Download pdf - Seismic Meta-Attributes and the Illumination of the Internal Reservoir Architecture of a Deepwater Synthetic Channel Model

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SeismicMeta

Attributesandthe

IlluminationoftheInternalReservoir

IlluminationoftheInternalReservoir

Architecture

ofaDeepwaterSynthetic

ChannelModel

ChannelModel

By:StaffanVanDyke

andRenjunWen

GeomodelingTechnologyCorporation

Outline

Outline

Ci

fd

hll

l•

Constructionofdeepwaterchannelleveecomplex

syntheticseismicdataset

•Instantaneousattributes

•Instantaneousattributes

•Volumecurvature

•Meta

attributes

•Meta

attributes

•Semblance

St

ld

iti

•Spectraldecomposition

•Colorblending

Pi

ilC

tA

li(PCA)

•PrincipalComponentAnalysis(PCA)

•Neuralnetw

ork

faciesclassification

SyntheticDeepwaterCLC

FaciesModel

SyntheticDeepwaterCLC

FaciesModel

•Adeepwaterchannel

Adeepwaterchannel

leveecomplexmodel

wasbuiltusingprocess

orientedmethodology

orientedmethodology,

inwhichthreefan

channelsare

responsibleforthe

responsibleforthe

depositionanderosion

overtimeof9

distinctivelithofacies.

CLC

Model–Velocity

andDensity

CLC

ModelVelocity

andDensity

•Thefaciesmodelwas

populatedwithseismic

velocities(Vp)and

densitiesusingthe

conventionalgeostatistical

methodbyassigning

mean,standard

deviation

andvariogram

modelsfor

each

lithofacies.

•Each

lithofacieswas

populatedwithdistinctive

Vpanddensity

statistics.

•Anacousticim

pedance

volumewasthen

calculatedfrom

theVpand

density

volumes.

CLC

Model–SeismicResponse

CLC

Model

SeismicResponse

•A3Dseismicpost

stack

volume

wasgeneratedbyusinga30Hz

Rickerwaveletandtheacoustic

impedance

volumecalculated

from

velocity

anddensity

volumes,

througha1Dconvolutional

process.Majorcharacteristicsof

deepwaterturbiditechannelsseen

inactualseismicdata

are

re

createdinthissyntheticmodel.

•Weappliedworkflowsofseismic

attribute

analysisandfacies

classificationto

thissynthetic3D

seismicvolume.

•Because

weknowthe“ground

truth”faciesmodelresultingin

this3Dseismicmodel,wewere

this3Dseismicmodel,wewere

ableto

examinetheefficacy

of

differentseismicattribute

analysis

methodsinrevealingtheinitial

faciesmodel.

faciesmodel.

BasicSeismicAttributes

BasicSeismicAttributes

•In

reflectionseismology,seismicattributesrepresenta

quantity

derived,orextracted,from

theseismicwavelet(s),

such

asphase/frequency/amplitude

such

asphase/frequency/amplitude.

•Attributescanbeanalyzedeitherpost

stack

orpre

stack

(CMP

gathers)

gathers).

•Instantaneousattributesare

typicallyextractedfrom

asingle

trace,butmore

complexattributesare

calculatedacross

,p

multipletraceswithinadefinedwindow.

InstantaneousAttributes

•Thefirstattributeswere

InstantaneousAttributes

derivedfrom

the1D

complexseismictrace.

•Therecordedseismictrace

is

knownastherealpartofthe

complextrace.By

perform

inga90phase

tti

kth

rotation,knownasthe

HilbertTransform

,the

imaginary

partofthe

complextrace

isrevealed

complextrace

isrevealed.

•From

thiscomplextrace,

such

attributesas

instantaneous

instantaneous

amplitude/phase/frequency

canbecalculated.

(Hardage,2010)

InstantaneousAmplitude


•Atanycoordinate

on

Atanycoordinate

on

thetimeaxis,avector

a(t)canbecalculated

thatextends

thatextends

perpendicularlyaway

from

thetimeaxisto

interceptthehelical

interceptthehelical

complextrace

z(t).

•Thelength

ofthisvector

istheamplitudeofthe

complextrace

atthat

instantoftime–hence

theterm

“instantaneous

amplitude.”

InstantaneousPhase

InstantaneousPhase

•Thephase

atone

Thephase

atone

instantalonga

trace,independent

oftrace

amplitudes.

•Excellentindicator

forlateralcontinuity

ofreflectionevents.

InstantaneousFrequency


•Therate

ofchange

Therate

ofchange

ofphase

overtime.

•Goodindicatorfor

Goodindicatorfor

porosity,thickness,

andpresence

of

hydrocarbons.

Meta

Attributes

Meta

Attributes

Fth

fthi

til

ttt

ibt

•Forthepurposesofthisarticle,meta

attributesare

consideredto

beanycombinationofseismicattributes

designedto

enhance

thesignalofthewavelet.

