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1(Slide 1)
Tip/Trick: Spectral Decomposition with PetrelEBN Symposium āEchoes from Seismicā¦ ā
18th February 2016
Reinoud Veenhof
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2(Slide 2)
Introduction
ā¢ Spectral decomposition can be a big help in viewing details in your seismic
ā Adding āto the eyeā frequency information to the standard amplitude data
ā¢ Example of company/software propagating this is GeoTeric
ā What they call āCognitive Interpretationā (gotta give it a nameā¦)
ā¢ This presentation shows how to create the spectral decomposition and display it by yourself with just Petrel
ā After Marfurt, Techniques and best practices in multi-attribute display (SEG, 2015)
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3(Slide 3)
Introduction
ā¢ Spectral decomposition in seismic consists of 2 steps
1. Selection of the attribute to de-compose
ā¢ Should be meaningful, i.e. attributes that are mathematically independent but correlated through the underlying geology
ā¢ Frequency is the prime attribute (others are dip, azimuth etc.):
ā In time itās called š or temporal frequency (cycle/second = Hz)
ā In depth itās called š or spatial frequency (wave number) = nr of wavelengths/distance = inverse of wavelength = 1 š)
2. Co-render with the existing seismic display
ā¢ Combination of RGB color model and Alpha (opacity) blending
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4(Slide 4)
The Trick ā Step 1
ā¢ This can all be done by Petrelā¦
ā As an example I take a PSDM processed depth seismic
ā Determine the dominant frequency (by Volume Attribute process):
ā A rather meaningless histogram
But among 100 million buttonsā¦
Petrel has couple of Magic ButtonsMagic button1
Dominant Wave Number from PSDM depth
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5(Slide 5)
The Trick ā Step 1
ā¢ Magic Button 1 pipes all histogram values to the message log (including percentiles) which in Excel gives a meaningful histogram
ā Multiplying the wave number with 1000 gives units comparable to temporal frequency numbers we are used to.
Wave Number * 1000
Co
un
t
K = 18/1000 = Blue
K = 23/1000 = Green
K = 37/1000 = Red
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6(Slide 6)
The Trick ā Step 1
ā¢ I assign the following ācomponentsā:
ā Wave number = 18/1000 = Blue
ā Wave number = 23/1000 = Green
ā Wave number = 37/1000 = Red
ā¢ Next is extracting these dominant frequencies from the PSDM
ā Petrel has a volume attribute process for this called āIso-frequency componentā which is the isolation of the local contribution of individual frequencies to the make-up of the input signal
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7(Slide 7)
The Trick ā Step 1 and 2
ā¢ The Iso-frequency component is a normalized measure of contribution of that specific frequency to the total seismic input at a specific location
ā These can be colored by a color scale where 0 = no color and 1 is full monochrome color of either blue, green or red
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8(Slide 8)
The Trick ā Step 2
ā¢ Opacity blending the separate seismic volumes
ā Define opacity level for the three monochrome volumes where 0 should be completely transparent and 1 is a ācertain percentageā of that color
ā A ācertain percentageā means whatever brings out the geology best
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9(Slide 9)
The Trick ā Step 2
ā¢ Co-rendering the normal seismic with volume red with Magic Button 2
Magic button2
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10(Slide 10)
The Trick ā Step 2
ā¢ Frequency spectral decomposition on depth slices works best with coherency (or variance) cubes instead of normal seismic
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11(Slide 11)
The Trick ā Step 2
ā¢ All volumes rendered with normal seismic as backdrop for the vertical section and coherency as backdrop for the horizontal slice
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12(Slide 12)
The Show
Depth 440m
Channel
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13(Slide 13)
The Show
Depth 840m
Slump
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14(Slide 14)
The Show
Depth 1220m
Polygonal faulting (intra formational)
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15(Slide 15)
The Show
Depth 1510m
Chalk folding
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16(Slide 16)
The Tip
ā¢ A partial list of attributes that can be effectively displayed with blending a color model
ā From: Marfurt, Techniques and best practices in multi-attribute display (SEG, 2015)
i.e. backdrop
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17(Slide 17)
Thanks
ā¢ Thatās all there is to itā¦