Embed Size (px)
Citation preview
F
AJB
imwer
e
p©
GEOPHYSICS, VOL. 72, NO. 1 �JANUARY-FEBRUARY 2007�; P. N1–N9, 14 FIGS., 1 TABLE.10.1190/1.2399458
Dow
nloa
ded
12/0
3/13
to 9
8.19
9.23
2.11
8. R
edis
trib
utio
n su
bjec
t to
SEG
lice
nse
or c
opyr
ight
; see
Ter
ms
of U
se a
t http
://lib
rary
.seg
.org
/
ield tests of electroseismic hydrocarbon detection
. H. Thompson1, Scott Hornbostel1, Jim Burns1, Tom Murray1, Robert Raschke1,ohn Wride1, Paul McCammon1, John Sumner1, Greg Haake1, Mark Bixby1, Warren Ross1,enjamin S. White2, Minyao Zhou2, and Pawel Peczak2
ea
Aeadsn
fiTsp
nti�terfrt
btswids
ived SepTexas 7m.1. E-m
ABSTRACT
Geophysicists, looking for new exploration tools, havestudied the coupling between seismic and electromagneticwaves in the near-surface since the 1930s. Our research ex-plores the possibility that electromagnetic-to-seismic �ES�conversion is useful at greater depths. Field tests of ES con-version over gas sands and carbonate oil reservoirs succeed-ed in delineating known hydrocarbon accumulations fromdepths up to 1500 m. This is the first observation of electro-magnetic-to-seismic coupling from surface electrodes andgeophones. Electrodes at the earth’s surface generate electricfields at the target and digital accelerometers detect the re-turning seismic wave. Conversion at depth is confirmed withhydrophones placed in wells. The gas sands yielded a linearES response, as expected for electrokinetic energy conver-sion, and in qualitative agreement with numerical simula-tions. The carbonate oil reservoirs generate nonlinear conver-sions; a qualitatively new observation and a new probe ofrock properties. The hard-rock results suggest applications inlithologies where seismic hydrocarbon indicators are weak.With greater effort, deeper penetration should be possible.
INTRODUCTION
Electroseismic �ES� surveying is a method for remotely identify-ng the presence of hydrocarbons using the conversion of electro-
agnetic energy to seismic energy. A computer-controlled, coded-aveform voltage, applied to electrodes at the earth’s surface, caus-
s a current to flow in the subsurface. At certain discontinuities inock properties, a portion of the electrical current converts to seismic
Manuscript received by the Editor March 8, 2006; revised manuscript rece1ExxonMobil Upstream Research Co., P.O. Box 2189, Houston,
xxonmobil.com, [email protected], [email protected] Research and Engineering, Annandale, New Jersey 0880
[email protected] Society of Exploration Geophysicists.All rights reserved.
N1
nergy. Geophones record the resulting seismic wave at the surfacend/or in boreholes �Figure 1�.
The spacing of the electrodes is similar to the depth of the target.t a contrast in electrical properties, the vertical component of the
lectric field is discontinuous. The resulting gradient in field createslocal displacement of the pore-surface dipole layers. The chargeisplacement creates local, relative flow between the pore and grainpaces or induces a pressure gradient in the rock. This is electroki-etic coupling.
Many mechanisms can create ES coupling. An applied electriceld interacts with any internal field in a rock to create ES coupling.he field can also induce second-order coupling through electro-triction. Generally, the literature only discusses electrokinetic cou-ling; coupling to fluids in dipole layers on pore surfaces.
Hydrocarbon-bearing formations should produce a stronger sig-al than nearby nonhydrocarbon-bearing formations of the same li-hology because hydrocarbons are more resistive than water, and theons in water and the oil in the pore space are mobile in reservoir rockPride, 1994�. The largest ES signals will occur where high resis-ance creates large discontinuities in the vertical component of thelectric field and, at the same time, the high-resistance rock containsesidual water that has mobile ions. Large signals are not expectedrom high-resistance rock that contains no mobile water ions or inocks where the pore space is disconnected so that fluid or ionicransport does not occur over macroscopic distances.
At the present state of technology, the generated signals are weakecause of limits in driving large currents into the ground. With bet-er sources and methods, the ES signals can be as large as typicaleismic reflections �Thompson and Gist, 1993�. The small signalse are currently able to detect must be extracted by signal process-
ng with specially designed source waveforms and via redundantata collection from a noise background several orders of magnitudetronger, as described in Hornbostel and Thompson �2005�.
tember 29, 2006; published online December 13, 2006.7252-2189. E-mail: [email protected], scott.c.hornbostel@
tTectet
maOecmSe
piTteoaeeneCb
sbuti
bf
batsaur
F
sWlLu
fap
Fspficm
FfcTatslp
N2 Thompson et al.
