Seismic Interpretation by Dr. Ali Bakr

8/10/2019 Seismic Interpretation by Dr. Ali Bakr

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ALI BAKR ALI BAKR ALI BAKR

SEISMIC INTERPRETATION

Dr. ALI BAKR

1. Basic background

2. Structural Interpretation

3. Seismic attributes

4. AVO implications

5. Seismic Inversion

6. Seismic stratigraphy

7. 4D seismic (Time Laps)

Contents

1-BASIC BACKGROUND

• Seismic acquisition

• Seismic processing• Understanding the data

1-Basic Background

• Seismic interpretation and subsurface mapping are key skills thatare used commonly in the oil industry

• This teaching resource introduces the basic principles of seismic

interpretation and then, if time permits, they can be applied in apractical exercise

• The resource dovetails with the A level Geology specifications

1-Basic Background

• An air gun towed behind the surveyship transmits sound waves through thewater column and into the subsurface

• Changes in rock type or fluid contentreflect the sound waves towards thesurface

• Receivers towed behind the vesselrecord how long it takes for the soundwaves to return to the surface

• Sound waves reflected by differentboundaries arrive at different times.

• The same principles apply to onshoreacquisition

Seismic acquisition offshore

1-Basic Background

Seismic acquisition onshore • Onshore seismic acquisition requires an energy input from a“thumper” truck. Geophones arrayed in a line behind thetruck record the returning seismic signal.

Sub-horizontal beds

Unconformity

Dipping beds

Geophones(receivers)

Vibrator(source)

1-Basic Background

Seismic acquisition onshore

Lithology change

Angular unconformity

Lithology change

• Seismic horizons represent changes in density and allow the subsurfacegeology to be interpreted.

1-Basic Background

• Wiggle trace to CDP gather

• Normal move out correction

• Stacking

• What is a reflector?

Seismic Processing

1-Basic Background

Seismic Processing Wiggle trace to CDP gather

Graphs of intensity of sound as received bythe recorders

Graphs of intensity for one location collectedinto groups and shown in a sequence.

Wiggle traces CDP gather

1-Basic Background

Seismic Processing

Normal move out correction

Original CDPgather …

corrected fornormal move out

Change in lithology from mud to sand so soundis reflected back to surface

CMPSound sources

S1 S2 S3

Data for one point from different signals to different receivers

1. More time needed to reach distant receivers so the data look likea curve.

2. Correcting for normal move out restores the curve to a nearhorizontal display.

Sound receiversR3 R2 R1

1-Basic Background

Next, take all the sound traces forthat one placeand stack them on top of eachother

First, gather sound data for onelocation and correct for delayedarrival (normal move out)

Finally, place stacks foradjacent locations side byside to produce a seismicline

Stacking Seismic Processing

1-Basic Background

There are many reflectors on aseismic section. Major changesin properties usually producestrong, continuous reflectors as

shown by the arrow.

A seismic reflector is a boundary betweenbeds with different properties. There maybe a change of lithology or fluid fill fromBed 1 to Bed 2. These property changescause some sound waves to be reflected

towards the surface.

lower velocity

higher velocity

energy source signal receiver

What is a reflector?

1-Basic Background

• Common Depth Points (CDPs)

• Floating datum• Two way time (TWT)

• Time versus depth

Understanding the data

1-Basic Background

CDPs are defined as‘the common reflectingpoint at depth on a

reflector or the halfwaypoint when a wavetravels from a source toa reflector to areceiver’.

Common midpoint above CDP

Change in lithology =reflecting horizon

Common reflecting point orcommon depth point (CDP)

Sound sourcesS1 S2 S3

Sound receiversR3 R2 R1

Common Depth Points

1-Basic Background

The floating datum line represents travel time between the recording surface and the zeroline (generally sea level). This travel time depends on rock type, how weathered the rock is,and other factors.

The topographic elevation is the height above sea level of the surface along which theseismic data were acquired.

Floating datum

1-Basic Background

0.25 seconds

Two way time (TWT)indicates the time requiredfor the seismic wave totravel from a source to

some point below thesurface and back up to areceiver.

In this example the TWT is

0.5 seconds.

0.25 seconds

s e c o n d s

surface

1-Basic Background

0.58 sec

• Two way time (TWT) doesnot equate directly to depth

• Depth of a specific reflector

can be determined usingboreholes

• For example, 926 m depth =0.58 sec. TWT

Time versus depth

1-Basic Background

• Check line scale and orientation.

• Work from the top of the section, where clarity is usually best,

towards the bottom.

• Distinguish the major reflectors and geometries of seismicsequences.

1-BASIC BACKGROUND

1-Basic Background

• Some energy will be reflected, some will betransmitted where there is a change in AI

• Amount reflected (amplitude of reflection)will depend on the relative difference inphysical properties across the interface

1-Basic Background

– Define reflectioncoefficient (RC)

RC = AI2 – AI1

AI2 + AI1

– If AI2 > AI1 – positive RC

– If AI2 < AI1 – negative RC

2 2 11

1-Basic Background

Polarity Conventions

Slow, Less

Fast, m ore

+veR.C.

Blue (90%)

Red (10%)

Blue (10%)

Red (90%)

Trough

1-Basic Background

• Not all changes in lithology associated withchange in AI. Changes in fluid content in asingle lithology can give rise to reflections

• Different combinations of layers lithologies canhave the same RC Seismic “non-unique”

• Seismic data image interfaces – we observe

changes in AI across an interface, not propertiesof layers themselves

1-Basic BackgroundConvolutional Theorem

Subsurface at any one location as consists of a one-dimensionalseries of reflection coefficients

1-Basic Background

Subsurface at any one location as consists of a one-dimensionalseries of reflection coefficients

Convolutional Theorem

1-Basic Background

Each RC gives rise to a separate reflection event, the amplitude ofwhich is proportional to the change in AI across the interface

1-Basic Background

• The final image we will record for that location consists of thealgebraic sum of all the individual reflections

• Mathematically we “convolve” the wavelet with the series ofreflection coefficients

1- Basic BackgroundData required for synthetic calculation

• Seismic Data

• Well Curves (Sonic and Density)

• Well Position relative to Seismic

• Check Shot / T-D relationship

• Well Deviation Survey

• Seismic Acquisition and Processing Info

Impedance High Frequency

Top & Base

Resolved

Low Frequency

Top & Base

Unresolved

1-Basic BackgroundVertical Resolution

Seismic ability to define topand bottom of a rock layer

In general, reflections are composites of thin layer effects.

Resolution depends on:

Frequency content in seismic data.

The interval velocity at the objective level

V Dominant Wavelength of Seismic Wave =

Where: V is the velocity in unit distance per second and

f is the dominant frequency in Hz

f dom4

int v ~

• Most of the energy in a seismic wavelet is contained in a band offrequencies centered about the dominant frequency. The dominantperiod can be defined as the time between two major crests. Thedominant frequency is the reciprocal of the dominant period. Theequation for wavelength, , is:

= velocity/frequency

Calculate wavelengths for the following cases:

Shallow rocks: V=2000 m/s, f=50 Hz;

Deep rocks: V=6000 m/s, f=25 Hz.

Conventional HFITM

Vertical Resolution – Example (‘HFI’ Processing from Geotrace )

• Example 1:

V = 7,000 m/s

F = 50 Hz

= 7,000/50 [(m/s)/(cycles/s)]

= 140 m

• Example 2:

V = 3,000 m/s

F = 50 Hz

l = V/F

= 3,000/50 [(m/s)/(cycles/s)]

= 60 m

1-Basic BackgroundVertical Resolution (Summery)

• Vertical Resolution is the ability to detect and map thin eventssuch as reservoir sand bodies

• It is determined by the average frequency and bandwidth of the

seismic data

• We can typically resolve down to ¼ wavelength

• Wavelength is determined by frequency and velocity:

λ=V/f so resolution ~ V/(4*f)

• Resolution deteriorates with depth

1 B i B k d

• The seismic signal contains a range of frequencies (left)• The broader the bandwidth, the sharper the pulse (smallerside lobes)

- 0. 5

1 B i B k d

Fourier analysis may be used to see the bandwidth

of the seismic data in a given portion of the data.

• Amplitude spectrum on left shows a broad bandwidth,rich in high frequencies

• Spectrum on right is irregular and abruptly truncated atabout 45 Hz. Data were filtered post-stack as a noisereduction exercise.

1 B i B k d

What is the dominant frequency of the seismic data in the intervalbetween 1500 and 1600 ms? If the velocity is 5000 m/s, what is thetuning thickness? If it is possible to detect a bed down to 1/16 ofthe wavelength, what would that be?

1 B i B k d

Dominant frequency:

about 4 ½ cycles in 100 ms

= 45 cycles/second = 45 Hz

1 B i B k d

Tuning thickness:Frequency = 45 Hz, Velocity = 5000 m/s

Wavelength = 5000/45 = 111 m

Tuning thickness = ¼ x 111 = 28 m

1 B i B k d

1-Basic Background Horizontal Resolution

Horizontal Resolution is the ability to map lateral changes in reservoir – edges and internal structures.

• Seismic energy is reflected from a patch rather than a point. Migrationcollapses this patch and improves resolution.

• Prior to migration horizontal resolution is poor

• Horizontal resolution can approach vertical resolution if ‘aperture’ isadequate

• The wider the aperture the closer the horizontal resolution approachesthe vertical resolution

• Other seismic processes can also reduce lateral resolution

1 B i B k d

Seismic Energy Reflects from a Patch, not a Point

1-Basic Background Horizontal Resolution Fresnel Zone

1 B i B k d

Lateral resolution described by Fresnel Zone

Seismic data image (“illuminate”) an area, rather than a single point

1 Ba i Ba k ou d

Fresnel zone diameter (F) depends upon:• Average velocity (v)

• Two-way travel time (t)

• Dominant frequency (f)F = v (t/f)1/2

1 Basic Background

Migration collapses diffractions and gives us horizontal resolution

To do this properly we need to record the whole diffraction

1 Basic Background

• Fresnel Zone example:

v = 2440 m/s

f = 25 Hz

t = 2 s

F = v (t/f)1/2

= 2440*(1/25) 1/2

= 488 m

2- SEISMIC INTERPRETATION

Interpretation Workflow

RegionalStudy

Review-QCData

Time/Depth/Attribute/Properties integration

Peer Review

Report

DHI/Seis. Attributes /Inversion Analysis

Reservoir PropertyMapping

Volumetric / SpatialDistribution Analysis

Structural mapping

Borehole to SurfaceSeismic Match

Seismic Horizon andFault interpretation

Velocity Modelling

Time to DepthConversion

Seismic reservoir

property mapping Geomodelling

Basic Structural Geology Background

Fault Classes

STRIKE-SLIP FAULT

Fault Classes

DIP-SLIP OBLIQUE-SLIP STRIKE-SLIP

Pitch = 90 Pitch = 45”E” Pitch = 0

Fault Classes

PlannersListirc

BASIN ANALYSIS

SUBSIDENCEL L

T = 30 KM (CONTINENTAL)

L’ > L

T > t CRUSTAL THINING

β=L’ /L= T/ t (streching factor)

BASIN ANALYSIS

SUBSIDENCE

SHEARING STRESS

LISTRIC FAULT MODEL

LISTRIC FAULT

BASIN ANALYSIS

SUBSIDENCEPLANAR FAULT MODEL

BASIN ANALYSIS

SUBSIDENCE

BASIN RANGE

SHEARING STRESS

PLANAR FAULT

BLOCK ROTATION

Fault Classes

Only on gravitational structures…not tectonics?

