GRC Transactions, Vol. 37, 2013
Application of Radar Interferometry to Detect Subsidence and Uplift
at the Heber Geothermal Field, Southern California
Mariana Eneva1, David Adams1, Giacomo Falorni2, and Jessica Morgan2
1
Imageair Inc., Reno, Nevada
TRE Canada Inc., Vancouver, BC, Canada
[email protected]
2
1. Study Area
Keywords
InSAR, SqueeSAR, PSInSAR, radar interferometry, subsidence,
uplift, surface deformation, geothermal, Heber, Imperial Valley, Salton Trough
The Imperial Valley extends for about 80 km in southern California, from the southern shore of the Salton Sea toward the U.S.
– Mexico border (Figure 1). Together with the Coachella Valley
Abstract
Interferometric synthetic aperture radar (InSAR) is applied
to data from the Envisat satellite, collected in the period 20032010, to detect surface deformation at the Heber geothermal
field in Imperial Valley of southern California. The particular
technique applied, SqueeSARTM developed at TRE, makes use
of permanent and distributed scatterers. This makes it possible
to observe deformation in agricultural areas, where conventional
InSAR does not work, so our results are the first of this kind
for Heber. Observations are obtained first in the line-of-sight
(LOS) to the satellite from two orbital geometries, descending
and ascending, and are subsequently used to calculate horizontal
movements in the west-east direction, as well as vertical displacements. Maps of annual deformation rates derived from the
satellite data (2003-2010) show two adjacent areas of subsidence and uplift at Heber, confirming observations from annual
ground-based leveling surveys. As to the horizontal movements
in these areas, they are westward in the uplift area and eastward
in the subsidence area. Maximum LOS rates away from the
satellite (indicative of subsidence) reach –46 mm/year, while
maximum LOS rates toward the satellite (indicative of uplift)
reach +22 mm/year. However, the uplift is only taking place
after 2005, prior to which the leveling data show mostly subsidence traced back to the beginning of leveling data availability
from 1994. These changing trends of surface deformation in
the 2003-1010 uplift area can be readily traced to changes in
injection volumes. Examples of rates along profiles and mean
deformation time series within small polygons of interest are
also shown. The results demonstrate the utility of InSAR for
geothermal operations management, planning, and environmental impact mitigation.
B SZ
Salton Sea
Salton Sea G F
Nor th B r awley G F
GF
SH F
E ast M esa G F
I mpF
H eber G F
Figure 1. Geothermal areas in Imperial Valley, southern California. Green
outlines mark KGRAs. Names show currently operating geothermal fields
(GF). Blue traces denote faults and assumed fault zones (USGS). BSZ - the
center of the wide Brawley Seismic Zone, SHF - Superstition Hills Fault,
ImpF - Imperial Fault. Superimposed on a satellite image.
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to the north, it is part of the Salton Trough, which is a spreading
center associated with the relative movement of the Pacific and
North American Plates. Thus it is characterized by active tectonics,
with both subsidence and substantial horizontal movements taking
place on a regional scale. Local tectonic sources of deformation
are represented by networks of strike-slip and normal faults,
many of which do not have surface expression, especially in the
agricultural areas.
In addition to the gradual deformation due to regional and
local tectonics, the Salton Trough experiences abrupt surface
ruptures due to large earthquakes and associated aseismic slip.
Seismic swarms, such as those in 1981, 1989, 2005, 2009, and
2012 have been related to the high heat flow in the region (BenZion and Lyakhovsky, 2006). Aseismic creep has been detected
on many occasions in Imperial Valley, usually triggered by larger
earthquakes in the region and the wider vicinity (e.g., Rymer et
al., 2002), but sometimes occurring independently. Of particular
interest in the study period (2003-2010) are a M7.2 event, which
occurred south of the U.S. – Mexico border in April 2010, and
an aseismic event of equivalent magnitude Mw~4.7, which occurred in October 2006. Both events triggered slip on some faults
in Imperial Valley (Wei et al., 2009, 2011). We have previously
observed these effects as well, along with the expression of three
faults (San Andres, Superstition Hills, and Imperial) in the surface
deformation field (Eneva et al., 2013).