Dow
nloa
ded
12/0
3/13
to 9
8.19
9.23
2.11
8. R
edis
trib
utio
n su
bjec
t to
SEG
lice
nse
or c
opyr
ight
; see
Ter
ms
of U
se a
t http
://lib
rary
.seg
.org
/
Electroseismic conversion should be clearly distinguished fromhe reciprocal process, seismic-to-electromagnetic �SE� conversion.hompson and Gist �1993 and 1999� discuss the reciprocal process-s and the fact that, although the linear responses are predictably re-iprocal processes, one process may be more practical to implementhan the other, and they may give different information about the res-rvoir properties. We have found that ES has certain field-applica-ion advantages.
Three properties favor large amplitude conversions between seis-ic and electromagnetic energies: �1� contrast in acoustic imped-
nce, �2� permeable pore space, and �3� high-resistivity pore fluids.f these three, the contrast in acoustic impedance may be the weak-
st determinant of amplitude for SE conversion. Seismic reflectionoefficients are small, often less than 1%. Most of the incident seis-ic energy propagates through the target interface unperturbed.mall seismic reflection coefficients favor using the inverse process,lectroseismic conversion.
Contrasts in viscosity, porosity, and elastic properties are not ex-ected to yield large ES signals. Contrasts in permeability may bemportant because extremely small permeabilities are not ES active.he theory of ES conversion �Pride, 1994� suggests that permeabili-
y is a second-order contributor to the conversion amplitude. How-ver, the permeability and electrical properties are related to eachther in rock so that the permeability and conductivity sensitivitiesre not generally separable. Other properties that are indirectly relat-d to electrical properties may be important to ES conversion. Forxample, wettability changes may create large contrasts in electroki-etics. Boundaries between different lithologies will induce gradi-nts in the chemical potential that create internal electric fields.ompressible fluids and gradients in diagenetic alteration will alsoe important.
Despite this host of possible influences on ES coupling, the largestingle influence on amplitude of conversion in a single rock type wille the conductivity of the pore fluids, and hence the hydrocarbon sat-ration. Numerical models of the full conversion process from elec-romagnetic to seismic waves indicate that 20% oil saturation mayncrease the ES amplitude by a factor of ten.
The ES method has been under active investigation by ExxonMo-il and a few other researchers for several years. The reader is re-erred to Thompson and Gist �1993 and 1999�, Pride �1994�, Horn-
Geophones Electrode
Reservoir
Oil -Gas
Current paths
Grain
PowerSource
Current / pressureIn pore water
Seismicwave
igure 1. Description of the ES method. A current injected into theubsurface creates local field gradients at discontinuities in electricalroperties. Applied fields couple to internal rock fields, includingelds in the dipolar boundaries on pore surfaces. This electrokineticoupling displaces the dipolar fluid layers causing relative move-ent or pressure generation in the grain space.
ostel and Thompson �2002�, Hornbostel et al. �2003�, Deckman etl. �2005�, Thompson �2005�, and White �2005� for background onhe underlying principles of the method. In the present paper, weummarize the results of three field tests of the method. Field tests 1nd 2 show application of the method to shallow gas sands, at depthsp to 1000 m. Field test 3 shows application to a deeper carbonate oileservoir.
FIELD TEST RESULTS
ield example 1: Webster, Texas
The Webster field is located along the Texas Gulf Coast, 20 mioutheast of the city of Houston. Though the primary production atebster is from the Frio formation, gas was produced from five shal-
ow zones. These sands occur in the Pleistocene age Beaumont andissie formations deposited in fluvial and deltaic systems. They arenconsolidated with porosities of up to 34%.
The ES experiments were conducted to detect possible responsesrom these shallow gas targets. The ES 3D surface survey covers anrea of 0.2 km2. A typical field test layout is shown in Figure 2. Theower source in the center of the figure is connected to a power line
Southernelectrode
PWSsite
WFU - 180
SeismicCW1
130 m
SeismicCW2
SeismicCW3
N
Geophones8 x 18 grid
3D ES survey
SeismicCW4WFU - 181WFU - 182Doghouse
Busswires
Northernelectrode
igure 2. Typical field layout for Webster field test. A power wave-orm synthesizer �PWS� is located in the center of the layout and isonnected to the north and south electrodes by bus wires �yellow�.he north electrode �two inverted L-shaped electrodes separated byspace� and the south electrode �straight east-west-running elec-
rode� are at opposite voltages. Four 2D seismic lines �two north-outh and two east-west� are shown in red. A 3D ES survey was col-ected with eight east-west geophone lines of 18 geophones eachlaced south of the south electrode.
aTwtcl
silfistauf
sstcadwab
t
lcpsaeca3Td
Ttlocapcd
Fs
Fwte
FtlE
Electroseismic hydrocarbon detection N3
Dow
nloa
ded
12/0
3/13
to 9
8.19
9.23
2.11
8. R
edis
trib
utio
n su
bjec
t to
SEG
lice
nse
or c
opyr
ight
; see
Ter
ms
of U
se a
t http
://lib
rary
.seg
.org
/
nd has outputs connected to buried electrode wires via bus wires.he angular electrodes at the north are at one polarity while the east-est segments to the south are at the opposite polarity. In addition to
he red 2D seismic lines depicted in the figure, a 3D ES survey wasonducted with geophones south of the south electrode. We also col-ected a 3D seismic survey.
