Seismic Field School Report

8/12/2019 Seismic Field School Report

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July - November 2006

SeismicFieldSchoolReportRevised version February 2007

Utrecht University Netherlands

Supervisor Kabir Chowdhury

Pablo Ortega 0500941

Wijb Sommer 0217158


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Tableofcontents1 Introduction 32 Processing 5

2.1 Loading of data2.2 Geometry setup2.3 Cross-correlation

2.4 True Amplitude Recovery2.5 Bandpass

2.6 FK filter

2.7 Trace killing

2.8 Sorting2.9 Velocity analysis

2.10 Stack

2.11 Time to depth

3 Special project: GPR 213.1 GPR processing

3.2 True Amplitude Recovery3.3 Velocity analysis

4 Results and conclusions 26

4.1 Seismic results4.2 GPR results

4.3 Combining seismic and GPR

4.4 Evaluation

5 Word of gratitude 296 References 29


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1 IntroductionI n J ul y 2006 a sei smi c sur vey was car r i ed out t o i mage t he shal l owsubsur f ace of Reppel . The obj ect i ve was t o t r y to l ocat e t he f aul tsout h of t he Peel r andbl ock. The f aul t i s par t of a gr aben system whi chi s f or med by t he col l i si on of t he Eur asi an pl at e wi t h t he Af r i can pl at eon t he sout h and st r esses caused by t he spr eadi ng ri dge i n the Nort hAt l ant i c Ocean.

Figure 1: Seismic survey area. Reppel, Belgium.

I n t hi s r eport we wi l l deal mai nl y wi t h t he st eps t aken t o obt ai n t hebest pr ocessed data and descr i bi ng t he possi bl e pr obl ems encount ereddur i ng pr ocessi ng. Fi nal l y thi s pr ocessi ng r esul t s i n i nf or mat i on ont he shal l ow st r uct ur e and wi l l possi bl y gi ves an i ndi cat i on on t hepr esence of f aul t s.Measurement s were t aken by f el l ow st udent s dur i ng a 3 day f i el dt r i p. AP- wave vi br o- sei s sour ce was used (Fi gur e 2) and a st r i ng of 48geophones.

The vi bro- sei s produces a 5000 ms sweep wi t h f r equenci es goi ng l i near l yup f r om 20 to 300 Hz. The acqui si t i on was conduct ed as a push sur vey,usi ng t he f ol l owi ng geomet r y.


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Recor d Lengt h 6000 msSampl i ng Rat e 0. 5 msGeophone spaci ng 1 mNumber of channel s 48Mi ni mum sour ce- r ecei ver of f set 20 mNumber of shot s 169

Sur vey l ength 403 mGeophone t ype 10 Hz hor i zontal

Figure 2: VibroseisEver y par t i cul ar shot i s r epeat ed f our t i mes wi t h exact l y the same set -up t o i mpr ove t he si gnal t o noi se r at i o. The dat a ar e st acked i n- si t u.

As a speci al pr oj ect a GPR st udy i s conducted over t he same l i ne. Themai n goal of t hi s i s t o compar e the resul t s of bot h sur veys.

The survey i s car r i ed out as part of t he cour se Seismic Fieldschool,gi ven at Ut r echt Uni ver si t y by Dr . K. Roy Chowdhur y.


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2 ProcessingSei smi c data pr ocessi ng i s t he process by whi ch r aw uncor r el ated datai s conver t ed i nt o usef ul i nf or mat i on. The pr ocess i s a sequent i al -r ei t er at i ve one, as di f f er ent st eps ar e r eadj ust ed sever al t i mesopt i mi zi ng t he output . As we now know: gar bage i n means gar bage out .

The f ol l owi ng st ages can be i dent i f i ed:

A. - Loadi ng of r aw- uncor r el at ed sei smi c dat a.B. - Geomet r y def i ni t i on.C. - Si gnal pr ocessi ng.D. - Vel oci t y pi cki ng.E. - Ti me t o dept h conver si on.

I n t he f ol l owi ng pages t he compl ete pr ocess wi l l be descr i bed i n dept h.Al l t he processi ng done i n our dat a was done usi ng t he Landmark si nt eract i ve sei smi c pr ocessi ng syst em: Promax.