The high heat flow in the Salton Trough is associated with
a number of geothermal resources. We have previously shown
surface deformation maps for the Salton Sea geothermal field
(Eneva et al., 2009, 2012, 2013; Eneva and Adams, 2010) and
Heber, North Brawley, and East Mesa geothermal fields (Eneva
et al., 2013). Here we focus on more details of the surface deformation observed at Heber. This field was first developed in the
early 1980’s by the Chevron Geothermal Company. Although the
initial output was lower than expected, the operation of the field
has been successful since mid-1993 (Sones and Krieger, 2000),
when a modular binary power plant was added to an earlier double
flash plant. The reservoir model includes three major permeability
units (James et al., 1987) – “capping” clays at depth of 500-1800
ft, high matrix permeability sandstone “outflow” reservoir at
1800-5500 ft, and high permeability “feeder” faults and fractures
in indurated sediments below 5500 ft. These were deduced from
seismic lines, and maps and cross-sections of lost circulation and
temperature distribution. James et al. (1987) also commented on
a steep pressure decline under initial production, but subsequent
rapid stabilization due to regional aquifer support, from which they
concluded that the reservoir is very permeable and that there is
a significant opportunity for additional development of the field.
Allison (1990) used borehole breakout orientations to confirm
these findings, particularly the right strike-slip and normal faults
suggested by James et al. (1987).
been differential InSAR (DInSAR) (e.g., see Eneva, 2010 for
an overview). There have been DInSAR observations at some
geothermal fields, such as East Mesa in southern California
(Massonnet et al., 1997), fields in Nevada (e.g., Oppliger et al.,
2008), Coso in eastern California (Wicks et al., 2001; Fialko and
Simmons, 2000), and Cerro Prieto in Mexico (Carnec and Fabriol,
1999). However, DInSAR does not work in agricultural areas like
Imperial Valley. For such areas, a recent innovation, PSInSARTM
(Ferretti et al., 2000, 2007) is needed. It makes use of so-called
“permanent scatterers” (PS) to produce detailed deformation
time series and deformation rates derived from those time series.
PS are buildings, fences, lampposts, transmission towers, rock
outcrops, points aligned along roads and canals, etc., which serve
as reflectors of the radar waves. We have previously applied the
PSInSAR technique for the Salton Sea geothermal field, using
two-year data from a Canadian satellite, Radarsat (Eneva et al.,
2009; Eneva and Adams, 2010).
The latest improvement of PSInSAR, called SqueeSARTM
(Ferretti et al., 2011), adds to the PS so-called “distributed scatterers” (DS). These are homogeneous areas emitting signals with
smaller signal-to-noise ratios than the PS, but still significantly
above the background. These include rangelands, pastures, and
bare earth characteristic of relatively arid environments. This
technique is particularly well suited to study rural areas. We have
successfully applied SqueeSARTM for the San Emidio geothermal
field in northwestern Nevada (Eneva et al., 2011) and to the Salton
Sea geothermal field (Eneva et al., 2012, 2013) using data from
the European Envisat satellite collected over an 8-year period
(2003-2010).
Displacement measurements with SqueeSAR are done relative to a reference point, considered to be stable. This is similar
to choosing a reference (datum) point when performing leveling
surveys. Thus only relatively local movements are measured with
SqueeSAR, rather than regional ones. At Heber we compare the
satellite observations with measurements from leveling surveys,
so we use as a reference point the same datum (benchmark A-33)
used for those surveys.
The deformation is first measured in the line-of-sight (LOS)
to the satellite. The LOS movements are negative when their
direction is away from the satellite and positive toward the satellite. We use two sets of scenes, where the satellite moves north to
south (descending) and south to north (ascending). The resulting
two sets of LOS movements can be decomposed into vertical and
horizontal components.
