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Multitransient electromagnetic demonstration survey in France
Citation for published version:Ziolkowski, A, Hobbs, B & Wright, D 2007, 'Multitransient electromagnetic demonstration survey in France'Geophysics, vol 72, no. 4, pp. F197-F209., 10.1190/1.2735802
Digital Object Identifier (DOI):10.1190/1.2735802
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Multitransient electromagnetic demonstration survey in France
Anton Ziolkowski1, Bruce A. Hobbs1, and David Wright1
ABSTRACT
We describe the acquisition, processing, and inversion of amultitransient electromagnetic MTEM single-line survey,conducted in December 2004 over an underground gas stor-age reservoir in southwestern France. The objective was tofind a resistor corresponding to known gas about 500 m be-low the survey line. In data acquisition, we deployed a 100-minline bipole current source and twenty 100-m inline poten-tial receivers in various configurations along the 5-km surveyline; we measured the input current step and received volt-ages simultaneously. Then we deconvolved the receivedvoltages for the measured input current to determine the earthimpulse responses. We show how both amplitude and travel-time information contained in the recovered earth impulse re-sponses reveal the lateral location and approximate depth ofthe resistive reservoir. Integrating the impulse responsesyields step responses, from which the asymptotic DC valueswere estimated and used in rapid 2D dipole-dipole DC resis-tivity inversion to find the top of the reservoir.Aseries of col-lated 1D full-waveform inversions performed on individualcommon midpoint gathers of the step responses position thetop and bottom of a resistor corresponding to known gas inthe reservoir and also obtain the transverse resistance. The re-sults imply that the MTEM method can be used as a tool forhydrocarbon exploration and production.
INTRODUCTION
Porous rocks are saturated with fluids. The fluids may be water,gas, oil, or a mixture of all three. The flow of electric current in theearth is determined by the resistivities of such rocks, which are af-fected by the saturating fluids. For instance, brine-saturated porousrocks are much less resistive than the same rocks filled with hydro-carbons e.g., Archie, 1942. Hence, the exploration objective is todetermine whether hydrocarbons are present by measuring the resis-tivity of geologic formations. If tests using other methods, e.g., seis-
mic exploration, suggest that a geologic formation has the potentialto bear hydrocarbons, then, before drilling, it is important to havesome indication of whether the formation contains hydrocarbons orwhether it is primarily water bearing. This can be done using electro-magnetic EM techniques and, more specifically, time-domain EMtechniques.
Kaufman and Keller 1983 give the theoretical basis for the useof transient EM methods and show that resistive layers can be re-solved best by measuring the electric fields from a galvanic source.Rocroi and Gole 1983 describe the use of grounded dipole currentsources on a transmission axis and dipole receivers on a parallel re-ceiver axis. They apply transient boxcar pulses at the sources and an-alyze the signal at the receiver from the time the source current isswitched off, i.e., they aim to measure the step response of the earth.Strack et al. 1989 describe the long-offset transient electromagnet-ic LOTEM method, including the data interpretation. LOTEMuses a 1–2 km grounded bipole current source 5–20 km from an ar-ray of EM receivers: horizontal magnetic loops and horizontal elec-tric bipoles. The source-current waveform is a square wave, alternat-ing between positive and negative polarity. The received response isa series of step responses of alternating polarity. In the interpretationof the data, Strack et al. 1989 use 1D inversion and place the result-ing earth model beneath the receiver. Strack 1992 contains threechapters on case histories of LOTEM exploration and, in each case,the 1D inversion results are posted vertically beneath the receivers.The reciprocity principle states that the impulse response of the earthfor a dipole-dipole configuration is the same when source at A andreceiver at B are interchanged, so the inversion would give the sameresult in both situations, but in one case the result would be posted atA and in the other at B. It makes more sense to post the 1D inversionresult at the midpoint between source and receiver: The result is in-variant when source and receiver are interchanged.
The multitransient electromagnetic MTEM method differs fromprevious transient EM work in that both the received voltage and theinput current are measured simultaneously, and the impulse re-sponse of the earth is recovered from these two measurements by de-convolution. This is new. A patent application was filed in 2001 andgranted in the United States in 2005 Wright et al., 2005. Recover-ing the impulse response allows the data to be processed in a manner
Manuscript received by the EditorAugust 11, 2006; revised manuscript received February 16, 2007; published online May 25, 2007.1MTEM Limited, Edinburgh, United Kingdom. E-mail: [email protected]; [email protected]; [email protected].
© 2007 Society of Exploration Geophysicists.All rights reserved.
GEOPHYSICS, VOL. 72, NO. 4 JULY-AUGUST 2007; P. F197–F209, 20 FIGS., 2 TABLES.10.1190/1.2735802
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similar to seismic data processing, and this has allowed us to makesignificant progress. We use seismic data-processing software fordata handling, processing, and display.
Wright et al. 2002 describe an MTEM survey over an under-ground gas storage reservoir near Paris. Inline and crossline bipolecurrent sources and inline and crossline electric-field bipole receiv-ers were laid out along a line; horizontal magnetic loops also wereused to measure the vertical component of the rate of change of themagnetic field. Wright 2003 analyzes all the data from this surveyand finds that only the inline source and inline receivers need beused. The other components provided no additional information.Wright et al. 2002 use only the inline source and inline receiverdata. They recover the time derivative of the earth-impulse re-sponses by deconvolution and differentiation and display them ascommon-offset sections, with the source-receiver midpoint as thehorizontal coordinate and time as the vertical axis. This clearlyshows the resistor corresponding to the known gas in the correct lat-eral position. Note that common-offset sections are standard dis-plays in seismic data processing.
Here, we describe an MTEM survey over an underground gasstorage reservoir in southwestern France, conducted in December2004. The survey was part of a collaborative project between themultinational oil company TOTAL, MTEM Ltd., and the Universityof Edinburgh to test the MTEM method’s ability to detect resistivehydrocarbons. It followed from an earlier survey, conducted in Janu-ary 2004, which was part of a Scottish Enterprise Proof of ConceptProject.The primary objective of the survey was to locate the gas-bearing part of the reservoir.Asecondary objective was to determineits thickness and resistivity.
We outline the MTEM method, using 1D modeling to illustratethe salient points, and then describe the field procedure, equipment,and field parameters. We describe our data-processing procedure,with emphasis on the use of the reciprocity principle to check the re-covered impulse responses.We show that the processed data can beinterpreted in four different ways to estimate subsurface resistivities.The results of these four approaches are consistent with each otherand with seismic data.
