1

Dip Filtering

Overview

• It is frequently useful to remove steeply dipping events from

seismic data.

• This can be done using trace-mixing (i.e. averaging adjacent

traces).

• The effectiveness of the filtering can be controlled by adjusting

the weighting of traces in the mix and/or the number of traces

averaged.

• Best trace-mix is judged visually.

• Better, but more expensive, dip filtering can be done using a

frequency domain approach (fk filtering)

2

3

Dip Filtering - Synthetic

Example

Before Filtering After Filtering

4

Dip Filtering

- Real Data

Example

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time

(s)

0 0

.05

0.1

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tim

e (s

)

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Trace Mixing

0 ms/trace &

10 ms/trace events

1:1:1 Trace mix

10 ms/trace event

attenuated

0.1 s

0.2 s

0.3 s

0.0 s

Enlarged

areas in

next 2 slides

6

Trace Mixing Detail (See Next

Slide)

• Each output cell on right hand panel

contains average of three adjacent cells

from left hand panel.

• Highlighted cells show high amplitude

events.

• Note that trace mixing has preserved

horizontal event but attenuated dipping

event.

7

Trace Mixing Detail

Unfiltered 1:1:1 Trace Mix

Tim

e

Trace 0.00445432 0.03283108 0.0119643 0.02085961

-0.18760995 -0.19891523 -0.208489 -0.19133988

-0.04988526 -0.09047286 -0.0648111 -0.07389957

0.48495042 0.50119696 0.51532741 0.49373048

0.93039594 1.00097501 0.96651243 0.97618398

0.84474202 0.8068696 0.78494081 0.81331757

0.40447664 0.13993176 0.19537655 0.18407127

0.12921171 -0.22134325 -0.18019304 -0.22078064

0.19980474 0.02721792 -0.12354398 -0.10729745

0.34819709 0.40218534 0.06148628 0.13206535

0.34506448 0.41148528 0.12364785 0.08577543

0.26528419 0.19886339 0.15466824 -0.10987665

0.22868365 0.1746954 0.26688555 -0.0836694

0.17570828 0.34829511 0.34829511 0.17570828

0.03968815 0.3902431 0.29805295 0.3520412

-0.07234255 0.19220234 0.23639749 0.30281829

-0.04423972 -0.0063673 0.28147013 0.21504933

0.04364099 -0.02693809 0.31376097 0.25977272

0.04251409 0.02626756 0.17702946 0.34961628

0.08997784 -0.03151028 0.04197542 0.02451832

-0.21050505 -0.23014901 -0.15514516 -0.2417893

-0.16458458 -0.01586981 -0.09322489 -0.08447757

0.50455115 0.54909826 0.44848991 0.55041944

1.1025449 0.91055006 0.99257023 0.99562738

0.81959905 0.73279026 0.87046433 0.74897621

-0.0178747 0.26150449 0.17248146 0.1528375

-0.2769012 -0.09603344 -0.29489236 -0.14617758

0.4006079 -0.20788651 -0.10394325 -0.05939615

1.08405175 -0.09603344 0.23363524 0.0416404

0.87899136 0.26150449 0.09850487 0.01169609

0.1153034 0.73279026 -0.26768311 0.01169609

-0.26953513 0.91055006 -0.13922735 0.0416404

-0.05939615 0.54909826 0.54909826 -0.05939615

0.16499795 -0.01586981 1.03390761 -0.14617758

0.04923019 -0.23014901 0.77032436 0.1528375

-0.11831906 -0.03151028 0.13148934 0.74897621

-0.04678396 0.14521088 -0.18445781 0.99562738

0.0904154 0.04586829 -0.05807497 0.55041944

average

8

Trace Mixing Weights

• A 1:1:1 mix implies simple 3 trace averaging.

• Other weights are possible. For example, 1:2:1 implies (left +

2xcentre + right)/4. This is weighted towards the centre and so

is less extreme in its effects.

• More than 3 adjacent traces can be mixed. E.g. 1:2:3:2:1 would

be a 5-trace mix.

• Usual approach is to try a number of different mixes and then

visually choose best.

9

Trace Mix Tests (Real Data)

Raw 1:6:1

10

Trace Mix Tests (Real Data)

1:3:1 1:1:1

FK filtering

• FK filtering is a frequency-based method for

filtering dips.

• It is much more expensive than trace mixing

but is more precise in its effects (e.g. a

specified range of dips can be surgically

removed).

11

FK filtering

• An FK transform is simply a 2-dimensional

Fourier Transform (explained on next slide).

• Once transformed, signals with different dips

appear in different parts of the transformed

amplitude spectrum.

• Hence, multiplying by a window removes

specific dips (cf frequency filtering in which a

window removes specific frequencies).

12

13

FK Transforms & Dip Filters

a

xt

xt domain

FourierTransformall columns

xf

fx domain

FourierTransformall rows

kf

fk domain

xt

xt domain

InverseFK transform

Pass region

Reject Reject

14

Quick Test

• Go back to the trace mixing

example. Which would you

choose and why?

1:3:1 1:1:1

Raw 1:6:1

15

Quick Test Answer

• Problem here is steeply

dipping noise shown on the

raw section.

• This is obscuring strong sub-

horizontal reflections.

• There is no “correct” answer in

this case as it is a question of

judgement but I like the 1:1:1

mix.

1:3:1 1:1:1

Raw 1:6:1