Figure 3 compares a portion of the ES data to the correspondingeismic data and to a stratigraphic interpretation based on well datan the field �the WFU wells in Figure 3�. The ES response begins be-ow the shale response and illuminates the gas sand interval. Thisgure shows ES responses associated with the 320-sand and the 350-and at WFU-182. �The numbers in the sand formation names refero the depth of the sand in feet.� The figure also shows an ES responsessociated with the top of the 450-sand on this line. ES data acquiredsing downhole receivers in the WFU-182 well also show a responserom the gas sands.
Figure 4 shows a 3D perspective view of large amplitude ES re-ponses inserted into the 3D seismic survey. The top two blue ES re-ponses correspond to the 320-/350-sand and the 450-sand, respec-ively. As in Figure 3, the labeled high-amplitude seismic horizonorresponds to a laterally extensive high-impedance shale layer justbove the gas sands. There is no strong seismic response at the actualepths of the gas sands. The top two ES responses closely correlateith the known gas sands. There are three deeper ES responses that,
t the time of the survey, were not known to be present at this locationecause no well had penetrated them.
After the ES survey was completed, a deeper well �indicated byhe yellow line in Figure 4�, the WFU-183 well, was drilled and
100
150
100
150
Depth(m)
Depth(m)
Gasreservoirs
ShaleSeismic
ElectroseismicWFU - 182 WFU - 181
5 7 10 20 100 >1000
Resistivity in ohm-meters
200 m
igure 3. Webster field. Seismic, ES, and stratigraphic interpreta-ion. The upper seismic display from the 3D seismic survey showsarge amplitude response to the shale above the gas sands. The lowerS display shows large amplitude response to the gas sands.
ogged. This well penetrated the deeper sands. Figure 5 shows logurves superimposed on the ES data. The WFU-183 log confirms theresence of resistive sand intervals at the depths of the deeper ES re-ponses. Seismic and well data indicate that the 320-sand extendscross the entire line. A channel has eroded into the 350-sand to theast of the WFU-182 and subsequently filled with shale. This wellonfirmed the interpretation that the 350-sand would not be presentt this location. The well also encountered low-gas saturations in a1-m sand at 140 m, a 12-m sand at 250 m, and a 6-m sand at 285 m.he latter two gas sands correlate with the previously identifiedeeper ES events at 320 ms and 370 ms, respectively.
We now consider the 1D and 3D modeling of the ES responses.he model used for comparison of simulated 1D ES responses with
he field data is based on well WFU-182. The model is horizontallyayered and includes the upper two gas sands. Table 1 shows detailsf the layered model. The model response to this layered structure isomputed using a 90° phase-rotated 40-Hz Ricker wavelet, whichpproximately matches the amplitude and phase spectrum of therocessed data. ES model responses are computed at 144 surface lo-ations corresponding to those in the field data. The field and modelata are averaged over all traces for comparison.
Seismic
ES events
Test well
200 m
3D display of ES events
100
150
200
300
Dep
th (
m)
igure 4. Webster field. Perspective view of large amplitude ES re-ponses inserted into 3D seismic survey.
WFU -182 WFU -183 WFU -181
200 m
0.1
0.2
0.3
0.4
0.5
Tim
e (s
)
igure 5. Webster field. Deeper ES events and well logs. The middleell log is from the WFU-183 well, drilled after the survey was shot
o confirm the presence of deeper gas sands correlative with the ESvents.
wttba�sapttrasfi
odottgov
wowctim
oF
weeai
1
2
3
sttwenw
tdshsrffftss
hW
T
N4 Thompson et al.
Dow
nloa
ded
12/0
3/13
to 9
8.19
9.23
2.11
8. R
edis
trib
utio
n su
bjec
t to
SEG
lice
nse
or c
opyr
ight
; see
Ter
ms
of U
se a
t http
://lib
rary
.seg
.org
/
Figure 6 shows the average response as computed by modelingith the average response of the data for a depth corresponding to
he top two sands. The two gas sands are not individually resolved athis frequency but are characterized by a large oscillation where thease of the upper sand and the top of the lower sand merge to producesingle trough at 130 m. Because the lower gas sand is much thicker
31 m versus 15 m for the upper sand�, its base is individually re-olved as a trough at about 175 m. Following the gas sand responsesre oscillations representing acoustic reverberations �internal multi-les� set off by the primary ES responses and their repeated interac-ions with the layering. The model response must be scaled by a fac-or of five to match the data amplitude. With that scaling, the match iseasonably good in timing and general character. The only real char-cter difference between the two is that the base of the deeper gasand is more sharply defined in the model response than it is in theeld-data response.At present, we do not have a definitive explanation for the factor
f five amplitude mismatch. We have observed a similar underpre-iction of field amplitudes in several cases. We hypothesize that lackf detail in the models, or lack of information about the right parame-ers �e.g., permeabilities, conductivities, gas saturations�, explainshe difference. Layered models of ES conversion show that a layer ofas only 10 cm thick doubles the modeled response. The influencef thin compressible layers can also be large. A 5-cm-thick layer ofery low conductivity increases the response tenfold.