2.1Loading of dataUsi ng a si mpl e work f l ow i n Promax t he sei smi c dat a that was on di sk i sr ead i n and conver t ed t o Pr omax f ormat .

2.2Geometry SetupWe def i ned t he geometr y i n order t o cor r ect l y pl ace t he sei smi c surveypar amet er s. The par amet ers def i ned i ncl ude S- R i nt erval ( 1) S- Si nt er val ( 2) and t ot al number of l i ve st at i ons ( 404) . Speci f i c UTMcoordi nat es wer e not def i ned, i nst ead a si mpl e coordi nat e syst em was

used wer e the f i r st shot poi nt was gi ven t he 0. 0 coordi nat e, and t hef ol l owi ng sour ces and recei ver s poi nt s wer e def i ned accor di ng to t hi sf i rst coordi nat e.

Even though some sl i ght hi l l s ( hal f a meter ) wer e observed i n thesur vey ar ea, i t was deci ded t hat i t woul d not af f ect t he f i nal r esul tof t he sei smi c sur vey. Fol l owi ng t hi s concl usi on no el evat i on orst at i c cor r ect i ons wer e def i ned i n t he geomet r y.

The sur vey consi st ed of an ar r ay of 48 l i ve channel s ( shot f ol d) pershot . The f i r st CMP i s l ocat ed at 10. 0 met er s f r om t he f i r st shot poi ntand the CMP i nt er val i s gi ven by t he f ormul a:

[ ]Minimum Shot distance, Receiver distance

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so f or t hi s sur vey t he i nt er val i s 0. 5 met er s. The l ast CMP i s l ocat edat 369. 5 met er s f r om t he f i r st sour ce.

The maxi mum nomi nal f ol d can be comput ed usi ng t he f ol l owi ng f or mul a:

in-line fold =Receiver line length

2 Source line Intervalx


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For our speci f i c case t hi s r esul t s i n a maxi mum f ol d of 12 t r aces, t hi sf ol d i s r eached af t er 12 shot s ( 34 met er s f r om f i r st shot poi nt ) .

When t he geomet r y was f i nal l y appl i ed t o the sei smi c shot gather , t het wo auxi l i ar y t r aces ( t r ace 50 and 51) whi ch cont ai ned the sour ce

si gnat ur e wer e r ul e out of t he out put gat hers.

Al t hough i t may seem as a tr i vi al st ep a cor r ect geomet r y i s vi t albecause i t has a di r ect i nf l uence on t he vel oci t y pi cki ng pr ocess.

2.3Cross-CorrelationI n or der t o r esol ve t he r ef l ecti vi t i es of t he beds, i t i s necessar y t or emove t he sweep f r om t he sei smi c t r aces. Cr oss- cor r el at i on i s t hest andar d met hod t o do thi s. The sour ce si gnat ur e, whi ch i s cont ai ned i nt he t wo auxi l i ar y t r aces, i s t hen cross- cor r el at ed wi t h t he sei smi cdat a. Af t er t hi s pr ocess, t heor et i cal l y, t he t r ace wi l l onl y cont ai ni nf ormat i on t hat i s r el at ed t o t he convol ut i on of an i mpul si ve sei smi c

sour ce ( del t a sour ce) wi t h t he r ef l ect i vi t y ser i es. Fi gur e 3 shows t heef f ect of t he cross- cor r el at i on. Not e t he di f f er ence i n t i me scal es asbef ore appl yi ng the cross- cor r el at i on the i nf or mat i on about anyi ndi vi dual r ef l ect i on i s di st r i but ed over t he whol e t i me dur at i on oft he sweep.


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Figure 3: Left: uncorrelated shotgather, Right: correlated shotgather.

2.4True Amplitude RecoveryThe goal of TAR i s t o get t he data t o a st at e where t he r ef l ect orampl i t udes r el at e di r ect l y t o t he change i n rock pr oper t i es gi vi ng ri set o them. I n or der t o recover t he t r ue ampl i t ude, a cor r ect i on f orgeomet r i cal spr eadi ng i s appl i ed. A spher i cal spr eadi ng cor r ect i ng( 1/ di st ance) i s used.

