High Resolution, Deep-Tow Seismic Survey to Investigate the Methane Hydrate Stability Zone in the...

1. Introduction

Large-scale deposits of methane hydrate have beeninferred from the widespread occurrence of a BSR (bot-tom-simulating reflector) in the Nankai AccretionaryPrism, Offshore Japan (Morita et al., 2002). In the peri-od 1995 – 99, JNOC (Japan National Oil Corporation)conducted a “methane hydrate joint research project”employing a range of exploration technology to investi-gate the methane hydrate layer and BSR in the NankaiTrough area, including conventional 2D seismic stream-er lines, multi-component OBS (ocean-bottom seis-mometers) and a high resolution deep-tow survey. Thisdeep-tow survey was acquired in 1996 using theDTAGS (deep-towed acoustics/geophysics system)developed by the Naval Research Laboratory, USA(Gettrust et al., 1991; Rowe and Gettrust 1993).Processing part of the data in 1997/98 showed that itwas possible to obtain very high resolution images ofthe shallow sediments below the seabed, where thehydrate layers are expected (Shimizu et al., 2002). In1999 the MITI (Ministry of International Trading andIndustry) “Nankai Trough Well” yielded cores whichcontained methane hydrate in the pores of sandstone

layers, and high saturation levels of up to 80 % wereinferred (JNOC report, 2000). Following these results,in 2001 METI (Ministry of Economy, Trade andIndustry; former MITI) started a long-term project,named MH21, to develop methane hydrate as a naturalresource. The objective of the first six years of MH21 isto employ geophysical and geological techniques todetermine the quantity, distribution and mode of occur-rence of the methane hydrate and associated free gas. Aspart of this first phase, the 1996 DTAGS data is current-ly being re-evaluated to estimate to what extent deep-tow surveys could contribute to knowledge of themethane hydrate accumulations. The map, Figure 1,shows the location of the deep-tow survey lines in rela-tion to the Japanese Coast, the MITI Nankai TroughWell and the 2002 Tokai Oki 3D survey, acquired aspart of the first phase of MH21.

1.1. Why DTAGS?

The DTAGS system has two key features whichmake it highly suited to investigating the hydrate layers.1. The source and receivers are towed close to the

seabed. In deep water this offers a significant advan-tage over conventional seismic surveys with surfaceairguns and streamer cables. Quite simply we obtain a

RESOURCE GEOLOGY, vol. 54, no. 1, 115–124, 2004

115

High Resolution, Deep-Tow Seismic Survey to Investigate the Methane Hydrate Stability Zone in the Nankai Trough

Peter WARD, Eiichi ASAKAWA and Shoshiro SHIMIZU*

JGI Inc., Meikei Building, 1-5-21 Otsuka, Bunkyo-Ku, Tokyo 112-0012, Japan [e-mail: [email protected]]* Japan National Oil Corporation, Technology Research Center, 1-2-2 Hamada, Mihama-Ku, Chiba 261-0025, Japan

Received on October 4, 2003; accepted on February 6, 2004

Abstract: A high frequency deep-tow seismic survey was carried out in the Nankai Trough area in 1996. The objective ofthe survey was to obtain high resolution seismic sections and velocity profiles of the methane hydrate zone, inferred from thestrong BSR events seen on conventional seismic data in the area. A special feature of the survey is that both the source andthe streamer cable are towed close to the seabed. This special acquisition geometry requires special data processing to han-dle the varying source and receiver depths. A CMP floating datum processing sequence was designed which led to high qual-ity sections of the shallow geology. A key step in the processing was devising a residual statics technique to compensate forerrors in the measured depths.

The processing sequence was applied to a number of lines, totaling 200 km. The final data quality was highly variable.Some lines produced high quality sections and others, much poorer sections with few interpretable events. Conventional seismicdata in the area also shows variation in the data quality so part of the reason is a variation in the sub-sea geology, but the deep-towdata is much more sensitive to change in conditions than conventional data. With the current acquired data and processingsequence the deep-tow system offers most advantages when 1) the water depth is around 1 km or greater, 2) the seabed andunderlying geology is not too complex, and 3) the acquisition proceeds smoothly with regular shotpoints, slowly varying depths,and with accurate positioning.