Fault Classes

listric

planar

Fault Classes

Footwall uplift

Picking faultson seismic

Fault Classes

Fault-scarp degradation

Fault Classes

Eroded crest

Fault Classes

Talus at foot

Fault Classes

Then banked in with sediment

Fault Classes

F l Cl

Fault Classes

F l Cl

Fault Classes

F lt Cl

Fault Classes

False fault pick

F lt Cl

Fault Classes

F lt Cl

Fault Classes

V i F ld

Various Folds

Various Folds (cont'd)

Various Folds (cont d)

Axial plane near axis should be close to horizontal

Fault Mo e e t I di ato

Cross section analysis

Example 1: Onlap

Syn-faulting strata

Active faulting and upliftduring deposition

Fault Movement Indicators

Example 2: Offset beds ofequal thickness

Pre-faulting strata

Faulting post deposition

Offset onlap:1. 3R>1R2. 3R>BRR

0.5 mile

100 ms

Isochore: line drawn through points of equalvertical (apparent) thickness of a unit

Calitroleum

Wilhelm

MYA4-A

McDonald

x1 x2 x3 x4 x5

1 mile

500 ms

2. Thin beds

c) filled inpaleo high(post tectonic)

b) fault belowinterval(syn tectonic)

1. Close contours

a)a) fault cut

intervalat time(syn tectonic)

Two Signatures:

Structural high

Fault Classes

Hydrocarbon Traps

Fault Related

Fault Free

Hydrocarbon Traps

Over flowing point or spill point Closure

height

Closure area

oil/gas column

oil/gas area

oil-water/gas-oil contact

Note: All measurements are in 3D space. All pools are in traps, but not

all traps could be pools.

Hydrocarbon Traps

Spill point: the lowest point at which hydrocarbon may be contained in the trap. A trap may or maynot be full to the spill plane.

Closure: the vertical distance from crest (the highest point of the trap, or culmination) to spill plane. Oil-water contact (OWC): the deepest level of producible oil. Gas-oil contact (GOC) or gas-water contact (GWC): the lower limit of producible gas.

Hydrocarbon Traps

Height of closure

Reservoir rock

Cap rock

Spill point

Height of gas

Height of oil

Basic Inversion Terminology

Modified from William 1996

Horst -Graben Inversion -Southern North Sea

South Hewett Fault

Horst -Graben Inversion -Southern North Sea

South Hewett Fault

Seismic Interpretation

To Interpret:

Structure

Stratigraphy

Lithology

FracturesPressure

Pore Fluid

Predict and Characterize Subsurface Reservoirs

3D Seismic

Automated Structural Interpretation

Ant-track

Faults

Horizons

Combined visualisation of Dip-Azimuth and Fault Enhancementattributes.

Well 1

Well 3

Well 2

Guidance for accurate faultinterpretation

Wells are provennot to be incommunication.

Initial Check List

• Seismic data vintage (acquisition year)?

– Acquisition report• Processing sequence, type (PSTM, PSDM, etc.)?

– Processing report• Source of data (tape, project backup) and format?

– 8-, 16-, 32-bit data? Have any AGC, Time gain filters, beenapplied? Amplitude fidelity?

• Overall data quality:– Good for structural interpretation?– Good for stratigraphic interpretation?– Good for reservoir characterization?

• Can we see fluid effects, lithology, both?• Which phase and polarity?

• Dominant frequency at reservoir level and expected resolution?• Well tie analysis?• Existing seismic picks and interpretation review (time and depth)

Initial QuestionsMigration Type?

Time Migration Depth Migration

Migration Type?

Initial QuestionsDigitization of Geophysical Data

Digitization of Geophysical Data

• Dynamic range:

If digital sampling ranges from 1 to 256 units of amplitude:

20log10 (256) 48 dB

The number of bits in each word determines the data dynamic

range:8-bit = 28 = 256

16-bit = 216 = 65536 20log10 (65536) 96 dB

32-bit = 232 = 4,…109 192 dB

Initial Questions Amplitude Fidelity and Filtering

Smoothing filter, improves signal to noise ratio for interpretationpurpose, but removes discontinuities, potential faults…

Amplitude Dip guided Gaussian Filter

Initial Questions Amplitude Fidelity and Filtering

AGC effect on data: good for interpretation and bad for attributes and

reservoir characterization

Original Amplitude AGC filter Time Gain

3D Data Load QC

Initial QuestionsAmplitude Fidelity and Footprints

Amplitude Fidelity and Footprints

Shallow time slice on Variance cube

Acquisition/Processing

footprints

Shallow Area ReefBuildups

footprints

Shallow Area ReefBuildups

fooprints

Initial Questions Amplitude Fidelity and Footprints

Strong processing artifacts indicating pooramplitude fidelity

RMS Amplitude

Initial QuestionsStructural and Stratigraphic Interpretation: Good

Initial Questions3D Data Comparison

2000 Processed

Shift between the 1984 and the 2000 Surveys

1984-Processing Seismic Results

Initial QuestionsPolarity and Phase

Using this convention, in a seismic section displayed with SEG normal polarity

we would expect:

• A reflecting boundary to appear as a trough in the seismic trace if Z2 > Zl

• A reflecting boundary to appear as a peak in the seismic trace if Z2 < Zl

(a) minimum- and(b) zero-phasewavelets at anacoustic-impedanceboundary with apositive reflectioncoefficient

Initial QuestionsIdeal Vertical Resolution

Dominant Wavelength of Seismic Wave =

Where: V is the velocity in unit distance per second and

f is the dominant frequency in Hz

V(m/sec) F(Hz) /2 to /4 (m)

2000 50 20-10

3000 40 38-19

4000 30 66-33

5000 20 125-62.5

Initial QuestionsVertical Resolution and Tuning Thickness

Zero phase

wavelets

Tuning separation

in time = 1/2 of the wavelet period

in depth = T

X interval velocity

Example:

If T = .020 Sec

and Vint = 6000’/Sec the tuning thickness is 60 feet

Initial QuestionsBorehole to seismic tie

•Quality of check

shot data?

•Phase?

•Match with surface

seismic?

•Any stretch and

squeeze?

•Position of markers

versus seismic

picks?

DT RHOB AI RC WaveletTime

Review of Well TieSynthetics in time domain

Updated well tie

New Time-Depth

Review of Well TieBorehole to 3D seismic

Review of Well TieCheckshot Data

Horizon 2 outlier maker

Outlier well

Do’s and Don’ts Borehole to seismic tie

Review of Seismic InterpretationPicks in time/depth domain

• Consistency between inlinesand cross-lines picks?

• Signal consistency (peak,trough, zero-crossing)

• Auto-tracking or manual, orcombination of both?

• Geological consistency(isochrone, isochore)?

Review of Seismic InterpretationPicks in time/depth domain

Examples of inconsistencies between inlines and cross-lines

picks and impact on time grid

ick in time/depth domain

Vertical exag. 7.5x

Review of Seismic InterpretationStructural consistency

• Starting from key/stronghorizons, here coal level.

• Is the interpretationstructurallymeaningful/flawless?

•Look at the fault throws andtheir vertical evolution alongfault planes

• Understand the big picturefirst

Review of Velocity Modellingand Depth Conversion

Original stacking velocity

Well velocity (checkshots)

Evaluate the need for calibration of stacking velocity

Review of Velocity Modelingand Depth Conversion

Marker Depth Old Model Residual (m)

T -2612.46 -2512.62 -99.8408

U -2727.96 -2631.32 -96.6397

V -2838.46 -2743.55 -94.9091

W -2884.56 -2791.08 -93.4754

X -2922.96 -2838.74 -84.2182

Y -3015.8 -2930.85 -84.9545

Z -3073.45 -2994.24 -79.2136

ZZ -3144.13 -3065.24 -78.8872

T -2623.88 -2506.14 -117.745

U -2736.98 -2622.13 -114.85

V -2843.4 -2733.7 -109.695

W -2890.87 -2783.39 -107.485

X -2928.84 -2830.8 -98.0448

Y -3017.93 -2914.42 -103.508

Z -3076.67 -2980.04 -96.6268

ZZ -3148.31 -3053.87 -94.4429

•Review depthresiduals before wellcorrection is applied

• It provides a directindication of thevelocity model quality

Data Review Completed

• Highlighted where to focus interpretation efforts and attention

(minimize valuable mouse clicks)• What data is ok to use for either further:

– Depth conversion

– Geomodeling

• Identified data that revision/update or interpretation from scratch– Go back to essentials (geology, well correlation panels,

geological environment, regional structural style, etc..

– Geology is not limited to well markers!

Geologic Correlations

Understand well correlation first at bigpicture level guided by key/stronghorizons

Horizon Selection

•Start with obvious and

most continuous seismicreflections detectedduring panning

•More difficult horizonsare addressed later orphantomed from keyhorizons

•Get the framework first

Structural InterpretationTraditional Fault picking

2D on optimal section = perpendicular to fault strike

Structural InterpretationData Conditioning

filteredinput

Data conditioning for structural interpretation

Structural InterpretationNoise Removal

Edge preserving filtering – Structurally Oriented

Original Filtered Difference- =

Structural FrameworkScreening and Panning of Amplitude data

Inlines, Xlines and Time slices

Structural FrameworkScreening and Panning of Amplitude data

Random sections orthogonal to fault planes

Structural FrameworkScreening of Amplitude data

Volume rendering with transparency

Structural FrameworkScreening of Amplitude data

Volume rendering with transparency

Structural FrameworkScreening of Dip and Azimuth Volumes

Time slice on Azimuth

Structural FrameworkScreening of Dip and Azimuth Volumes

Time slice on Dip

Structural FrameworkScreening of Edge Enhancement Attributes

Time slice on Variance

Interpretation- Structural Mapping

Fault sticks

Fault markers

Fault sticks

Fault markers

Modeled Fault plane

Screening of Structural Framework Auto-tracking time structural map

3D Auto-tracking will reveal data quality and

interpretation issues to be addressed eventually

•Transfer low level,repetitive tasks to theworkstation such asauto-tracking

•Maximise the valueof a mouse click!!!!

QC Your Horizon PicksIn 2D and 3D Views

Looking for mispicks in 3D views using vertical exaggeration

1X vertical exaggeration 10X vertical exaggeration

Looking for bulls eyes and slope

anomalies on contoured maps

Pick quality and signal

consistency check on

instantaneous phase

Pick quality and signal

consistency on instantaneous

amplitude

Velocity Modeling andDepth conversion

•Check all available data:Check shotsVSPSyntheticsStacking velocities

Geologic tops correlation

•Select, use and integrate as needed:Simple TDR from wellsAverage interval velocity

Full velocity modelling: wells + calibrated stackingEtc..

InterpretationSeismic Geomorphology

100 m100 m

channels

Crevasse splay

TIME SLICE Y ATRIBUTOS

Stratal Slice of Amplitud Maps

Time slice

Horizon slice

Proportional slice T W

Reference horizon 1

Reference horizon 2

Interpretation Summary

• QC existing data and interpretation

– Data type, phase, resolution, amplitude, well ties, picks, etc..• Beware of noise level, noise removal to support interpretation

• Use the full 3D data and auto-tracker as much as possible

• Use 3D attributes (Dip, Azimuth, Edge Enhancement) and 3Drendering techniques (geobodies mapping, transparency) for data

screening• Minimize manual picks and clicks and maximize the use of the

workstation for repetitive low level tasks

• Ensure signal consistent horizon interpretation and geologicalconsistency before embarking on geofantasy!

• Ensure good tie with wells in time• Use and integrated all available data

3- SEISMIC ATTRIBUTES

Seismic Attributes

• Seismic attributes are all theinformation obtained fromseismic data, either by directmeasurements or by logic orexperienced-based reasoning.

• The main objective of theattributes is to provide detailedand accurate information to theinterpreter on structural,stratigraphic and lithologicalparameters of the seismicprospect.

Seismic Attributes

• Pre stack:– Input data is CDP or image gathers

– Have directional (azimuth) and offset related information

– Lots of information that may not be practical in initial or basicstudies

– Contain considerable amounts of data that can be directlyrelated to fluid content and fracture orientation.

– AVO, velocities, azimuthal are the most prominent of thisclass.

• Post stack

– After data is stacked, these are computed on the trace.

