Cleburne sequences (Fig. 2c). Previous studies of the
Cleburne and DFW Airport relied on only Trigg well data
(Frohlich et al., 2011;Justinic et al. 2013).
Well-log data do not constrain the very shallow
(<0:5km) or deep (>5km) velocity structure required for
accurate hypocenter location. Ambient-noise analysis of a
10-day deployment of 130 10 Hz vertical-component nodes,
deployed near Azle (DeShon et al., 2018), yields Rayleigh
phase velocities between 0.3 and 0.9 s, which are then
inverted for 1D VPand VS(Sufri et al., 2018). These data
constrain the upper 100 m of the Azle 1D velocity model
(Fig. 2b) but were not extrapolated to the other 1D models.
TA automated receiver functions place Moho depth between
37 and 42 km in and near the FWB with a VP=VSrange of
1.65–1.81 (Data and Resources); we set Moho to 40 km.
Frohlich et al. (2011) incorporated a midcrustal boundary
at 18 km to best model arrivals from DFW Airport earth-
quakes and regional refraction studies across the Ouachita
thrust front show a midcrustal boundary in Laurentia craton
between 20 and 22 km (Keller and Hatcher, 1999). We take
the velocities proved by Keller and Hatcher (1999) with mid-
crustal boundaries between 15 and 25 km, and we find that
18 km best fits first-arrival times on FWB stations. We
adopted the midcrust and lower crust velocities for all 1D
models (Fig. 2d). When an earthquake occurs away from a
known monitored sequence, we adopt the FWB regional
velocity model (Fig. 2d). Models are provided in ⒺTable S1
and every earthquake is reported with the associated velocity
model in ⒺDataset S1.
Magnitude Determination
We determine the magnitude scaling functions for the
FWB and surrounding region using local and regional
recordings of earthquakes in the basin between 2013 and
2018. Whereas at close epicentral distances (<100 km),
earthquakes are recorded by broadband, short-period, and
strong-motion sensors, at regional distances (>100 km) the
earthquake signals are best recorded by the broadband sta-
tions. At very close epicentral distances (<50 km), the dom-
inant recorded phase is the first-arriving Swave; however, at
epicentral distances beyond 50 km, the Lg wave begins to
dominate the signal (Nuttli, 1973;Atkinson and Boore,
2013). Local magnitude is expressed as
EQ-TARGET;temp:intralink-;df1;313;569MLlog10 AΔ−log10 A0Δc; 1
in which log10 AΔis the base-10 logarithm of the peak
amplitude (in millimeters) on a Wood–Anderson seismom-
eter measured at some epicentral distance Δ(in kilometers),
and cis a station correction term that is not applied in this
study (Richter, 1935). The log10 A0Δterm is a distance-
scaling factor that is determined by constraining the zero
point of the magnitude scale to a hypothetical Wood–
Anderson instrument. For instance, at 100 km from the epi-
center, the peak amplitude of an ML3.0 earthquake is equal
to 1 mm as defined by Richter (1935). With a c-value of 0,
the distance-scaling factor can thus be expressed as
EQ-TARGET;temp:intralink-;df2;313;404 log10 A0100log10 A100−3log10 1−3:2
We empirically derive the log10 A0Δterm by first convolv-
ing instrument-corrected waveforms with a Wood–Anderson
instrument response. We then sample events with at least
one recording station at an epicentral distance of ∼100 km,
which is then used as a normalization station for that earth-
quake. Peak amplitudes are derived from the greater of the
two horizontal-component waveforms bandpass filtered
between 0.1 and 5.0 Hz (Fig. 3), following the original prac-
tice described by Richter (1935) and adopted by U.S.
Geological Survey for computation of ML(Patton et al.,
2016). Normalization of all stations for each event to the
recording at ∼100 km conditions each earthquake to ML3.0.
A previous local magnitude scale derived using FWB data
calibrated MLto the ANSS ComCat reported mbLg follow-
ing the method of Walter et al. (2016) and Scales et al.
(2017). The Scales et al. (2017) relation has been adopted
as MLfor the TexNet (Savvaidis et al., 2019).