To cor r ect f or absor pt i on of wave ener gy by t he medi um an i nel ast i cat t enuat i on cor r ect i on (const ant 0. 0002) i s appl i ed.Fi gur e 4 shows a r esul t i ng shot gather .


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Figure 4: CMP gather resulting from TAR.

2.5BandpassThe vi bro- sei s source f unct i on cont ai ns f r equenci es f r om 20- 300 Hz. Ascan be seen i n f i gur e 5, t he f r equency spect r um cont ai ns al so hi gherf r equenci es. These f r equenci es ar e not usef ul si gnal ; t her ef or e af i l t er i s desi gned i n or der t o r ej ect t hem ( NB al so some l owf r equenci es ar e f i l t er ed t o pr event al i asi ng) .Fi gur e 6 shows t he char act er i st i cs of t he bandpassf i l t er ( bl ack) .


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Figure 5: Left: Frequency spectrum of original data, Right: Frequency content after applying

bandpass filter.

Figure 6: Bandpassfilter black: [8-20-250-300], blue: [8-20-70-90].

2.6FK filterThe next st ep i n processi ng i s t o i mprove t he si gnal t o noi se r at i o bydesi gni ng a f i l t er i n the f r equency domai n whi ch wi l l r emove random andcoher ent noi se wi t hout di mi ni shi ng the usef ul si gnal . By doi ng aFour i er t r ansf or m of t he sei smi c t r aces i n bot h t i me and of f set , af r equency wavenumber pl ot can be gener ated. Noi se and si gnal shoul di deal l y have di f f er ent sl opes i n t hi s gr aph. I t i s t hen possi bl e t or emove noi se wi t hout l oosi ng usef ul si gnal , i mpr ovi ng t he si gnal t onoi se rat i o. We removed the gr ound rol l cone, whi ch has a l ow vel oci t y,l ow f r equency and over shadowed t he shal l ow event s i n our sei smi c dat a.I n f i gur e 7 and 8 t he ori gi nal and FK f i l t ered dat a ar e shown f or oneCMP gather . The l ef t panel shows t he t r aces and the r i ght panel showst he FK pl ot wi t h t he desi gned f i l t er pol ygon. Al l f r equenci es i nsi det he pol ygon wi l l be removed.


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Figure 7: CMP gather and FK transform.


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Figure 8: CMP gather and FK transform after FK filtering.

I n the i ntermedi ate unst acked dat a much hi gh f r equency noi se wasobserved. Theref ore another zero- phase Or msby bandpass f i l t er i s usedi n t he f r equency domai n ( bl ue l i ne i n f i gur e 6) . Fi gur e 9 shows t her esul t of t he 2e bandpass.


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Figure 9: Filtered data without 2

ndbandpass (left) and with 2

ndbandpass (right).

A t op and bot t om mut e ar e appl i ed ( f i gur e 10) t o r emove i nst r ument andf i el d noi se and to r emove t he deep st r uct ur e whi ch has a l ow si gnal t onoi se r at i o. Thi s way t he pr ocessi ng t i me i n l at er st eps wi l l ber educed.


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Figure 10: Data with top/ bottom mute.

2.7 Trace killing

Af t er scanni ng the sei smi c gather s, i t was not i ced t hat some t r aces hadan out of t he nor m behavi or . A t r ace ki l l i ng f l ow was done i n or der t or emove them, el i mi nat i ng then t he possi bl e ef f ect t hey mi ght have hadon the st ack.As can be see i n t he f i gur e 11, t r ace number 39 has a compl etedi f f er ent behavi or t han the nei ghbori ng t r aces. Thi s i s a commonbehavi or i n al l gat her , so t hi s t r ace was ki l l ed f or al l of t hem. Someother t r aces t hat had anomal ous f r equency cont ent and a t i me shi f t werehand pi cked and r emoved f r om t he gat her s.


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Figure 11: shotgather with killed traces.

2.8SortingI n t hi s s t ep Common mi d poi nt ( CMP) gat her s were generated. CMP sor t i ngi s t he pr ocess by whi ch t r aces t hat cor r espond t o the same ref l ect i onpoi nt i n t he subsur f ace ar e sequent i al l y pl aced f r om smal l t o l ar gersour ce r ecei ver of f set . Thi s was done as a basi c pr e- st ep pr i or t ost ack vel oci t y anal ysi s. The sor t i ng was done usi ng t he CDP bi n numberand t he si gned sour ce- r ecei ver of f set .