•Themostwellknownofthese

istheSweetness

attribute:




•Sweetness

worksbecause

frequency

isanexcellentindicator

notonlyforporosity

andthickness,butforhydrocarbons.It

hasbeenobservedthatsiliciclasticreservoirsstandoutfrom

hasbeenobservedthatsiliciclasticreservoirsstandoutfrom

thebackgroundmuch

betterthanwhenemployingasingle

attribute.

Sweetness

Sweetness

NewMeta

Attributes

NewMeta

Attributes

•Duringtheanalysisofthesyntheticdata,we

derivedanumberofnewmeta

attributes,

including:

–ContinuityofAmplitudeResponses

ContinuityofAmplitudeResponses

–AmplitudeResponse

ofSim

ilarlyThickBodies

–ContinuityofSim

ilarlyThickBodies

–PondingMeta

Attributes

g

PondingAttributes

PondingAttributes

GeometricalAttributes

PondingAttributes

PondingAttributes

PondingAttributes

PondingAttributes



MostNegative

Curvature

MostNegative

Curvature

PondingAttribute

1

MAtt(P1)=ƒ(Inst.Amp,Dom.Freq,MostNeg.Curv.)



ShapeIndex

ShapeIndex

PondingAttribute

2PondingAttribute

2

MAtt(P2)=ƒ(Inst.Amp,Dom.Freq,ShapeIndex)



MAtt(CAR)=ƒ(Inst.Amp,Inst.Phase,Dom.Freq)

AmplitudeResponse

ofSim

ilarlyThickBodies

AmplitudeResponse

ofSim

ilarlyThickBodies

Amplituderesponse

of

similarlythickbodies

MAtt(ATB)=ƒ(Inst.Amp,Inst.Freq,Dom.Freq)

ContinuityofSim

ilarlyThickBodies

ContinuityofSim

ilarlyThickBodies

MAtt(CTB)=ƒ(Inst.Freq,Inst.Phase)

RefiningSemblance

RefiningSemblance

•Seismiccoherency

(semblance)isameasure

oflateral

changesintheseismicresponse

causedbyvariationin

tt

tti

hlith

lit

dth

structure,stratigraphy,lithology,porosity,andthe

presence

ofhydrocarbons(Chopra

andMarfurt,2005).

Ti

llbl

il

ith

ff

•Typicallysemblance

involvescomparingthewaveform

of

adjacenttracesto

oneanotherviathecalculationof

reflectordip/azimuthsthroughoutthedata

volume

reflectordip/azimuthsthroughoutthedata

volume.

•However,potentialbandingfrom

thezero

crossingcan

occurwhenthedip/azimuthsare

calculated

manifesting

occurwhenthedip/azimuthsare

calculated,manifesting

artificialanomaliesinthedata.

RefiningSemblance

RefiningSemblance

bl

ll

dh

k•Semblance

wascalculatedonthepost

stack

dataset.

•Thepost

stack

volumewasphase

rotated90

toobtaintheim

aginary

trace

component.

gy

p

•Thesemblance

from

theim

aginary

trace

was

calculated

calculated.

•Therotatedsemblance

volumewas

bt

tdf

thii

lbl

subtractedfrom

theoriginalsemblance

volume.

RefiningSemblance

RefiningSemblance

OriginalSemblance

RefinedSemblance

ColorBlending

ColorBlending

•Colorblendingofthefirst3PrincipalComponentAnalysis(PCA)

componentscalculatedbyStransform

methodologyofSpectral

Decomposition.

VolumeFaciesClassification

•Aneuralnetw

ork

classificationschemewasusedto

derive

aseismic

lithofaciesvolumebasedontheinputofmultipleseismicattributes.

Summary

andConclusions

Summary

andConclusions

Ct

tif

thti

3D

ii

t•

Constructionofasynthetic3Dseismicresponse

toa

deepwaterchannelleveecomplexmodelallowedcontrolled

analysisoftheefficacy

ofindividualandmeta

attributes.

•Meta

attribute

analysisofaSouth

Texasdataset–and

subsequently,anAlbertadataset–revealedsignificant

correlationsto

welllogdata,whichwere

strongerthanthose

g,

gforindividualattributes.Developmentandtestingofthese

andothernewmeta

attributescontinues.

•Otherquantitative

post

stack

techniquesperform

edbythe

Otherquantitative

post

stack

techniquesperform

edbythe

interpreteralsoilluminate

internalreservoirarchitecture.

–SpectralDecomposition

St

tlSli

/St

tGid

–StratalSlices/Strata

Grids

–FaciesClassification(trainedanduntrained)

–Colorblending

ContactInform

ation

ContactInform

ation

Sff

kStaffanVanDyke

SeniorGeophysicist

1001S.DairyAshford,Suite110

Houston,TX77077

(281)6774410

staffanvandyke@geomodelingcom

[email protected]

RenjunWen

ChiefArchitect

11006658thStreetSW

Calgary,AB

T2P3K7

Calgary,AB

T2P3K7

(403)2629172

[email protected]