Here, we derive an attenuation curve using recordings
of earthquakes reported in the ComCat, following Scales
et al. (2017), but normalized as described earlier. Events
reported in the ComCat exhibit good signal-to-noise ratio
at regional broadband stations (Fig. 1c) and at broadband
and strong-motion stations within the basin. In addition, we
use recordings from the TA between 2008 and 2011. The
initial earthquake set (black circles, Fig. 3) yields primarily
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regional distance data out to 400 km. The best-fit attenuation
curve (gray line, Fig. 3) models amplitude of first-arriving S,
transition to Lg. This curve fit represents the attenuation of
the Lg waves and could also be considered an mbLg mag-
nitude equivalent. This station–event dataset is identical to
Scales et al. (2017), but the change in normalization sig-
nificantly reduces scatter in the amplitudes at individual
stations (Scales et al., 2017) and matches ComCat mbLg
without need of additional correction. The resulting ML
relationship is
EQ-TARGET;temp:intralink-;df3;55;322ML2019alog10 A0Δ−1:19 log10Δ−0:6:3
The NTXES catalog contains many very small earth-
quakes that were not recorded at 100 km or on the broadband
and strong-motion sensors originally analyzed. We found
that the ML Scales and ML2019arelationship significantly
overestimated peak amplitudes for local stations (<50 km).
Therefore, we normalize the short epicentral distance peak
amplitudes (light gray symbols, Fig. 3) using stations at
50 km distance and then adjust the amplitude values to the
zero point based on the 100 km normalization distance data.
The resulting MLis
EQ-TARGET;temp:intralink-;df4;55;169ML2019blog10 A0Δ−1:9log10Δ0:6:4
This attenuation curve calculates MLthat match the mbLg
well for earthquakes at local distances (<50 km) but over-
estimates the magnitudes of earthquakes at regional distances
(Fig. 3). The scatter in the plot is attributed partly to stations’
site effect and radiation pattern.
The NTXES catalog reports a single magnitude per earth-
quake calculated using the Antelope software magnitude cal-
culator dbevproc. Any event reported within the NTXES
catalog recorded using only stations within the 50 km epicen-
tral distance limit uses the ML2019battenuation curve func-
tion, which is included as a modification to the dbevproc
parameter file. Meanwhile, if an event recorded within the
FWBusesmanyregionalstationsatdistancesexceeding
50 km, then the ML2019aattenuation curve function applies.
However, no events reported in the 2008–2018 NTXES cata-
log use regional phases because the 1D velocity models are
designed for local network data, and hence regional phases
are not integrated into the Antelope database, even for larger
earthquakes. In practice, all MLreported in the NTXES catalog
through 2019 reflect ML2019b. Uncertainty is estimated to be
on the order of 0.1–0.3 units. ⒺFigure S1 shows the crossplot
between ML2019band mbLg for earthquakes reported in the
NTXES and ComCat catalogs, respectively.
Results
Earthquake Catalog
The seismicity reported in the NTXES catalog describes
individual earthquake sequences along linear features iden-
tified as faults and contains individual earthquakes scattered
in time that are not easily ascribed to known faults (Fig. 4).
The catalog describes two separate time periods of seismic
monitoring activity: 2008–2010 and post-2013 (Fig. 4). In
the NTXES catalog, we identify nine active earthquake
sequences on discrete faults described by their location and
year of initial activity here: DFW Airport (2008), Cleburne
(2009), Azle–Reno (2013), Irving–Dallas (2015), Venus
(2015), Haslet (2015), Lake Lewisville (2017), Fort Worth
(2017), and west Cleburne (2018). Of these, Lake Lewisville,
Fort Worth, and west Cleburne have not been previously
reported and have only one or two monitoring stations within
a 10 km hypocentral distance. These three sequences are
shown in cross section in Figure 5but have significant depth
uncertainty compared with the well-recorded Azle–Reno,
Irving–Dallas, and Venus sequences. Figure 6shows the
formal uncertainties for the NTXES catalog, subdivided by
the three significant post-2013 event sequences, and all
earthquakes located using the regional velocity model.