THE MTEM METHOD
The MTEM method is described by Wright et al. 2001, 2002,2005. The setup is shown in Figure 1. A time-varying current, typi-cally a step function or a pseudo-random binary sequence PRBS, isinjected between the two source electrodes A and B and is measuredand recorded. This is the input to the earth. The time-varying voltageresponse between the two receiver electrodes C and D is also mea-sured simultaneously. If the response reaches steady state before thenext change in current is applied at the source, the full response hasbeen measured and is the convolution
vk,xC,xD;xA,xB,t = ik,xA,xB,t*gxC,xD;xA,xB,t*rCDt
+ nk,xC,xD,t , 1
in which vk,xC,xD;xA,xB,t is the measured voltage response,ik,xA,xB,t is the measured input current, gxC,xD;xA,xB,t is the un-known impulse response of the earth, rCDt is the response of the re-cording system at the receiver, nk,xC,xD,t is uncorrelated noise, kis the record number in the transmission sequence, xA and xB are thesource electrode positions, xC and xD are the receiver electrode posi-tions, and t is time.
The convolution of the input current with the response of the re-cording system is known as the system response:
sCDk,xA,xB,t = ik,xA,xB,t*rCDt . 2
Normally, the current is recorded using a device that is identical withthat at the receiver, so the system response is known. The electric cir-cuit consists of the transmitter, the cables to the electrodes, the elec-trodes themselves, and the earth. If there are inductive and capacitiveeffects in this circuit, the phase between the voltage across the trans-mitter terminals and the current in the circuit will be nonzero andwill vary with frequency. That is, the input current may not followexactly the prescribed function used to drive the transmitter. Howev-er, this has no bearing on the theory of the method because the cur-rent input to the earth and the response of the recording system aremeasured, and we use the measurement in the deconvolution, not theprescribed function.
The impulse response of the earth is obtained by deconvolving themeasured voltage response for the measured system response. De-convolution became an established data-processing tool in geophys-ics following Robinson 1957, who bases his work on the founda-tions laid by Wiener 1949 and Levinson 1947. Robinson 1967,Webster 1978, and Robinson and Osman 1996 show how meth-ods have progressed in geophysics since. Our method is explained inAppendix A.
1D MODELING
Figure 2 illustrates a 1D earth model consisting of a 20 ohm-mhalf-space with a layer 25 m thick and resistivity of 500 ohm-m at adepth of 500 m. The source is a 1-A-m dipole, and the receiver is inline with the source electrodes at an offset of 1 km.
The black curve in Figure 3a shows the response of the 20 ohm-mhalf-space to a switch-on step, computed using the theory of Ed-wards 1997. There is an instantaneous rise at t = 0, followed by a
Receiver Receiver Receiver ReceiverReceiver
ElectrodesElectrodes∆x
∆xs ∆xrSource
A B C D
Figure 1. Plan view of a typical land MTEM source-receiver config-uration with a current bipole source and its two electrodes, A and B,and a line of receivers in line with the source, measuring the potentialbetween pairs of receiver electrodes, for instance, C and D.
∆x
1 A. m source Receiver (V)
x = 1000 m
20 ohm-m500 ohm-m
500 m
25 m
Figure 2. Model of a source and a receiver 1000 m apart at the surfaceof a 20 ohm-m half-space.At a depth of 500 m, a 25-m-thick layer isinserted with a resistivity that takes a value of 500 ohm-m if hydro-carbons are present and 20 ohm-m if they are absent.
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slower rise to an asymptotic value equal to twice the value of the ini-tial step. The initial step is a pure inductive effect; the current in thedipole creates a magnetic field that induces a voltage at the receiverposition. The red curve in Figure 3a shows the effect of a 25-m-thickresistive layer of 500 ohm-m at a depth of 500 m; the amplitude ofthe response after the initial step is greater.
Figure 3b shows the corresponding impulse responses obtainedby differentiating Figure 3a. The initial step in Figure 3a, the air-wave, becomes an impulse at t = 0 in Figure 3b, and the earth im-pulse response shows a rise to a peak at about 6.28 ms, followed byan asymptotic decay to zero. The influence of the thin resistive layeron the response is shown as the red curve, which has a significantlyhigher peak arriving at 5.85 ms — slightly earlier than the peak ofthe half-space response. Thus, the effect of the resistor can be seen inboth the amplitude of the earth impulse response and the arrival timeof the peak. These effects are seen at offsets greater than about twicethe target depth.
Figure 3 is purely theoretical. In practice, the data are recordedwith a band-limited recording system. The effect of this on the re-corded response is simulated in Figure 4. The airwave becomes asharp peak, and the peak of the earth response is smaller and followsthe airwave; however, the peak of the earth response is larger whenthe resistor is present.
FIELD LAYOUT, EQUIPMENT, AND PARAMETERS
TOTALchose the line of the MTEM profile and informed the Uni-versity of Edinburgh and MTEM Ltd. that the crest of the reservoirwas beneath the line at about 500 m depth. No other informationabout the extent of the reservoir or the subsurface structure wasgiven. Several wellheads were in the area, which indicated the ap-proximate horizontal location of the reservoir.
The layout of the north-south survey line is shown in Figure 5,with source and receiver electrode positions pegged at 100-m inter-vals. The object of the survey was to delineate, in a 2D sense, the sub-surface resistor that corresponds to the stored gas.
a)8
7
6
5
4
3
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1
0
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/A-m
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Uniform half-spaceHydrocarbon reservoir
0.04 0.06
b) 1
0.8
0.6
0.4
0.2
0
Nor
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ized
der
ivat
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(Ω/m
/s)
2
–0.02 0 0.02
Time (s)
Uniform half-spaceHydrocarbon reservoir
0.04 0.06
Figure 3. a Response of a 20 ohm-m half-space at an offset of1000 m to a 1-A-m step at the source dipole black curve and with a25-m-thick, 500-ohm-m resistive layer at a depth of 500 m redcurve. b Normalized impulse response, with normalization factor3.433E + 6 for a 20 ohm-m half-space black curve, with peak at0.00628 s, and with a 25-m-thick, 500-ohm-m resistive layer at adepth of 500 m red curve, with peak at 0.00585 s. The source andreceiver are 1 km apart. The black vertical arrow at time = 0.0 repre-sents the pure inductive effect of the impulse at the source.