Seismic Attributes

G l Cl ifi i

General Classification

From A.R. Brown

Seismic Attributes

Seismic attributes are specific measures of geometric, kinematic, dynamic, orstatistical features derived from seismic data. ‘General’ attributes include:

1) Reflector amplitude,

2) Reflector time3) Reflector dip and azimuth

4) Complex amplitude and frequency

5) Generalized Hilbert attributes

6) Illumination

7) Edge detection/coherence

8) Spectral decomposition

Some Important Post stack Attributes

These have a physicalas well as statisticalbasis!

Seismic Attributes

•Envelope presence of gas (bright spots), thin-bed tuning effects,lithology changes.

•Phase lateral continuity of reflectors, bedding configurations.

•Frequency bed thickness, presence of hydrocarbons, fracture zones.

•Spectral Decomposition bed thickness.

•Coherence faults, fractures, lateral stratigraphicdiscontinuities

Why Seismic Attributes

Seismic Attributes

• By their computational characteristics:– Instantaneous Attributes: Computed sample by sample. Trace

envelope, its derivatives, frequency and phase,… – Wavelet Attributes: Computed at peak of trace envelope and

have a direct relation to the Fourier Transform. InstantaneousFrequency

– Physical Attributes: Relate to physical qualities. Frequenciesrelate to bed thickness, magnitude of trace envelope relates toimpedance contrast.

– Geometrical Attributes: Describe spatial and temporalrelationship of all other attributes. Lateral continuity measured by semblance is a good indicator of a discontinuity. Assist in the

recognition of depositional patterns and related lithology.

Seismic Attributes

• By their origin in the wave phenomena, we can also sub-divide the attributes into two categories:

– Reflective Attributes:

• Attributes corresponding to the characteristics ofinterfaces.

• All instantaneous and wavelet attributes can be

included under this category.• Pre-stack attributes such as AVO are also reflective

attributes,

– Transmissive Attributes

• Relate to the characteristics of a bed between twointerfaces (all physical attributes)

• Interval, RMS and average velocities, Q, absorptionand dispersion come under this category.

Attributes Interpretation

Objectives:– Recognize an hydrocarbon anomaly or lithology

– Validate anomalies, revealing the relation rock-seismic

Methodology:

• Assume a model

• Compute or evaluate the response to the model at known locations

• Compare response of model to actual data

• Verification in new areas or intervals

Seismic Attributes

• Seismic attributes

• Seismic attributes:

– Properties of the seismic trace when thought of as an analytic

(complex) trace with both real and imaginary parts

Hilbert transform complex trace from the Real seismic trace

Real:conventionalseismic trace

Quadrature:

imaginary partseismic trace fromHilbert transform

Seismic Attributes

I i i ib d i d f h l i i

• Instantaneous seismic attributes are derived from the actual seismic

data• Quality of attributes is dependent on signal consistent interpretation

(grid based)

• Used as both seismic display (seismic sections), as maps (grids) andvolumes

Why do we generate Seismic Attributes ?

Enhance structural and stratigraphic features for the interpreter onseismic sections

• Enhance structural and stratigraphic features on maps

• Locate misinterpretation

• Get information on lithology, facies or fluid content

• Correlate with other properties

reservoir characterisation

Display and use of Seismic Attributes

• Seismic Amplitude:

– Trace’s amplitude value at the horizon time/depth

– Identify bright spots/dim spots

• Reflection Strength/Envelope:

– Total envelope of energy at any instant along the trace– High reflection strength is often associated with major change in

acoustic impedance due to lithology, fluid content (gas), orstratigraphy.

Seismic trace

Envelope

Q d A li d

• Quadrature Amplitude:

– Imaginary part of the complex seismic trace– Used in conjunction with other attributes to identify

bright spots

Seismic trace

Quadrature trace

• The Trace Envelope is a physical attribute and it can be used as aneffective discriminator for the following characteristics:

– Reflectivity, since mainly represents the acoustic impedance contrast

– Bright spots, possible gas accumulation,

– Sequence boundaries,

– Thin-bed tuning effects

– Major changes in depositional environment,– Spatial correlation to porosity and other lithologic variations,

– Indicates the group, rather than phase component of the seismic wavepropagation.

• Instantaneous Phase

– Description of the phase angle at any instant along a trace– Independent of amplitude

Expresses the degree oflateral continuity or

discontinuity of seismicreflections, pinchouts,angular unconformities,thickening and thinningzones, offlap, onlap, and

makes weak coherentreflection clearer.

• Cosine of Phase:

– Cosine function applied to the instantaneous phase (+/-1)

May enhance definition ofstructural delineation

• Instantaneous Frequency:– Time derivative of the phase

– Low: 0 to 1/2 of the Nyquist Frequency

Helps in correlatingreflection alongseismic section andhighlights low

frequency anomaliesbelow HCaccumulations

• Apparent Polarity:– Sign of the seismic trace where reflection strength has a

local maximum value (+1 or -1)

May help distinguishdifferent kinds of brightspots (due to gas,limestone..)

• Response Phase:– Calculates the instantaneous phase when the reflection

strength has its maximum

Alternate way of displayinginstantaneous attributes, lesssubject to noise sincecomputed where seismic tracehas maximum energy

• Sweetness:

– Sweetness is the Envelope(Reflection Strength) dividedby the square root of theInstantaneous Frequency.

It can sometimes help indelineating subtle discontinuities

Variance

Sweetness

• Bump mapping:

p pp g

– Uses illumination and shading to add another dimension to thenormal rendering of the data

This display allowsenhancing of very subtlestructural features, likesmall fault patterns

Display and use of Seismic AttributesToo many attributes…highly correlated

Common amplitudeattributes computedin a 100ms window

Barnes, 2006

D i ti

• Derivatives:

– First derivative calculates the slope of the tangent of theselected seismic amplitude (QC interpretation on zerocrossing)

– Second derivative measures the variation in the tangents of theselected seismic amplitude, directly above and below the

reflection. High values indicate rapid shift from peak totrough (short wavelength)

amplitude 1st derivative 2nd derivative

• Application of Amplitude first and second

Application of Amplitude first and secondderivatives:

Second derivative can beused to help guiding thepick by providing continuityin areas of where reflectionsare poorly resolved on theraw amplitude.

Original amplitude

Second derivative

• Band pass filtering:

Original amplitude

High pass > 25 Hz

High pass > 35 Hz

Display of Attributes Amplitude Fidelity and Filtering

AGC effect on data: good for interpretation and bad for attributes and

g preservoir characterization

Original Amplitude AGC filter Time Gain

Heterogeneity:• Curve length of the function within an interval for the given attribute

• Shows the heterogeneic nature of any internal reflector in a givenvolume

Low heterogeneity High heterogeneity

Display and use of Seismic AttributesLocal Attributes

Upper Loop

Duration

Lower LoopDuration

Upper Loop

Lower LoopArea

Seismic section crossing

high Upper Loop Areavalues

Upper Loop Area

Seismic Amplitude

• Surface based attribute maps:– Extracted along or close to an interpreted surface

Extracted along or

close to a surface

• Volume based attribute maps:– Calculated in a time/depth

window:

– Between two interpretedsurfaces

– Below/above/around aninterpreted surface

Extracted in between twosurfaces or within a constanttime window

• Grid based attribute

Grid based attribute

maps:– Derived directlyfrom seismicinterpretation,independent ofseismic amplitude

data– Dip, Azimuth,

Curvature,Illumination, Edge,etc…

Dip map Carbonate Buildups, Barents Sea

Courtesy of Norsk Hydro

Seismic Attributes and Reservoir Characterisation

• Combining attributes:

-cross-plotting of attributes against reservoir property of interestusing well data

-selection of the ones that correlate best

-statistics helps defining attribute contribution to the variance

-resultant attributes used in geostatistical kriging to interpolatethe reservoir property between wells (RAVE, LPM).

Geometric Attributes, Looking for Similarityin Seismic Data

• Geometric attributes - Stratigraphic attributes – Multi-trace

attributes

• 4 families of multi-trace attributes:– Dip/azimuth – measures reflector shape– Texture attributes– Discontinuity – measures waveform similarity– Amplitude – measure lateral changes in impedance contrast

Geometric Attributes

– Dip/azimuth – measures reflector shapeC t f t di

• Components of vector dip

• Gradient• Curvature• Rotation

– Texture attributes• Chaos• Flatness• Divergence

• Dip Histogram• Gabor Filter bank• Volume reflection Spectral (VRS) decomposition

– Discontinuity – measures waveform similarity• Cross correlation coherence• Semblance and variance• Principal component coherence

• Principal projected gradient– Amplitude – measure lateral changes in impedance contrast

• Amplitude gradients• Cohereny energy gradients

Pre- and Post-Conditioning:Gaussian low-pass smoothing filter

Gaussian dip-guided filter / Layer-Parallel Smoothing

• Pre- and Post-Conditioning:

– Gaussian dip-guided filter / Layer-Parallel Smoothing

Amplitude Dip guided Gaussian Filter

• Dip and Azimuth:

Calculate localgradient

Estimate the covariancematrix of the gradient

vectors

Perform principalcomponent analysis:

Dominating orientation

PCA is a time expensive dip computation, other methods exist such as Event dip and Gradient dip

• Dip and Azimuth:

Dip from estimated event(0 to 90)

Dip from PCA (0 to 90)Dip from instantaneous

local gradient vector(-90 to 90)

Geometric AttributesLooking for Similarity

Coherence AttributesExample Results

Coherencyas it is mostcommonlydisplayed;

as time-slices

C1 – correlation

C2 – semblance

C3 – eigenstruct.

Coherency as it is less commonly displayed; as vertical slices

C1 C1 – correlation

We clearly see the effect of the vertical window…

C2 C2 – semblance

C3 C3 – eigenstruct.

3D Automated Fault Mapping Ant Tracking: Results

Seismic ChaosVariance Ant track

Ant TrackingBiology lesson

FoodNest

Ant TrackingBiology lesson: swarm intelligence

FoodNest

Ant TrackingBiology lesson: swarm intelligence

FoodNest

Conclusion:“Dumb” ants do smart things!

Automated Fault Mapping Ant Tracking

Seismic

Fault AttributeAnt Track Cube

Ant Track FaultsFault System Analysis

Fault Attribute vs. Ant Tracking

Time slice

Ant trackVariance

• Dip/azimuth – measure reflector orientation

• Partial derivatives of Dip enable to compute curvature (change ofdip as a function of azimuth)

• 2D Curvature:

Curvature calculated along picked horizons

1. pick horizon2. smooth horizon3. calculate curvature on tight grid for short wavelength estimates4. smooth horizon some more5. calculate curvature on coarse grid for long wavelength estimates

Curvature Attributes

Courtesy of Bruce Hart, McGill Univ.

Definition of curvature Second-order derivative of

Curvature describes howbent a curve is at a particularpoint on the curve

( Roberts, 2001 )

2D Curvature Attributes

Drainage system onbasement

Basement faults

CurvZ: Negative Curvature (Concave up)(short length filter)

Deep Canyons related todrainage system

N-S trend ofdistinctive scarpand dip slopes

geomorphologySinkhole

basement

Courtesy of Bruce Hart, McGill Univ.

Variance

Time slice at 680ms

3D Mean Curvature

Time slice at 680ms

3D Maximum Curvature

Time slice at 680ms

3D Minimum Curvature

Time slice at 680ms

Seismic Attributes

Some Important Post stack Attributes (Volume Attributes)

• Post-stacked attributes ( i.e. not AVO or Velocity) can be calculated as a volume, as aslice, in a time window, or along a horizon .

– The volume can be displayed and interpreted like any other cube of data…however most interpretation packages include the ability to transform the data byslice

– The window can be a constant flat time interval, hung from a structurallyinterpreted horizon or between two horizons

– Horizon attributes are normally calculated and extracted from a data volumefollowing automatic spatial tracking or snapping.

• Time derived attributes are very helpful for checking your interpretation. If you useauto-tracking a lot then this step is especially important.