Taking the entire dataset, median values for major, minor,
and depth axes are <0:4km and median origin time error
is 0.04 s. The residual measure, sdobs, also has a median
of 0.04 s. Individual event uncertainties can range higher,
however, and we provide formal error estimates for each
event in ⒺDataset S1.
The majority of earthquakes in the FWB are occurring
within the Precambrian granitic basement (Fig. 5b–g).
However, a portion of earthquakes within the Azle–Reno and
regionally located sequences locate within the Ellenburger
formation (Fig. 5b,e–g). Whereas the shallower Azle–Reno
events are associated with an antithetic feature near the main
Figure 3. Attenuation curves created for the FWB. Light gray
symbols represent peak amplitudes normalized to a station located
50 km from the epicenter; symbol shape follows Figure 1. Black
circles represent peak amplitude normalized to a station located
100 km for earthquakes reported in the comprehensive catalog
(ComCat). The dashed gray line best fits small-magnitude earth-
quakes recorded by the NTXES networks, and the solid gray line
best fits regional broadband data. Hence, we adopt ML2019battenu-
ation relation for data recorded at <50 km and the ML2019afor data
at >50 km (solid portions of lines).
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fault (Hornbach et al., 2015), the shallower events in the
regionally located sequences are likely an effect of larger
depth uncertainties because of a lack of close hypocentral
distance stations.
Each of the earthquake sequences within the FWB
exhibits swarm-like behavior rather than resembling main-
shock–aftershock sequences. Figure 4shows the magnitude
versus time distribution of all earthquakes recorded within
the FWB separated by reporting catalog. The characteristic
distribution of seismicity over time associated with each indi-
vidual sequence in the FWB is a relatively short period (6–12
months) of peak seismicity followed by a steep decline in
subsequent seismicity. However, overall basinwide seismic-
ity rates have remained steady since the onset of recorded
seismicity in the FWB in 2008. Thus, the gap in recorded
seismicity within the NTXES catalog from 2010 to 2013
is actually a gap in local seismic monitoring capabilities
rather than seismic activity.
Magnitude Distribution
All NTXES catalog magnitudes are calculated using the
ML2019battenuation curve function (Fig. 3). The overall
magnitude range of earthquakes within the NTXES catalog
is ML−1:0to ML4.0, although the magnitude range of each
individual sequence varies. The differences in the number of
stations, station geometry, and overall noise levels across the
sequences described in the NTXES catalog led to large
variations in the degree of catalog completeness across the
nine sequences in the FWB.
There is spatial variation in the magnitude of complete-
ness (Mc) and b-values of the sequences described within the
NTXES catalog. The NTXES catalog is divided into four
subgroups; the three significant post-2013 sequences being
the Azle–Reno, Irving–Dallas, and Venus sequences and the
sequences located using a regional velocity model hereafter
referred to as the regional sequences. Mcand b-values are
calculated for each subgroup using the 90% goodness-of-
fit method (Wiemer and Wyss, 2000) and the maximum-
likelihood estimation method, respectively (Bender, 1983).
We observe a wide range in Mcvalues across the subgroups
from Mc0:0for the Venus subgroup to Mc2:1for the
regional events subgroup (Fig. 7). The higher Mcvalue for
the regional events can be attributed to a lack of local stations
to monitor the small-magnitude events. Meanwhile, the
variation in Mcvalues across the three locally monitored
sequences in the NTXES catalog can be attributed to a
nonoptimal initial network geometry in the case of the
Azle–Reno sequence and to elevated noise levels in the
Irving–Dallas sequence, which is embedded in the metroplex
(DeShon et al., 2018). The b-values also vary across the sub-
groups from 0.67 for the Irving–Dallas subgroup to 1.01 for
the Azle subgroup (Fig. 7). The lower b-values calculated for
the Irving–Dallas and Venus subgroups are likely due to a
(a)
(b)
Figure 4. (a) Magnitude versus time plot of the NTXES catalog separated into the Azle, Irving–Dallas, Venus, and regional subgroups
(dashed lines indicate time period in which there were no active stations within the FWB). (b) Magnitude versus time plot of the earthquakes
located within the FWB from the Frohlich (2012), ComCat, and Texas Seismic Network (TexNet) earthquake catalogs.