Keywords: deep-tow seismic, DTAGS system, floating datum processing, methane hydrate, residual statics, seabed reflec-tion picking

“closer look” at the target just a few hundred metersbelow the source.

2. The DTAGS source is a high frequency vibrator with asweep 250 – 650 Hz. This gives a dominant frequencyabout ten times that of standard airgun data and evenfour times that of high-resolution airgun data. The highfrequencies are rapidly absorbed and so DTAGS is notsuited to studying deeper geology, but the hydratelayer in Nankai trough is within about 300 m of theseabed and within range of the DTAGS source.The result of using this high frequency source close to

the target can be a very high resolution seismic section,and also, a high resolution velocity analysis of the shal-low layers. Interval velocities in particular are believed tobe important indicators of the hydrate layers and possibleunderlying free gas (Dillon and Paull, 1983; Ecker et al.,2000; Hato and Inamori, 2002). The DTAGS data not

only allows high resolution picking of RMS velocities,but perhaps more important, the short travel-times to thetarget allow a much more robust conversion from RMSto interval velocity. Putting this another way, for conven-tional deep water seismic data, the long travel time to theseabed means that all reflectors near the seabed haveRMS (root mean square) velocities very close to the seawater velocity; a tiny change in the RMS velocity pickingleads to a very big change in calculated interval veloci-ties, especially for the thin layers in which methanehydrate is found.

1.2. Processing challenges

The same keys features of the DTAGS system whichare seen as advantages – a high frequency system towednear the target – also lead to problems or challenges in thedata processing (also in the acquisition, but that is not the

P. WARD, E. ASAKAWA and S. SHIMIZU116 RESOURCE GEOLOGY :

AB C

D

17

ED

43 7

910

11

10 km0Water Depth (m)

250

800

1350

1900

2450

MITI Well, Nankai Trough’

Nagoya

IzuPeninsula

Deep-Tow Line Names all begin, D96-for example, line A on the map is shortfor D96-A

Fig. 1 Deep-Tow Survey Location Map. The colored region shows the extent of the 2002 Tokai Oki 3D survey. The colorsrepresent the sea water depth.

focus of this paper).1. The fact that the source and receivers must be towed

close to a varying seabed means that, unlike conven-tional marine data, they are not at a fixed elevation.This requires floating datum processing with static cor-rections similar to that in land data processing, but withtwo additional difficulties;(a) The very high frequency of the data makes it muchmore sensitive to errors or approximations.(b) There are no fixed receiver locations and thus nopossibility of receiver-consistent static corrections.

2. The source wavelet is high frequency but does not havea large bandwidth (about 1.4 octaves) so it has largesidelobes. This leads to a muchgreater risk of loop-skippingduring correlation-based staticscalculations, velocity analysisand stacking.

3. A third issue is the correct posi-tioning of the source andreceivers. This is obviouslyvery difficult at great depthsbeneath the ship and there arebelieved to be some positioningerrors in the existing processeddata. This is a matter of ongo-ing investigation.

2. Acquisition

The Nankai Trough DTAGSsurvey was acquired by SSI(Seafloor Surveys International) inNovember 1996. There were prob-lems with the equipment whileshooting and the lines shown inthe map, Figure 1, are segmentsthat were suitable for data process-ing and interpretation.

During the acquisition thesource and streamer were towedapproximately 200 m above theseafloor. The streamer cable had

48 hydrophones in two sub-arrays. The nearest 24receivers were closely spaced at 2.1 m interval. The far-ther offset 24 channels were spaced at 21 m, i.e. ten timesthe near-offset interval. Figure 2 shows a schematic dia-gram of the acquisition configuration and also a typicalshot record before and after sweep correlation.