3. Data
3.1 Satellite data
Two sets of radar scenes from the European Envisat satellite are
used in this analysis. The data were obtained from the European
Space Agency (ESA). One data set consists of 45 descending
images from track 356, covering the period February 7, 2003 –
September 3, 2010. The other one consists of 33 ascending images
from track 306, covering the period December 16, 2003 – August
21, 2010. The viewing direction from the satellite is right-looking,
perpendicular to the heading direction of satellite movement,
so it is west-northwest (WNW) for the descending scenes and
east-northeast (ENE) for the ascending scenes. The PS and DS
2. Techniques
The method we use for mapping surface deformation in
Imperial Valley is satellite radar interferometry, also known as
interferometric synthetic aperture radar (InSAR). The traditional
InSAR technique used for detecting deformation from earthquakes, water pumping, mining, and some geothermal areas, has
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determined from these two geometries are not identical, and it is
common for one of the orbital geometries to be more favorable
for a given area, yielding more PS and DS. At Heber this is the ascending geometry. The look (incidence) angles toward the ground,
(i.e., measured from the vertical to the ground), are 200 to 220,
i.e. rather steep. The sensitivity of the movements detected in the
line-of sight (LOS) is measured with values between 0 and 1, with
larger values indicating greater sensitivity. These are calculated
from products of the sines and cosines of the look and heading
angles. Because of the steep look angle, the LOS movements are
most sensitive to the vertical surface deformation, with sensitivity
~0.93. The sensitivity to the west-east horizontal component of
surface deformation is about three times smaller, ~0.34-0.37. This
means that if the east component is significantly lower than the
triple amount of the vertical movement, the LOS displacement is
rather representative of the vertical component of deformation.
The sensitivity to the south-north horizontal component is negligible (~0.07-0.08). Therefore, InSAR cannot provide information
on the north horizontal displacements.
Public Works (ICDPW). Our current leveling data set for Heber
consists of the locations and the annual surveys for 132 benchmarks, for the period 1994-2011. The reference point for these
measurements is benchmark A-33 shown in Figure 2.
We also use relocated earthquake epicenters for the period
January 1981 – June 2011 (Hauksson et al., 2012), which are
superimposed on deformation maps and time series. We also look
at cross-sections in depth along profiles, either along or across
linear features suggested by the earthquake epicenters (Eneva et
al., 2012, 2013).
Furthermore, we look at the locations of production and injection wells, as well as the monthly volumes of produced and
injected fluid for individual wells, or the total from all wells within
polygons of interest. These data were obtained from the Division
of Oil, Gas and Geothermal Resources (http://www.conservation.
ca.gov/dog/geothermal/).
Finally, there are some reports for the existence of right strikeslip and normal faults (James et al., 1987; Allison, 1990) at Heber,
shown in Fig. 2. Their locations are approximate at this time,
because the sketches in the cited papers do not show geographic
coordinates. James et al. (1987) also show temperature maps and
cross-sections, indicating that the maximum of the temperature
anomaly (3800 F) at 6000 ft is located just west of the normal
fault, while Allison (1990) reports on the location of the maximum
temperature gradient (580 F/100 ft) further northwest.
3.2 Other Data
The surface deformation measured by SqueeSAR is compared
with leveling data (i.e., vertical measurements) at the Heber geothermal field, provided by the Imperial County Department of
4. Results
Our results are shown as maps of the annual deformation
rates in mm/year, plots of deformation time series, and plots of
deformation rates along profiles of interest. The deformation rates
are color-coded with “warm” colors (red and yellow) indicating
negative movements and “cold” colors (blue) indicating positive
movements. When LOS deformation is shown, negative and
positive displacements mean movements away from and toward
the satellite, respectively. For decomposed vertical movements,
negative values indicate subsidence and positive values show
uplift. For decomposed east movements, negative values indicate westward movements and positive values show eastward
movements. Since the look angle is steep, the LOS movements
are highly sensitive to the vertical displacements, so often LOS
movements away from the satellite are indicative of subsidence,
and toward the satellite – of uplift.