2.9Velocity analysisThe mai n goal of al l processi ng i s t o i ncr ease t he si gnal t o noi ser at i o. Vel oci t i es are pi cked i n common mi dpoi nt gat her s t o cor r ect f ora geometr i cal ef f ect known as nor mal moveout . The vel oci t y t hat r esul t si n the best l i ne- up of sei smi c event s t hat corr espond to t he samer ef l ect i on i s assi gned t o a par t i cul ar t i me. Thi s pr ocess i s r epeat edf or ever y 11t h CDP. I n t hi s way a 2D vel oci t y model i s bui l t . To pi ckt he vel oci t i es we used an envi r onment as shown i n f i gur e 12. I n t hef i gur e 5 ar eas can be seen. From l ef t t o ri ght we have: vel oci t yspr ect r um, CMP gat her , dynami c st ack, f l i pped stack, st acks wi t h an


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appl i ed i ncr easi ng NMO vel oci t y cor r ect i on. I n t he l ast panel t hepi cked vel oci t y f unct i on i n t i me can be seen i n red. The met hodol ogyf ol l owed was t o choose t he vel oci t y whi ch produced t he best CMP gatherwi t hout r ecur r i ng t o st eep vel oci t y changes i n t i me.

The NMO cor r ect i on hyper bol a i s gi ven by:

,wher e t i s t he t r avel t i me at of f set h, t 0 i s t he zer o- of f set ( nor mali nci dence) t r avel t i me and VNMO i s t he normal moveout vel oci t y (Di x,1955) .Because of NMO corr ect i ons, t he f ar er t he of f set t he more t he t r ace i sst r etched. Thi s i s known as NMO st r etch. Thi s changes t he wavef orm andf r equency cont ent t hus decr easi ng t he st ack ef f i ci ency. To r emove t hi sef f ect a maxi mum per cent age of st r et ch i s al l owed. I n our speci f i c casef or a st r et ch l ar ger t han 45%, t he dat a i s mut ed.

Figure 12: Screenshot of the velocity picking environment.The r esul t i ng vel oci t y model f or t he compl et e sei smi c sect i on i s shownbel ow i n f i gur e 13.


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Figure 13: RMS velocity model.

2.10 StackSt acki ng i s t he pr ocess by whi ch sei smi c t r aces t hat corr espond to thesame CMP t hat have been NMO cor r ect ed are summed up. Thi s great l yi mpr oves t he si gnal t o noi se r at i o (t hi s r at i o i s pr opor t i onal t o t hesquar e root of t he f ol d) and reduces ( 1/ f ol d) t he dat a vol ume.Fi gur e 14 shows t he NMO cor r ect i on gr aphi cal l y and the ef f ect ofst acki ng. Event s t hat not have a hyper bol i c moveout ( r andom noi se) wi l lnot l i ne up af t er cor r ect i on and t heref ore have l ow ampl i t ude i n t hest acked sect i on.


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Figure 14: Schematic representation of applying the NMO correction and stack.

A st ack sect i on was gener at ed f i r st usi ng a l i near vel oci t y model .Another st ack ( f i gur e 15) was gener at ed usi ng t he vel oci t i es pi cked i nt he vel oci t y anal ysi s.

Compar i ng t hese t wo sect i ons i s used as a QC f or t he pi cki ng. The RMSvel oci t i es ar e r e- pi cked sever al t i mes unt i l a consi st ent st ack i spr oduced. A consi st ent st ack has l at er al cont i nui t y and deeper event sar e easi er t o obser ve.

Ther e wer e al so er r oneous pi cks ( i . e. same r ef l ect i on pi cked wi t h t wodi f f er ent vel oci t i es i n the same gat her ) t hat wer e obser ved dur i ng theQual i t y cont r ol of t he vel oci t y model .


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Figure 15: Stacked section with picked velocity model.

2.11 Time to depthThe st ack sect i on i s st i l l i n t he t i me domai n. Wi t h our vel oci t y modelwe can conver t t hi s t o dept h.