The DTAGS source is a marine vibrator, Helmholtztransducer (piezoelectric unit). The sweep has frequencyband 650 – 250 Hz (down-sweep) and length 0.25 sec.The data was recorded at a sampling rate of 432 micro-sec. The correlation of the signal was done using therecorded sweep in a calibrated hydrophone, 57 m from thesource. Figure 3 shows the source sweep signature, the

vol. 54, no. 1, 2004 Deep-Tow Seismic Survey in the Nankai Trough 117

source #1 #24 #25 #26 #27

2.1 m 21 m

70.9 m

136.5 m

#48#47

#46

tailswivel

~200m

~1km +

Near 24 Channels

Far 24 Channels

Shot Before Sweep Correlation

Sea Bottom Reflection

Direct Arrival

Shot After Sweep Correlation

(a)

(b)

TW

O-W

AY

TIM

E (

SE

C)

0.1

0.2

0.3

0.4

0.5

0.6

0.7

(c)

0.1

0.2

0.3

0.4

0.5

0.6

0.7

TW

O-W

AY

TIM

E (

SE

C)

Fig. 2 (a) Acquisition Geometry. (b) Shot record before and (c) after sweep correlation.

SweepCorrelated Sweep 50 100 200 600

-6 dB

-18 dB

-30 dB

Frequency (Hz)

Ai rgun

DTAGS

20 m

sec

250

mse

c

Fig. 3 DTAGS sweep,correlated waveletand frequency spec-trum (log-log scale).High-resolution air-gun spectrum plottedfor comparison.

correlated wavelet and the frequency spectrum. For com-parison, the frequency spectrum of conventional high-res-olution airgun data from the same area is also plotted.

2.1. Navigation data

The nominal shotpoint spacing was around 17.5 m, cor-responding to a vessel speed of 2 knots and a shot every17 seconds. In practice it is not possible to maintain a con-stant shot interval for such a deep source. If all shot pointintervals between successive shots are plotted on a his-togram, they show a normal distribution around the nomi-nal 17.5 m, with a standard deviation of about 5 m.

The accuracy of the X, Y and Z positions of the sourceand receivers is a key issue in the processing of the deep-tow data. In conventional marine acquisition the positionof the vessel and the streamer cable can be determinedwith sufficient accuracy for the resolution of the data. Forthe DTAGS system the position of the vessel can bedetermined accurately but it is much more difficult todetermine the position of the source and receivers, typi-cally 1 km below the surface. The depths were deter-mined from pressure-sensors on the source and at fourlocations along the streamer. Residual statics analysis dur-ing the processing indicated that the source and near-offsetstreamer depths had errors of around 2 m but the longeroffsets had much larger errors, up to 25 m (see Fig. 8).

The X-Y position of the source was determined rela-tive to the vessel using a trackpoint transponder on thesource and receiver beneath the vessel, together withheading sensor readings on the source. The position ofthe streamer relative to the source was determined fromfour heading sensors adjacent to the depth sensors. Itwas found during the data processing that the calculatedpositions of the receivers were unreliable; they oftenshowed a curved streamer when the direct arrivalsshowed the streamer was straight. As a result, thestreamer heading data and the calculated streamer posi-tions were not used in the processing. Instead, the directarrivals were used to determine which line segments hadan almost straight cable, and these were the segmentsprocessed. The shotpoint X-Y positions from the navi-gation data were used in the processing. It is not easy toverify these positions and this is still an ongoing study.

3. Data Processing - Key Points

The data processing followed a similar sequence tostandard marine processing; set geometry, gain recovery,trace scaling (shot and offset consistent), deconvolution,CMP (common mid point) sort, datum and residual staticcorrections, velocity analysis and stack. In this sequenceonly static corrections are unusual for marine processing.The deconvolution had very little visual effect because thefrequency bandwidth of the data is very narrow and there

are no strong short-period multiples. In this section wefocus on the processing aspects which are related to theunique geometry and high frequency of the DTAGS data.