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variety of factors such as Mcuncertainties (Woessner and
Wiemer, 2005), missing early lower magnitude events before
instrument deployment (Scales et al., 2017), or noise-level
issues (DeShon et al., 2018). In addition, using the same
methodology, we calculated that the 2008–2018 ComCat
catalog of FWB earthquakes has an Mcvalue of 2.6 and
b-value of 1.25 (Fig. 7). Last, we calculated the b-value
for the NTXES catalog using the Mcvalue from the regional
events subgroup (2.1) and found a value of 0.74.
Location Changes from Prior Catalogs
The seismicity reported within the NTXES catalog for
the DFW Airport, Cleburne, Azle–Reno, Irving–Dallas, and
Venus areas has been presented and discussed in prior pub-
lications but now have some differences in earthquake loca-
tions to the NTXES catalog presented here. The NTXES
catalog locations are different than in prior publications
because of the updating of velocity models used for earth-
quake location (Fig. 2). Previous publications presented the
original velocity models used to calculate earthquake loca-
tions were based on then-available well-log and geologic
data. The updated velocity models have been supplemented
with newly available sonic log, seismic reflection, ambient-
noise tomography, and geologic data as described in the
Velocity Models section. Overall, there is little change in the
earthquake hypocenter locations with median changes (with
50% confidence error values) of 0:00 0:07,−0:01 0:07,
and 0:00 0:19 km for the latitude, longitude, and depth,
respectively, from the prior published catalogs to those pre-
sented here. In addition, origin time differs only slightly with
a median change of −0:01 0:03 s(ⒺFig. S3). Therefore,
although the earthquake locations have slightly changed with
the updating of the velocity models, the fault structures
described by the distributions of the earthquake locations at
each sequence site are similar. Thus, previous interpretations
of fault geometries and earthquake location distributions
remain valid.
Discussion
Earthquakes and Faults
The majority of active faults in the FWB are northeast–
southwest-trending normal faults, which are concentrated in
the northeast portion of the basin (Fig. 1b). Prior studies
focusing on the three most significant post-2013 FWB
(c)(b)
(e)(d)
(g)(f)
(a)
Figure 5. (a) Map view of the NTXES study area showing the locations of all earthquakes in the catalog shaded by their time of occur-
rence and scaled by their magnitude. The major roads and highways (gray lines) in the region are also shown. Lettered dashed lines represent
profile lines used to create the separate cross-sectional views for each named sequence. (b–g) Cross-sectional views of each named sequence
site using the same occurrence timescale. The depths of the top of the Ellenburger (dashed lines) and basement (solid lines) at each sequence
site are also shown. The color version of this figure is available only in the electronic edition.
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(a) (b)
(c) (d)
(e) (f)
(g) (h)
Figure 6. (a,c,e,g) Scatter plot views showing the lengths of the (a) major and (c) minor axes of the 68% confidence error ellipsis,
(e) associated depth errors, and (g) origin time errors of the NTXES catalog earthquakes versus time (dashed lines indicate time period
in which there were no active stations within the FWB). Each earthquake is represented by a separate circle shaded by its sequence.
(b,d,f,h) Stacked histograms showing the distributions of the same four error parameters in the same order for the NTXES catalog.
Each sequence’s contribution to the cumulative distribution of location errors is shown. The median and median absolute deviation
(MAD) values for each location parameter are also shown. The color version of this figure is available only in the electronic edition.
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sequences have used the NTXES catalog to interpret fault
geometries and deformation histories of the active faults in
the FWB through the use of focal mechanism (Quinones
et al., 2018) and seismic reflection data (Magnani et al.,
2017). The focal mechanisms generated from the NTXES
catalog described the source faults of each of these sequences
as steeply dipping normal faults with strikes of ∼40° and dips
of between 56° and 70° (Quinones et al., 2018). Meanwhile,
seismic reflection data collected across the Venus and
Irving–Dallas sequence sites revealed a lack of vertical dis-
placement on the faults at both sites in rocks younger then
∼310 Ma (Magnani et al., 2017). This implies that the faults
at both sites remained inactive since the Pennsylvanian.
