Removing seafloor multiple using predictive deconvolution and NMO correction

Noppadol Poomvises Geologist 6

Seismic suffering from undesirable noises.

Ghost A short-path seismic pulse leaving s

ource in upward direction, following and arriving at receivers closely with primary (P) signal.

Superimposition to primary and broadening seismic waveform.

Seafloor multiple Seismic energy trapped between two strong

interfaces of high reflection coefficient (R). Periodicity interval equals to 2-way travel ti

me. Effect as wave-train reverberation in seismic

stacked section.

10 mR = -1

Air

Water

0.013 s

Air

Water

SeafloorWater

SB =Primary reflection from seafloor

M1=Twice-bounced multiple

M2=Three-bounced multiple

R

-R2

-R4

R3

0

R=-1

R

P

M1

M2

M3

(a) Seafloor multiple model (modified from Russel, 1993).

(b) Ghost model (modified from Jadell, 1987).

Objectives of the study

1 To evaluate the ability of multiple attenuation, both in modeled and real data, using conventional predictive deconvolution (PDC) in common shot domain using Focus/Disco 4.1, the in-house processing software

2 To examine the multiple removing technique by applying the periodicity enhancement and PDC in the common shot domain, using the same software.

3 To compare the quality of processed data using the methods in 1 with those obtained from 2 to demonstrate whether significant improvement is achieved by the proposed technique.

Data collection Modeled data

Generating modeled data on a two-layered and a three-layered models using a Forward modeling technique.

Using Osiris modeling s/w, Odegaard & Danneskoild-Samsoe, Denmark.

Running on a Unix-based computer, Sun Sparc 20, 128 MB RAM, and 20 GB hard disk.

Real data Two real seismic data sets acquired on shallow seafloor of two

different areas and times. The Ist set contains fair degree of multiples while the 2nd set shows

stronger degree of multiples.

Concept of the removing technique.

Filter

t

NMO

Primary Multiple Sf = Reflection from seafloor

Msf = Seafloor multiples

Deconvolution DNMO

Sf

Msf

Msf

Msf

Msf

Figure 1 Concept of new technique proposed in this research. First step, all curvatures are moved up by NMO correction using the velocity of multiple, Second step filtered by predictive deconvolution, and last step moved down by DNMO correction using the same velocity function.

Sf

Sf

Sf

Data processing works.

Generating modeled data.Verifying the data.Processing modeled data.Processing real data.

Generating modeled data.

Source

Receiver arrayWater layer

Sea bottom50

Distance (m)

Water surface

Dep

th (

m)

0 10 600

Vw = 1,500 m/s, Dw = 1.0 kg/m3

Vsb = 2,000 m/s, Dsb = 2.0 kg/m3

10

(b) A two-layer modeled shot simulated by Osiris application

UD

SBSBG1SBG2

M1M1G1M1G2

M2M2G1M2G2

M3M3G1M3G2

RfrRfrG1RfrG2Rfr2Rfr2G1Rfr2G2

Figure 2-7 Two-layer modeled shot overlaid by calculated shot.U=upging wave, D=direct wave, SB=Sea bottom, G=ghost, M=multipl in order,and Rfr=refracted wave.

Source Receiver array

Layer 1

100

Distance (m)Water surface0 10 600

V1 = 1,441 m/s, D = 1.0 kg/m3

V2 = 1,800 m/s, D = 1.5 kg/m3

10

400

V3 = 5,250 m/s, D = 2.6 kg/m3

Layer 2

Layer 3

UD

SBSBG1SBG2

M1M1G1M1G2

M2M2G1M2G2

M3M3G1M3G2

RfrRfrG1RfrG2

Tim

e (s)

Offset (meter)

Figure 2-11 Three-layer modeled shot overlaid by its calculated shot.U = upgoing wave, D = direct wave, SB = primary of sea bottom,G = ghost, M = sea bottom multipl in order, and Rfr = refracted wave.