3.1. X-Y positioning and CMP binning

The shotpoint X-Y coordinates were read from the nav-igation files. As stated in section 2, the receiver coordi-nates in the navigation files were found to be unreliable.Plots were made of the direct arrival of every 10th shot,LMO (linear moveout) corrected with sea water veloci-ty, 1490 m/sec. Where this corrected arrival was flat thecable was assumed to be straight and where the longoffset arrivals were early the cable was assumed to bebent. It was found that most of the line segments hadvery close to straight cables and these were the dataranges processed. So in the processing we assumed thatthe SP X-Y coordinates were correct and that the cablewas following straight behind the source.

The objective of the processing was to obtain highresolution sections and velocities and the best way to dothis is to sort the data to the common mid-point domain.The acquisition parameters produce a mid-point spacingof 2.1/2 = 1.05 m for the near 24 channels and 21/2 =10.5 m for the far 24 channels. To obtain the highestspatial resolution section, only the near-offsets could beused to obtain sections with a 1.05 m trace spacing(Wood and Gettrust, 2001) but this produces only a 1 or2-fold section and requires regular shooting, and it isunsuitable for velocity analysis. It was decided to tryprocessing using the 10.5 m CMP binning natural forthe long-offset spacing. This gave CMP gathers with anaverage fold of around 28. The advantages of the largerCMP gathers are; higher S/N ratio in the stack sections,better statistics for the statics calculations (section 3.2.)and good offset distribution for velocity analysis. Thedisadvantage is loss of spatial resolution and consequentaliasing of events with more than 4 degrees of dip.

3.2. Floating datum and residual statics

The measured depths of the shots and receivers weresmoothed over a spreadlength (600 m) to define a CMPfloating datum. The idea of the floating datum is to applythe relatively small corrections from measured depth tofloating datum before velocity analysis and NMO correc-tions and then later apply the large correction from float-ing datum to final datum (mean sea level) after stacking.Figure 4 shows the depth profile, the uncorrected near-off-set section (channel 1) and the final datum near-offset(channels 1-24) CMP stack of line D96-9.

This stack was made using measured depths, and on asmall-scale plot the sea bottom looks correctly aligned.However, in detail it is seen that there is often a verypoor alignment of events, even for this near-offset stack.If longer offsets (channels 25-48) are included, the stack


gets much worse. Figure 5 showsdetail from a near-offset stack andfull-offset range NMO (normalmoveout) corrected CMP gathers,made using only the measureddepths.

It is clear that the measureddepths are not accurate enough toproduce CMP gathers for stackingor velocity analysis and that someresidual correction is required.The standard land residual staticstechnique of picking shifts bycross-correlations in the CMPgathers and decomposing theseshifts into shot and receiver staticsdoes not work with DTAGS data.


Floating Datum

Seabed

Surface Reflection

1600

00

400

0

(a)

Seabed Reflection

Surface Reflection

(b)

Surface Reflection

Seabed Reflection

First Multiple

(c)

Floating Datum

3 km0

Dep

th (

m)

0.0

0.5

1.0

1.5

0.5

1.0

1.5

2.1

TW

O-W

AY

TIM

E (

SE

C)

TW

O-W

AY

TIM

E (

SE

C)

Fig. 4 (a) Depth profile,from navigation data. (b)Near-offset section,uncorrected. (c) Datum-corrected near-offsetstack. (Line D96-9).

Near-Offset StackNMO-Corrected CMP Gathers

500 m070 m offset 620 m offset

100

mse

c

2155 2175 2195 2215 2235 2255 2275 2295 2315

Fig. 5 Near-offset stack and NMO-corrected CMP gathers before residual statics.

First, the shifts at longer offset are several waveletslong and this leads to severe loopskip problems.Second, there are no fixed receiver positions so thedecomposition into shot and receiver statics cannot beapplied.