Subsequently, additional proprietary seismic reflection data
collected across the basin revealed more widespread north-
east–southwest-trending faulting in the northeast portion of
the FWB. Also, the majority of northeast–southwest-trend-
ing faults in the FWB are considered optimally oriented for
failure with high-slip potentials within the local and regional
stress fields described by the focal mechanisms and borehole
breakout data collected from the basin (Quinones et al.,
2018; P. H. Hennings et al., unpublished manuscript, 2019;
see Data and Resources). In each study, the NTXES catalog
was essential in providing proper constraints and interpreta-
tions of the resulting imaged fault structures in the FWB.
The NTXES catalog contains a record of seismicity
occurring within the previously undocumented Lake
Lewisville (2017), Fort Worth (2017), and west Cleburne
(2018) sequences. The earthquakes within these sequences
are located using the regional velocity model with data
collected by a combination of TexNet- and SMU-operated sta-
tions, although no dedicated local networks have been
installed at any of these sequence sites. Thus, fewer earth-
quakes have been detected within these sequences, and those
that have been located have higher associated depth uncertain-
ties. Because of these issues, we cannot provide the same
degree of fault interpretation for these three sequences com-
pared with the other post-2013 sequences. The Lake
Lewisville sequence consists of 17 earthquakes with depths
ranging from 2 to 9.5 km, which appear to occur along a
steeply dipping northeast–southwest-trending fault plane
(Fig. 5e). The Fort Worth sequence consists of only nine
detected earthquakes ranging in depth from 2 to 7 km
(Fig. 5f). We have not provided a fault interpretation for
the Fort Worth sequence because of the lack of associated
hypocenter locations. The west Cleburne sequence is the most
recent to become active; however, its associated earthquake
count has already surpassed those of the Lake Lewisville
and Fort Worth sequences. The west Cleburne sequence earth-
quakes have the highest location uncertainty values in the
NTXES catalog because of a sizable network azimuthal
gap and the lack of local stations for depth control. The earth-
quakes in west Cleburne range in depths from 1 to 5 km and
appear to describe a steeply dipping north–south-trending
fault similar in orientation to the fault described by the original
Cleburne sequence (Fig. 5g,Justinic et al.,2013). This north–
south-trending fault interpretation means this fault would not
be optimally oriented for failure within the previously reported
FWB stress regimes (Lund Snee and Zoback, 2016;Quinones
et al.,2018); however, seismic reflection and well head data
interpretation also point to a north–south-trending fault at this
location (P. H. Hennings et al., unpublished manuscript, 2019;
see Data and Resources).
Earthquakes and Injection Data
The seismicity occurring within the FWB is part of the
larger trend of increasing amounts of induced seismicity
within the central United States, which has been associated
with fluid injection activities. Pore-pressure diffusion asso-
ciated with fluid injection activities is hypothesized to be the
primary mechanism driving induced seismicity within the
FWB (Frohlich et al., 2016;Hornbach et al., 2016) and
throughout the central United States (e.g., Keranen and
Weingarten, 2018). Monthly volumes of fluids injected into
the Ellenburger formation, the main disposal unit in the
basin, by SWD wells are reported by the Texas Railroad
Commission and can be accessed electronically using their
public database. Over the time period of October 2005 to
October 2017, more than 2 billion U.S. barrels of fluids from
179 SWD wells were injected into the Ellenburger formation.
When we examine an interpolated surface describing the
cumulative volumes of injected fluids from 2005 to 2017,
we observe that the northeast portion of the FWB is where
Figure 7. Gutenberg–Richter plot showing the magnitude of
completeness (Mc) and b-values for each subsection of the
NTXES catalog, the NTXES catalog as a whole, and the
National Earthquake Information Center catalog of FWB events
for comparison. The Mcvalues are represented by the inverted tri-
angles in the plot. The color version of this figure is available only
in the electronic edition.