Nor
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ized
der
ivat
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(Ω/m
/s)
2
–0.02 0 0.02
Time (s)
WaterHydrocarbons
0.04 0.06
1
0.8
0.6
0.4
0.2
0
–0.2
Figure 4. The result of convolving the responses in Figure 3 with afilter to simulate the recording system. The airwave becomes a sharppeak before the earth response. The impulse response has been nor-malized by its maximum value of 1.4515841910−6 V/m/A-m/s.The maximum values of the second peaks normalized are 0.12287water and 0.18922 hydrocarbons, giving a 54% increase in the re-sponse when hydrocarbons are present.
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The field procedure consisted of switching a DC current betweentwo source electrodes and recording the voltage responses at receiv-er locations along the line. The current source was a Zonge GGT-30
transmitter, powered by a ZMG-30 generator that switched DC cur-rent between opposite polarities. The time for the current to changepolarity is on the order of microseconds, much shorter than the sam-pling interval used to record the data. The recording equipment wasdesigned and built at the University of Edinburgh, in Scottish Enter-prise Proof of Concept Project 4-ENO 004, to meet the specifica-tions required by the MTEM method Wright et al., 2002, 2005.Eleven two-channel recording units were made, ten for the receivingarray and one to record the system response. Signal conditioning in-cluded a high-pass filter to attenuate very-low-frequency MT signalsand a four-pole Butterworth antialias filter with a 6-dB point at two-thirds times the Nyquist frequency. A range of sampling rates wasavailable, each with its own antialias filter.
Each unit had its own global positioning system GPS receiverand onboard computers for analog-digital conversion, data record-ing and storage, and communication via fast transmission cable to acentral recording workstation. Where communications were diffi-cult across dense woods, independent GPS-synchronized recordingworkstations were used. A newly designed online quality controlQC system enabled the layout and status of the system to bechecked and the incoming data on all channels to be viewed simulta-neously, before and after stack.
With the 10 receiver boxes and 100 m between a pair of receiverelectrodes, a 2-km receiving spread was used, and the whole spreadwas shifted along the line with transient current input from thesource from each end. The source was normally 100 m between cur-rent electrodes, and the offset between the source and nearest receiv-er was variable, as shown in Figure 6.
In principle, the source input current can be any time-varying sig-nal. In practice, it is convenient to keep the load constant, so the cur-rent level is constant but switches polarity at predetermined times.For this survey, we used a simple step in current, reversing the polar-ity every second or half-second, for a 0.1-s record sampled at15 kHz; that is, there were 1500 samples per record. The recordingwindow was chosen such that steady state was reached before theend of recording at all offsets. The time between current reversalswas much longer than the record length, so we recorded the step re-sponse each time. For later surveys, we used pseudo-random binarysequences PRBS rather than steps because this approach improvesefficiency. Our real-time QC system allowed us to see how the stepresponses stacked up. We found that we needed to record about 1500responses at each source position to achieve adequate signal-to-noise ratio S/N at all offsets. The parameters are summarized inTable 1.
Figure 6 shows the data coverage in common-midpoint CMP offset coordinates. The horizon-tal vector positions of the source and receiverelectrodes for a given source/receiver pair are xS1,xS2, xR1, and xR2; the corresponding midpoint andoffset are defined as
xCMP = xS1 + xS2 + xR1 + xR2/4, 3
xoffset = xS1 + xS22
−xR1 + xR2
2 . 4
As in seismic reflection, each CMP is shared byseveral source/receiver pairs. Note that the offsetis the modulus of the source/receiver separation;that is, we assume the reciprocity principle. In
Table 1. Data-acquisition parameters.
Parameter
Frequency of current switch 1 Hz, 0.5 Hz
Amplitude of current switch 20–50 A
Voltage across source electrodes 750–1000 V
Record length 0.1 s
Sampling frequency 15 kHz
Number of records recorded per source position 1500–3000
Source electrode separation 100 m normal, 300 m, 500 m
Receiver electrode separation, per channel 100 m
4
3
2
1
0
Dis
tanc
e (k
m)
Distance (km)
0 1
51
4139
34
28
E27
21
15
E14
9E8
1
2 3 4
Electrode positionsSource midpoint
Figure 5. Layout of the line, showing source and receiver electrodepositions pegged at 100-m intervals.
Offs
et (
m)
Distance along profile from north (m)
December 2004 – Coverage
2000.0 4000.00
Shots from southShots from northJanuary 2004 data
0.0
1000.0
2000.0
3000.0
4000.0
5000.0
Figure 6. Data coverage in CMP-offset coordinates. Each point inthe plot represents a single source/receiver pair, for which approxi-mately 1500 transients were recorded.
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fact, we use this principle to check the quality of our data acquisitionand processing.
DATA PROCESSING AND RECIPROCITY
For each switch of the transmitter, a 1500-sample, 0.1-s transientresponse of each channel was recorded. Data processing analyzedthe 8 GB of recorded data for noise bursts and identified unaccept-able transients approximately 10%. The accepted data were treatedfor 50-Hz noise removal, deconvolved for the recorded systemresponse, and stacked to recover the impulse response. The resultwas then filtered with a zero-phase Gaussian filter of the formexp− 2f2, in which f is frequency, with e−1 cut-off frequency −1
varied with source/receiver offset to recover a band-limited estimateof the impulse response gxs,xr,t.
The deconvolution compensates for the variation in current at thesource for each transient response and for each source position. Thereceived voltage is also proportional to the separation betweensource electrodes and the separation between receiver electrodes.The data are scaled at the deconvolution stage to compensate forthese effects, such that the integrated impulse response is whatwould be obtained for a 1 A-m step. The zero-phase filtering is de-signed to have no effect on the late-time values of the integrated im-pulse responses.
The reciprocity principle can be expressed mathematically as
gxA,xB;xC,xD,t = gxC,xD;xA,xB,t . 5
That is, the impulse response of the earth is invariant when the posi-tions of source and receiver are interchanged. Our data set containsnumerous examples of this reciprocity principle, and we used it tocheck our data quality. Figure 7 shows one typical example: The twoimpulse responses lie on top of each other, apart from small uncorre-lated differences that we attribute to noise. This result is obtained be-cause the S/N is good and the deconvolution is performed correctly.
This check is not foolproof. If, for example, the source measure-ment were always divided by a factor of two in the processing flow,the reciprocal impulse responses would still be identical, but bothwould be too big by a factor of two. To guard against mistakes of thiskind, we have instituted a check on the processing flow using identi-cal signals at the source and receiver: The impulse response shouldbe a band-limited impulse with integral equal to unity.