Figure 3 shows the 2003-2010 ascending annual deformation rates in the line-of-sight (LOS) direction to the satellite,
superimposed on an optical satellite image. Urban areas have
the largest numbers of PS and DS, as seen at El Centro and
Calexico. Otherwise PS and DS often align along roads and
canals, while the agricultural fields remain mostly devoid of
them. We observe that an area of negative LOS movements,
i.e. away from the satellite, is seen in the middle of the Heber
KGRA, while an area of positive movements, i.e. towards the
satellite, is located to the northwest in the KGRA and outside
it. These areas are actually associated with subsidence and
uplift, respectively, and this is how we refer to them further
in the text. The subsidence area appears to be associated with
the local right strike-slip and normal faults (James et al., 1987;
Allison, 1990) shown in Fig. 2.
I mpF
E l C entr o
H eber
C alexico
M exicali
Figure 2. Zoom-in on the Heber KGRA from Fig 1. Yellow triangles show
locations of leveling benchmarks. Thick blue lines show approximate locations of right strike-slip and normal faults according to James et al. (1987)
and Allison (1999). Other notations like in Fig. 1.
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Figure 3. Locations of ascending LOS PS and DS. Color coding indicates
movements away (yellow-red) and toward (blue) the satellite. Reference
point is a GPS station, P503, on the Superstition Hills Fault (to the northwest of this map). Other notations like in Figs. 1 and 2.
E l C entr o
Figure 4 shows examples of ascending LOS time series at two
individual PS locations, one in the subsidence area (deformation
decreasing with time) and one in the uplift area (deformation
increasing with time). The slopes of the straight lines fitted to
the individual time series represent the annual deformation rates,
which are color-coded in Fig. 3.
The ascending satellite geometry is more favorable for the
Heber area, so there are more PS and DS points compared with
the descending geometry. Similar to Fig. 3, we also examine maps
of the descending deformation rates and averaged ascending and
descending rates for 200-m pixels (not shown here). Whenever PS
and DS from both the ascending and descending geometries are
observed within a given 200-m pixel, their mean LOS rates are
used to decompose into vertical and horizontal east components.
As seen in Fig. 3, there are areas rather devoid of PS and
DS points, so the next step is to interpolate through these areas.
Figure 5 shows a linear interpolation. Negative values (yellowred) indicate movements away from the satellite for LOS,
subsidence for the vertical decomposition and westward movement for the horizontal decomposition. Positive values (blue)
show LOS movements toward the satellite, uplift for the vertical decomposition, and eastward movement for the horizontal
component. The advantage of this type of deformation maps is
that they show a reasonable spatially continuous model
of the deformation, and the subsidence and uplift areas
are clearer compared with Fig. 3. The “east” deformation
map shows westward movements in the uplift area and
eastward movements in the subsidence area. However,
the maximum westward and eastward movements are not
centered where the maximum uplift and subsidence are,
and are shifted to the northwest.
Table 1 shows the maximum and minimum (i.e.,
maximum negative) rates of the four types of estimated
movements. Note that these are observed at different
points for the ascending, descending, vertical, and east
rates. The vertical and east horizontal decompositions
can be only done within pixels where there are both ascending and descending PS and DS. Since there are no
descending PS and DS near the location of the minimum
ascending value (–45.9 mm/year) in the center of the
subsidence area, the vertical and east components could
not be estimated there. Instead, the minimum descending
value is observed on the periphery of the subsidence area,
and this explains why it is significantly smaller (–22.8
C alexico
Figure 4. Examples of LOS time series at two individual ascending PS locations. Top – surface deformation occurs away from the
satellite, at one of the “red” ascending PS in the subsidence area
shown in Fig. 3. Bottom – surface deformation is toward the satellite, at one of the “blue” ascending PS in the uplift area shown in
Fig. 3. Annual ascending LOS deformation rates, calculated from
the slopes of straight lines fitting these time series, are −39.6 ± 0.9
mm/year and +13.5 ± 1.0 mm/year, respectively.