Whichever of these or potentially several other effects are presentith thin layers, it is not simply a matter of using the full resolutionf the logging-tool data. We have remodeled the above responsesith all beds in the original logs, which results in essentially identi-
al amplitudes. Whatever might explain the particular amplitudes athe Webster site is below the resolution of the logging tool, related tonaccuracies in the choice of model parameters, or related to the 1D
odel limitations.Some aspects of the model and field results require consideration
f 3D effects. For example, if the cross-sectional model as shown inigure 3 is accurate, and there are no unaccounted for gas pockets to-
able 1. The layered model used to calculate the ES response
Depth�m�
Conductivity�S/m�
Vp
�m/s�Perm�m2�
L�m2/V − s
0 0.04 1524 1e − 16 1e − 16
30 0.1 1646 1e − 18 1e − 16
107 0.02 976 1e − 13 1e − 09
122 0.1 1646 1e − 18 1e − 16
137 0.02 976 1e − 13 1e − 09
168 0.13 1829 1e − 18 1e − 16
244 0.13 2012 1e − 16 1e − 16
396 0.25 2134 1e − 16 1e − 16
549 0.5 2287 1e − 16 1e − 16
610 0.67 2378 1e − 16 1e − 16
1311 1 2591 1e − 18 1e − 16
1707 0.05 2439 1e − 13 1e − 09
1799 1 2744 1e − 18 1e − 16
4000 0.1 2744 1e − 16 1e − 16
ard the right of the section, one would expect the ES event to weak-n over the shale-filled channel.As shown in the figure, however, thevent from the 350-sand in the WFU-182 continues and strengthenscross the channel to the WFU-181 where the 350-sand does not ex-st. There are several explanations for this result:
� Surface geophones closer to the center of the electrode arrayrecord a stronger response than geophones near the edges.
� Higher resistivities at the surface near WFU-182 and over the350-sand reduce the current flux and, hence, the ES response.
� Gas in the 350-sand actually guides the current to the perimeterof the gas sand, thus reducing the response over the gas sand.
We eliminated electrode response functions and near-surface re-istivity variations as causes of the strengthening of the ES event,hough they do affect amplitudes. The electrode response �the elec-ric-field illumination pattern� is strongest at the electrode center andeakens uniformly at both ends and at offsets perpendicular to the
lectrode. There is no preferential east-west dependence. Even afterormalization for the electrode arrays, the ES response remainseak for the gas-charged 350-sand at the WFU-182.Higher resistivities at the surface may also affect the ES ampli-
udes. A shallow resistivity survey was conducted using shallow in-uction tools �EM-31, EM-38�, and it was found that the average re-istivity over the survey area is 8–10 ohm-m. There is an area ofigh resistivity �12–15 ohm-m� in the southwest portion of the ESurvey that coincides with the area around the WFU-182. The higheresistivity in this area limited the current passing into the groundrom the electrode and resulted in a weaker ES response. Several dif-erent solutions were attempted to mitigate the problem, but the ef-ect of the shallow, resistive area persisted in the data. Nonetheless,he normalization by both this resistivity ratio and the electrode re-ponse function did not eliminate the ES amplitude variation ob-erved in the data.
Three dimensional models of the ES response indicate that theigher resistivities associated with the gas in the 350-sand at theFU-182 may displace the current lines to the edges of the gas sand.
The 3D modeling was performed using the meth-od discussed in White �2005�. The importance ofcurrent steering is situation dependent. The reser-voir depth, size, thickness, and resistivity controlthe degree to which this phenomenon is impor-tant. In the Webster example, 3D modeling is pos-sibly less accurate than desired because the depth,electrode separation, electrode size, and reservoirstructure all have similar dimensions.
In summary, this first survey detected shallowgas sands and identified several gas sands deeperin the section that were not identified prior to thesurvey but were subsequently confirmed by drill-ing a postsurvey well. One-dimensional ES mod-el responses match the character of the field-dataresponses but are low by a factor of five in overallamplitude. For this combination of reservoirdepth, resistivity, thickness, shape, and lateral ex-tent, and within the resolution of a 3D model, cur-rents are steered towards the edge of the reservoir,illuminating most brightly the parts where thereservoir is thinnest.
This is the first successful demonstration thatES can distinguish between aquifers and gas
bster.