To make sure we have r eal i st i c vel oci t i es f or t hi s conversi on, f i r st asmoothi ng f i l t er i s appl i ed t o t he RMS vel oci t i es. Thi s 1) i mpr oves

consi st ency and 2) r educes pi cki ng noi se. Fi gur e 16 shows t he smoot hedvel oci t y model .


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Figure 16: Smoothed velocity model. Red square corresponds to the subcrop shown in Figure 25.

From t hese smoot hed RMS vel oci t i es, i nt er val vel oci t i es are der i vedusi ng a 50 ms ver t i cal i nt er val . An unsmoot hed ver si on of t he i nt er valvel oci t y model i s shown i n f i gur e 17. For t he dept h conver si on we useda smoot hed ver si on of t he model shown i n f i gur e 17.


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Figure 17: Unsmoothed interval velocity model.

Figure 18 shows a plot of our final depth converted stacked section.

Figure 18: Depth converted stacked section. Red square corresponds to the subcrop

shown in Figure 26.


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3 Specialproject:GPRAs a speci al pr oj ect f or t hi s cour se GPR dat a taken on the same l i neare processed and compared wi t h t he sei smi c r ef l ect i on data. The GPRdata was acqui r ed i n t wo di f f erent f r equency ranges, one hi gh f r equency( 100 MHz) and one wi t h l ower f r equency ( 50 MHz) . The 100 MHz dat a has

0. 5 m r ecei ver di st ance, whi l e t he 50 MHz dat a has 1 m spaci ng. Ther ei s a t r ade out bet ween f r equency and penetr at i on dept h. For hi ghf r equenci es t her e i s a hi gher ver t i cal and hori zont al accur acy, butl ess penetr at i on dept h ( because of di sper si ve at t enuat i on) . GPRsect i ons can be t r eated as zero- of f set st acked dat a. Thi s makespr ocessi ng l ess extensi ve.

3.1GPR processingThe processi ng of t he data i s di vi ded i n t he f ol l owi ng st eps: 1)l oadi ng of t he dat a, 2) vel oci t y anal ysi s and 3) dept h conver si on.

The l oadi ng of t he data i ni t i al l y gave r i se t o di f f er ent probl ems. Thi swas due t o a f ormat conver si on pr obl em of t he ori gi nal dat aset . Oncet hi s was cor r ect ed f or t he raw dat a was l oaded usi ng t he acqui si t i onpar amet er s st at ed ear l i er .On thi s case i t was not necessar y t o def i ne t he geomet r y by t he use ofl i br ar i es. A si mpl e r emappi ng of t he header val ues was suf f i ci ent . Event hough thi s i s a si mpl e pr ocedur e, i t i s i mport ant when compar i ng thedat a wi t h t he sei smi c dat a f r om t he pr evi ous sect i on. Speci f i cal l y wedef i ned CDP- X, CDP- Y coor di nates, of f set t o be zero and CDP number.

These headers were needed t o be abl e t o use t he pi cki ng vel oci t y t oolwi t hi n Pr oMax.

The r aw dat a i s pl ot t ed i n f i gur es 19 and 20.

Figure 19: raw GPR data 50 MHz.


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Figure 20: raw GPR data 100 MHz.

3.2True Amplitude RecoveryTo cor r ect f or geomet r i cal spr eadi ng and at t enuat i on we appl i ed a t r ueampl i t ude r ecover y si mi l ar t o t he TAR appl i ed t o t he sei smi c data. I nf i gure 21 and 22 ( f or 50 MHz, 100 MHz r espect i vel y) i t can be seen,

t hat t hi s pr ocedur e i mpr oves t he vi si bi l i t y of t he r ef l ecti onss i gni f i cant l y.


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Figure 21: GPR data 50 MHz with TAR applied.

Figure 22: GPR data 100 MHz with TAR applied.