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Desc L OS
A sc L OS
A -33
A -33
E ast
V er tical
A -33
A -33
Figure 5. Interpolated mean annual rates (mm/year). Dashed lines show an
arbitrary division between the subsidence and uplift areas, indicating that
the pattern of the east horizontal movements is shifted when compared
with that of the vertical movements.
Figure 6. Ascending LOS deformation map with superimposed leveling
benchmarks, wells, and earthquake locations. Benchmarks - empty triangles. Reference benchmark A-33 – solid black triangle. Production wells
- black circles. Injection wells – black squares. M > 0 epicenters – small
crosses. Other notations like in Fig. 5.
mm/year) than the minimum ascending value in the middle.
Consequently, the minimum vertical rate could be only estimated
at the periphery of the subsidence area as well, where there are
both ascending and descending PS and DS. Inside the subsidence area, the vertical component is likely larger, approaching
the ascending observation there, and was likely underestimated
by the interpolation.
Fault (see Fig. 1 for the fault trace). By comparison, only few
epicenters are seen within the Heber KGRA, however the local
Heber seismic network has likely recorded more events; we have
no access to these data at present.
Figure 7 shows four profiles superimposed on the ascending
LOS deformation map from Fig. 5. They traverse the subsidence
and uplift areas. The corresponding deformation rate profiles are
shown in Figure 8. Each plot in this figure shows the four types
of rates (ascending, descending, vertical, and east horizontal),
together with the leveling rates for the period 2005-2010. The
reason these calculations start in 2005 is that in the uplift area
there was a subsidence before that, so if the whole period of the
satellite data is used (2003-2010), the rates reflecting the uplift
would be contaminated by the earlier subsidence, and therefore
underestimated. Note that the leveling rates (green triangles in
Fig. 8) are directly comparable only with the vertical decomposed
rates (pink lines in Fig. 8). We can see that for the most part there
Table 1. Observed maximum and minimum annual rates (mm/year) at Heber.
Ascending Descending
+22.3
+17.6
Maximum
–45.9
–22.8
Minimum
Vertical
+18.2
–27.2
East
+22.4
–27.4
Figure 6 shows a zoom-out of the interpolated ascending LOS
deformation map (from the upper left corner of Fig. 5), with superimposed locations of the leveling benchmarks, production and
injection wells, and relocated M > 0 earthquake epicenters (Hauksson et al., 2012) as recorded by the Southern California Earthquake
Network. The seismicity is abundant along the Imperial fault to
the northeast and along seismic lineaments, not associated with
known faults, which appear to continue from the Superstition Hills
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is good agreement between the leveling and satellite vertical rates
(i.e., the green triangles are on, or close to the pink curves). The
largest discrepancy is seen for one benchmark along profile 3.
The reason is that this benchmark is located near the maximum
observed subsidence, where there are only ascending PS. Since
the presence of both ascending and descending PS is needed to
calculate the vertical component, the vertical movement near
this benchmark can be only interpolated from the flanks of the
subsidence area. Because the interpolation is linear, the vertical
movement here (pink line) is likely underestimated.
Pr ofile 1
NW
SE
Defor mation r ate (mm/year )
Pr ofile 2
1
E
W
Pr ofile 3
N
S
Pr ofile 4
2
4
S
N
Distance along pr ofile (km)
3
Figure 8. Annual deformation rates within 200 m along profiles shown
in Fig. 7, calculated for the period 2005-2010. Green triangles show
rates from leveling benchmarks. Curves show satellite results. Symbols
on curves show mean (crosses) and interpolated (dots) values. Dark blue
- descending LOS rates. Red - ascending LOS rates. Pink – decomposed
vertical rates. Light blue - decomposed east horizontal rates.
A -33
Figure 7. Four profiles marked on the ascending LOS deformation map, for
which annual deformation rates are shown in Fig. 8 next.
results (2003-2010) show eastward (positive) movements in the
subsidence area and westward (negative) movements in the uplift
area. In this rendition of the deformation results, one compares
the slopes (measuring the rates) of the leveling time series (green
curves) with the slopes of the vertical time series (pink curves).