Porosity
0.39
0.385831
0.375131
0.373046
0.370962
0.366654
0.356092
0.334969
0.313708
0.305231
0.207815
0.152785
0.14
0.14
at We
�
sds
F
cvdddTogt
strpfualofintd
Abirttalt
awtccrt
fis�acwttcdrn
pdtwa
Ft
FTo�pt
Electroseismic hydrocarbon detection N5
Dow
nloa
ded
12/0
3/13
to 9
8.19
9.23
2.11
8. R
edis
trib
utio
n su
bjec
t to
SEG
lice
nse
or c
opyr
ight
; see
Ter
ms
of U
se a
t http
://lib
rary
.seg
.org
/
ands. There are no reports in the literature prior to this work thatocument electromagnetic-to-seismic conversion and none that useurface-mounted equipment to detect hydrocarbons at these depths.
ield example 2: Turin, Alberta, Canada
The Turin field is located in Southern Alberta. The Lower Creta-eous Glauconitic Sand produces oil in point-bar sands deposited asalley fill in an estuarine environment. The reservoir is at 1000-mrill depth and has porosities as high as 28%, permeability up to 4arcies, and maximum net sand thickness of 35 m. Both surface andownhole data in the vicinity of two wells, the Turin 12-14 and theurin 8-15, were acquired to compare ES responses over a very thinil leg �essentially wet reservoir� and a thin oil leg overlain by a thickas cap, respectively. Figure 7 shows the stratigraphy and fluid con-ent in each well.
Figure 8 shows the ES responses at the two locations. The mea-ured trace on the right side of both Figure 8a and b is a stacked tracehat is the sum of thousands of acquired traces, processed to sum allepetitions and all geophone stations together �after noise editing� toroduce one final trace representing the ES response of the subsur-ace at each location. Four different types of source waveforms weresed to generate sweeps, two at approximately 8 Hz, one at 18 Hz,nd one at 25 Hz. The model trace in the figure was computed via theayered-modeling method using the waveform corresponding to onef the lowest frequency sweeps at 8 Hz. Three-dimensional electric-eld modeling was performed to confirm relatively uniform illumi-ation of the sands, thus eliminating the need for full 3D modeling ofhe ES response. The stacked and model traces are converted toepth for comparison to well data using sonic log velocities.
The total equivalent field effort is different for the two locations.fter trace editing, the effective field effort at Turin 8-15 was greatery a factor of six. Each trace has a noise bound posted �red lines� thatncorporates the expected noise level for each set of experiments, de-ived from the standard deviation of the amplitude of all the prestackraces at each time sample. For the Turin 8-15 surface data, 143,000races are stacked together to obtain the final trace. A time taper waspplied to the traces to ensure that below 300 ms only the 54,482owest-frequency traces contribute to the sum. Prior to stacking,hese traces are essentially noise. Hence, at each time sample, there
0
50
100
150
200
250
0
50
100
150
200
250-5 0 5 10 10 100 1 2
Rho
Dep
th (
m)
V3 smash
Model 5 x Field
V3 (10 m/s/A)–13 Rho (ohm-m)
a) b)
igure 6. �a� ES field versus �b� model data for a smash of all traces inhe survey. Model data is scaled up by a factor of five.
re 143,000 samples from the noise distribution. The distributionas plotted and confirmed to be approximately Gaussian. At each
ime sample, the standard deviation of the samples in the stack �ac-ounting for the time taper� was computed and converted to a 95%onfidence interval using the Gaussian distribution, plotted as theed line. An equivalent calculation was done for the 50,000 traces athe Turin 12-14 location.
In both cases, strong shallow ES events are visible above the con-dence bound. These events originate at the water table or somehallow layer that is illuminated with a very strong local electric fieldbefore decay with depth�. The differences between the two tracesre most apparent at the reservoir level. The Turin 12-14 trace has os-illations at all times, but they are contained within the noise bounds,hich means no signal is statistically significant at any depth below
he shallow arrivals. The Turin 8-15 trace also has oscillationshroughout time. For most of the trace, those oscillations are alsoontained within the noise bounds.At the reservoir level, however, aistinct event is present. This event has a 95% probability of being aeal arrival rather than an oscillation related to residual randomoise.
For the Turin data, the mismatch in predicted and measured am-litudes is much larger than for Webster. The model amplitudes un-erpredict the observed data by several orders of magnitude. Unfor-unately, the level of field effort used in acquiring these surface dataas not high enough to definitively resolve issues about the absolute
mplitude of the signals.
Gammaray Resistivity
Gammaray Resistivity
970
990
1010
1030
970
990
1010
1030
CARBONATECARBONATE
OIL OILOWC OWC
GOC
GAS
Sand thickness = 25 mNet pay = 2 m (present day)
Sand thickness = 35 mNet pay = 35 m
Oil only
Dep
th (
m)
Oil + gasa) b)
igure 7. Stratigraphy at the �a� Turin 12-14 and �b� Turin 8-15 wells.he Turin 12-14 well has a thin oil leg. The Turin 8-15 well has a thinil leg overlain by a thick gas cap. In both logs, the oil-water contactOWC� is indicated shallower than the logs show because theresent-day OWC has moved upward relative to where it was whenhe wells were logged.
dlfidwi
wnadufgizpe
r
5
sNlcaw
hwfaati
ddshh
sb
F
N6 Thompson et al.
