using seismic attributes

7/31/2019 Using Seismic Attributes

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FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil

Lecture 13

Horizon A

Horizon B

Good SealGood Reservoir

W1 W2W3

W5

W4

W6W7

W8 W9


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Review causes of seismic response Modeling the seismic response

What are seismic attributes?

Overview of seismic attribute applications- Qualitative analyses

Exercise: Mapping depositional environments

- Quantitative analyses

Exercise: Predicting average porosity

Outline


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Limestone Shale

Seismic Response

What causes a seismic response?

1. Changes in bulk-rock velocity or density

Lithology (e.g., sandstone, shale, limestone, salt)


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Fast Slow

Seismic Response



Porosity (e.g., intrinsic, compaction, diagenesis)



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Seismic Response

Mineralogy (e.g., calcite vs. dolomite, carbonaceousshales)






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Fluid type and saturation (water, oil, gas)

Pore Fluid Density

Salt Water 2.164

Fresh Water 2.155

Oil 2.095

Gas 1.856

Sandstone with 30% Porosity:

Seismic Response

Mineralogy (e.g., calcite vs. dolomite, carbonaceousshales)






7/42FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobil

Modeling the seismic response:

Determine bulk-rock velocity and density

Calculate impedance (Recall: I = x v)

Represent impedance changes as reflection coefficient

Convolve seismic wavelet to reflection coefficients

I2 - I1

I2+ I1RC=

Seismic Modeling



The Convolution Method

Velocity Density Impedance

Reflection

Coefficients Wavelet ModelLithology

=x *

Shale

Sand

Shale

Sand

Shale



A wedge model isused to display theinteractions ofreflectioncoefficients as thethickness changes

Note how themiddle peakchanges amplitude,shape, and durationas the sand thins tothe east

W E

Wedge Modeling

Seismic Modeling



What are seismic attributes?

Seismic attributes are mathematical descriptions

of the shape or other characteristic of a seismic

trace over specific time intervals.

Definition



Why are seismic attributes important?

Our increasing reliance on seismic data requires that weextract the most information available from the seismicresponse

Seismic attributes enable interpreters to extract moreinformation from the seismic data

Applications include hydrocarbon play evaluation,

prospect identification and risking, reservoircharacterization, and well planning and fielddevelopment

Importance / Benefits


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Classes of seismic attributes?

Horizon (loop) Horizon A Peak amplitude

Duration Symmetry

Sample (volume, instantaneous) Amplitude

Time Frequency

Interval Average amplitude

Maximum (Minimum) Duration

Isochron

Horizon B

Single-Trace Types


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Classes of seismic attributes?

Multi-Trace

- Dip / azimuth- Coherency

CorrelationWindow

Trace A Trace B

AmplitudeA

Amplitude B

R2 = 0.92

Multi-Trace Types


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Faults

Stratigrahicfeatures

Dip map

Multi-Trace Types


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Seismic attribute applications:

Qualitative

Quantitative

- Data quality; seismic artifact identification- Seismic facies; depositional environment

- Equations relating rock property changes to

changes in seismic attributes Reservoir thickness Lithology Porosity Type of fluid fill

Applications


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Data Quality Analysis (Artifact detection): Identify zones where seismic data quality is adversely

affected by acquisition or processing methods or bygeologic interference.

- Acquisition gaps, Inline-parallel striping

- Multiples, migration errors, incorrect velocities

- Improper amplitude and phase balancing

- Frequency attenuation- Overlying geology (e.g., shallow gas, channel)

Qualitative Analyses


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Data Quality Analysis (Artifact detection):

Inline-parallel acquisition striping at water bottom (~ 40 ms)

Data Quality

InlineDirection


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Data Quality

Data Quality Analysis (Artifact detection):

Inline-parallel acquisition striping at 1000ms

InlineDirection


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Seismic facies mapping:

Facies are packages of rocks that exhibit similarcharacteristics (e.g., lithofacies, petrophysical facies,depositional facies)

Seismic facies are packages of seismically-definedbodies that exhibit similar seismic characteristics (e.g.,reflection geometry, amplitude, continuity, frequency).

Environment of Deposition (EoD) can be interpretedfrom patterns of seismic facies (i.e., similar seismicattributes)



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Orange

Datum



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Conceptual Depositional Model:

Stacked, prograding fluvial to nearshore tooffshore siliciclastic parasequences

Orange

Magenta

Seismic Facies Mapping Exercise

Fluvialshales - sands

Offshoreshales

Nearshoresands


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Marine Shale (seal)

Porous Sand (reservoir)

Marine Shale (seal)

Marine Shale (seal)

Porous Sand (reservoir)

Fluvial (reservoir)Orange

Magenta

Prograding sands increase in porosity upwards beforebeing capped by variable quality marine shale.