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both the majority of injection activities and seismicity is
occurring within the basin (Fig. 8). In fact, with the excep-
tions of the Irving–Dallas and Lake Lewisville sequences,
the majority of seismicity within the FWB is occurring
within 15 km of at least one injection well. The spatial prox-
imity of these near-well sequences, along with the strong
temporal correlation between the onset of seismicity and
increasing injection rates within the FWB (Fig. 8, inset), sug-
gests that pore-pressure diffusion is the main driving force
for induced seismicity at these sequence sites. However,
injection rates have decreased in recent years from their peak
levels in 2014, mainly because of economic reasons, which
do appear to coincide with lowering rates of seismicity across
the FWB. Previous studies using the NTXES catalog data
focusing on these near well sequences have found that pore-
pressure changes associated with injection activities are sig-
nificant and are the primary mechanism driving seismicity at
these sites (Frohlich et al., 2011;Hornbach et al., 2015,
2016;Scales et al., 2017;Ogwari et al., 2018;Quinones
et al., 2018). However, stress changes associated with pore-
pressure diffusion are often limited to distances close to wells
(<15 km; Segall and Lu, 2015;Goebel et al., 2017), leaving
the question for what the main mechanisms driving seismic-
ity at sites that are at far distances from injection wells.
Far-Field versus Near-Source Triggering
Although pore-pressure changes caused by fluid injection
activities are the dominant stress change effect at near well
distances, modeling results have shown that at farther distan-
ces from injection wells (>15 km), poroelastic stress changes
dominate. Recent studies on stress changes associated with
injection activities have focused on not only understanding
direct pore-pressure changes but also on understanding the
far-field effects of poroelastic stress changes (Segall and
Lu, 2015;Chang and Segall, 2016;Goebel et al.,2017). In the
FWB, two sequences occur away from injection wells: the
Irving–Dallas and Lake Lewisville sequences (Fig. 8).
Results of injection-related stress change modeling pre-
dict a crossover distance at which poroelastic stress effects
become dominant over direct pore-pressure stress changes
(Segall and Lu, 2015;Goebel et al., 2017). However, this
crossover distance is highly variable, relying on factors such
as the properties of the injection unit, the injection rate, and
the duration of injection activities. Prior studies sought to
model pore-pressure stress changes within the FWB, focus-
ing on the basinwide effects of injection activities (Gono
et al., 2015;Hornbach et al., 2016;Zhai and Shirzaei, 2018)
and the localized stress changes associated with injection
activities at the DFW Airport (Ogwari et al., 2018).
Hornbach et al. (2016) found the Ellenburger to be overpres-
sured by about 1.7–4.5 MPa at injection well sites in north-
east Johnson county, and Zhai and Shirzaei (2018) calculated
overpressure within the Ellenburger to be ∼2MPa in that
same area. Ogwari et al. (2018) also found that injection
activities increased pore fluid pressure within both the
Ellenburger and basement formations in the DFW Airport
area. In these studies, we observe that stress changes asso-
ciated with direct pore-pressure effects are highly concen-
trated at close distances to the wells. Thus, it is believed that
poroelastic rather than pore-pressure stress changes are the
primary driving mechanism of seismicity sequences at far
distance sites. However, although poroelastic stress changes
are dominant over pore-pressure stress changes at far distan-
ces, the actual magnitude of the poroelastic stress changes is
still lower than the near well pore-pressure effects (Segall
and Lu, 2015). This leads to a larger question, still remaining
to be resolved in the FWB: Would poroelastic stress changes
alone be large enough to have induced slip on the far distance
sequences? Previous studies attempted to calculate the slip
probability and stress change necessary to induce slip of the
Irving–Dallas sequence fault (Quinones et al., 2018;P.H.
Hennings et al., unpublished manuscript, 2019; see Data and
Resources). Both studies determined that the Irving–Dallas
fault is an optimally oriented for failure within the given
stress field (3:48 2:39 MPa), but it is unclear whether
poroelastic stress changes alone would be enough to induce
slip on the fault.