Dow
nloa
ded
12/0
3/13
to 9
8.19
9.23
2.11
8. R
edis
trib
utio
n su
bjec
t to
SEG
lice
nse
or c
opyr
ight
; see
Ter
ms
of U
se a
t http
://lib
rary
.seg
.org
/
The primary purpose of the Turin experiments was to acquire ESata in several wells. Downhole ES responses were observed in ear-ier field tests where they were of very good quality, required lesseld effort to acquire than surface ES data, and correlated with hy-rocarbons. Downhole responses are recorded with hydrophones,hich respond to the tube waves generated at ES conversion points
n the subsurface.Figure 9 shows an example of these responses at the Turin 12-14
ell. The inverted V-shaped pattern to the tube waves, which ema-ate from discrete depth levels and travel up and down the borehole,re very clear in these data. The S/N is very high due to the quietownhole environment and the large amplitude of tube waves. In thenscaled record, the largest response comes from the bottom of sur-ace casing. There is also a response from a zone labeled the “hetero-eneous” zone, which is a zone of rapid oscillation in a through-cas-ng resistivity log acquired near 500 m depth. This heterogeneousone has the largest response in the record after scaling by the ex-ected decay of the electric field with depth. There are other respons-s at depth in the scaled version, and there may be a small reservoir-
elated signal as well, indicated by ®.To test whether the heterogeneous zone response in the record at
00 m was caused by hydrocarbons, we perforated and stimulated
0
400
800
1200
1600
2000
Dep
th (
m)
0
400
800
1200
1600
2000
Dep
th (
m)
Modeled Rho log Measured
Modeled Rho log Measured
100 10Rho (ohm-m)
2
100 102
Rho (ohm-m)
a)
b)
igure 8. ES response for �a� thin oil zone versus �b� thick gas zone.
everal intervals that had high resistivity in the through-casing log.o hydrocarbons were found. After reinspecting the cement-bond
ogs, our posttesting interpretation is that a slight degradation in theement bond behind casing generated the response from the zone,nd likely generated the oscillations in the through-casing log asell.Figure 10 shows downhole data for the Turin 8-15 well. This well
ad a variable water level, and at the time of acquisition, the averageater level was at a depth of about 350 m.An ES response is present
rom this depth. On the scaled record, the largest ES response is fromdepth of 670 m and is near the top of the lower Cretaceous. Therere also deeper responses.Asignal from the reservoir level is visible,hough its strength is not observably larger than the reservoir signaln the Turin 12-14 well.
In both cases of downhole data, although there may be weak hy-rocarbon-related responses, the most prominent responses are fromiscontinuities in subsurface or near-borehole properties. Such re-ponses may be useful as indications of cement-bond quality, bore-ole state, or properties of the subsurface in the vicinity of the bore-ole.
In summary, this second shallow gas-sand survey was most likelyuccessful at discriminating the presence or absence of hydrocar-ons at a depth of 1000 m. This is more than double the depth
achieved for the deepest observed gas sand in theWebster field test. Field effort was much lowerthan that at Webster but sufficient to show indica-tions of an ES response to a thick, highly resistivegas cap. Evidence that signal is present comesfrom comparing the final stacked trace as well assubsets of the data to noise bounds, all of whichshow that a cycle at the right time for the reservoiris present above the noise. The residual noiseshows all indications of being uncanceled ran-dom noise and may thus be overcome by a higherfield effort.
Downhole data, acquired during the Albertaexperiments, clearly illustrate evidence for ESconversions because of the characteristic invert-ed-V signals indicative of up- and downgoingtube waves emanating from several depth levelsstarting at zero time. No mechanical disturbanceor elastic wave could reach those depth levels inthis short a time interval. The ES conversionsmay or may not be indicative of hydrocarbons.Frequently, they are conversions from borehole-related structures, stratigraphy, or subsurfaceconditions restricted to the vicinity of the bore-hole.
Field example 3: Bronte, Texas
The Bronte field is located on the Eastern Shelfof the Midland Basin in Coke County, Texas.Bronte represents a significant departure from thepreviously discussed field tests, differing fromWebster and Alberta in depth, rock type, and hy-drocarbon fluid. There are five stacked reservoirformations shown in Figure 11. The Palo Pinto,Capps, Goen, and Cambrian formations produceoil, while the Gardner produces gas. Reservoir
-m oil zone
s zone
onfidence
2
Ga
95% cbound
d1n
P
GipprfiTrrwod
semfiadd2
tlsE
PwteTnrt
G
Fdt
Fa
Fa
Electroseismic hydrocarbon detection N7
Dow
nloa
ded
12/0
3/13
to 9
8.19
9.23
2.11
8. R
edis
trib
utio
n su
bjec
t to
SEG
lice
nse
or c
opyr
ight
; see
Ter
ms
of U
se a
t http
://lib
rary
.seg
.org
/
epths range from 1310 to 1615 m. Porosities range from 6% to2%. Permeability ranges from 7 to 200 millidarcies. Net pay thick-ess averages 11 m.