There is overall good correspondence between the leveling and
satellite vertical measurements. Note that the leveling time series
are from individual locations throughout the polygons, whereas
the satellite results are averaged over the whole polygons.
Table 2 shows mean rates for the two polygons, A and B, from
Fig. 9. Mean ascending and descending LOS rates are generally not
the same for a given polygon, but the differences are exaggerated
here, because of lack of descending PS points where the largest
movements are observed (only “witnessed” by the ascending data).
The uplift rates are calculated after 2005, because this is when the
uplift starts. Comparing the mean values of the satellite derived
Another way to look at the results is to calculate the mean
time series within small polygons of interest. Figure 9 shows
two polygons, A and B, from the uplift and subsidence areas,
respectively. The corresponding mean deformation time series
from SqueeSAR are shown in Figure 10, along with the individual
leveling time series for the benchmarks falling within the polygons. The leveling time series are shown for the whole period,
for which leveling data are available, i.e., since 1994. It is clear
that in the subsidence area outlined from the satellite data (i.e.,
for the period 2003-2010), the benchmarks have been indicating
subsidence since 1994, whose rate got accelerated after 2005. In
the uplift area, the benchmark time series also indicate subsidence for a while, but after 2005 the vertical movements turn into
uplift. Note that the horizontal components from the satellite
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?
Sur face defor mation (mm)
Polygon A
B
A
Polygon B
A -33
Figure 9. Polygons superimposed on the ascending LOS deformation map,
for which the mean time series are shown in Fig. 10 next. Polygon A is in
the subsidence area and polygon B in the uplift area.
Table 2. Mean rates at polygons A and B from Fig. 9.
T ime
Area
Asc
Desc
Vert
East
Mean Lev.
Subsidence
–38.7±0.2 –19.3±0.3 –27.5±0.3 +13.8±0.8 –25.4±4.7
2003-2010
Uplift
+19.3±0.4 +6.2±0.2 +14.5±0.2 –19.6±0.5 +16.4±0.9
2005-2010
Figure 10. Deformation time series from the polygons in Fig. 9. Top – results for polygon A in the subsidence area. Bottom – results for polygon B
in the uplift area. Time series from the satellite results are estimated means
for the polygons and are shown with dark blue for descending LOS, red
for ascending LOS, pink for vertical, and light blue for east horizontal
movements. Time series for individual benchmarks are shown in green.
A likely erroneous leveling measurement is marked with a green “?”
Black empty circles show occurrence times of M > 0 earthquakes in the
polygons.
vertical rates and the leveling rates for these two polygons, we can
see that they are within only about 2 mm/year from each other.
Figure 11 shows the production and injection wells at Heber. In
Figure 12 we compare the time series of the monthly fluid volumes
with the leveling time series at the benchmarks in the vicinity of
the wells. For this purpose, four polygons are outlined, A to D.
Polygon A, near the border between the uplift and subsidence areas, includes only injection wells. Polygon B, in the western part
of the subsidence area, includes only production wells. Polygons
C and D include both production and injection wells.
Fig. 12 reveals the connection between the characteristics of
the leveling benchmark time series and the production/injection
volumes. The turn-around from subsidence to uplift, indicated by
the leveling benchmarks in Polygon A, occurs when the injection
levels are ramped up over a period of about 5 to 6 years. The
injection volume levels out in mid-2010, which leads to resumed
subsidence, but this is after the 2003-2010 period of the satellite
data, so this effect cannot be observed in our SqueeSAR results.
In Polygon B, production is increased at the same time when
injection is increased in Polygon A to the west. This initially
leads to flattening of the benchmark time series, but subsidence
resumes after 2008 with changes in the ratio between the injected
and produced fluid volumes. Polygons C and D contain both injection and production wells. After 2008 subsidence accelerates
with increased production in Polygon C, even though injection is
also increased. In polygon D, where production is steadily larger
than injection, increased subsidence occurs after 2005, when the
injection volume is decreased by about 25%.