ERRORS AND NOISE
The measurements we make are subject to errors. We account forthese errors by the noise term in equation 1. In an analysis of the fit ofmodelled results to our measured data, it is normal practice to definethe uncertainty of the measurements using a statistical model of theerrors e.g., Parker, 1994. Such models make assumptions about theprobability distribution of the errors. One such commonly used as-sumption is that the errors are a random-noise process and the proba-bility distribution function PDF of the errors is the normal orGaussian distribution.
Random errors, however, are extremely small compared with themain sources of noise in our data, which are very often cultural noisesuch as power-line and railway noise. Such noise is not random: Itoften consists of a fundamental frequency, say, 50 Hz in Europe or60 Hz in NorthAmerica, plus harmonics — typically odd harmonics— and often there are fluctuations in the value of the fundamental
frequency. Appendix B describes our approach to suppressing cul-tural noise. Appendix C describes a conventional error analysis ofthe data after processing to suppress cultural noise.
RESULTS
Real-time analysis
We have developed two useful tools to obtain a quick look at sub-surface resistivity: 1 common-offset displays of the recovered im-pulse responses or any transformation of them and 2 an apparentresistivity section based on the arrival times of the peaks of the im-pulse responses. These two types of display can be made withinabout a day of finishing a line.
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Am
plitu
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Ω/s
)
0 0.02
Time (s)
SRC16 REC24SRC24 REC16
0.04 0.06 0.08 0.1
a)
Am
plitu
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Time (s)
SRC16 REC24SRC24 REC16
0.04 0.06 0.08 0.1
b)0.25
0.20
0.15
0.10
0.05
0.0
Figure 7. Estimates of the earth impulse response a and b are thesame data with different vertical scales. There has been no divisionby source and receiver bipole lengths. In red, the source electrodeswere at pegs 16 and 17 with the receiver electrodes at pegs 24 and 25;in green, the source electrodes were at pegs 24 and 25, and the re-ceiver electrodes were at pegs16 and 17. The sharp peak at 5 ms isthe airwave, corresponding to the current switch 5 ms after start ofdata. The earth impulse response follows and is almost identical forthe two estimates, the rms difference being 0.00025 ohm/s.
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Figure 8 shows the impulse response data displayed as a series ofcommon-offset sections. Each section displays the impulse responsedata of a single horizontal line in Figure 6. We know that the pres-ence of a resistor is manifested by increased amplitude and earlier ar-rival of the peak of the earth impulse response. Figure 8 displays theamplitudes. The effect of a resistor is noticeable at offsets greaterthan about twice its depth. In Figure 8 we see high amplitudes be-tween pegs 18 and 40 horizontal distances of 1800–4000 m fromthe north at offsets of about 1400 m and greater. We interpret this asthe effect of the resistor corresponding to the known gas at a depth of500 m and greater.
We can use the traveltime of the peak as well as the amplitudes.Appendix D shows that the arrival time of the peak for a uniformhalf-space is given by
tpeak,r =r2
10, 6
where = 410−7 H/m, r is offset in meters, and is resistivity inohm-meters. For example, with r = 1000 m and = 20 ohm-m,tpeak,r = 210−3, as shown in Figure 3b. Equation 6 can be rearrangedto define an apparent resistivity:
H =r2
10tpeak,r, 7
in which H is the apparent resistivity of the half-space that yields thesame peak arrival time at offset r as the data.
This new apparent resistivity is a useful addition to the list of ap-parent resistivities given by Spies and Eggers 1986. Using thissimple formula on each recovered impulse response, we make thedisplay shown in Figure 9, in which there is a deep resistor betweenpegs 18 and 40 horizontal positions 1800–4000 m overlain by aconductor and variable near-surface resistors. This interpretation isconsistent with the results of the common-offset sections.
The theory used to derive equation 7 is basedon a dipole source, that is, a point source. We areusing bipole sources with a finite separation be-tween the poles. In practice, a bipole behaves likea dipole at distances greater than about five timesthe bipole length. In this survey, we worked with-in this rule of thumb.
It would be interesting to map from offset todepth, but this is not straightforward. The prob-lem can be understood by considering Figure 10.The colored curves are obtained using equation 6for different resistivities. The black circles aretraveltime peaks as a function of offset for CMP3600. For offsets 900–1100 m, the increase intraveltime with offset, or moveout, is large, indi-cating low resistivity. At 1100 m, the data pointcircled in red, there is an abrupt change in slopeand the moveout is less steep, indicating more re-sistive material. The equivalent half-space resis-tivity for the circled data point lies between the 10and 20 ohm-m curves, so it is about 15 ohm-m.
Distance (km)
700 m offset 1200 m offset 1700 m offset
800 m offset 1300 m offset 1800 m offset
900 m offset 1400 m offset 1900 m offset
1000 m offset 1500 m offset
1100 m offset 1600 m offset
2000 m offset
Tim
e (m
s)
Tim
e (m
s)30
0 5 Distance (km)0 5 Distance (km)0 5
60
90
30
60
90 Tim
e (m
s) 30
60
90
Distance (km)
Tim
e (m
s)
Tim
e (m
s)30
0 5 Distance (km)0 5 Distance (km)0 5
60
90
30
60
90 Tim
e (m
s) 30
60
90
Distance (km)
Tim
e (m
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Tim
e (m
s)30
0 5 Distance (km)0 5 Distance (km)0 5
60
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30
60
90 Tim
e (m
s) 30
60
90
Distance (km)
Tim
e (m
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Tim
e (m
s)30
0 5 Distance (km)0 5 Distance (km)
Normalized amplitude(Ω/m2/s)
0 5
60
90
30
60
90
Distance (km)
Tim
e (m
s)
Tim
e (m
s)30
0 5 Distance (km)0 5
0 1
60
90
30
60
90
Tim
e (m
s) 30
60
90
Figure 8. Common-offset sections of the earth impulse responsefunction for offsets 700–2000 m. The horizontal coordinate is themidpoint between source and receiver, and the scale is shown at thetop of each figure; the vertical coordinate is time, with the completeaxis being 0–100 ms. The gray bar at the top of each section showswhere the airwave has been muted out. The relative amplitude scaleis denoted by the color bar. The airwave has been muted out. Thepresence of a deep 500 m resistor can be seen at offsets of about1400 m and greater.