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3.3Velocity analysis

GPR uses ref l ect i on of el ect r omagnet i c waves. Ref l ect i ons are generat edby a change i n di el ect r i c const ant of a medi um. To do a t i me t o dept hconver si on a vel oci t y model i s needed ( anal ogous t o t he sei smi c

vel oci t y model ) . The vel oci t y of el ect r omagnet i c waves i n a medi umdepends al so on the di el ect r i c const ant of t hat medi um as:

'

cv

K

=

wher e c i s t he speed of el ect r omagnet i c waves i n vacuum ( 2. 99792458 108m/ s) , and K` i s t he r eal par t of t he di el ect r i c const ant .We assume t he di el ect r i c const ant t o have an average val ue i n oursur vey and equal t o the one of gl ass. Thi s r esul t s i n a speed of 200m/ ns. We al so deri ved t he vel oci t y by anal yzi ng a r ef l ect i on hyper bol af rom t he dat a usi ng t he vel oci t y pi cki ng t ool f rom ProMax. Thi sr esul t ed i n a vel oci t y of about 210 m/ ns. Because t he GPR surveypenetr at es onl y the shal l ow subsurf ace ( about 50 m) , no si gni f i cantchange i n ver t i cal vel oci t y i s expect ed.

For t he dept h conver si on a const ant vel oci t y of 200 m/ ns i s used. Ther esul t i ng zer o- of f set GPR sect i on i s shown i n f i gur e 23 and 24. Not et hat Fi gur es 19, 20, 21 and 23 i s f l i pped, because of t he way i t wasacqui r ed i n t he f i el d, so i n or der t o compar e i t shoul d f i r st bemi r r or ed.

Figure 23: Depth converted GPR data 50 MHz (with TAR).


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Figure 24: Depth converted GPR data 100 MHz (with TAR).


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4 ResultsandConclusionsThe goal of t hi s proj ect was t wo- f ol d. The mai n goal was t o get handson exper i ence on sei smi c pr ocessi ng. As a speci al pr oj ect sei smi c dat ai s compar ed wi t h GPR dat a, t o i nvest i gat e whet her t he t wo compl ement oneach other and r ef l ect t he same geol ogi c st r uct ur e. Thi s i s done byi nvest i gat i ng the pr esence and l ocat i on of a f aul t as i t was expect edi n t he ar ea of t hi s st udy.

4.1Seismic resultsVel oci t i es can be used as a pr el i mi nar y at t r i but e f or some st r uct ur aldef i ni t i on. The pr esence of a f aul t i n an ar ea coul d cause a r api dl at er al change i n vel oci t i es. By anal yzi ng our vel oci t y model ( f i gur e15) an area wi t h l at eral change can be spot t ed bet ween CDP 120 and 270t o a dept h of 250 ms. Lat er al change i s al so observed i n ot her par t s of

t he vel oci t y model ( i . e. i n the deeper part s ( 600 ms) under CDP 100) .But we concent r at e on t he shal l ow par t , f or l at er t hi s wi l l be ti edwi t h (shal l ow) GPR dat a. I n Fi gur e 25 a subset showi ng thi s ef f ect i spl ot t ed.

Figure 25: Subset of Smoothed velocity model. CDP vs. time [ms].

I f t hi s behavi or t r ul y cor r esponds t o a geol ogi cal st r uctur e, i t shoul dmani f est i n our f i nal dept h st ack.

The f i nal sei smi c st ack i n dept h shows good cont i nui t y of some sei smi cevent s. The si gnal t o noi se rat i o was gr eat l y i mpr oved by the sei smi cpr ocessi ng, as ref l ector ar e now more evi dent and cont i nuous. Thever t i cal sei smi c r esol ut i on at gr eat er dept hs ( l ar ger t han ~80 m. )l i mi t s t he range wher e compet ent sei smi c r ef l ect i ons can bei nt erpret ed. As was shown i n our vel oci t y model , t her e exi st s t hepossi bi l i t y of t he pr esence of a f aul t i n t he ar ea. By anal yzi ng oursei smi c sect i on i n can be seen that i n the same ar ea as i n t he vel oci t ymodel , a f aul t l i ke behavi or can be observed i n t he sei smi c data.Fi gur e 26 shows t hat t he coher ent pack of sei smi c r ef l ect ors t er mi nat esat what coul d possi bl y be a f aul t . Al so i n r ed a l i kel y i nt er pr et at i onof t he f aul t i s shown. The endi ng of t he possi bl e f aul t i s not cl ear as


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t her e i s a decr ease i n r esol ut i on wi t h dept h t hat does not al l owper f or mi ng a good i nt er pr et at i on.