Figure 8. Map view showing the interpolated cumulative injec-
tion volumes of all fluids injected into the Ellenburger formation
from October 2005 to October 2017. The interpolation was con-
ducted using an inverse distance weighting scheme using a weight-
ing power of 1 and using data values taken from the 10 nearest wells
to each point in space. Each cell is approximately 1.94 km by
1.94 km in size. The earthquake (circles) and injection well (arrows)
locations are also shown. (Inset) Plot showing the monthly injection
volumes in millions of U.S. barrels (M bbls) for the FWB as a whole
(dashed line) and the monthly number of earthquakes recorded
within the NTXES catalog (solid line) over the same time period.
The color version of this figure is available only in the electronic
edition.
Tracking Induced Seismicity in the FWB: A Summary of the 2008–2018 North Texas Earthquake Study Catalog 1213
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North Texas
The FWB seismicity shares many characteristics with
other induced seismicity sites occurring throughout the cen-
tral United States such as primarily being concentrated near
injection wells, occurring within the basement formations,
and having a strong temporal correlation with increasing
injection rates. Numerous catalogs of induced seismicity
throughout the central United States report that the majority
of seismicity is occurring along faults residing within the
Precambrian basement, which typically underlies the main
fluid disposal unit in the region. This pattern in induced
earthquake depths has been observed in the FWB, Guy-
Greenbriar (Horton, 2012), Raton basin (Rubinstein et al.,
2014), Oklahoma (Keranen et al., 2014), southern Kansas
(Rubinstein et al., 2018), and Delaware basin sequence sites.
This is not to say that no seismicity occurs within the units
above the basement; seismicity was also recorded within the
fluid disposal unit at each of the aforementioned sequence
sites. These earthquake depth distributions imply that the
active faults within the basement formations are either
hydraulically conductive or connected to the fluid disposal
formations (Chang and Segall, 2016).
Seismic reflection data collected across the Irving–
Dallas and Venus regions show that the faults at each site
stretch into the overlying units above the basement (Magnani
et al., 2017). This means that the faults themselves could act
as the connection between the fluid disposal and basement
units allowing for the transfer of pore pressure between them.
Pore-pressure modeling work focusing on the Azle–Reno
and Venus sites is ongoing; however, such modeling efforts
are not currently underway for the Irving–Dallas site because
of its far distance from injection wells. At present, all mea-
surements of pore-pressure and poroelastic stress changes
affecting the Irving–Dallas site come from basinwide mod-
eling efforts, which have calculated very little to no stress
changes in the Irving–Dallas area (e.g., Zhai and Shirzaei,
2018). The Irving–Dallas sequence, still the most enigmatic
of the sequences, generated significant felt earthquakes
within the NTXES catalog, and determining the main driving
mechanism behind its seismicity will require a better under-
standing of how pore pressure, poroelasticity, and the
injected fluids flow and diffuse throughout the FWB.
Summary
The NTXES catalog represents the most complete rec-
ord of seismicity occurring within the FWB. All catalog
earthquake locations are manually reviewed and calculated
using the GENLOC location algorithm within the Antelope
database software system. The earthquake hypocenter loca-
tions and their 68% confidence error ellipsoid information
are reported within the catalog (see Ⓔsupplemental con-
tent). The 1D velocity models used for locating the FWB
earthquakes were generated using a combination of geo-
logic, well-log, ambient-noise, receiver function, and seismic
reflection data collected from across the basin. All magni-
tudes reported in the NTXES catalog are local magnitudes
calculated using new specialized regional attenuation curve
functions for earthquakes located using either local or re-
gional distance station data. As a whole, the NTXES catalog
earthquakes have low location uncertainties due to the major-
ity of events being located by dedicated local seismic net-
works at close epicentral distances with good azimuthal
coverage. In the NTXES catalog, we identify nine separate
earthquake sequences occurring along discrete steeply dip-
ping northeast–southwest-trending normal faults located pri-
marily within the Precambrian basement formation. The Mc
of the NTXES catalog varies across the sequences because of
differences in station density and network geometry; how-
ever, the overall Mcof the catalog is lower than that of other
seismicity catalogs in the FWB such as the ComCat catalog.