0
–200
–400
–600
–800
–1000
–1200
–1400
–1600
–1800
–2000
–2200
–2400
–2600
–2800
–3000
–3200
Offs
et (
m)
50
45
40
35
30
25
20
15
App
aren
t res
istiv
ity (
ohm
-m)
Position of midpoint (m) (Peg number x 100)
0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 3200 3400 3600 3800 4000 4200 4400 4600 4800 5000
Figure 9. Traveltime-to-resistivity mapping in CMP-offset coordinates using equation 7;horizontal distances are measured from peg 1 in the north.
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This is the value returned by equation 7 and plotted in Figure 9.However, from the average slope between 1100 and 1700 m, it isclear that the resistivity is much greater — perhaps 60 to 80 ohm-m.
Clearly, we should be using the slope to estimate the equivalenthalf-space resistivity. That is, we differentiate equation 6 to yield
dtpeak,r
dr=
r
58
and rearrange this formula to give another new apparent resistivity,
I =r
5dtpeak,r
dr−1
. 9
The relationship between H and I is roughly analogous to the rela-tionship between stacking velocity and interval velocity in the anal-ysis of seismic reflection data. So we refer to I as the apparent inter-val resistivity.
We have tried to extract apparent interval resistivities becausethese would have higher vertical resolution than the apparent half-space resistivities, but we have not been able to make this work onthese data. The reason is that errors in the estimates of the peak trav-eltimes are increased by noise. To compute the slope requires at leasttwo traveltimes, each with errors, and our data are not good enoughto make this computation. With improved data acquisition, we ex-pect to make this work on data in the future.
Integration of impulse responsesto recover step responses
The impulse responses may be integrated to give step responses.Figure 11 shows a real data example of a step response.At late times,the curve rises slowly and is asymptotic to some value V. An esti-mate of V may be made by fitting an appropriate curve to the data atlate times. V is in fact the DC value that would be obtained for a 1-A-m source; thus, the apparent resistance is V ohm.
We may estimate one value of the apparent resistance for eachsource-receiver pair and, knowing the positions of the source and re-ceiver electrodes, use a standard DC resistivity inversion routine,
such as described by Loke and Barker 1996, to obtain an estimateof subsurface resistivities. The result of this inversion for these datais shown in Figure 12. This is quite a nice result, especially as it clear-ly shows the top of the reservoir and is consistent with the results ofreal-time analysis. One shortcoming is that it does not show the bot-tom of the reservoir.
In the standard terminology of DC resistivity, a dipole-dipole ar-ray has the same spacing a between current electrodes and betweenpotential electrodes, and the distance between the closest current andpotential electrodes is denoted by na. The spread length is thus n+ 2a. Conventionally, n-factors up to about six are used, the S/N forlarger values being generally too small for a meaningful measure-ment Dahlin and Zhou, 2004. However, DC values derived fromMTEM measurements can use much larger values of n because ofthe increase in S/N obtained by the data processing. In this study, val-ues up to n = 25 were used. According to Edwards 1977, the pene-tration depth for the dipole-dipole array with large n values lies be-tween 0.239 and 0.250 times the length of the array, making it645–675 m. This is in agreement with Figure 12. To see beneath thereservoir with this method, we would need to use a longer spreadlength.
0
0.005
0.01
0.015
0.02
Mov
eout
tim
e (s
)
500Offset (m)
1 ohm-m2 ohm-m5 ohm-m10 ohm-m20 ohm-m30 ohm-m40 ohm-m60 ohm-m80 ohm-m100 ohm-m150 ohm-m200 ohm-mCMP 3600
1000 1500 20000
Figure 10. Times of earth impulse response peaks plotted againstoffset. The black circles are data points from CMP position 3600.The colored lines are plots of peak time versus offset, using equation6 for different values of resistivity. The traveltime data show a clearbreak in the slope at an offset of 1100 m — at the data point circled inred — indicating the presence of a resistor.
2.0
1.5
1.0
0.5
Vol
ts/m
0.02
Time (s)
x10–9
0.04 0.06 0.08 0.1
8
V
Figure 11. Real-data example of an integrated impulse response, orstep response. At late times, the curve rises slowly and is asymptoticto some value V.
100.0 –100.0 –300.0 –500.0 –700.0E
leva
tion
(m)
Resistivity (ohm-m)Unit electrode spacing = 100.0 m
Distance along profile (m)
Model resistivity with topographyiteration 4 rms error = 11.4
20.0 26.4 35.0 46.3 61.2 80.9 107 142
100 1700 3300 4900
Figure 12. Two-dimensional dipole-dipole DC resistivity inversionof the MTEM data using the estimated asymptotic values of the stepresponses. The red curve shows the top of the reservoir.
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Collated 1D inversions of CMP gathers
The traditional approach to interpreting EM data is to use inver-sion. We have developed a simple approach using 1D inversion. Wearrange our step response data in CMPgathers and try to find a singlestratified one-dimensional earth model whose step responses at thesame offsets fit the data. Each CMP gather is treated independently.The inversion results from each CMP are displayed side by side toform a 2D section.
The layered model has fixed boundaries, and the parameters arethe layer resistivities. We may choose a parameterization in whichthe layer thicknesses are constant or increase logarithmically.As off-
set increases within a CMP gather, the corresponding step responsesare sensitive to layers at increasing depth. We adopt, in general, a lin-ear scale for depth and a logarithmic scale for resistivity for directcomparison with both well-log information if there is any and in-terpreted seismic cross sections if there are any. However, the vari-ation in resistivity values found in this survey is much less than oneorder of magnitude, so the model results are best displayed with alinear depth scale and a linear resistivity scale. A typical model has20 layers of equal thickness overlying a uniform half-space.
We find this parameterization enables the inversion scheme to re-cover a resistive layer in synthetic models and resolves resistive tar-get layers, as in this paper. No a priori information is used in fact, wehad none; the starting model is a uniform half-space. A full wave-form multioffset Occam inversion has been developed, based on thework of Constable et al. 1987, and this finds the smoothest modelthat satisfies a collection of offset data within a CMP gather. Conver-gence occurs in about four to eight iterations.