Consequently a new approach to residual statics wasdeveloped for this data. A known event is picked for alltraces and the picks fitted in a least-squares sense to amodel of the event. The shift between the picks and thefitted model event are the residual statics. The modelevent must be well-known and give good picks. Thereare two candidates; the sea surface reflection and thesea bottom reflection, as illustrated in Figure 6.

At first glance the sea surface appears to be the betterchoice of model event; it is flat and it gives a verystrong reflection event. In fact, however, the sea surfaceis not exactly flat, depending on weather conditionsthere will be a swell and even a 2 m swell will causeunacceptable errors. Another problem with the surfacereflection is that it is not a first-arrival and is often dis-torted by interference with other events. The sea bottomreflection on the other hand is always the first arrivaland generally very easy to pick. Hence, sea bottompicks were used to estimate the residual depth correc-tions. The technique for deriving residual statics is sum-marized in the following steps.1. Sort to CMP gathers (10.5 m CMP bins).2. Separate measured depths into a smooth floating

datum component and the small corrections to thisdatum. Apply the corrections to datum (pre-NMOstatics).

3. Pick the sea-bottom reflection for all traces.4. Fit the picks to a hyperbola with velocity 1490 m/sec

(determined from direct arrivals). Fix zero-offset timeof the model hyperbola from the average zero-offsettime of the near 24 channels (with the smallest errorsin the measured depths).

5. The residual static withineach CMP is the differencebetween the picked time andthe model hyperbola time.The traces now line-up with-in each CMP but there is stilla shift between CMP’s.

6. Make near-offset (channels1-24) stacks with staticsapplied. Cross-correlateneighboring traces to esti-mate shift between CMP’s.

7. Match the long wavelengthtrend of the CMP statics tothe measured depth trend.That is, force the statics to beonly short wavelength cor-

rections to the measured depths.8. The final static for each trace is the sum of the shift

to the model hyperbola and the CMP correlationshift. The statics are not resolved into shot andreceiver terms.Figure 7 shows the same stack and NMO-corrected

gathers as Figure 5 but now with residual staticsapplied.

On average, the residual statics were found to bemuch larger for the far offsets than the near offsets.Figure 8a shows the offset dependency of the statics forone line. A similar trend was found for the other lines.Plotting the RMS statics against CMP location it wasfound that the statics were largest where the source andreceiver depth was changing rapidly. Figure 8b shows


Sea Surface Reflections

Sea Bottom Reflections

Fig. 6 Sea surface and sea bottom reflection ray-paths.

NMO-Corrected CMP GathersNear-Offset Stack

500 m070 m offset 620 m offset

100

mse

c

2155 2175 2195 2215 2235 2255 2275 2295 2315

Fig. 7 Near-offset stack and NMO-corrected CMP gathers after residual statics.

the residual statics for one lineplotted against CMP location.The floating datum is also plot-ted and it is clear that thebiggest corrections are neededwhere the datum changes.

3.3. Velocity analysis

The floating datum CMPgathers after residual static cor-rections were suitable input forvelocity analysis. The resolutionof the picks on the semblancedisplays was found to be im-proved by two additional steps.1. Averaging the semblance

from 7 consecutive CMP’sgave improved S/N.

2. Sub-stacking the near-offsettraces into 21 m offset bins.This gave all offsets an equalweight and sharpened thesemblance peaks.Figure 9 shows a typical sem-

blance plot at one CMP locationtogether with a color-coded


Channel Number (1 – 48)

(a)

0

40

Floating Datum

0

600

(b)

CMP

RM

S D

epth

Err

or (

m)

RM

S D

epth

Err

or (

m)

RM

S D

epth

Err

or (

m)

25

0

5

10

15

20

1 5 10 15 20 25 30 35 40 45

10

20

30

Fig. 8 (a) RMS depth errors vs. Channel Number (Offset). (b) RMS depth errors vs.CMP location.