• While most horizon attributes are from near the structural top of the reservoir do notforget that attributes from below the reservoir can also give you valuable information -i.e. the gas shadow zone

Instantaneous Attributes

Seismic Attributes

• When considered as an analytical signal a seismic trace can be expressed as acomplex function such as u(t)=x(t)+iy(t) where x(t) is the recorded trace itselfand y(t) is its quadrature (a 90 degree phase-shifted version of the recordedtrace).

• There are 3 instantaneous attributes

– Amplitude which is proportional to the square root of the of the total

energy of the signal at an instant in time and is used to identify brightand dim spots.

– Phase which is a measure of continuity and is used to delineate featuressuch as pinchouts, onlaps, and prograding reflectors.

– Frequency which is the time rate of change of instantaneous phase andcan help identify condensate and gas reservoirs, which tend to attenuatehigh frequencies

Seismic Attributes

Input Trace with envelope

Quadrature trace with envelope

Instantaneous Phase

Instantaneous Frequency

Envelope attribute also calledinstantaneous amplitude orreflection strength Frequency

Seismic Attributes

Dr ALI BAKR

• Four “principal” volumePost Stack attributes.

• Reflection strength,instantaneous phase andinstantaneous frequency are“complex-trace” attributes

Seismic Attributes

Instantaneous Amplitude

• Amplitude provides information on : – Sediments and their fluids by virtue of their velocity density contrst.

– Amplitude change suggest changes in the nature of rocks and fluids (oil,gasand water).

– Commonly used amplitude based indicators, in hydrocarbon industryindustry , are Bright spots, Dim spots, and Flat spots.

Not all hydrocarbon accumulations produce detectable amplitude changes.Not all changes in seismic amplitude are associated with changes in fluid saturation.Changes in lithology, bed thickness, porosity and other factors can cause changes inseismic amplitude.It only takes a small amount of gas to generate an impressive looking bright spot;not all are associated with commercial accumulations of hydrocarbon. Conformitybetween structure contours and the limits of a high-amplitude area is oftenconsidered to be an indication that the amplitudes are related to the presence ofhydrocarbons (a bright spot).However, this correspondence will only be observed if:

the sand is continuous (not compartmentalized by stratigraphic or structuralfeatures),there are no hydrodynamic factors that tilt the fluid contact.

Seismic Attributes

• Amplitude provides information on :

– Sediments and their fluids by virtue of their velocity density contrst.

– Amplitude change suggest changes in the nature of rocks and fluids (oil,gasand water).

– Commonly used amplitude based indicators, in hydrocarbon industryindustry , are Bright spots, Dim spots, and Flat spots.

• Not all hydrocarbon accumulations produce detectable amplitude changes.Not all changes in seismic amplitude are associated with changes in fluidsaturation. Changes in lithology, bed thickness, porosity and other factorscan cause changes in seismic amplitude.

Seismic Attributes

• Bright spot : It is associated with strong amplitude contrastacross lithologies and their fluid (oil, gas and water) content.

• Dim spot: It is associated with weak amplitude contrast acrosslithologies and their fluid (oil, gas and water) content.

• Flat spot: Associated with fluid contact.

Seismic Attributes

Instantaneous Phase

• It is phase independent ofamplitude, and its valuesare in degrees and rangefrom +180 to -180. Becauseinstantaneous phase

contains no amplitudeinformation, it iscommonly used to examinereflection (i.e.,stratigraphic) continuity;changes in amplitude alonga reflection can sometimesgive the impression oflateral discontinuity.

Dr ALI BAKR

Seismic Attributes

• Instantaneous frequency is therate of change of phase. Itsvalues are in cycles/second(Hertz).

• Instantaneous frequency is

useful for detecting tuningeffects (although peak frequencyoccurs at a different thicknessthan for tuning of seismicamplitude), fractures, gas (seenext slide) and other features.

Seismic Attributes

Can be used to detect gas however is not really reliable because ittends to be noisy

• Arc Length

– total length of the seismic trace over a time window– increase in amplitude gives more trace length as well as

oscillation caused by increased frequency hence is really acomposite of amplitude and frequency

– can be used to map depositional facies

OGCI - SER - Attributes

Intro thru Horizon ... -

Seismic Attributes

Amplitude-Bright Spot

Gas SS

Bright Spot

The Sag

Not all Bright Spot prospects are as obvious as this simple model,but the idea is the same, and most are as subtle as a migraine.

Seismic Attributes

Amplitude-Dim Spot

Frequently, an increasein porosity, > 0,perhaps accompanied bya pore fluid change tohydrocarbons, leads to adecrease in theimpedance of an

otherwise highimpedance rock – suchas a carbonate or olderSS.

V (low )

V (high

Dim SpotNote the high amplitudeexit event - with a timesag caused by the lower

velocity in the porouszone

Seismic Attributes

Amplitude-Dim Spot

Generalized curves showing how theacoustic impedances of gas sand, watersand and shales increase with depth.

Bright spot occurs above depth A, where islarge contrast in and gas-sand impedancesbut a modest difference between shale andwater –sand impedances.

Polarity reversals occur between depths Aand B, where water –sand impedance isgreater than shale impedance but gas-sandimpedance is less than shale impedance.

Dim spot occur below depth B, where thethree impedance curves converge and there

are only samll impedance contrastsbetween shale and either type of sand,brine-filled or gas –filled.

Seismic Attributes

Amplitude-Flat Spot

Old and venerable, theflat spot, resulting

from gas-water contactreflections, is still

widely used inexploration anddevelopment.

GasWater

Note that the flat spot is

tilted on the time section.

The flat spot has regained it

flaticity when converted to depth.

Seismic Attributes

Amplitude-Flat Spot

3-Seismic Attributes

Amplitude-Flat Spot

Modified from Brown, 1996

Seismic Attributes

Data specification needed for Attributes

• For 8-bit data, amplitudes theoretically range from ±128,16-bit data theoretically range from ± 32,768 and 32-bitdata range from ± 4,294,967,296. 32- and 16-bit data havemore dynamic range than 8-bit data, but take up

correspondingly more amounts of storage space.

• You should work with 16- or 32-bit data when doingquantitative attribute analyses.

Seismic Attributes

Attributes Combination

• Attributes may be combined with each other

– E.g., amplitude-weighted phase

• This helps to combine their effects

• Although simple linear correlations between a physical propertyand an attribute are sometimes found, relationships are moreoften non-linear (e.g., Hart and Chen, 2004) and more than one

attribute is needed predict the physical property of interest

Seismic Attributes

Attributes Combination

Dr ALI BAKR

CoherencyAmplitude

Amplitude Coherency

Multiplying coherency(semblance) by amplitude makesstructural and stratigraphicfeatures more distinctive - in this

case fault arrays and meanderingturbidities channels[Shiehallion].

Seismic Attributes

Horizon Attributes

1. Identify horizon of interest2. Pick horizon on a selected grid of lines3. Pick all intermediate traces using an automatic picking

algorithm4. Extract horizon attributes:

• Time• Amplitude• Dip• Azimuth• Combined dip/azimuth

Seismic Attributes

Horizon Attributes

Seismic Attributes

Horizon Attributes

Dip & Azimuth• Dip/azimuth cubes only show relative changes in dip and azimuth, since

we do not in general have an accurate time to depth conversion

• Dip/azimuth estimated using a vertical window in general provide more

robust estimates than those based on picked horizons

• Dip/azimuth volumes form the basis for volumetric curvature, coherence,and structurally-oriented filtering

• Dip/azimuth will be one of the key components for future computer-

aided 3-D seismic stratigraphy

Seismic Attributes

Horizon Attributes

A h(Rijks and Jauffred, 1991)

Dip& Azimuth

Time Dip Azimuth

Seismic Attributes

Horizon Attributes

i A li d E i (Rijk d J ff d 1991)

Horizon Amplitude Extraction (Rijks and Jauffred, 1991)

t ( s )

Seismic Attributes

Horizon AttributesA li d K d H i S

Amplitude Keyed to a Horizon or Sequence

Seismic Attributes

Attributes Extractions

U d t d th l it f d t If t it t h

• Understand the polarity of your data. If necessary, convert it to zero phase.

• Tie expected reservoir response from logs to seismic.

• Pick top and bottom of reservoir using autotracking of peaks and troughs.

• Picking the top of a stratigraphic unit is usually more indicative of the sequence than the bottom.

• Composite amplitude partially compensates for adjacent acoustic impedances adjacent to the topand bottom of the reservoir by ‘stacking’ the absolute value of the reflectivity at the topand bottom.

• Be sure to annotate your amplitude extractions!• Polarity

• Offset above or below picked horizon• Measure (e.g. composite, top, bottom, average absolute value, etc)• Window length (if any)

Seismic Attributes

Coherency Attribute

A f t t t i il it f th i i f

A measure of trace to trace similarity of the seismic wavformwithin a samll analysis window.

inline inline

Coherence compares the waveforms of neighboring traces

Seismic Attributes

Coherency AttributeWhy we use Coherency

• Excellent tool for delineating geological boundaries (faults,lateral stratigraphic contacts, etc).

• Allows accelerated evaluation of larg data sets.

• Provided quantitative estimate of fault /fracture presence.

• Often enhance stratigraphic information

Seismic Attributes

Coherency AttributeCoherency data volume

Seismic Attributes

Coherency AttributeCoherency data volume

Coherence Time Slice

Seismic Time Slice

Seismic Attributes

Coherency AttributesCoherency data volume

Coherence Time Slice

Seismic Time Slice

Seismic Attributes

Horizon Slice

AdvantagesDi ad a ta e

• Focuses on reservoir or otherzone of interest

• Illuminates depositionalenvironment at a fixed geologictime

• Avoids low coherence “structuralleakage” due to steep dip

• Steers coherence calculationalong an interpreter-defineddip/azimuth, resulting in

generally sharper contact images

Disadvantages• Analysis limited to only a few

discreet horizons, which aretime consuming to pick

• Analysis limited to the extent

of the interpreted horizon• Picking errors can bias the

result or create artifacts

• Some geological surfacessimply cannot be characterized

by peaks, troughs, or zerocrossings

Seismic Attributes

Time Slice

Advantages Disadvantages

Advantages• Focuses on reservoir or other

zone of interest

• Illuminates depositionalenvironment at a fixed geologic

time• Avoids low coherence “structuralleakage” due to steep dip

• Steers coherence calculationalong an interpreter-defineddip/azimuth, resulting in

generally sharper contact images

Disadvantages

• Analysis limited to only a fewdiscreet horizons, which aretime consuming to pick

• Analysis limited to the extentof the interpreted horizon

• Picking errors can bias theresult or create artifacts

• Some geological surfacessimply cannot be characterizedby peaks, troughs, or zerocrossings

Seismic Attributes

Coherence volumes

Coherence on a time slice Coherence along structure

Seismic Attributes

Spectral Decomposition

Uses the dis rete Fourier transform to

3-D Seismic Volume

Uses the discrete Fourier transform to:

• quantify thin-bed interference,and

• detect subtle discontinuities.