A key issue in the inversion is what is known as static shift. Thereare lateral resistivity variations, especially in the near surface, thatclearly are not included in a 1D model. Compensation for these vari-ations can be made in a number of ways. One is to adopt the methodof Newman 1989 for transient EM with a grounded source and amagnetic receiver, whereby a multiplicative scaling factor is deter-mined that leads to a minimum rms inversion model. An alternativeis to impose an approximation that the amplitude within a CMPgath-er falls off such as 1/offset3, the theoretical value for a half-spaceWeir, 1980, and to scale accordingly. The second method is adopt-ed here.
Illustrative full-waveform, multioffset inversion results areshown in Figures 13 and 14. Figure 13a shows models derived atseveral CMP locations to the northeast of the profile pegs 11–15,and Figure 13b displays models over the central section of the profile
0
200
400
600
800
1000
Dep
th (
m)
Resistivity (ohm-m) 0 50 100 150 200 250
CMP 1000 CMP 1050 CMP 1100 CMP 1150 CMP 1250 CMP 1400
a)
0
200
400
600
800
1000
Dep
th (
m)
Resistivity (ohm-m) 0 50 100 150 200 250
CMP 2450 CMP 2500 CMP 2550
b)
Figure 13. a Resistivity models obtained by full-waveform multi-offset inversion at CMPpositions 1000–1400. b Resistivity modelsobtained by full waveform multioffset inversion at CMP positions2450–2550.
2.5 x 10–9
2.0 x 10–9
1.5 x 10–9
1.0 x 10–9
5.0 x 10–10
E-f
ield
am
plitu
de (
V/m
)
0.02 0.0
Time (s)
Offset 2045 m, data
Offset 2045 m, model response
Offset 1850 m, data
Offset 1850 m, model response
Offset 1649 m, data
Offset 1649 m, model response
0.04 0.06 0.08 0
Figure 14. Step-response data and modelled responses at CMP posi-tion 2500.
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around peg 25. The derived structures are similar to a depth ofaround 500 m, but thereafter the models depart significantly. Overthe central and southwest sections, a resistive layer is seen in allmodels, with resistivity values between 100 and 200 ohm-m. To thenortheast, the resistivity of the corresponding layer is less than60 ohm-m. Between 500 and 700 m depth, the transverse resistancein the central section is around 20,000 ohm-m2, in contrast to around6400 ohm-m2 to the northeast.
To execute an inversion routine, uncertainties must be includedfor each data point. Appendix C shows that, on average, errors in thestep response are a fraction of 1% of their value. Inversion using 1Dmodeling is unable to represent data obtained in the 3D world to thatlevel of accuracy. Instead, one-standard-deviation error bars are setto 1% of the amplitude of the step function at each time sample. Thecorresponding standard chi-squared misfit, whose expected value isunity, is shown in Table 2 for the CMP positions displayed in Figure13a and b. The expected value of chi-squared is one, so these misfitsindicate that an error allocation of 1% of the step function amplitudeis reasonable. An example of the fit to multitrace data is shown inFigure 14 for three offsets at CMP position 2500, with a misfit of3.12 as in Table 2.
The result of collating all of the 1D inversions is shown in Figure15. The resistor corresponding to the known gas is in red, and its topand bottom are clearly delineated. There is some ambiguity in the in-version because the earth’s response depends partly on the trans-verse resistance of a layer, that is, the product of its thickness and re-sistivity. For example, a 10-m-thick layer of 200 ohm-m resistivityhas the same transverse resistance as a 20-m-thick layer with100 ohm-m resistivity. However, the response also depends strong-
ly on the position of such a resistive layer. Thus, the results of Figure15 give a good indication of the top and bottom of the layer, with ver-tical uncertainties on the order of the layer thickness used — in thiscase, 50 m.
CONCLUSIONS
The data we collected with very limited equipment are of goodquality and are sufficient, with simple processing, to show the apexof the gas reservoir. Each of the 522 data points shown in Figure 6represents an impulse response of 1500 samples. Recovery of theimpulse responses requires a significant effort to suppress culturalnoise, which is generally of much greater amplitude than any ran-dom noise component.Appendix B provides the details.Appendix Cshows that the step responses are determined with an uncertainty of afraction of 1% of their value.
To interpret the data, we have developed four different approachesthat are consistent with each other, which is very encouraging. Twoof these methods — display of common-offset sections and mappingof peak arrival time to equivalent half-space resistivity — may beperformed quite quickly after the data have been recorded. The sec-ond method uses a new apparent equivalent half-space resistivity,defined by equation 7. A formula for apparent interval resistivityequation 9 has also been derived, but we did not succeed in apply-ing it to these data.
The integration of the impulse responses to generate step respons-es allowed us to estimate the DC value and use standard 2D dipole-dipole DC resistivity inversion of the data, which found the top of theresistor corresponding to known gas. Both the top and bottom of thereservoir were identified using a series of full-waveform multioffset1D Occam inversions performed independently on the step respons-es of individual CMP gathers. No constraints were used in the inver-sion, and the vertical uncertainty in the position of the resistive layerwas about 50 m.
The results demonstrate that the MTEM method has the potentialto be used as an exploration tool for hydrocarbons. A particular ap-plication of the method is where a potential hydrocarbon reservoirhas been identified using other geophysical methods, e.g., seismicreflection, and there is a need to reduce the risk of drilling a dry well.
ACKNOWLEDGMENTSWe thank TOTAL for inviting the University of Edinburgh and
MTEM Ltd. to test the MTEM method at the gas storage site. Wealso thank TOTALfor very generously arranging the permitting withlandowners at the site, switching off the cathodic protection whilewe were surveying, and providing the position of the top of the reser-
voir shown in Figures 12 and 15. The recordingsystem and the data-processing flow were devel-oped under Proof of Concept Project 4-ENO 004,funded by Scottish Enterprise. We thank the Uni-versity of Cologne for the loan of their generatorand Zonge switch box. We thank PierreAndrieux,two anonymous reviewers, and Kerry Key, asso-ciate editor, for their very helpful comments onour paper. This paper is published with the per-mission of the executive directors of MTEM.
Table 2. Chi-squared misfit of inverted models to data forvarious CMP positions.
CMP Position Chi-squared misfit
1000 1.49
1050 1.42
1100 1.10
1150 1.31
1250 2.18
1400 0.60
2450 0.93
2500 3.12
2550 2.58
0
200
400
600
800
1000
Dep
th (
m)
100908070605040302010R
esis
tivity
(oh
m-m
)
CMP0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 3200 3400 3600 3800 4000 4200 4400 4600 4800 5000
Figure 15. Collated 1D full-waveform inversions of CMP gathers of the step-responsedata. The black curve shows the top of the reservoir.