Figure 26: Subcrop of the depth stack. In red fault interpretation.I t can be seen i n f i gur e 18 t hat t he t op 10 meter s of t he sect i on ar emut ed. Thi s i s because t hi s ar ea has r eal l y l ow si gnal t o noi se r at i odue t o t he presence of gui ded waves.

4.2GPR resultsAs expect ed t he two (50/ 100 MHz) sect i ons have a di f f er ent ver t i calr esol ut i on. Thi s i s shown cl ear l y be obser ved i n f i gur e 27. The sei smi cl ayer i ng i n t he 100 MHz dat a i s much t hi nner al t hough t hey show t hesame st r uct ur al pat t er n.

The 50 MHz data was expect ed t o have a great er expl or at or y dept h.However compar i ng f i gur e 23 and 24 does not show t hi s behavi or . On t he50 MHz dat a, some si gnal i s obser ved bel ow 16 m, but i t i s merel ynoi se, whi ch cannot cor r espond to a r eal st r uct ur e.

Figure 27: Comparison of two subsets of GPR data. Left 50 MHz, Right 100 MHz.


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4.3Combining seismic and GPRI n t hi s sect i on a compar i son i s made bet ween sei smi c and GPR dat a.I deal l y t hi s woul d i nvol ve over l appi ng bot h f i nal sect i ons andcompar i ng. Never t hel ess t hi s won t be possi bl e because both sect i onshave di f f erent dept h r anges so onl y smal l overl ap occur s. The GPR data

r anges f r om6 t o 14 m dept h whi l e the sei smi c dat a st ar t s at 10 m.A f i gur e i s made showi ng t he GPR data pl ot t ed above t he sei smi c dat a.I t shoul d be noted t hat GPR and sei smi c data are by natur e sensi t i ve t odi f f er ent physi cal pr oper t i es. Speci f i cal l y GPR r ef l ect i ons ar e causedby changes i n di el ect r i c const ant whi l e sei smi c ref l ect i ons r eact onchangi ng i mpedance ( vel oci t y t i mes densi t y) . Because f aul t i ng of f set st he medi um a j ump i n r ef l ect i ons i s expect ed both i n GPR as sei smi cdat a. For compar i son we use t he 50 MHz GPR dat a f or i t has compar abl ewavel ength as t he domi nant sei smi c dat a.Fi gur e 28 shows GPR dat a super posed to t he sei smi c dat a.

Figure 28: Overlap of Seismic stack in time with 50 MHz GPR stackCont i nui t y can be observed between both st acks, i . e. under t he CMP 140i t i s easy t o f ol l ow t he ant i cl i ne goi ng f r om t he t op GPR sect i on i nt ot he sei smi c dat a. I t i s i mpor t ant t o poi nt out t hat ef f ect of t hepossi bl e f aul t i s al so obser ved i n t he GPR dat a i n a si mi l ar l ocat i onas can be seen i n Fi gur e 27.

4.4EvaluationDoi ng t hi s st udy gave us a r eal l y good grasp on how t o conduct asei smi c study, f r om acqui r i ng dat a i n t he f i el d t o pr ocessi ng andpr oduci ng a f i nal sect i on i n dept h. Our f el l ow cl assmat es Gi j s and

J el l e wor ked paral l el on t he same data set . I t woul d be i nt er est i ng t ocompar e bot h resul t s. Dur i ng process i ng some cr ude compar i son was done.Al t hough not compl et el y di f f er ent , i nt er est i ng di f f er ences wer eobserved. Thi s i s not unexpect ed, as sei smi c pr ocessi ng i s a subj ect i vepr ocedur e.


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5 Wordofgratitude

We woul d l i ke t o t hank Henk van den Meer , Kabi r Roy Chowdhury andSt ef an Car pent i er f or t hei r t i me and suppor t .

6 ReferencesPi ct ur e NMO- corr ect i on3D Sei smi c Sur vey Desi gn, C. Pet er Ashton et al . , Apr i l 1994

Expl orat i on Sei smol ogy, Sher i f f and Gel dar t , Cambr i dge Uni ver si t yPress, 1995

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Schl umber ger gl ossar y oi l f i el dht t p: / / www. gl ossary. oi l f i el d. sl b. com/

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