Interpret

Subset

Compute

Animate

Interpreted3-D Seismic Volume

Zone-of-InterestSubvolume

Zone-of-InterestTuning Cube

(cross-section view)

Frequency Slicesthrough Tuning Cube

(plan view)

Seismic Attributes

Spectral Decompositionx

3-D Seismic Volume

Interpret

Subset

Compute

Animate

Interpreted3-D Seismic Volume

Zone-of-InterestSubvolume

Zone-of-InterestTuning Cube

(cross-section view)

(plan view)

Multiply

Tuning Cube

Seismic Wavelet Noise Thin Bed Interference +

Seismic Attributes

Split Spectral Tuning Cubeinto Discrete Frequencies

Tuning Cube

Spectrally BalancedTuning Cube

Gather Discrete Frequencies

into Tuning Cube

Independently NormalizeEach Frequency Map

Frequency 1 Frequency 2 Frequency 3 Frequency 4 Frequency n

(plan view)

Spectrally BalancedFrequency Slices

through Tuning Cube(plan view)

Seismic Attributes

Dr ALI BAKR

Spectral DecompositionReal Data ExampleOffshore Africa

spectral decomposition

80ms analysis window

centred 80ms above

a picked horizon

Dr ALI BAKR

hrz - 040ms

hrz - 120ms

a picked horizon

Red = 60hz amplitude

Green = 50hz amplitude

Blue = 40hz amplitude

Courtesy of Lantz, Aluvihare and Partyk

80ms analysis window

centred 40ms above

a picked horizon

Dr ALI BAKR

a picked horizon

Red = 60hz amplitude

Green = 50hz amplitude

Blue = 40hz amplitude

hrz - 000ms

hrz - 080ms

60hz amplitudeanalysis window = 80ms

Centred:

80ms above the picked hrz

Dr ALI BAKR

80ms above the picked hrz40ms above the picked hrz

00ms above the picked hrz

youngest oldest

higher lower

Seismic Attributes

Real Data Example

Dr ALI BAKR

Real Data ExampleGulf of Mexico , Pleistocene age equivalentOf modern day Mississippi River Delta

Seismic Attributes

Channel “A”

Gulf of Mexico Example 10,000 ft

Channel “B”

Fault-Controlled Channel

Point Bar

Amplitude

analysis window length = 100ms

Seismic Attributes

Channel “A”

F lt C t ll d Ch l

Channel “B”

Point Bar

Amplitude

Seismic Attributes

Channel “A”

North-South Extent

of Channel “A” Delineation

Channel “B”

Point Bar

Amplitude

4- AVO

Factors Affecting Amplitudes

Superimpose

d Noise

Instrument Balance

Geophone

Sensitivity &Coupling

Coupling

SourceStrength,Coupling andDirectivity

Spherical

divergence

Variation ofReflectionCoefficient with

Incident Angle

Reflector Curvatureand rugosity

Interference ofdifferent Events

Absorption

Array Directivity

ScatteringPeg-Leg multiplesfrom thin reflectors

Reflectioncoefficient

AVO definition

The variation in the amplitude of a seismic reflection with

source-geophone distance. Depends on the velocity, density

and Poisson ratio contrast. Used as a hydrocarbon

indicator for gas because a large change in Poisson’s ratio

(as may occur when the pore fluid is a gas) tends to produce

an increase in amplitude with offset.

AVO Assumptions

AVO A ti

•AVO Assumption

•No seismic attenuation

•No transmission loss

•No wavelet interference (tuning)

•Amplitude vs angle(

•Large angles

•Pre-stack events flattened

•Seismic Processing

•Q compensation

•Gain function

•Broad amplitude spectrum

•Remove wavelet•Zero-phase data

•Pre-stack migration

•Map offset to angle,

•Avoid offset mute

•Accurate (high-order) NMOcorrection

4-AVO Implications

• Amplitude Versus Offset is a

AVO definition

Amplitude Versus Offset is achange of reflectivity withOffset across a CMP gather.

• It is determined by the P-wave,

S-wave and density contrast atthe interface

• For clastic rocks, theseparameters are dictated byphysical properties such as

porosity, fluid and lithology.

4-AVO Implications

AVO principles

• Seismic waves are reflected

at a boundary between Layer 1

a a bou da y be eedifferent rocks

• At normal incidence,the reflected wave

has an amplitude R :

• R = 0.1 is a BIG reflection !

incident

reflected

transmitted

density wavespeed

Layer 2

4-AVO Implications

AVO principles

At fl ti i l d ti P

At every reflection in land section - P-waves that are not exactly at right-anglesto a reflector partially convert into S-waves which continue on down the

section reflecting and refracting.

AVO: is due to partitioning ofthe sound energy at interface

• The AVO technique for DHI is based on two principles:

AVO principles

4-AVO Implications

• The AVO technique for DHI is based on two principles:

1. When Gas replaces brine in reservoir rocks, Poisson’sRatio (Vp/Vs) Decreases.

2. When Poisson’s ratio decreases, Rc and amplitudebecomes more negative with increasing angle.

4-AVO Implications

AVO /AVA principles

• Change in Incident Angle ->Change in Amplitude

g gChange in Amplitude

• Different Offsets, Same Time ->Different Incident Angles ->Different Amplitudes

• Same Offset, Different Times ->

Different Incident Angles ->Different Amplitudes

• Amplitude changes with OffsetAND Time

• Temporal & Spatial change in

velocity complicates theproceedings!

4-AVO Implications

AVO /AVA principles

Angle of incidence decreases with depth for constantoffset trace

Angle of incidence constant for all depths on a constant

angle trace.

G E C O L O N G V A

O S L O

4-AVO Implications

P-wave & S-Wave

incident

P wave

reflected

P wave

WaterVp = 1500m/s

Vs = 0m/s

Hard Sea-bedVp = 2500m/sVs = 1200m/s

transmitted

P wavetransmitted

S wave

4-AVO Implications

• P Wave Velocity Measured :

AVO Parameters

• P-Wave Velocity - Measured :

– Well logs

– Seismic Velocity Analysis• Density - Measured :

– Well logs– Empirically from P-Wave Velocity

• S-Wave Velocity - Difficult to Measure

– P-Wave velocity/S-Wave velocity Ratio

– Poisson's Ratio (Rock Property)– Multi-component data analysis

4-AVO Implications

AVO principles

4-AVO Implications

AVO principles

4-AVO Implications

AVO principles

4-AVO Implications

Modulus = Stiffness(Stress/Strain Ratio)

Bulk Modulus κ (incompressibility)

Bulk modulus – measure ofcompressibility of rocks and fluids

Change in volume, not in shape

Dr ALI BAKR

Bulk Modulus κ (incompressibility)Response to Compressive Stress

Change in Pressure

Relative Change in Volume

Shear Modulus μ (rigidity)Response to Shear Stress

Change in Shear Force per unit area

Relative Displacement

Shear modulus – measurereluctance to change shape

Change in shape, not in volume

4-AVO Implications

3/4 P V

4-AVO Implications

• At any point in the sub-surface, there are only three independentacoustic rock properties responsible for seismic reflection :

– Vp,

– Vs,

– density

• All attributes we compute will depend on the the spatial distribution

of the above three properties.• From these attributes we would like to infer:

– Rock Properties

– Fluid type

– Porosity/Permeability

– Pressure

4-AVO Implications

AVO principles

Poisson's ratio

Poisson's ratio is simply a measure of how much thecross-section of a rod changes when it is stretched. In afluid, doubling the length halves the width (the volumeis retained) which yields a Poisson's ratio of 0.5. A rod

which never got any thinner, regardless of the amount ofstretching applied, would have a Poisson's ratio ofzero. There is a simple relationship between the P-wavevelocity, the S-wave velocity and Poisson's ratio...

4-AVO Implications

Relative Change in Width

AVO principles Poisson’ ratio

V V V V

Dr ALI BAKR

gRelative Change in Length

Poisson’s ratio is related to VP /VS ratio:

/ S P V V

Poisson`s Ratio σ

4-AVO Implications

Poisson’s Ratio varies :

may be thought of as a measure of Incompressibility

= .1= .4 = .3

may be thought of as a measure of Incompressibility

Wet Sand Oil Sand Gas Sand

0.00.5

4-AVO Implications

Th h d l f k d t h h

• The shear modulus of a rock does not change whenthe fluid is changed.

• However, the bulk modulus changes significantly

when the fluid changes.• As such, the p-wave velocity of a rock will change ashydrocarbon saturation changes whereas the s-wavevelocity will change relatively little (there is a slightdensity effect).

4-AVO Implications

AVO principles

In basins where the geologic section is relatively young and unconsolidated-ater oil and/or gas response may be seen in amplitude studies DHI’

4-AVO Implications

water, oil, and/or gas response may be seen in amplitude studies-DHI’s.

• Gas or light oil can significantly decrease the Acoustic Impedance ofa porous zone versus a brine fill.

• The anomalous amplitude should conform to a trap configuration.

• The hydrocarbon-water contact may occur as a flat reflection.

• Area and thickness of a seismic hydrocarbon anomaly may be used

for pre-drill volumetric estimates

I II III IV

4-AVO Implications

AVO Classes

I II III IV

Top ofReservo

Far Near F N F N F NOffsets

4-AVO Implications

Class 1 events areencountered in

high impedance reservoirs.The

AVO Classes

TheAVO behavior is a peakthat dims.

Class 2 events are encountered innear zero impedance reservoirs.

The AVO behavior is a weak peakor trough that brightens to astronger trough at far offsets orincident angles.

Class 3 events are encounteredin low impedance reservoirs.The AVO behavior is a troughthat brightens at far offsets orincident angles.

IncidenceAngle (offset)

Class 2

R e f l e c t i o n

C o e f f i c i e n

Low Impedance Reservoirs

C l a s s 3

High Impedance Reservoirs

C l a s s 1

Dimming

Brightening

Dimming

Brightening

4-AVO Implications

AVO Classes

4-AVO Implications

AVO Attributes

If we measure the amplitude of each reflection amplitude as a function ofoffset, and plot them on a graph as a function of the sine of angle of incidence

, p g p gsquared, weobserve a straight line. For any line, the intercept and gradient can bemeasured. By linearzing the complicated mathematics behind the AVOtechnique, Richards and Frasier (1976) and Wiggins et al (1986) gave us the

following physical interpretation of the intercept and gradient:

Intercept A = the P-wave reflection amplitude.

Gradient B = the P-wave reflection amplitude minus twice the S- wave reflection amplitude.

4-AVO Implications

AVO Attributes

When you plot the amplitude of the signalfor a reflector (i.e., horizon) against the offset

of the trace (or the calculated angle that thecorresponding sound wave would makewhen it met the reflector), the plot yields the"Intercept", where the trend of the amplitude

measurements meets the zero-offset line (soit would be equivalent to a geophone directlynext to the source, and a 90° angle to thereflector). It also yields the "Gradient", whichis the slope of the curve made by the plotpoints. The sums or differences of these

gradients and intercept values can then beused for mapping AVO anomalies. A

4-AVO Implications

AVO Attributes

Common Angle ofincidence calculatedfrom smoothed

stacking velocities

4-AVO Implications

AVO Attributes

R() P + G sin2

Intercept Gradienttrace trace

slope = G

( ) G si

ObservedLinear Fit

intercept

4-AVO Implications

AVO Attributes

Using the values for VP, VS, and density ρ shown in last

Figure , we can now work out the values for the AVOintercept and gradient for the wet and gas sands. For the wetsand, the VP/VS ratio in both the sand and shale layer is

sand, the VP/VS ratio in both the sand and shale layer isequal to 2. As shown in this leads to the simplification that B= −A for both the top and base of the layer.Using the parameters shown in the figure gives: ATOP_WET= BBASE_WET = +0.1 and ABASE_WET =B TOP_WET = -0.1.For the gas sand, the VP/VS ratio is equal to 1.65, and theintercept does not simplify as it did the wet sand.

However, the calculation is still straightforward, and leads toATOP_GAS = BTOP_GAS = -0.1 and ABASE_GAS =BBASE_GAS = +0.1. Note that, for the gas case, A=B for boththe top and base of the layer.The AVO curves for the wet and gas cases are shown in figure4, for an angular aperture of 0º to 30º. It is observed that theabsolute values of the gas sand curves show an increase inamplitude, whereas the absolute values of the wet sandcurves show a decrease in amplitude. These values do fall

within a reasonable petrophysical range for class 3 anomalies.

4-AVO Implications

AVO Attributes

After scaling each of the values of A and B by a factor of 10 (to give values of +1 and -1) they

have been put on an A-B cross plot, as shown in Figure 5. In our example, the wet points(shown as solid blue circles) establish the wet sand-shale trend, and the top and base gas

, p g(shown as solid red circles) plot in the other two quadrants of the A-B crossplot. This is atypical class 3 AVO anomaly (Rutherford and Williams, 1989), caused by gas saturationreducing the sand impedance and the Vp/Vs ratio of the sand encased in the shale.