No more picks belowthis level

IntervalVelocity

(m/s)1500

1700

1900

2100

2300

2500500 m0

RMS Velocity

100

mse

c

1400

19

00

15

00

1600

1800

1700C

DP

240

0

0.4

0.5

0.6

0.7

Fig. 9 Interval velocity section derived from semblance analysis. One semblance scan at CDP 2400 is also shown (Line D96-E).

interval velocity section inthe neighborhood of thepicked CMP. The intervalvelocities were calculatedfrom the picked RMS veloci-ties. The figure illustrates ageneral feature of theDTAGS data; the picks showa clear sharp velocity trendfor a few hundred msecbelow the sea bottom andthen, abruptly, the trend islost at about the BSR level.

4. Discussion

4.1. Variable data quality

The final deep-tow stacksections showed a highlyvariable data quality, in some areas a very clear imageof the shallow layers was obtained and in others theimage was very poor. Figure 10 shows an example fromthe highest and lowest quality results.

The variable quality was partly due to changes in sub-sea geology because the conventional data also showsclear sedimentary reflections in some areas and nothingmuch below the seabed in others. The deep-tow howev-er was much more sensitive to changes in conditions.The following factors strongly affected the quality ofthe deep-tow sections;

4.1.1. Complex seabed: The residual statics methodassumes the seabed reflections are hyperbolic. Whenthere are rapid changes in the seabed this is not true andthe statics and consequently the resulting gather andstack become poor.

4.1.2. Steep dips: The CMP bin size of 10.5 m is verymuch larger than the vertical resolution of the data. Thismeans that aliasing occurs at relatively low dips ofaround 4 degrees or more. Most of the hydrate layersare gently dipping (vertical scales in plots are generallyhighly exaggerated) but where there are steeper dips the10.5 m CMP processing sequence does not work well.

4.1.3. Water depth: In the Eastern side of the survey theseabed rises to within a few hundred meters of the sur-face. The DTAGS system is not suitable at these depthsbecause the source and receiver at 200 m above theseabed are getting close to the surface. The reflectionfrom the surface arrives early and often interferes withthe reflections in the target zone.

4.1.4. Rapid changes in source/receiver depths: Thefloating datum statics method works best if the sourceand receiver depths do not change too rapidly. This is

because the range of elevation corrections within a CMPmust be as small as possible to satisfy the static shiftapproximation (large elevation corrections require adynamic correction). There are several places where thedepths of DTAGS changed by around 100 m within aspreadlength (within a CMP) and this is too much forthe static approximation to work well for such high fre-quency data. As a result the quality of the gathers andstacks deteriorated whenever the DTAGS depths werenot smoothly varying.

4.1.5. Acquisition problems: There were problems dur-ing the acquisition along some of the lines resulting indropped shotpoints. This is a more serious problem forDTAGS data than conventional data because the near 24channels are very important to fix the residual staticshifts. Where there is a gap in shooting longer thanaround 25 m then there are no near offsets in someCMP’s and the data quality rapidly deteriorates.

4.1.6. Positioning accuracy: If the shot X-Y coordi-nates are inaccurate then the CMP binning will also beinaccurate and the quality of the stack will deteriorate,especially where there are structures. It is difficult toverify the shotpoint locations during processing butonce stack sections are obtained a check can be made atthe line intersections. If all positioning information isaccurate then the sections should tie very well at the lineintersections. It was found that the lines did not tie at thenavigation data line intersections. Cross-correlationanalysis of the sections around the intersection pointsdid find very convincing line ties but at locations about100-300 m away from the expected points. This indi-cates that there are quite large positioning errors, of theorder hundreds of meters.


High Quality Deep-Tow Result Low Quality Deep-Tow Result

100

mse

c

1 km0 1 km0

Fig. 10 Comparison of high quality and low quality deep-tow final stack sections;D96-D and D96-17 respectively.