The maximum uplift occurs to the west and northwest from
the subsidence area, at a distance of 4 to 5 km from its center, and
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D
A
about 2 km from the westernmost injection wells (Polygon A in
Fig. 11). There is more total injection in Polygons C and D, but
there is also production there, whereas injection and production
in Polygons A and B are spatially separated. Although the wells
are directional (James et al., 1987), in the absence of additional
information, the structural control leading to uplift at such a distance from injection, is not clear.
Figure 11.
Polygons, for
which benchmark
time series and
monthly volumes
of produced and
injected fluid are
shown in Fig. 12
next. Benchmarks
are shown with
empty triangles,
production wells
with black circles,
and injection wells
with black squares.
Small crosses mark
M > 0 earthquake
epicenters.
5. Conclusions
The InSAR technique used in this work, SqueeSAR, as
applied to satellite data, is very effective in detecting surface
deformation in agricultural areas, such as that of the Heber
geothermal field in southern California. We present surface deformation maps, profiles of annual deformation rates, and mean
deformation time series in polygons of interest, with all of these
compared to observations from annual ground-based leveling
surveys. For the period of satellite data used, 2003-2010, two
distinct areas of uplift and subsidence are observed at Heber,
but leveling data back to 1994 show that the uplift area was
previously subsiding, up to about 2005. This changing trend can
be directly connected to changes in levels of injection. In this
capacity, we demonstrate that satellite observations of surface
deformation can be effectively used for assessment of the conditions in geothermal fields,
planning, and if needed,
impact mitigation.
B
C
Polygon C
Polygon A
Sur face Defor mation (mm)
Polygon B
F luid V olume (x 1000 kg)
F luid V olume (x 1000 kg)
Sur face Defor mation (mm)
6. Acknowledgments
Polygon D
T ime
T ime
Figure 12. Time series of leveling at benchmarks and of monthly fluid volume produced and injected within the four
polygons marked in Fig. 11. Bold lines show time series of total monthly fluid volume for all wells within a polygon.
Dashed lines show time series at individual wells. Injection is shown with red lines, and production with blue lines.
Leveling time series at individual benchmarks within the polygons are shown with green. Circles show earthquake
occurrence times.
498
Support from the Geothermal Grants and Loans
Program of the California Energy Commission
(CEC), Grant GEO-10-001,
is gratefully acknowledged.
The Imperial County Department of Public Works
(ICDPW) is thanked for
providing digital data for
the leveling surveys at the
Heber geothermal field. We
also thank Alex Schriener
from CalEnergy for assuring match share to the
CEC grant, helping with the
interpretation of the InSAR
results, and directing us to
relevant information. The
Envisat satellite data were
obtained from the European
Space Agency (ESA) as part
of an approved Category-1
research data proposal. Data
for the production and injection wells were obtained
from http://www.conservation.ca.gov/dog/geothermal/.
Eneva, et al.
7. References
SqueeSAR,” IEEE Transactions on Geoscience and Remote Sensing,
49 (9), 3460-3470.
Allison, M. L. (1990), “Remote Detection of Active Faults Using Borehole
Breakouts in the Heber Geothermal Field, Imperial Valley, California.”
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Fialko, Y. and Simmons, M. (2000), “Deformation and Seismicity in the Coso
Geothermal Area, Inyo County, California: Observations and Modeling
Using Satellite Radar Interferometry,” Journal of Geophysical Research,
105, 21,781-21,793.
Ben-Zion, Y. and Lyakhovsky, V. (2006), “Analysis of Aftershocks in a Lithosphere Model with Seismogenic Zone Governed by Damage Rheology,”
Geophysical Journal International, 165, 197– 210.
James, E. D., V. T. Hoang, and I. J. Epperson (1987), “Structure, Permeability and Production Characteristics of the Heber, California Geothermal
Field,” Proc. 12th Workshop Geothermal Reservoir Engineering, Stanford
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