Two-w

ay time (m

s)

1. Introducing earth models and parameters to the S/W.2. Simulating the models.3. Receiving model shots.

(a) Direct wave, D

(c) Primary from seabottom, SB

(b) Upgoing wave, U

(d) Primary with a ghost, SBG1 (e) Primary with source and receiver ghost, SBG2

(h) Two-bounced multiple with souce and receiver ghost, M1G2

(g) Two-bounced multiple with a ghost, M1G1

(f) Two-bounced multiple, M1

(i) Three-bounced multiple, M2(j) Three-bounced multiple with a ghost,

M2G1(k) Three-bounce multiple with source and receiver ghost,

M2G2

(l) Four-bounced multiple, M3 (m) Four-bounced multiple with a ghost, M3G1 (n) Four-bounced multiple with source and receiver ghost, M3G2

(o) Refracted wave, Rfr

48o

(p) Refracted wave with a ghost, RfrG1

48o

(q) Refracted wave with source and receiver ghost, RfrG2

48o

(r) Two-bounced Refracted multiple, RfrM1

48o

(s) Two-bounced Refracted multiple with a ghost,

RfrM1G1

48o

(c) Possibilities of seismic events predicted from the two-layer input model.

Source Receiver array

Water layer

Sea bottom50

Distance (m)

Water surface

Dep

th (

m)

0 10 600

Vw = 1,500 m/s, Dw = 1.0 kg/m3

Vsb = 2,000 m/s, Dsb = 2.0 kg/m3

10

(a) A two-layer model for numerical computation

(a) Simulated shot.

UD

SBSBG1SBG2

M1M1G1M1G2

M2M2G1M2G2

M3M3G1M3G2

(b) Calculated shot

Offset (m)

300

400

500

600

200

100

0

Time (ms)

10 200 400 600

RfrRfrG1RfrG2Rfr2Rfr2G1Rfr2G2

Offset (m)

(d) A calculated shot computed from the two-layer input model.

(a) A two-layer model for numerical computation

Generating the modeled and calculated shots

Both contains primary and multiple events. Well agreement between the simulated and predicted seismic events.

UD

SBSBG1SBG2

M1M1G1M1G2

M2M2G1M2G2

M3M3G1M3G2

RfrRfrG1RfrG2Rfr2Rfr2G1Rfr2G2

Data verification by comparison between the modeled and calculated shot of the two-layer case.

UD

SBSBG1SBG2

M1M1G1M1G2

M2M2G1M2G2

M3M3G1M3G2

RfrRfrG1RfrG2

Tim

e (s)

Offset (meter)

Figure 2-11 Three-layer modeled shot overlaid by its calculated shot.U = upgoing wave, D = direct wave, SB = primary of sea bottom,G = ghost, M = sea bottom multipl in order, and Rfr = refracted wave.

Both contains primary and multiple events. Well agreement between the simulated and predicted seismic events.

Data verification by comparison between the modeled and calculated shot of the three-layer case.

Flow processing sequencesof modeled data in three cases.

(1) Raw shot with no

deconvolution

(3) Conventional

PDC

(4) Periodic

Enhancement before

PDC

Remarks

Input Input Input Modeled shot

Trace Editing Trace Editing Trace Editing Killing first 3 near traces.

Filtering Filtering Filtering Desired output minimum phase.

NMO V=1,500 m/s for two-layer and 1,441

m/s for three-layers data.

Front-end mute Front-end mute Front-end mute Under first-break zone

PDC 24 ms n = 164 ms, = 0.1 %,

G = 1,000 ms.

DNMO V=1,500 m/s for two-layer and 1,441

m/s for three-layers data.

Output Output Output

PDC

(2) (3)

(a) No deconvolution. (b) Conventional predictive deconvolution.

(c) Periodicity enhancement and predictive deconvolution.

Figure 4 Processing result of two-layer model shots in three different cases with their autocorrelation(middle), and semblance analysis (lower).

(a) No PDC (b) Conventional PDC (c) Periodicity before PDC

Processing results of two-layer modeled data

Changes

Figure 5 Processing result of three-layer model shots in three cases with their autocorrelation(middle), and semblance analysis (lower).

(a) No PDC (b) Conventional PDC (c) Periodicity before PDC

Processing results of three-layer modeled data

Changes

Processing sequence of real data and parameters used.