4-AVO Implications

AVO Attributes

•When we introduce gas into a sandstone, VP decreases whereas VS increases slightly

W ill th t thi d i VP/VS ti h i l ti lit d th t

•We will see that this decrease in VP/VS ratio causes a change in relative amplitude thatwill vary with angle of incidence.

•By analyzing this variation in amplitude we will try to extract some lithologicalinformation from the data

•Poisson’s Ratio is a useful number to know as it may be a direct hydrocarbon indicator(DHI)

•S-Waves do not travel in water – they are converted back to P-Waves at the waterboundary

•S-waves are less affected by gas than P-waves

4-AVO Implications

AVO AttributesSeismic Gather

A m p l i t u d e

Offset

4-AVO Implications

AVO Attributes

Full Stack

m p l i t u d e

A(Y Intercept)

B (Slope)

Compressional Impedance Reflectivity

AVO Gradient Section

4-AVO Implications

AVO Attributes

Full Stack

A m p l i t u d e

A (Y Intercept)

B(Slope)

Far Offset Stack

Near offset Stack

4-AVO Implications

AVO Attributes

Full Stack

A m p l i t u d

A (Y Intercept)

B (Slope)

Far Offset Stack

Near offset Stack

4-AVO Implications

Myth• AVO does not work

G d li d i

Reality• AVO does work under the right

circumstances

AVO Misconceptions

• Gas-sand amplitude increaseswith offset

• AVO can not be used to detect oilsands

• AVO does not work incarbonates• Land AVO is more difficult than

marine AVO• Vp/Vs is 1.6 for brine sands, 1.8

for dolomites, 1.9 for limestones,and 2 for shales

• Rp and Rs are readily extractedfrom R(0)

circumstances• Gas-sand reflection coefficients

generally become more negativewith increasing of offset.

• High GOR light oil-saturatedrocks may exibit significant AVOanomalies

• There are some applications• The marine short-period

multiples are still a problem• Vp/Vs varies significantly

• Rp and Rs can be extracted fromR(0) and G if Vp/Vs is kbown

5. SEISMIC INVERSION

Inversion vs Modeling

SyntheticLogs

Wavelet

Impedance Seismic

Wavelet

Post-Stack Inversion

Low impedance zone is interpreted as higher porosity

ICI Horizontal Georgetown Field

Patch Reefs in the Edwards?

Interpreting an acoustic impedance inversion forlithology, porosity and fluids is simular tointerpreting a sonic log without the use of any

other logs. Why do it if there is more information?

Glen Rose Reef

Terminology and Background

Acoustic Impedance = Velocity X Density

Vp = Velocity of Compressional waveVs = Velocity of Shear wave

-Acoustic Impedance Inversion is a technique for measuring the

Impedance of the Earth’s sub-surface layers from seismic data

Vp/Vs ~ Poisson’s ratio

-Using Shear and Compressional Velocities, we can estimatePhysical rock properties from seismic data

Benefits of 3D Inversion

• Lithology and Fluid Discrimination

• Used for Reservoir Property Prediction

• Best Tool for Reservoir Characterization

• Best Method for Optimized Field Development

• Increased Reflectivity in Shear Volume

• Calibration to Well Data and Rock Properties

• Increased Signal Bandwidth

• Easier to Interpret

Rock Property Calibration

Top Reservoir

Laminated Pay

Rock Property Summary

• From well calibrations, seismic derived attributes can be used todiscriminate between the following rock/fluid classes:

• Clean Gas Sands Low Pwave Impedance, Low Vp/VsRatio

• Clean Water Sands High Pwave Impedance, IntermediateVp/Vs Ratio

• Laminated Gas Sands Reduced Pwave Impedance andVp/Vs Ratio

• Shales Increased Pwave Impedance,Intermediate to higher Vp/Vs Ratio

Deliverables

• Acoustic Impedance Volume (Product of Velocity and Density)

– Porosity, Geometry and Lithology• Shear Impedance VolumeLithology Fluid

– Lithology, Fluid

• Density Volume– Fluid type and ‘fizz water’ discriminator

• Vp/Vs Volume or• Poisson’s Ratio Volume – Lithology, Fluid type, Net/Gross ratio’s

• Porosity Volume

• N/G and Sw Estimations

Avo Analysis – Obtaining Shear Velocity estimates

Rock Property Calibration

Sh V l it

Shear Velocity

Pwave Velocity

Easier to Interpret

Inversion Workflow

AVO Analysis and

Processing

Pre-Stack Full

WaveformInversion

Rock Physics

Analysis andModeling

LowFrequencyModels

Petro-Acoustic Calibration

P,S, Absolute Impedance & Density

Volumes

IRDIntegratedReservoirDescription

P, S, Density Reflectivity Volumes

Quality Control of Inversion Process

• Well logs should be examined for suitable relationships between

measured impedance logs (calculated by dividing the density bythe the sonic log) and properties such as porosity and fluid type

• Well Logs should be converted to time and edited for borehole

• Well Logs should be converted to time and edited for boreholeeffects, balanced, and classified based upon quality

• Synthetics should be generated for all wells. Logs that do not tie

should be investigated for problems in log, wavelet, or seismic• It is generally preferable to run a loosely constrained trace based

inversion first (possibly augmented by non seismic data such astrend data from velocities or wells) to use for interpretation of amore tightly constrained model for later use in a model based

inversion

Dr ALI BAKRAfter R. B. Latimer

• The main test of inversion accuracy is how well it ties to the input

data• Volumes that rely heavily on log derived models should matchthe logs at the well locations

the logs at the well locations

• More model based volumes should match the seismic and thesynthetic created after inversion

• To make a valid comparison between log data and invertedimpedance the log data should be filtered t o the range of theseismic frequencies

• In all cases a universal check is to compare the model to well datathat was not included in the processing - a “blind” accuracy test

If results of the inversion do not tie and you have correctly processed

logs then check the wavelet• an inversion should be done over a time target with a waveletextracted from that interval

extracted from that interval

• if a wavelet from deeper is used it may have too low of frequencyand can result in “ringing”

• if a higher frequency wavelet from a shallower interval is useddeeper than results will appear smeared

• wavelets with an incorrect phase or amplitude spectrum can resultin erroneous time shifts that contain extra side lobes an createfalse geological features

• Lack of low frequency can also be a problem. Sources other thanlogs include pre-stack time or depth migration velocities

• The final AI product should also be checked against a relativeimpedance result (low frequencies have been filtered out) While

impedance result (low frequencies have been filtered out). Whilethis model is limited structurally and stratigraphically … anyfeature that is only seen on the broadband volume but notapparent on the band-limited target should be carefully examined.It could be the result of a poorly implemented low frequencymodel.

A Question of Scale

Dr ALI BAKR

Question of Heterogeneous Reservoirs

Dr ALI BAKR

Establishing a Relationship Between AI and Lithology

Dr ALI BAKRFrom C. Torres-Verdin et al

6-SEISMIC STRATIGRAPHY

Seismic StratigraphyWhy doing Seismic straigraphy?

• Geological age correlations

• Thickness estimates• Environment of deposition

• Paleobathymetry

• Burial history

•Relief

• Topography on unconformities

• Lithology

• Porosity/permeability

• Fluid content

• Insight into source and seal

Seismic StratigraphyScale of Study

There are three scales for seismic straigraphy studies:

• Regional Scale Seismic Strat-Interpretation – Large-scalestratigraphic interpretation of data “seismic stratigraphy”.

g p p g p y

• Prospect Scale Seismic Strat-interpretation. Localized

interpretation to define a prospect. May include use ofreflection configurations, wave shape, amplitude, etc.

• Reservoir scale Seismic Strat-interpretation. Quantitativelycharacterize reservoir (net sand, phi-H, etc.) to permit reservedetermination, reservoir simulation ,etc…

Seismic Stratigraphy

• Why doing seismic stratigraphy?

• Scale of seismic stratigraphy study

• Assumptions

• Categories

Seismic Stratigraphy Assumptions for Reflection Character Analysis

• Reflections are boundaries of impedance contrast.

• Reflections have areas in excess of the first Fresnel zone or .

• Reflections are from bedding surfaces.

• Reflections parallel time/age lines.

2-Seismic Stratigraphy

•Definitions

• Scale of seismic stratigraphy study

• Assumptions

• Categories

Seismic StratigraphyCategories

Seismic stratigraphy is divided into two main categories:

• R fl ti h t l i

• Reflection- character analysis

•Seismic facies analysis

2-Seismic StratigraphyCategories- Reflection Character Analysis

Reflection character analysis

Analyse the lateral variation of an individual reflectionunit or units in order to localise where stratigraphic

changes are found and identify their nature.

Seismic StratigraphyCategories- Reflection Character Analysis

222321

Reflector terminations defining the upper and lower boundaryof a sequences

Onlap aboveTilting or original depositional

attitude

123456

1234567

21 2322 24 25 26

212223

21 2322 24 25 26

12 5 61 2 3 4

212322 24 25 26

123456

Concordant aboveErosional: angular, structural

Downlap aboveErosional: angular, structural

Onlap aboveErosional: angular, structural

Onlap aboveErosional: angular, nonstructural

Downlap aboveErosional: angular, nonstructural

Concordant aboveToplap below

Concordant aboveConcordant below

Downlap aboveConcordant below

Reflector terminations defining the upper and lower boundaryof seismic sequences

Toplap (Upper Boundaries)

It is a termination of strata, or seismic marker, against an overlying surfacemainly resulting of non-deposition (sedimentary bypassing) with perhapsonly minor erosion. Each unit of strata laps out in a landward direction atthe top of the unit, and each successive termination lies progressively

seaward.

Toplap

1- Coastal toplap

2- Marine toplap

3- Non-marine toplap

2-Seismic StratigraphyReflection Character Analysis

Toplap

1- Coastal toplap

Seismic StratigraphyReflection Character Analysis

Toplap

2- Marine toplap

Seismic StratigraphyReflection Character Analysis

Toplap

3- Non-marine toplap

Mark Toplap

(Upper Boundaries)

Erosional truncation (Upper Boundaries)

Where inclined strata terminate against an erosional surface.

An unconformity is an erosional surface that separates younger strata from older rocks andrepresents a significant hiatus (at least a correlatable part of a geochronologic unit is notrepresented by strata). In very particular cases, an unconformity can corresponds to an non-depositional surface. Periods of erosion and non deposition occur at each global fall of sea levelproducing interregional unconformities. Although in some areas of continuous deposition, the

hiatus may be too small to be detected paleontologically or seismically, and the surface is definedas a conformity.

Erosional truncation (Upper Boundaries)

Mark Erosional truncation

(Upper Boundaries)

Onlap (Lower Boundaries) If a period of deposition dominated by bedload transport ( sandsized materials) ceases and is followed by a period of depositionfrom suspended load, then filling the latter ususally produces anonlapping sequence.

Onlap 1-Proximal onlap

2-Distal onlap

3-Coastal onlap

4-Marine onlap

5-Apparent onlap

6-Nonmarine onlap

7-True onlap

8-Tilted onlap (Apparent downlap)

1- Proximal onlap : is onlap in the direction of the source ofclastic supply.

2-Distal onlap onlap in the direction away from the source of

clastic supply.

3-Coastal onlap is the progressive landward onlap of the coastal

deposits in a given stratigraphic unit.

4- Marine onlap is the onlap of marine strata, primarily deep

marine (deposited seaward of the shelf break) in nature.

5- Apparent onlap is the onlap observed in any randomly oriented

vertical section, which may or may not be oriented parallel todepositional dip.

6- Non-marine onlap is the onlap observed in non-marine

environments, that is to say, landward of the depositionalcoastal break.