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APPENDIX A
DECONVOLUTION
Combine equations 1 and 2 and simplify:
vt = st * gt + nt , A-1
in which vt and st are known. In general, st is not close to an im-pulse t, so the convolution st*gt is not close to the impulse re-sponse. The objective of deconvolution is to replace st with an im-pulse.
Transform equation 1 from the time domain to the frequency do-main:
V = SG + N , A-2
in which, as the result of the convolution theorem, the convolutionbecomes a multiplication. At this point, the obvious step is to divideby S, but this is numerically unstable because the noise blows upat frequencies where S is small. Instead, we multiply by
F =S*
S2 +
1
S, A-3
in which the asterisk denotes complex conjugate and is a small pos-itive constant. The denominator is real, and prevents division byzero where S is small. This is still not perfectly satisfactory as itdoes not recognize the inherent bandwidth limitation of the system.As a finishing touch, we apply a zero-phase filter of the form
D = exp−
02 . A-4
The Fourier transform of D is dt:
dt = 0 exp− 202t2 . A-5
This is a band-limited approximation to a delta function, t; it has apeak at t = 0 and its integral is unity:
−
dtdt = 1. A-6
Multiplying equation A-2 by F and D gives
FDV = FDSG + FDN
DG + FDN . A-7
Finally, transforming back to the time domain gives
ft * dt * vt = ft * dt * st * gt
+ ft * dt * nt dt * gt
+ ft * dt * nt
t * gt + ft * t * nt
= gt + ft * nt . A-8
Comparing equations A-1 andA-8, we see that the objective of re-placing st by an impulse has almost been achieved; but because ofthe presence of noise, we have had to settle for a band-limited im-
pulse. The noise is still present but has been controlled. The angularfrequency 0 at which D decays to 1/e is normally chosen to behalf the angular Nyquist frequency:
0 =
2t. A-9
APPENDIX B
SUPPRESSING CULTURAL NOISE
We use two methods to reduce the effects of cultural noise: signalpolarity reversals and filtering.
Signal polarity reversals
Let the voltage measurement for the kth transient in the sequencebe
vk,t = mk,t + cnk,t + rnk,t , B-1
where mk,t is the signal we want to measure, cnk,t is culturalnoise typically 50 Hz plus harmonics or 60 Hz plus harmonics,and rnk,t is random noise. Normally, the random noise is verysmall compared with the cultural noise. We now make a repeat mea-surement at time T later, only this time the input current is reversedso the response is reversed. We have
vk + 1,t − T = mk + 1,t − T + cnk + 1,t − T
+ rnk + 1,t − T . B-2
We assume the earth has not changed, so the earth response in equa-tion B-2 is the same as that in equation B-1 except that its polarity isreversed, that is,
mk + 1,t − T = − mk,t . B-3
We expect the cultural noise to be periodic and choose T to be a mul-tiple of the period; for example, T = 1 s is one possibility for 50- and60-Hz noise. Then, ideally,
cnk + 1,t − T = cnk,t . B-4
Subtracting equation B-2 from equation B-1 and dividing by twogives
vk,t − vk + 1,t − T2
= mk,t +rnk,t − rnk − 1,t − T
2. B-5
Thus, the cultural noise is eliminated, and the signal and the incoher-ent random noise in both measurements remain. This procedure ob-viously relies on the cultural noise being periodic. The proceduremay be repeated as often as necessary. Odd traces have one polarity;even traces have reversed polarity.
Figure B-1 illustrates the procedure. The first measurement, cor-responding to equation B-1, is green; the second measurement, withreversed polarity, is red; and the stack of the two, corresponding toequation B-5, is black. It is clearly a step response plus noise. If thesignal polarity is not reversed, stacking two even traces or two oddtraces summing them and dividing the result by two does not pro-
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duce any discernible increase in S/N. The step response is invisible,as it is on either of the prestack traces of Figure B-1.
These examples show that polarity reversal is an important weap-on in suppressing cultural noise.
Filtering
The cultural noise component usually has a known fundamentalfrequency and harmonics, each of which has an amplitude and aphase and can be plotted as a vector in the complex plane. The phaseof any component of the noise is unlikely to be the same as the phaseof the signal at the same frequency, and the sum of the two compo-nents at that frequency will have a phase not equal to the phase of ei-ther component.
Figure B-2 shows a possible situation in which the transient re-sponse is 1 s long, so its frequency components are at 1, 2, 3, etc.,Hz. The vectors of the 48-, 49-, 50-, 51-, and 52-Hz componentsmight look as shown by the solid vectors in Figure B-2, with the 50-Hz vector not conforming to the pattern of the others. If the data havebeen sampled properly, the amplitude and phase of the earth re-sponse are both smoothly varying functions. The 50-Hz vector is toobig and has the wrong phase. We attribute this behavior to the noisecontribution, known to be at 50 Hz, and conjecture that the signalvector should be somewhere between the vectors for 49 and 51 Hz,which we expect to be composed of signal plus random noise. Wefind the magnitude and phase of the 50-Hz signal vector by interpo-lation, as shown schematically by the dotted vector.
APPENDIX C
ERRORS
To obtain an estimate of the error present in the processed data, weconsider the data as consisting of stacks of pairs of consecutive rawtraces, as described in Appendix B. This is because we alternate thepolarity of the source signal. The standard error on the mean mtfor traces from a single-source receiver was calculated using theequation
mt =tN
, C-1
where t is the standard deviation of the population and N is thenumber of pairs of traces in the population. Figure C-1 shows thestacked step response with plus and minus one standard error of themean. The error on the stacked step response is extremely small. Fig-ure C-2 shows the standard error on the mean for this trace as a per-centage of the amplitude of the step response. On average, the errorof the stacked response is less than 0.4%.
Ele
ctric
-fie
ld a
mpl
itude
(V
)
0.025
Time (s)
Trace 1Trace 2Stack of 1 & 2
0.05 0.075 0.10
0.00100
0.00075
0.00050
0.00025
0
–0.00025
–0.00050
Figure B-1. Two consecutive raw traces after reversing the polarityof one to correct for the source polarity are shown in green and red.The result of stacking these two traces is shown in black.
50
0
48
49
51
52Imaginary
[50]
Real
Figure B-2. Diagram to show the effect of 50-Hz cultural noise onthe spectral components from 48–52 Hz. The solid vectors representthe data before filtering; after filtering, only the 50-Hz componenthas changed, shown by the dashed vector.