(The numbers in embraces are of the data set 2)

StartGeometry setting

EditingFiltering High pass 6/18 ,

Desired output minimum phaseGain Recovery 2 Db/sec to 4 sec,

Spherical Divergence (V2T)Front-End Mute

NMO Corrected velocity of 1,500 m/s

Predictive Deconvolution Gap length 18 (12) ms,Operator length 164 (138) ms,Prewhitening 0.1 %,Design Autocorrelation Gate Near trace 120 - 3,500 (180 - 3,000) ms,

far trace 2,300 - 3,500 (1,800 - 4,000) ms.

DNMO Corrected velocity of 1,500 m/sBandpass filtering 6/18 – 120/72

Sorting CDP and OffsetVelocity Analysis Picking every 0.5 km .

NMO Using the picked velocityPost NMO Mute

Stacking Nominal fold 60 (40)Stop

Processing resultsof 2-D seismic dataset 1

Figure 6 Processing result in a shot record of real data set 1 in three different cases (above)with their semblance analysis(below).

No PDC Conventional PDC Periodicity before PDCChanges

Figure 7 Normal stacked (NSTK) section of data set 1 with no predictive deconvolution (left) and its corresponding autocorrelation (right)

The numbers labeled are used to with other cases.

Normal stacked (NSTK) section with NO predictive deconvolution(PDC)

of data set 1.

Figure 8 Normal stacked (NSTK) section of data set 1 with conventional predictive deconvolution (left)and its corresponding autocorrelation (right).

NSTK section with conventional PDC

of data set 1.

Figure 9 Normal stacked (NSTK) section of data set 1 with periodicity before predictive deconvolution (left)and its corresponding autocorrelation (right).

NSTK section with periodicity enhancement and PDC of dat

a set 1.

NSTK of data set 1 in three cases

NSTK with N O PDC

NSTK with pe riodicity enh

ancement an d PDC

NSTK with conv. PDC

Autocorrelations of real data set 1in three cases.

NSTK with No PDC NSTK with PDC NSTK with periodicity enhancement and PDC

Processing results of 2-D seismic da

ta set 2

No PDC Conventional PDC Periodicity before PDC

Changes

Normal stacked (NSTK) section with NO predictive deconvolution(PDC) of da

ta set 2.

Figure 11 Normal stacked (NSTK) section of data set 2 with no predictive deconvolution (left) and its corresponding autocorrelation (right). The numbers labeled are used to compared with other cases.

NSTK section with conventional PDC of data set 2.

Figure 12 Normal stacked (NSTK) section of data set 2 with conventional predictive deconvolution (left) and its corresponding autocorrelation (right).

Figure 13 Normal stacked (NSTK) section of data set 2 with periodicity before predictive deconvolution (left) and its corresponding autocorrelation (right).

NSTK section with periodicity enhancement and PDC of dat

a set 2.

NSTK of data set 2 in three cases

NSTK with N O PDC

NSTK with conv. PDCNSTK with pe riodicity enh

ancement an d PDC

Autocorrelation of data set 2in three cases.

NSTK with PDC NSTK with periodicity enhancement and PDC

NSTK with NO PDC

Conclusions1. Conventional PDC in common shot domain can suppress some

amount of seafloor multiples from seismic data, especially at near offset range.

2. Periodicity enhancement and PDC can remove much amount of seafloor multiples from both data, especially at middle- and far-offset range.

3. The new technique can comparatively removes the seafloor multiples from seismic data much amount than that of the conventional technique.

4. Performance of the new technique relatively gives better improvement of the quality, and enhances resolution of stacked section than of the conventional method as well.

Recommendations

The package of NMO/PDC/DNMO consumes only a few CPU time than of the conventional one, therefore it is attractive to apply the method in an actual data processing work.

For better development of seafloor multiple removing technique, it is of interested to further study the effectiveness of this method in future by compiling the package in common shot domain with other existing removing techniques.

Acknowledgements.

PTTEP public Co., Ltd. Providing an excellence

chance. Supporting hardware, sof

tware, and valuable seismic data used.

CMU The place I really love an

d memorize. The place that giving so

many things more than education.

Dr.Chalermkiet Tongtaow Dr.Banjob Yodsombat Dr.Pisanu Wongpornchai Dr.Somchai Sri-israporn Mr.Montri Rawanchaikul Mr.Booncherd Kongwang For their advise, guidance

, and unwavering standing by me during my time of researching.

Million thanks !

For the good time on the Loy Krathong festival !

!