4.2. Comparison with conven-tional streamer data

The most obvious way toevaluate the processing of thedeep-tow data is to comparethe resulting stack sectionswith conventional streamerdata. There are many 2D linesin the area, including high res-olution lines with 1 msec sam-pling and frequencies exceed-ing 200 Hz (Fig. 3). There isalso a 3D survey, acquired in2002, and which covers mostof the deep-tow lines (Fig. 1).The 3D data is also high-reso-lution and is currently beingcompared with the deep-towdata. Figure 11 shows a com-parison between a deep-towsection and a conventional 2Dhigh-resolution line which runs over the same location asthe deep-tow line. The comparison shows that very shal-low events can be resolved with finer detail than on theconventional section. The high frequencies, however, arequickly attenuated and deeper down the conventional datais easier to interpret. A striking feature is that the strongBSR event on the conventional section is very weak onthe deep-tow section and appears as an incoherent seriesof events at the bottom of the reflection series. No reflec-tors are seen on any of the deep-tow sections below theBSR level.

4.3. Weak BSR

The weakness of the BSR event in the deep-tow datacompared to conventional data is a general feature ofthe Nankai Trough deep-tow survey. The absence ofdeeper reflectors in the deep-tow sections may be attrib-uted to the low power of the source and the rapid attenu-ation of the high frequencies. The BSR, however, comesjust below a series of reflectors which are quite strong inthe deep-tow sections and thus its weakness is not onlydue to the power of the source. A weak BSR has alsobeen reported in other high-resolution methane hydrateinvestigations (Chapman et al., 2002). More generally,on all seismic it is seen that the BSR reflection is fre-quency dependant; low frequencies are reflected morestrongly than high frequencies. This implies that theBSR does not correspond to a sharp interface, like sedi-mentary layers, with an abrupt change in acousticimpedance. There are two likely models of the BSRzone. The first is a transition zone several meters thick;low frequency waves longer than this zone are reflected

strongly but high frequency waves shorter than the zoneare not reflected. Chapman et al. (2002) conducted syn-thetic reflector modelling to demonstrate this effect. Thesecond model of the BSR zone is a rough, broken inter-face which scatters high frequency waves and onlylooks continuous at low resolution (Wood et al., 2002).Figure 12 shows the frequency dependency of the BSRon a high resolution airgun section.


100

mse

c

1 km0Deep-Tow Stack Conventional High-resolution Stack

BSR

BSR

BSR

Fig. 11 Comparison of deep-tow section, D96-D, with convention-al high-resolution line, N96-CH, at almost the same location.

Fig. 12 Frequency dependency of the BSR reflector.Note how the BSR looses continuity and amplitude,compared to other reflectors, when low frequencies arefiltered out. Detail from stack section, conventionalairgun line N96-CH .

Unfiltered

BSR

Sea Bottom

50 Hz Low-cut

100

mse

c

5. Conclusions

The CMP processing of the Nankai Trough deep-towdata can provide high resolution seismic sections downto a maximum of around 400 msec below the seabed.This depth range includes the methane hydrate stabilityzones and the BSR. There are no reflections in the deep-tow data below the BSR level and the BSR itself is avery weak and incoherent event. This implies that theBSR does not reflect higher frequency waves and doesnot correspond to an abrupt change in acoustic imped-ance but either a gradual transition over several metersor a rough interface, or a combination of the two.

The CMP gathers of the deep-tow data can provide asignificantly higher resolution velocity analysis of thehydrate layer than conventional seismic. This is particu-larly true for the conversion to an interval velocitymodel; compared to surface seismic data the short trav-el-times for the deep-tow data make the RMS velocitiesmuch more sensitive to changes in interval velocities inthe shallow layers beneath the seabed. A disappointingfeature is that velocities cannot be picked below theBSR and so the velocity profile of the BSR cannot bedetermined.

The quality of the final sections was very variable.With the current data and processing sequence we cansay that the DTAGS data can provide valuable addition-al information under the following conditions;1. The water depth is around 1 km or greater.2. The seabed and underlying geology are not too com-

plex.3. The acquisition is controlled to give regular shot-

points with slowly varying depths and accuratelydetermined locations.