The pay interval has average resistivity of 250 ohm-m in the Palointo and Cambrian formations, but only 25 ohm-m for the Capps,
0
0.2
0.4
0.6
0
0.2
0.4
0.6
0 200 400 600 800 1000
Depth (m)
“Heterogeneous”
zone
“Heterogeneous”
zone
“Hetero”
R
RSurfacecasing
Pickupa)
b)
Tim
e (s
)Ti
me
(s)
igure 9. Downhole data in the Turin 12-14 well. �a� Unscaled datafter correlation, �b� data scaled by time squared �T 2�.
0
0.2
0.4
0.6
0 200 400 600 800 1000
Depth (m)
R
0
0.2
0.4
0.6
a)
b)
Tim
e (s
)Ti
me
(s)
“Heterogeneous”
zone
Surfacecasing
Top lo
wer Cretace
ous
Averagewaterlevel
R
“Heterogeneous”
zone
Top lo
wer Cretace
ous
Deeper carbonate
igure 10. Downhole data in the Turin 8-15 well. �a� Unscaled datafter correlation, �b� data scaled by time squared �T 2�.
oen, and Gardner formations. Low porosity and thin net pay foundn all the producing intervals and the low resistivity for three of theroducing intervals suggest a weak ES linear response from theseay zones, even with the benefit of good electric-field illuminationesulting from a resistive overburden. This weak response is con-rmed by comparing acquired ES data to logs, shown in Figure 11.he response at the Palo Pinto is not much stronger than background
esponses or the response in the middle of the shale section above theeservoir. Modeling of the expected ES amplitude also shows veryeak response, but because such modeling regularly underpredictsbserved ES field amplitudes, this weak model response adds no ad-itional confirmation of the above observations.
Thus far, we have been discussing what we call the linear ES re-ponse, namely the response consistent with the linear theory oflectrokinetics as described by Pride �1994�. Other conversionechanisms �Hornbostel et al., 2003� provide the theoretical basis
or nonlinear ES responses, which we pursued in lab and field stud-es. In well measurements, the second harmonic had better S/N andppeared to have better hydrocarbon discrimination than the stan-ard linear data.As a result, we developed special source waveformsesigned to highlight nonlinearity �Hornbostel and Thompson,005�, and we collected a 3D ES survey using them.
The nonlinear data set had better S/N and was more coherent withhe reservoir than was the original linear data set. Figure 12 showsine 11 from the nonlinear 3D ES survey. This line shows weaker re-ponses from two of the other reservoirs and shallow, but incoherent,S responses we attribute to noise spikes.Figure 13 shows an aerial view of the nonlinear ES response at the
alo Pinto reservoir. The Palo Pinto amplitudes are confined to theest �upthrown� side of the Fort Chadbourne Fault, which is known
o be the boundary of production. This is a confirmation of the pres-nce of coherent nonlinear ES signal only where production occurs.he variability of amplitudes within the reservoir is considered sig-ificant, but the cause is unknown, possibly a result of enhanced po-osity, facies variations in the carbonates, or bypassed oil. Two addi-ional time slices are compared to the Palo Pinto time slice in Figure
300
600
900
1200
1500
Dep
th (
m)
Unscaled linear surfacedata line 10
Resistivity(ohm-m)
Gammaray
Leonardcarbonate
Palo Pinto
Capps
ardner
Goen
Cambrian
a) b)
igure 11. Bronte field. �a� Well logs and �b� linear ES data. Surfaceata are corrected to depth using well check shots. The black is therace at the location of the well.
1Pwlt
gap
aipfinp
odpgba
vwfrdvsu
dcvtB
pjamnwf
tcoBfic
lt
sWat
P
Fo
Ft
a
F�b
N8 Thompson et al.
Dow
nloa
ded
12/0
3/13
to 9
8.19
9.23
2.11
8. R
edis
trib
utio
n su
bjec
t to
SEG
lice
nse
or c
opyr
ight
; see
Ter
ms
of U
se a
t http
://lib
rary
.seg
.org
/
4. The time slice on the Cambrian reservoir is less coherent than thealo Pinto time slice, but amplitudes are still mostly confined to theestern side of the fault. The nonreservoir basement reflector has
ow ES amplitude and appears similar in amplitude on both sides ofhe fault.
This third ES survey stretched the limits of the linear ES technolo-y from the earlier surveys, attempting to discriminate hydrocarbonst deeper depths, in carbonates, and in oil-filled reservoirs. At ourresent level of effort, the linear data collected at Bronte are not us-
0.6
0.75
0.9
Tim
e (s
)
alo PintoGardner
Cambrian
Basement
FortChadbourneFault
SWBronte
118Bronte
110 NE
igure 12. Bronte field. Nonlinear ES response for line 11. Locationf line 11 is shown on the map in Figure 13.
500 m
N
Electrode
Line 11
Test wells
5x10 –11
10 –10
5x10 –10
Seismicamplitude(m/s)
FortChadbourne
Fault
Well 201
Well 118
igure 13. Bronte field. Aerial view of the nonlinear ES response onhe Palo Pinto reservoir.
