seismic interpretation

SEISMIC INTERPRETATION

RESERVOIR CHARACTERIZATION

UNIVERSITAS GAJAH MADA

20 OCT 2012

GERANICKY DELISATRA

PHE ONWJ

Geranicky Delisatra, Geophysicist – PHE ONWJ

Presentation Outline

• Introduction

• Fundamental of Seismic

• Seismic Data Acquisition & Processing

• Seismic Interpretation

• Reservoir Characterization Method

• Introduction

Introduction

• Seismic play an important role in every phase of oil &

gas industry

• Exploration phase usually 2D seismic data;

exploration play concept, prospect identification,

exploration well drilling, appraisal well drilling

• Development phase usually 3D seismic data;

reservoir characterization, geological modeling, infill well

drilling, field development

• EOR usually 4D seismic data; reservoir monitoring

Exploration

Source Rock ?

Structural Trap

Stratigraphic Trap

• Working with minimum

data; wells, seismic, etc

• Building exploration

concept

• Prospect identification

• Prove petroleum system

• If exploration well succeed,

drill appraisal well to

estimate reserve

accumulation

Transport

ComplexBasement high/

Thinned section

Figure 7: Idealized GDE Highlighting Additional Features with Patterns

MUDSTONES

BASIN FLOOR

MUDSTONES

Nonmarine

Deep Water Sands

(Fans)

Deep Water Sands

(Fans)

Development

• Dealing with numbers of well data, 3D seismic, engineering

• More detailed work; field scale to reservoir scale

• Reservoir characterization; property prediction, fluid

identification

• Building geological model as an input for reservoir

simulation

• Using 4D seismic data

• Monitoring movement of CO2 injection

• Introduction

Basic Seismic Concepts

S = R * W

S = Seismic

R = Reflection Coeff.

W = Wavelet

Polarity & Phase

Normal Polarity Reverse Polarity

Minimum Phase

Zero-Phase

Knowing Polarity & Phase

What is the polarity and phase of the above seismic section?

Exercise

ρ = 2.4 g/cc

V = 3000 m/s

Tight Limestone

ρ = 2.7 g/cc

V = 6000 m/s

ρ = 2.4 g/cc

V = 3000 m/s

RC = (IA2 – IA1)

(IA2+IA1) IA = ρ x V

Wet Sandstone

ρ = 2.6 g/cc

V = 4000 m/s

Vertical Resolution

Remember:

λ = V x f

λ = wave length (m)

V = velocity (m/s)

f = frequency (Hz)

• Introduction

Seismic Data Acquisition

• Type of survey:

– Land

– Transition

– Marine

• Type of data:

– 2D

– 3D

Land Acquisition

Transition Zone Acquisition

Marine Acquisition

Seismic Processing

• Introduction

Seismic 2D/3D data Subsurface Geological

Information

What is seismic interpretation?

Required Data for Seismic Interpretation

• Basemap

• Well Data

• …and of course…Seismic Data

Basemap

• Basemap is useful to know your map

view location while interpreting seismic

section

• Basemap will give us information about

coordinates, well location, 2D seismic

lines, 3D seismic area, scale bar, etc.

Well Data • Type of well data:

Digital data (LAS or ASCII

format)

Hardcopy (Final well report,

well completion, etc.)

• Well Data:

Logs: Gamma Ray, SP,

Resistivity, Density, Porosity,

Checkshot

• Well data will give us information

about geological condition, interest

zone, tested zone, top formation, etc.

CS KORINCI-1A

y = 0.0003x2 + 0.6078x + 9.5

R2 = 0.9992

0 200 400 600 800 1000 1200

TIME (ms)

General Steps in Seismic Interpretation

WELL-SEISMIC-TIE

FRAMEWORK MAPPING

- HORIZON PICKING

- FAULT MAPPING

TIME-STRUCTURE

DEPTH-STRUCTURE

TIME-DEPTH

CONVERSION

Well-to-Seismic Tie

• A process of tying well data

with seismic data by

correlating synthetic

seismogram with seismic

• Matching between well

marker (formation top,

top/bottom reservoir, etc.)

with certain reflector event in

seismic data

• Decide which reflector event

will be picked as horizon

Top B2a

Top B2b

Top B3a

Top B4a

Horizon Picking • This step is done after defining

which recletor event will be

picked as horizon

• Most of seismic interpretation

work is horizon picking

• Purpose : framework mapping,

amplitude mapping

What event to be picked? Well-to-seismic

tie will give you the answer

Horizon Picking

Amplitude Extraction

Structure Mapping

Fault Interpretation

• Fault interpretation must be

confirmed with regional geology

(strike/dip), tectonic regime

(extensional/compressional), etc.

• Know your fault better; is it normal

fault? Thrust fault? Wrong fault

interpretation will lead into wrong

framework

Time-Structure Map

• Picked horizon and fault will be grid to

generate structure map. Since horizon

value is in time domain, the structure map

is called time-structure map

• To have a real subsurface information,

time-structure map should be converted

into depth-structure map

Time-Depth Conversion

• Required data to convert time-structure map to depth-structure map is velocity

• Remember; D = V x t

• Velocity data can be obtained from:

– Checkshot

– Stacking data

– VSP

• Depth-structure map is a product of multiplying time-structure map with velocity function. Velocity is varied with depth and geological condition

CS KORINCI-1A

y = 0.0003x2 + 0.6078x + 9.5

R2 = 0.9992

0 200 400 600 800 1000 1200

TIME (ms)

Depth-Structure Map Time-structure Map Depth-structure Map

• Depth-structure map represent subsurface structural condition

• Due to velocity variation, depth-structure map can be different with time-

structure map

• Depth-structure map should be confirmed with depth at well location

Direct Hydrocarbon Indicator (DHI)

• A quick look for hydrocarbon indicator

• Common DHI:

– Bright spot

– Dim spot

– Polarity reversal

– Flat spot

• Can be a pitfall too!