7- True onlap : when two apparent onlaps are observed on two

sections intersecting at right angles, the true onlap is likely to beobserved on the section parallel to the depositional dip.

8- Tilted onlap is an apparent geometrical relationship, that looks

like a downlap. Generally, it is induced by tilting, compensatorysubsidence and salt or shale flowage.

Mark Onlap

(Lower Boundaries)

Mark Onlap

Faulted units beneath the NW continental margin of Australia, blanketed by a post-tectonic sedimentarycover of late Mesozoic and younger age. The faults are shown here as showing normal throws. However,there may be partial inversion of these structures to create the antiformal structure on the NW side of the

section. The post kinematic section lies on an erosional unconformity and onlaps significant relief acrossthe section. Author: Rob Butler

Mark Onlap

Profile across part of the Central Basin, Iran, NE of the city of Qom. Image from Morley et al.

(in press, 2009) Structural development of a major Late Cenozoic basin and transpressionalbelt in Central Iran: the Central Basin in the Qom-Saveh area. Author: Chris Morley

1-Onlap2- Erosional Truncation

A dipline (see the associated regional project for location) with a well location marked. Note theangular truncation and erosion of the carbonates below the major unconformity associated withthe karstification of the carbonates. This erosion formaed a distinct penenplain, that is readilytraced across basement rocks (right) into the karsted carbonates at the well location.

Mark Onlap

An interpretation of thefault geometry and basinfill in part of the Inner

Categories- Reflection Character Analysis

pMoray Firth. Thisinterpretation was done

using 2D seismic dataalone (see relatedregional line) andwithout reference toexternal data or models.The arrows denote stratal

terminations (onlap).

Mark 1-Onlap2- Erosional Truncation

Downlap (Lower Boundaries)

Seismic reflection of inclined strata terminate downdipagainst an inclined or horizontal surface

Surfaces are present at the base of prograding packages. They are commonly associated withmaximum flooding surfaces produced by a rise in relative sea level

Downlap

1- Distal downlap

2- False downlap

3- Shelf downlap

4- Basin downlap

5- Opposite (local) downlap

6- Apparent downlap

Downlap

1- Distal downlap is a downlap in the direction away from the source of clastic

supply. The majority of downlaps are distal downlaps.

Downlap

2- False downlap is a downdip tangential stratal termination. Strata flattenand continue as units, which, often, are so thin that they fall below theseismic resolution.

Downlap

3- Shelf downlap is a downlap recognized in a shelf. Often, it underlies the

slope of a depositional coastal break. The water depth is less than 200meters (prodelta).

Downlap

4- Slope downlap is a downlap associated with a continental slope.

The water depth is higher than 200 meters.

Downlap

5- Opposite downlaps are characteristics of overbank deposits,

whether associated with fluvial or turbiditic levees

Downlap

6- (Apparent downlaps) : original onlap terminations when deformed

by tectonics or halokinesis (salt tectonics) can become apparentdownlaps.

Mark Downlap (Lower Boundaries)

Seismic StratigraphyCategories

Seismic stratigraphy is divided into two main categories:

• Reflection- character analysis

Seismic facies analysis

Seismic StratigraphyCategories- Seismic Facies Analysis

Why Seismic facies analysis

• Estimating deposition environment using thecharacter of the seismic reflections

character of the seismic reflections.

• Understand depositional history.

•Locate and predict potential hydrocarbon reservoirand stratigraphic traps.

Seismic StratigraphyCategories-Seismic Facies Analysis

Seismic facies

It is the group of reflections bounded by top and base boundaries.

Seismic parameters used for facies detection are

1)-Reflection configuration

2)-Reflection amplitude

3)-Frequency

4)-Continuity

5)-Interval velocity

•Bedding patterns

1- Reflection Configuration

Geologic Interpretation Facies Parameters

•Bedding continuity

•Depositional processes

2- Reflection Continuity

•Depositional processes

Fluid contacts

a) Internal config formsb) External config forms

•Lithology •estimation

•Porosity estimation

•Fluid content•Pressure

5- Interval Velocity

•Bed thickness

•Fluid content

4- Reflection Frequency

•AI contrast

•Bed thickness (tuning)

•Fluid content

3- Reflection Amplitude

Categories-Seismic Facies Analysis

Internal & External Forms Configurations The overall geometry of a stratigraphic, or seismic unit, consists of the internal formand the external reflection configuration of the unit. Both must be described tounderstand the geometric interrelation and depositional setting of the units.

•Internal Forms of Reflection Configuration (Filling pattern)

1-Onlap2-Prograding3-Mounded onlap4-Divergent5-Complex6-Chaotic

Internal Reflection Configuration (Filling Pattern)

Onlap Prograding Mounded onlap

Low-energy filling oferosional channel

Low-energy filling of erosionalchannel

Higher-energy fill

in at least two stages.

Very high-energy fill,possibly sand-prone.

Sediment transport over the edge of thechannel or along channel at a bend.

Compactable (shale-prone)low-energy sediments

Divergent Complex Chaotic

2-Seismic StratigraphyCategories-Seismic Facies Analysis

Internal Reflection Configuration (Filling Pattern)Onlap

Prograding

Mounded onlap

Divergent

Chaotic

Complex

Mounded onlap

Apparent Dip

relation to the

channel

Internal & External Forms Configurations

The overall geometry of a stratigraphic, or seismic unit, consists of the internalform and the external reflection configuration of the unit. Both must be describedto understand the geometric interrelation and depositional setting of the units.

•Internal Forms of Reflection Configuration (Filling pattern)

g ( g p )

1-Onlap

2-Prograding3-Mounded onlap4-Divergent5-Complex6-Chaotic

Prograding Pattern types

Obli Oblique

Internal Reflection Configuration (Filling Pattern)

Sigmoid

Tangential

Hummocky Clinoforms

Shingled Complex Sigmoid-Oblique

Oblique Oblique

Parallel

sheet drape wedge bank lens

External Reflection Configuration

fanmound

front slope fill channel fillTrough fill

Basin fill

External forms of reflection configuration

Trough Fill

Seismic example illustratingthe complicated stratigraphyof a submarine slope valleyfill with adjacent leveedeposits. Image taken from

Mayall et al., 2006.

Front Slop Fill

Basin Fill

This 2D seismic line (BGS1993_02_C) is aligned NW-SE across the Hatton Basin. Buried volcanicescarpments are imaged on both margins of the basin. Each has a relief of c. 1 second TWT. The escarpments

are buried beneath the Tertiary sedimentary fill of the Hatton Basin, which thins towards the basinmargins, onlapping the flanks.

Channel fill

---684m--

A: Braided (low sinuosity, multi-channel stream)

B: Meandering (high sinuosity, single channel stream)C: Straight (low sinuosity, single channel stream)

Channel fill

Incised Valley System

NENESW

Seismic StratigraphySeismic Facies Analysis

Submarine Channel

Pliocene submarine channel-Nile Delta

2.75 02.5 km

Deposition occurs on inner

bends (point bars) and

erosion on outer bends.Cross-over reaches between

bends are largely area of

sediment transfer

Incised Valley System

Incised Canyons sourcing sediment down slope Off shore Mediterranean

Mark Incised Valley System

2- Reflection continuity:

• Bedding continuity

• Depositional processesHigh Continuity(continuous strata deposited inwidespread and uniformenvironment, (marineconditions)

Low Continuity(sediments deposited withvariable energy (by fluvial-Alluvial currents)

Difference incontinuity du todifferent shootingparameters

3- Amplitude

Low amplitudeHigh amplitude

Amplitude is the height ofreflection peak and it dependent

on the reflection coefficient.

•Vertical change in amplitude canbe used to locate unconformities.

•Lateral change can be used to helpdistinguish seismic facies.

•Lateral changes in amplitude canhelp delineate the edges of brightspots

4- Frequency (Spacing)

It describes the number of reflections

per unit time .

• It is a function of both frequency ofseismic signal and interference effects

High frequency-small spacing

seismic signal and interference effects.

•Vertical change in spacing can be usedto locate boundaries between

depositional sequences.

•Lateral change can be used to inferfacie

Low frequency-long spacing

5- Interval velocity:

Estimation of lithologyEstimation of porosity

Fluid content

Push down

Velocity Anomaly - pull down

V1 < V2Push down (velocity sag) due

to gas accumulation Velocity: V=( /c)4

Estimation of lithology

Estimation of porosity

Fluid content

Plio-Pleistoceneturbidities

Sea floor

5- Interval velocity: Push down Gas Chimney

~ 100 ms

Top Reservoir(= Top A)

Gas chimney emanating from sinkhole;am litude reduction and structural as sa

5-Interval velocity:

Fluid content

Pull up & Pull down

Velocity Anomaly - pull down

V1 < V2

Velocity: V=( /c)4

V2On this seismic line from offshore Angola, the pull-down ofthe yellow marker (bottom of the evaporitic interval) isinduced by the lateral change of the interval-velocity createdby the normal fault which limits a Upper Tertiary depocenter.Indeed, such a fault put limestones (upthrown block) and

shales (downthrown block in juxtaposition.

V1 V2 V2

On this reef geological model, above a planar limestone sole (light blue), a reef with a compressional wavevelocity of 5490 m/s, is laterally bounded by shaly sediments (yellow) with a much lower velocity (3660 m/s),which are overlain by even slower sediments (brown interval, 3050 m/s). The seismic answer of such a model is

roughly depicted on the right. The horizon associated with the bottom of the reef shows a significant pull-up.

Velocity Anomaly - pull up

V1 < V2

Velocity: V=(

V1 V2 V2

Palaeozoic carbonate reef build-ups (Barents Sea)

Velocity Anomaly - pull up

PSDM Migration No pull up Time Migration- pull up anomaly from reef

parallel, even,high amplitude

prograding

ll l di ti

frontslope

chaotic

moundprograding

subparallel

parallel, discontinuous,low amplitude

What is 4D Seismic?

• Is the analysis of differences found in seismic surveys repeated inan area where substantial changes in the subsurface have

occurred, due to production processes– Qualitative

– Quantitative

P id i f ti ith l t l ti it th t id

• Provides information with lateral continuity that provides a

VISION of actual changes in the reservoir– Fluid substitution

– Temperature

– …

4D Seismic - the Concept

• Also known as Seismic Reservoir Monitoring or Time-LapseSeismic

• Consists of 3D seismic surveys, repeated after intervals ofsubstantial production

• Successive surveys analysed for differences

Ob fl id h i th i

• Observes fluid changes in the reservoir

• Available between & beyond the wells

Classification of Gullfaks data

1995 Difference1985

SHCindicator0 1 No change Large change

34 well locations selected; additional 600 million bbl producible reservesfound as result of 4D

Continual Improvement

Foinaven Data, Norwegian Sea

ALI BAKR ALI BAKR ALI BAKR 95 towed

93 reprocessed 95

Flat Spot

Pioneer Examples: Duri Field

•Seismic image of DURI field, where

effects of steam injection are easily

visualized in the seismic data

•D. Lumley, 1995

4D Interpretation Workflows

• Fluid substitution modelling

• Seismic repeatability assessment

• Seismic interpretation

• Seismic attribute extraction

• Classification (Inversion)

• Reservoir optimisation

4D WorkflowFluid

substitution,

modelling Interpretation Inversion-

Classification

Seismic

repeatability

assessment,

wavelet, etc..