0.0004
0.0003
0.0002
0.0001
0
Ele
ctric
-fie
ld a
mpl
itude
(V
)
0.025
Time (s)
0.05 0.075 0.1 0
Mean Mean –1 std error Mean +1 std error
Figure C-1. The black line shows the step response recovered fromprocessing 1800 raw traces. The green and red lines, respectively,denote plus and minus one standard error on the mean.
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A measure of data quality can be made by calculating the S/N asfollows. The noise is taken as the rms amplitude of the pretriggersamples before the source switches, and the signal is taken as thelate-time amplitude of the step. The data shown in Figure C-1 have aS/N of 57 dB, that is, the pretrigger noise is 0.14% of the late-timemean value, consistent with Figure C-2. In general, data are consid-ered to be good if the S/N is greater than about 45 dB. Figure C-3shows the S/N for all the data collected in the survey.
APPENDIX D
DETERMINATION OF TIME TO THE PEAKOF THE EARTH IMPULSE RESPONSE
The inline electric-field response at the surface of a half-space ofresistivity ohm-m to a switch-off 1-A-m step in current at a dipoleat a distance r is given by Weir 1980:
E,r,t =1
2r3erf r
c2t −
2
r
c2texp−
r2
c24t ,
D-1
in which c2 = /, = 410−7H/m, and erf is the error function.The response to a unit impulse is obtained by differentiating equa-tion D-1 and multiplying by −1, as derived by Wilson 1997:
g,r,t =
8c3exp− r2
c24tt−5/2. D-2
Taking the natural logarithm of both sides of equation D-2 gives
lng,r,t = ln
8c3 −r2
c24t+ lnt−5/2
= ln
8c3 −r2
c24t−
5
2lnt . D-3
To find the time of the peak, differentiate equation D-3 with respectto t,
lng,r,tt
=r2
c24t2 −5
2t, D-4
and set the result to zero, yielding
tpeak,r =r2
10c2 =r2
10. D-6
REFERENCES
Archie, G. E., 1942, The electrical resistivity log as an aid in determiningsome reservoir characteristics: Journal of Petroleum Technology, 5, 1–8.
Constable, S. C., R. L. Parker, and C. G. Constable, 1987, Occam’s inversion:A practical algorithm for generating smooth models from EM soundingdata: Geophysics, 52, 289–300.
Dahlin, T., and B. Zhou, 2004, A numerical comparison of 2D resistivity im-aging with 10 electrode arrays: Geophysical Prospecting, 52, 379–398.
Edwards, L. S., 1977, A modified pseudosection for resistivity and IP: Geo-physics, 42, 1020–1036.
Edwards, R. N., 1997, On the resource evaluation of marine gas hydrate de-posits using sea-floor transient electric dipole-dipole methods: Geophys-ics, 62, 63–74.
Kaufman, A. A., and G. V. Keller, 1983, Frequency and transient soundings:Elsevier Science Publ. Co., Inc.
Levinson, N., 1947, The Wiener rms root mean square error criterion in fil-ter design and prediction: Journal of Mathematics and Physics, 25,261–278.
Loke, M. H., and R. D. Barker, 1996, Rapid least-squares inversion of appar-ent resistivity pseudo-sections using quasi-Newton method: GeophysicalProspecting, 48, 152–181.
Newman, G. A., 1989, Deep transient electromagnetic soundings with agrounded source over near-surface conductors: Geophysical Journal, 98,587–601.
Parker, R. L., 1994, Linear problems with uncertain data, in Geophysical in-verse theory: Princeton University Press, 119–198.
Robinson, E. A., 1957, Predictive decomposition of time series with applica-
Time (s)
Err
or (
%)
0 0.05 0.1
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Figure C-2. The standard error on the mean as a percentage of theamplitude of the stacked step response.
Offs
et (
m)
8075706560555045403530
Sig
nal t
o no
ise
ratio
(dB
)
Peg number of midpoint x 1000 500 1000 1500 2000 2500 3000 3500 4000 4500 5000
North South0
–500
–1000
–1500
–2000
–2500
–3000
–3500
–4000
–4500
–5000
Figure C-3. Aplot similar to Figure 6 but showing the S/N of all data.
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tion to seismic exploration: Geophysics, 22, 767–778.——–, 1967, Statistical communication and detection with special reference
to digital data processing of radar and seismic signals: Charles Griffin.Robinson, E. A., and O. A. Osman, 1996, Deconvolution 2: Geophysics Re-
print Series: SEG.Rocroi, J.-P., and F. Gole, 1983, Method of geophysical prospection using
transient currents: U. S. Patent 4 417 210.Spies, B. R., and D. E. Eggers, 1986, The use and mis-use of apparent resis-
tivity in electromagnetic methods: Geophysics, 51, 1462–1471.Strack, K.-M., 1992, Exploration with deep transient electromagnetics:
Elsevier Science Publ. Co., Inc.Strack, K.-M., T. Hanstein, K. LeBrocq, D. C. Moss, K. Vozoff, and P. A.
Wolfgram, 1989, Case histories of LOTEM surveys in hydrocarbon pro-spective areas: First Break, 7, 467–477.
Webster, G. M., 1978, Deconvolution: Geophysics Reprints Series: SEG.Weir, G., 1980, Transient electromagnetic fields about an infinitesimally
long grounded horizontal electric dipole on the surface of a uniform half-
space: Geophysical Journal of the RoyalAstronomical Society, 61, 41–56.Wiener, N., 1949, Time series: Massachusetts Institute of Technology Press.Wilson, A. J. S., 1997, The equivalent wavefield concept in multichannel
transient electromagnetic surveying: Ph.D. thesis, University of Edin-burgh.
Wright, D. A., 2003, Detection of hydrocarbons and their movement in a res-ervoir using time-lapse multi-transient electromagnetic MTEM data:Ph.D. thesis, University of Edinburgh.
Wright, D. A., A. Ziolkowski, and B. A. Hobbs, 2001, Hydrocarbon detec-tion with a multichannel transient electromagnetic survey: 71stAnnual In-ternational Meeting, SEG, ExpandedAbstracts, 1435–1438.
——–, 2002, Hydrocarbon detection and monitoring with a multichanneltransient electromagnetic MTEM survey: The Leading Edge, 21,852–864.
——–, 2005, Detection of subsurface resistivity contrasts with application tolocation of fluids: U. S. Patent 6 914 433.
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