Conceptual Depositional Model:


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Modern Analog:

Fluvial to nearshore progression resulting in wavedominated, barrier island complex (Texas Gulf Coast)



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Modeled Seismic Response

Seismic modeling indicates the following response tochanges in reservoir and seal quality:

Good Seal

Good Reservoir

Good Seal

Poor Reservoir

Poor Seal

Good Reservoir

Poor Seal

Poor Reservoir

Strong PeakStrong Trough

Strong PeakModerate Trough

Moderate PeakStrong Trough

Moderate PeakModerate Trough



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Objective:

Identify areas where good-quality seal rocks overlaygood-quality reservoir rocks

Available data / tools:

Seismic attribute maps

Orange time structure map

Depositional model and seismic response

Tracing paper and pencils



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Good SealPoor Reservoir

Poor SealGood Reservoir

Poor SealPoor Reservoir

Good SealGood Reservoir

Strong PeakStrong Trough Strong PeakModerate TroughModerate PeakStrong Trough Moderate PeakModerate Trough


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Seismic attribute applications:

Qualitative

Quantitative

- Data quality; seismic artifact identification- Seismic facies; depositional environment

- Equations relating rock property changes to

changes in seismic attributes. Reservoir thickness Lithology Porosity

Applications


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Goal: Build a correlation between seismic attributes and

sand thickness to predict areas of high reservoirproducibility.

Tools: Seismic - well log (i.e., rock property) models

Quantitative Analyses


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Backstepping, unconfined sheet-sands comprising twomulticycle reservoirs separated by a marine shale

Geologic Description


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FWS 06 L 13 - Seismic AttributesCourtesy of ExxonMobilWell 9Well 2 Well 6

Sand Shale Sand Shale Sand Shale

Which seismic attributes differentiate average sand thickness?

Attribute Response


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Maximum

Average

Minimum

Duration

0

50

100

150

200

250

300

30 40 50 60 70 80 90 100

Maximum Loop Duration (ms)

MeasuredAverageSandThickne

ss(ft)

0

50

100

150

200

250

300

30 35 40 45 50 55 60 65 70 75 80

Average Loop Duration (ms)

MeasuredAverageSandThicknes

s(ft)

0

50

100

150

200

250

300

0 10 20 30 40 50 60 70

Minimum Loop Duration (ms)

MeasuredAverageSandThickness

(ft)

0

50

100

150

200

250

300

40 60 80 100 120 140 160

Average Positive Amplitude

MeasuredAverageSandThicknes

s(ft)

Amplitude

0

50

100

150

200

250

300

80 90 1 00 110 120 130 140 150 160 170 180

Maximum Amplitude

MeasuredAverageSandThickn

ess(ft)

0

50

100

150

200

250

300

0 5 10 15 20 25 30 35 40

Average Amplitude

MeasuredAverageSandThickness(

ft)

Calibration


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Seismic Attribute Calibration

0

50

100

150

200

250

300

40 60 80 100 120 140 160

Average Positive Amplitude

MeasuredAverageSand

Thickness(ft)

Thickness = 3.3787 APA - 187.67R2 = 0.869

Seismic Attribute Calibration


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Low High

Average Amplitude

W1W2

W3

W5

W4

W6

W7

W8W9

Input Seismic Attribute

140125110957055


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RESULT

Thin Thick

Average Sand Thickness

W1W2

W3

W5

W4

W6

W7

W8W9

160 feet1401201008060


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Quantitative Analysis: A Brief Example

Porosity in the

Upper Smackover

PorousZone

Impedance

Smackove

rNorphlet

Haynesville

No Porosity in the

Upper Smackover

TightSmackoverNorphlet

Haynesville

Impedance

An Oil Field, Onshore Alabama


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Change Porosity -> Change Seismic Response

Representative In-LinePorosity

in the SmackoverNo Porosity

in the Smackover

The trough islower in amplitudeand loop duration

is longer

The trough ishigher in amplitudeand loop duration

is shorter

MappedHorizon(white)

2.84

2.82

2.92

2.84

2.82

2.92


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1-D Seismic Modeling

Changing the porosity in the Upper Smackover

in 1-D models confirms there is a seismicsignature related to porosity

Smackover

Haynesville

Norphlet

16 ft

Porous

Zone

3 ft

Porous

Zone

10 ft

Porous

Zone


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Attribute Calibration & Evaluation

Porosity for the Smackover Predicted based on 4 attributes

Calibration based on 8 wells

Actual Average Smackover Porosity

0 5321 8 9764

5

0

6

1

4

3

2

8

7

9

PredictedAverageSmackoverPorosity


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A Predicted Porosity Map

Applying the derived attribute equation to the 3D

seismic survey resulted in a Smackover porosity map

18%

0

porosity

Possible NewWell Location


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Inadequate well control:

Wells dont represent all variability within reservoir Use seismic modeling to infill gaps

Redundant attributes

Different attributes highly correlated to oneanother

Remove redundant attributes; keep one thatcorrelates best with rock property

Linear correlation Nonlinear correlation may be better representation Test other nonlinear correlation schemes but be

aware of extrapolation problems

Potential Pitfalls / Solutions


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Seismic attributes describe shape or other characteristics ofa seismic trace over specific intervals or at specific times

Seismic attributes are important because they enableinterpreters to extract more information from seismic data

Seismic attributes can be derived from a single-trace or bycomparison of multiple traces

Three common types of single-trace attributes are horizon-,interval-, and sample-based

Seismic attributes are used for qualitative analysis (e.g.,data quality, seismic facies mapping) and quantitativeanalysis (e.g., net sand, porosity prediction)

Summary

using seismic attributes

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