Palo Pinto Cambrian Basement
) b) c)
igure 14. Bronte field. Nonlinear ES response on three time slices:a� the Palo Pinto reservoir, �b� the Cambrian reservoir, and �c� aasement reflection �nonreservoir�.
ble in creating a 3D image. The nonlinear response did provide a 3Dmage that conforms to production at one of the reservoir levels. Inarticular, the nonlinear response on the Palo Pinto reservoir is con-ned to a portion of the survey area with hydrocarbons, whereasonlinear responses on nonreservoir horizons exhibit much moreatchy amplitudes.
CONCLUSIONS
Two field tests of the ES method have shown that the conversionf electromagnetic energy to seismic energy at gas sands 500 meep, and possibly as deep as 1000 m, can be detected with geo-hones placed on the surface of the earth. The detected seismic ener-y is at the same frequency as the source electrical power. Modelsased on an electrokinetic conversion mechanism and field datagree qualitatively, if not in absolute amplitude.
Athird field test at the Bronte Field detected second-order ES con-ersions from reservoirs greater than 1500 m deep. The ES signalas used to map the reservoir. Second-order conversions double the
requency of the electromagnetic source leading to enhanced spatialesolution. This is the first time second-order conversions have beenetected in field data. The coherence of the amplitudes at the reser-oir interval and the lack of coherence of the amplitudes elsewhereupport the interpretation of the second order conversions and stim-late interest in further investigations.
The nonlinear response is a new phenomenon and is not fully un-erstood. It is not obvious that the electrokinetic conversion processan account for second-order effects. Further work is required to de-elop theoretical explanations of second-order conversion and to de-ermine what mechanism generated the second-order conversions atronte.Detecting second-order responses at Bronte was made possible, in
art, because processing for the second-order signal enhances the re-ection of source noise. With the equipment and methods employedt Bronte, we were unable to detect the reservoir with the linear ESethod. Experience gained in this field work leads us to predict that
umerous advances in equipment and methods are possible. Furtherork is needed to determine if first-order conversions are detectable
rom depths greater than 1000 m in lithologies similar to Bronte.Well tests at Turin showed ES conversions from depth. Most of
he detected responses are indications of borehole properties such asement-bond quality, casing junctions, etc. Some may be indicationsf stratigraphy or near-borehole conditions. In other well tests atronte and Webster, we clearly observed the ES conversions in the
ormation. We conclude that ES well tests may be useful in diagnos-ng well properties, including cement integrity and near-well ESonversions.
More generally, the entire field of electroseismic technology, bothinear and nonlinear, warrants further investigation based on its po-ential and the qualitatively new observations presented herein.
ACKNOWLEDGMENTS
We acknowledge the cooporation of ExxonMobil Canada for as-isting during the field tests and for approval to publish the results.e thank our many colleagues at ExxonMobil Upstream Research
nd ExxonMobil Corporate Strategic Research who contributed tohis project over many years, especially Eric Herbolzheimer, Harry
Df
D
H
—
H
P
T
T
—W
Electroseismic hydrocarbon detection N9
Dow
nloa
ded
12/0
3/13
to 9
8.19
9.23
2.11
8. R
edis
trib
utio
n su
bjec
t to
SEG
lice
nse
or c
opyr
ight
; see
Ter
ms
of U
se a
t http
://lib
rary
.seg
.org
/
eckman, Mark Ephron, John Dickinson, Grant Gist, and Max Def-enbaugh.
REFERENCES
eckman, H. W., E. Herbolzheimer, and A. Kushnick, 2005, Determinationof electrokinetic coupling coefficients: 75th Annual International Meet-ing, SEG, ExpandedAbstracts, 561–564.
ornbostel, S. C., and A. H. Thompson, 2002, Source waveforms for elec-troseismic exploration: U. S. Patent 6,477,113 B2.—–, 2005, Waveform design for electroseismic exploration: 75th Annual
International Meeting, SEG, ExpandedAbstracts, 557–560.ornbostel, S. C., A. H. Thompson, T. C. Halsey, R. A. Raschke, and C. A.Davis, 2003, Nonlinear electroseismic exploration: U. S. Patent 6,664,788B.
ride, S., 1994, Governing equations for the coupled electromagnetics andacoustics of porous media: Physical Review B, 50, 15678–15696.
hompson, A. H., 2005, Electromagnetic-to-seismic conversion: Successfuldevelopments suggest viable applications in exploration and production:75thAnnual International Meeting., SEG, ExpandedAbstracts, 554–556.
hompson, A. H., and G. A. Gist, 1993, Geophysical applications of electro-kinetic conversion: The Leading Edge, 12, 1169–1173.—–, 1999, Geophysical prospecting: U. S. Patent 5,877,995.hite, B. S., 2005, Asymptotic theory of electroseismic prospecting: IMAJournal ofApplied Mathematics, 65, 1443–1462.