Seismic attribute

extraction

Reservoir

optimisation

Fluid Substitution

Synthetic Response to Change in Rock Physics

• Change of physicalparameters

• T dependence

• Fluid factor is veryimportant

• Change of physicalparameters

• T dependence

• Fluid factor is

very important

TEMPERATURA 25A 7A 1A 3A 4A 8A 10A

24,00 2,92 2,65 2,67 3,01 2,81 2,84 2,81

40,00 2,74 2,54 2,56 2,87 2,68 2,64 2,68

60,00 2,52 2,38 2,40 2,70 2,44 2,46 2,53

80,00 2,36 2,22 2,20 2,60 2,31 2,27 2,42

100,00 2,27 2,08 2,11 2,50 2,17 2,15 2,32

125,00 2,17 1,99 2,02 2,41 2,06 2,05 2,19

150,00 2,08 1,91 1,95 2,30 1,98 1,97 2,11

24,00 40,00 60,00 80,00 100,00 125,00 150,00

Serie1

Serie2

Serie3

Serie4

Serie5

Serie6

Serie7

Serie8

Serie9

Serie10

Serie11

Serie12

Serie1328 % 28 %

LS - 2203

importantvery important

4D (Time-Lapse) SeismicGullfaks Field, North Sea

Mapping fluid movements and identifying unswept hydrocarbons

SHC indicator0 1 No change Large change

1989 1996

Time Lapse SeismicSleipner CO2 Storage

1994 1999 2001Monitoring of C02 injection in aquifer

Data courtesy of Statoil

Time Lapse Seismic

Sleipner CO2 Storage

Seismic 1999 Seismic 2002

Amplitude difference and vertical time shift due to cumulated gas effectconduct to erroneous 4D effect if not compensated

Data courtesy of Statoil

4D Summary

• 4D seismic provide important information for decision making analysis

in reservoir management

• Tailor made interpretation tools and workflows for 4D analysis

• Demonstrated the use of qualitative or semi-quantitative 4D analysis

for updating reservoir models

• Seismic to Simulation and Simulation to Seismic (S2S) are established

workflows

• Beyond qualitative interpretation, the link between reservoirengineering and geophysics via rock physics enables quantitative 4D

analysis for reservoir management

What is a Neural Network?

Neural Networks:

• recognize ill-defined patterns without an explicit set of rules

• may adaptively infer heuristic knowledge from sample data

• unlike statistical estimators, they estimate a function without amathematical model of how outputs depend upon inputs

• they are model free estimators, they “learn from experience” with

y y pnumerical and , sometimes, linguistic sample data

• like brains, they recognize patterns we can not define, or what iscalled recognition without definition

OGCI - SER - Neural

Networks and Seismic Facies -

Stratigraphic Interpretation

Seismic Facies: The description and geologic interpretation of seismicreflection patterns including configurations, (continuous, sigmoidal, etc.),frequency, amplitude, and continuity.

Neural Network Technology (NNT): The ability to analyze and classify

Seismic Facies Analysis using NNT: What Is It ?

trace shapes using a discriminating process.

Seismic Facies Map: This is a similarity map of actual traces to a setof model traces that represents the diversity of various trace shapespresent in an interval.

Example for using NNT- Texas Ranch 3D

• 3D Survey - DeWitt Co., Texas

360 inlines - 382 crosslines

82.5’x82.5’ bin spacing (34 sq.miles)4 seconds of data @ 4 msec

W ll D t

Well A(~0.1

MMCFD)

Well B(~1

MMCFD)

• Well Data

Two wells drilled in main channelWell A - 15ft wet sand (“fizzy” water) Well B - 30ft gas sand

SW NEWell B

The Play: Frio Channel Sandstones

Well A Well BRandom Line

“Gas production comes from Oligocene Frio sandstonesdescribed as fluvial channel fills, point bars, and splay depositsdeposited in a plain mudstone”.

Reference

Horizon

FrioChannel

Structural Interpretation

• Horizon Attributes

Time Horizon Map combined

with seismic amplitude atreference horizon.

Note Channel systems.

Stratigraphic play with

Mixed map: Time (in color) and amplitude (in B&W)

Stratigraphic play with

several braided fluvialsystems with bright spots.

… structure-independent.

Structural Interpretation

• Time Slice

Taken at 824 msec.

Main Channel clearlyidentified by bright spots.

Is there a break in the

channel?

Why are the wells different?

• Horizon Slice

Parallel to ReferenceHorizon - 92 msec below.

Continuous channel nowclearly seen.

Still cannot adequatelyexplain differences atwells.

Seismic Facies: The description and geologic interpretation of seismicreflection patterns including configurations, (continuous, sigmoidal, etc.),frequency, amplitude, and continuity.

Neural Network Technology (NNT): The ability to analyze and classifyt h i di i i ti

Seismic Facies Analysis using NNT: What Is It ?

trace shapes using a discriminating process.

Seismic Facies Map: This is a similarity map of actual traces to a setof model traces that represents the diversity of various trace shapespresent in an interval.

Stratigraphic Interpretation Part I

• UnsupervisedRegional Seismic

Facies Analysis

Horizon slices indicate verticalchannel extent of approx. 40 msec.

Seismic Facies map of entire areaover the 40-msec interval and 15model traces.

Channel system characterized bymodel traces 1,2, and 3.

Stratigraphic Interpretation Part I

• Conventional AmplitudeVs. Seismic Facies Approach

The seismic facies map is very…colorful, but we still cannotdifferentiate between the twowells

wells.

Why use seismic facies technologyif it provides the same results as anamplitude-based approach ?

Stratigraphic Interpretation Part I• UnsupervisedChannel SeismicFacies Analysis

Seismic facies map over thechannel system shows a traceshape difference between the Aand B wells

What is the meaning of thistrace shape variation ?Lithology ?Porosity ?Fluid content ?

Petro-Acoustic Modeling• Modeling at Well A

1 2 3 4 65 7 8 9

Input is well logs, seismicfacies model trace, andseismic traces.

Synthetic Seismogramgenerated and calibrated to

Well A Well B

generated and calibrated to

seismic traces.

Model now modified withproperties observed at WellB (30-ft sand). Trace shapechange replicates variation

between A and B.Red=Sonic

Blue=Density

Stratigraphic Interpretation Part II

• 3D Model-BasedPropagation of theMain Channel

Time map of channelhorizon generated usingseismic character at wellsA and B

A and B.

Note: Well A structurallyhigher than well B in thetime domain.

• Supervised SeismicFacies Analysis

“Focused” interpretation, based onpetro-Acoustic modeling results andareal isolation of channel system. B

Model indicates that interval affectedby sand property changes is wider -increase to 72 msec (12 model classes).

Note difference in trace shape at wells.

BARandom line throughwells.

BEFORE showsunsupervised seismicfacies (similar atwells).

BEFORE

AFTER showssupervised seismicfacies (different atwells).

Final Seismic Facies Map of

channel system (in color), mixed

with average amplitude (in B&W)over same interval.

Note channel to south of Well B.B

Neural Networks Consist of:

• numerous, simple processing units or “neurons” that we canglobally program for computation.

• They can be programmed or trained to store, recognize, andassociatively retrieve patterns or database entries to solvecombinatorial optimization problems, to filter noise frommeasurement data, to control ill-defined problems - toestimate sampled functions when we do not know the form of

estimate sampled functions when we do not know the form of

the functions• artificial neural systems may contain millions of nonlinear

neurons and interconnecting synapses and future systemsmay contain billions of real or virtual model neurons

Natural Fracture Classification( A Genetic Classification )

• Tectonic Fractures

– Fold-related, Fault-related• Regional Fractures

– Joints, Cleat

• Contractional Fractures

Chi k i Di i l d C l J i

– Chickenwire, Diagenesis-related, Columnar Joints

• Surface-related & Induced

– Unloading, Spall, Weathering

Fractures Surrounding a Normal

Fault in Miocene Ss

Western Sinai,

EgyptHangingwall

East West

Footwall

S 3S 3

Fractures Around a Normal Fault

Clastics, Brunei

Variations in Fracture Intensity Associated with

Faults are Due To:1. Pre-Slip Effects

• Fracture zone preparing the rock mass for fault slip (halo zone).

• Precedes propagating fault.

• Interactions between propagating fault tips and halos.2. Effects Occurring During Slip

• More fracturing as “hanging wall” moves over an irregular faultsurface.

• Intense deformation occurs at the slip surface leading to a

“damage zone”. 3. Post-Slip Effects

• The presence of faults can warp today’s reservoir stress stategiving local changes in fracture permeability.

• More fractures could be created if the faults are reactivated &/or

inversion takes place (local fracture overprinting).

R.A. Nelson 9/02

Process zone fracturing surrounding a Normal Fault

Volume of rock

fractured prior to

through-going fault

Effective Process Zone (a few hundred feet)

Damage Zone (c. a few

feet)Not to scale

Effective process zone is

the zone that issignificantly greater than

matrix flow.

Damage zone is usuallylow in permeability.

Background

fractures related

fractures due to

normal stress state.

Pre-Slip Fracturing Forming the Process Zone

Fracture Swarm

Background Fracturing

Onset of Fault Slip: Propagating Slip Through

Process Zone

Extending

Process Zone

Process

Propagating Slip

Surface

Fault Propagation Interaction in 3-D Creating

New Fractures

Interacting Faults

Slip-Related Effects:

Fracturing Related to Fault Slip

• Additional fractures are generated as the hanging wall displacesover topography of the fault surface.

• Once generated at the asperity these fracture zones are translateddown the slip direction along the fault.

• If fault slip is small, little slip-related fracturing will take place.

• Curvature maps of the fault surface can be used as a guide forthis prediction.

• Accurate fault plane mapping is critical in predicting these zonesof kinematic fracturing.

R.A. Nelson 9/02

Slip-Related Fracturing in Map View

Outside bend Inside bend

High extensional strain High compressional strain

Displacementtransfer

Left-Lateral

Left-Stepping

Local Stress Variations at Fault Steps & Bends

Right-Stepping

Schematic Map View of an Inversion Fault

with Changes in Fault Strike

Zone of maximum localcompressional strain

Inversion-relatedcompression direction

Zone of maximumlocal extensionalstrain

Schematic Map View of an Inversion Fault with

Changes in Fault Strike

Major InversionFault

Schematic View of Fracture Systems Associated with Secondary

Faults Along Inversion Faults with and without Strike-slip

SecondaryAntithetic Faults Secondary Faults in a

strike-slip scenario

No Strike-slip With Strike-slip

Extension ZoneFracturing

Normal Fault With DipChanges in Cross Section

Kinematic Fracture Zones Associated with

Fault Topography in Cross Section View

Compression ZoneFracturing

Schematic Cross Section of an Inversion Fault

with Changes on Fault Dip

Zone of localextensional strain

Zone of local

compressional strain

Post-rift

Only reversefault fracturesets

Basement

Syn-rift

Post rift

Overprinted normal& reverse faultfracture sets?

Local Fracturing Due to Slip on an Irregular faultSurface

Compression ZoneFracturing

Extension ZoneFracturing

Slip-Related Effects:

Deformation at the Slip Surface

•Once through-going fault slip occurs, the zone immediatelysurrounding the slip surface can experience intensedeformation. (“Damage Zone”)

•This deformation is quite variable and can range from purelyductile to purely brittle.

•There is a relationship between the properties of this zoneand amount of slip.

•The width of these zones can be variable between faults andalong faults but range generally between 1 to 10 m.

•The width and properties of these zones are difficult topredict or image in the subsurface. Observational data basedon cores leads to the best predictions.

R.A. Nelson 9/02

Fracture Process Zone Surrounding a Planar

Normal Fault

Normal Fault Reactivated as a Reverse Fault

Overprinting

Mapping Fault Zone Properties

Geometry, Width and Intensity

1. Gather exploration & show history

2. Compile mechanical, petrophysical & production characteristics ofsection

3. Acquire and map surface & subsurface fracture distributions4. Determine fracture origin and make mechanical predictions of

orientation & intensity

5. Determine in situ reservoir stress directions and magnitudes

6. Constrain subsurface fracture intensity, width, & zone widths and

lengths from image logs, core, and geophysical Attributes7. Predict fracture distribution “sweet spots” from the above

8. Model reservoir volumes of the fracture system

9. High-grade and prioritize potential locations via checklist

10. Select well paths to optimize fracture intercept rate and chooseoptimum completion technique

Fold-Related Fractures

Phosphoria Ls, Black Canyon Anti., WY

Fold-Related Fractures

Seismic Interpretation by Dr. Ali Bakr

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