Bright Spot

Dim Spot

Polarity Reversal

Flat Spot

Some Technique to Guide Seismic Interpretation

• There are some technique to guide seismic interpretation

• Using seismic attributes (phase, frequency, amplitude)

• Good for quick interpretation

Coherency

Coherence Reflectivity (amplitude)

• Coherency attribute

detects discontinuity

in seismic reflector

• Good in detecting

fault or stratigraphic

features

Instantaneous Phase Reflectivity (Amplitude)

Instantaneous Phase

• Instantaneous Phase

attribute balance the

weak and strong

reflector

• Good in tracing

reflector continuity

Instantaneous Frequency Reflectivity (Amplitude)

Instantaneous Frequency

• Instantaneous Frequency gives an information

regarding frequency at certain time

• Gas column will absorp frequency content,

therefore, frequency below gas column will be

decreased

• Good in analyzing bright spots

Some Problems & Pitfall

• False Bright Spot

• Pull-up effect

• Mis-tie

False Bright Spot

• Gas sand and coal have a low impedance contrast with overlying shale

• Both gas sand and coal will give strong negative amplitude

• Lesson learned: bright spot is not always a good news!

Pull-up Effect

Mis-tie

• Mis-tie is a time gap between

intersecting seismic lines due

to different vintage or different

processing parameter ataupun

parameter processing yang

berbeda

• Mis-tie only occur in 2D

seismic data

• Introduction

Reservoir Characterization Method

• Seismic reservoir characterization is necessary

to predict reservoir property (porosity, Sw, etc.)

and its fluid contents (oil, gas, water)

• More quantitative analysis

• Require Rock Physics

• Basically, there are 2 main methods:

– Seismic AI Inversion

– Amplitude Variation with Offset (AVO)

– Multi-attribute

Seismic AI Inversion

Basic Theory

Seismic Acquisition

Earth * Wavelet = Seismic

Seismic / Wavelet = AI

Seismic Inversion

AI Earth

Reservoir Characterization

Workflow

Wavelet

Estimation

Feasibilty

Buidling

Initial Model

Invert

Seismic

Workflow

Wavelet

Estimation

Feasibilty

Buidling

Initial Model

Invert

Seismic

Workflow

Wavelet

Estimation

Feasibilty

Buidling

Initial Model

Invert

Seismic

Workflow

Wavelet

Estimation

Feasibilty

Buidling

Initial Model

Invert

Seismic

AVO stands for Amplitude Variations with Offset, or

Amplitude Versus Offset

The AVO technique uses the amplitude variations of pre-

stack seismic reflections to predict reservoir fluid effects

Basic Concept

Velocity

+ + + =

Basic Theory

Offset

AVO Classification

The Rutherford and Williams classification scheme as

modified by Ross and Kinman (1995).

Class 1

AI Sand >

AI Shale

Class 2

AI Sand ≈

AI Shale

Class 3

AI Sand <

AI Shale

Straight to…Case Study!!!

Background • Shallow biogenic gas in Lower Petani

Fm. → main exploration target

• Appear as ‘bright spot’ on Post-stack seismic section

• Coal in Upper Petani Fm. also appear as ‘bright spot’

• Bright spot can be a DHI, but also a pitfall as well

• Several dry-holes by the same pitfall

Gas Sand

UGM-1 UGM-2

Decrease Impedance

What Makes it Happen?

Decrease in Impedance cause a negative Reflective

Coefficient, and therefore appear as strong negative

amplitude in seismic section

UGM-1 UGM-2

Relationship Between AI & AVO Class

• Shallow biogenic gas are above 1200 m

• AI value of gas sands < shale Low impedance sand

• The crossplot between AI and depth suggest that those shallow gas is classified into class 3 gas sand

AVO Modeling of Gas Sand and Coal

Property Synthetic Modeling AVO Curve

AVO Classification

Gas Sand

Intercept (-)

Gradient (-)

AVO Class 3

Intercept (-)

Gradient (+/-)

AVO Class ???

AVO cross-plotting involves plotting the intercept against the gradient and

identifying anomalies. The theory of cross-plotting was developed by

Castagna et al (TLE, 1997, Geophysics, 1998) and Verm and Hilterman

(TLE, 1995)

AVO Cross-plot Theory

AVO Crossplot Analysis

• Cross-plot between intercept and gradient of pre-stack data confirms the model

• Gas sand anomaly is fall into class 3 gas sand region, while coal is tend to fall between mud-rock line and class 4 region

Multi-attribute

Multi-attribute analysis is a method

which uses more than one seismic

attribute to predict reservoir

physical properties based on well

logs data (Russell et. al, 1997)

You don’t have to

remember this!

Comparison between Inversion and

Multi-atttribute

Multi-attribute

Workflow

Prediction

Feasibilty

Generate

Pseudo-log

Volume

Workflow

Prediction

Feasibilty

Generate

Pseudo-log

Volume

Workflow

Prediction

Feasibilty

Generate

Pseudo-log

Volume

Other Methods

• Other methods in seismic reservoir

characterization is a combination of

Inversion and AVO

• For example:

– Lamda Mu Rho (AVO inversion)

– Simultaneous inversion (AVO inversion)

– Elastic Impedance/Extended Elastic

Impedance (AVO inversion)

Image Rights

Images are courtesy of:

• BP

• PHE ONWJ

• Chevron

• Fugro-Jason

• PGS

• Elnusa

• EMP

Thank You

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