5.1. Improvements to the deep-tow system

A major weakness in the current processing is thedip-limit imposed by the large 10.5 m CMP bin size.This could be solved in any future deep-tow survey bychanging the hydrophone configuration along the cable.The 600 m length is adequate but it would be much bet-ter to have hydrophones spaced at a regular 5 m alongthe cable. This would allow 2.5 m CMP bins and muchbetter imaging where there are dips.

It would also be a huge benefit to increase the band-width and power of the source, particularly towardslower frequencies, but it is understood that this is verydifficult due to the physics of the Helmholtz source.

5.2. Ongoing studies

The deep-tow data is still being studied with focus on

the following points;1. Estimating shotpoint positioning errors using the pre-

stack near-offset channels.2. Running continuous velocity analysis to obtain an

improved interval velocity model of the shallow lay-ers.

3. Interpretation of the deep-tow data, matching to theTokai Oki 3D data and to the well logs.

Acknowledgments: We would like to express ourthanks to JNOC (Japan National Oil Corporation) forpermission to show the data.

References

Chapman, N. R., Gettrust, J. F., Walia, R., Hannay, D.,Spence, G. D., Wood, W. T. and Hyndman, R. D. (2002)High-resolution, deep-towed, multichannel seismic surveyof deep-sea gas hydrates off Western Canada. Geophysics,67, 1038–1047.

Dillon, W. P. and Paull, C. K (1983) Marine gas hydrates, IIGeophysical evidence. in Cox, J. L. (ed.) Natural GasHydrates: Properties, Occurrence and Recovery, 73–90,Butterworth.

Ecker, C., Dvorkin, J. and Amos, M. N. (2000) Estimating theamount of gas hydrate and free gas from marine seismicdata. Geophysics, 65, 565–573.

Gettrust, J. F., Ross, J. H. and Rowe, M. M. (1991) Develop-ment of a low frequency deep-tow geoacoustics system.Sea Technol., 32, 23–32.

Hato, M. and Inamori, T. (2002) Delineation of methanehydrate zone using seismic methods on Nankai Trough.Butsuri-Tansa, 55, 435–445.

Japan National Oil Corporation (2000) MITI ‘Nankai TroughWell’ Drilling Report. July, 2000.

Morita, S. and the Seismic Interpretation Team for the METIFundamental Exploration (2002) Nankai Trough: JNOC’sHigh-Resolution 2D and 3D Seismic Surveys for MethaneHydrate Exploration in the Eastern Nankai Trough. Proc.4th Intern. Conf. Gas Hydrates, Yokohama.

Rowe, M. M. and Gettrust, J. F. (1993) Fine structure ofmethane hydrate-bearing sediments on the Blake Ridge asdetermined from deep-tow multi-channel seismic data.Jour. Geophys. Research, 98, 463–473.

Shimizu, S., Hato, M., Inamori, T. and Ward, P. (2002)Seismic Survey Using the Deep Tow Data AcquisitionSystem in the Nankai Trough Area. Proc. 4th Intern. Conf.Gas Hydrates, Yokohama.

Wood, W. T. and Gettrust, J. F. (2001) Deep-tow seismic inves-tigations of methane hydrates. in Natural Gas Hydrates:Occurrence, Distribution and Detection. Geophys. Monogr.124, AGU.

Wood, W. T., Gettrust, J. F., Chapman, N. R., Spence, G. D.and Hyndman, R. D. (2002) Decreased stability ofmethane hydrates in marine sediments owing to phase-boundary roughness. Nature, 420, 656.


High Resolution, Deep-Tow Seismic Survey to Investigate the Methane Hydrate Stability Zone in the...

Documents

Transcript of High Resolution, Deep-Tow Seismic Survey to Investigate the Methane Hydrate Stability Zone in the...