2


S. L.
This flashcard set delves into advanced seismic data processing techniques at the university level, focusing on noise suppression, velocity analysis, and amplitude recovery. It covers key concepts like predictive deconvolution, radon filtering, and various noise classifications, including ground roll, air blast, and cultural noise. The flashcards are particularly useful for geophysics students and professionals aiming to enhance their understanding of seismic data interpretation and processing methods.
Cartes-fiches
43
Utilisateurs
1
Langue
Anglais
Catégorie
Histoire naturelle
Niveau
Université
Créé / Mis à jour
08.01.2013 / 09.01.2013

Cartes-fiches

4 noise classifications

ramdom or coherant

source generated or ambient

removing taces from seismic data is called

muting

types of muting

refraction mute (at top)/top mute

noise cone mute (cone at bottom)

surgical mute (removal of specific area eg. ground roll)

AGC

automatic gain control

balances amplitudes down a trace (or 'window'-part of a trace)

opposite of the Fourier domain

Amplitude plotted against time

(normal)

Fourier domain

Fourier=Frequency

Amplitude plotted against frequency

why are pre processing algorithms applied?

to prepare data for velocity analysis

supress noise, boost signal

what does 'main processing' acheive?

velocity analysis

what does post processing achieve

migration 

(focuses the image)

air blast noise classification

coherent

330m/s

high frequency

weather noise classification

random

ground roll noise classification

coherent

slow

low frequency

cultural noise classification

random or coherent

multiples noise classification

coherent

5 examples of land noise

airblast

ground-roll

weather

cultural

multiples

6 examples of marine noise

multiples

swell

propellor

bubble pules

ocean bottom cables

drilling platforms

different noise classifications

random or coherent

source generated or ambient

type of noise?

bubble pulse

what is amplitude recovery

like adding gain to allow for energy spreading

why is amplitude recovery necessary?

because amplitude decays at 1/r

processes:

geometrical spreading (spherical divergence)
attenuation

how does energy spread in the ground

non-linearly, as velocity encreases with depth

typical things removed by frequency filtering

air blast (high freq)

ground roll (low freq)

swell

prop noise

what is a bandpass

a combined high and low pass filter

what is the f-k filter generally

a development of the frequency filter

f-k means?

frequency wavenumber

wavenumber?

k, reciprocal of wavelength

wavenumber of fast velocity v.s slow velocity

fast velocity wavenumber close to zero

slow velocity has positive or negative wavenumber

f-k spectrum

.

problem with f-k filter

spatial aliasing

worminess

introduction of cherent events

spatial aliasing is

making one event look like another

worminess is

filtered data looks striped

deconvolution simple explanation

 

if we know the waveform that was put into the ground, we can filter that waveform and simplify the data

DBS

Deconvolution before stack

what does DBS do

supresses short path multiples

short path multiple

energy which reflects between thin beds

how does predictive deconvoltion work

looks for wavelets that looks like the short path multiple and removes them from the trace

what delay do short path multiples have

a constant one

problem with predictive deconvolution

lag between primary and multiple wavelets can be predicted, if delays between primary arrivals is predictable (eg. sequential depostion) they may end up being deconvoluted.

4 deconvolutions

predictive deconvolution

source signature deconvolution

wavelet shaping

inverse q deconvolution

Typical use of radon filter

filter long path multiple

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