Overall, seismicity in the FWB does have a strong spatial and
temporal correlation with fluid injection activities with the
majority of seismicity occurring within 15 km of SWD wells.
The main exceptions to this are the Irving–Dallas and Lake
Lewisville sequences, which have no SWD wells within
15 km. This means that far-field rather than near-source
stress changes may contribute to driving seismicity at either
sequence site. Future work involving the NTXES catalog
may focus more on the modeling of geomechanical stress
changes associated with fluid injection activities to discern
the main mechanisms driving seismicity both near and far
from well distance sequence sites.
Data and Resources
All seismic data used in this study were collected as part
of the North Texas Earthquake Study (NTXES) projects
focusing on the study of seismicity occurring within the
northeastern portion of the Fort Worth basin (FWB). These
projects were conducted by Southern Methodist University
(SMU) using a combination of SMU, U.S. Geological Survey
(USGS), Incorporated Research Institutions for Seismology–
Program for the Array Seismic Studies of the Continental
Lithosphere (IRIS-PASSCAL), and Texas Seismic Network
(TexNet) instruments. The data used in this study can be
obtained from the IRIS Data Management Center at www
.iris.edu under the Federated Digital Seismic Network codes
NQ, ZW, 4F, and TX (last accessed February 2019).
Transportable Array (TA) receiver function information can
be accessed using the IRIS Earthscope Automated Receiver
Survey (EARS) data services product at doi: 10.17611/DP/
EARS.1. Injection volume information for saltwater disposal
(SWD) wells in the FWB can be obtained from the Texas
Railroad Commission’s online public database at webapps.
rrc.texas.gov/H10/h10PublicMain.do (last accessed January
2019). The TexNet earthquake catalog information can be
obtained from their public online website at www.beg.utexas.
edu/texnet-cisr/texnet (last accessed February 2019). The
Advanced National Seismic System (ANSS) Comprehen-
sive Catalog (ComCat) information can be obtained from
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the public online website at https://earthquake.usgs.gov/
earthquakes/search/ (last accessed May 2019). The other
information is from the unpublished manuscript by P. H.
Hennings, J. Lund Snee, J. Osmond, H. R. DeShon, R.
Dommisse, E. Horne, C. Lemons, and M. D. Zoback, 2019,
“Injection-induced seismicity and fault slip potential in the
Fort Worth basin, Texas.”
Acknowledgments
The North Texas Earthquake Study (NTXES) projects were partially
funded by U.S. Geological Survey (USGS) Earthquake Hazards Program
Cooperative Agreements G15AC00141 and G16AC00247 to H. R.
DeShon and M. B. Magnani in addition to funding provided by the Texas
Seismic Network (TexNet) program at the Bureau of Economic Geology,
University of Texas. The authors thank Kaylee Kaigler, Austen Klauser,
Elizabeth Layton, Remi Oldham, and Mason Phillips for aid in the manual
identification of phase onset times for many of the earthquakes within the
NTXES catalog. The authors declare that we have no real or perceived con-
flicts of interest.
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Louis Quinones
Heather R. DeShon
SeongJu Jeong
Oner Sufri
Kevin B. Kwong
Huffington Department of Earth Sciences
Southern Methodist University
P.O. Box 750395
Dallas, Texas 75275-0395 U.S.A.
hdeshon@smu.edu
Paul Ogwari
Oklahoma Geological Survey
100 E. Boyd Street, Suite N131
Norman, Oklahoma 73019 U.S.A.
Monique M. Holt
Department of Geology and Geophysics
115 S 1460 E, Room 383
Salt Lake City, Utah 84112-0102 U.S.A.
Manuscript received 2 March 2019;
Published Online 11 June 2019
1216 L. Quinones, H. R. DeShon, S. J. Jeong, P. Ogwari, O. Sufri, M. M. Holt, and K. B. Kwong
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