Geostatistical Inversion of Time-Lapse Seismic Data Inversion of...We have two ways to analyze...

ANNUAL MEETING MASTER OF PETROLEUM ENGINEERING

Pedro Rijo

28/May/2014 Instituto Superior Técnico

Geostatistical Inversion of

Time-Lapse Seismic Data

1

28/May/2014 Instituto Superior Técnico 2

1. What?

2. Why?

3. How?


1. What?

2. Why?

3. How?


Time-lapse seismic data is nothing more than seismic data repeatedly acquired at multiple times,

in order to monitor the changes in seismic response during the production phase.

Year 0 Year 10 Year 20 Year …

4D

SEIS

MIC

Year 0

3D

SEIS

MIC

What is 4D Seismic?


If we know the physical relations that link the measured properties (data) with the properties we

want to estimate (model)…

… then, we can estimate the model from the data using a mathematical tool called inverse

theory.

Earth Model Modelling

Algorithm Seismic Response

INPUT PROCESS OUTPUT

FO

RW

AR

D

MO

DELLIN

G

Seismic Response Inversion Algorithm Earth Model

INPUT PROCESS OUTPUT

INV

ER

SE

MO

DELLIN

G

What is Seismic Inversion?


1. What?

2. Why?

3. How?


We have two ways to analyze time-lapse seismic data:

Qualitatively

Analyse the differences by

direct observation

Without / with reservoir

dynamic model

Quantitatively

Calibration of the dynamic

model through the differences

of the infered seismic attributes

With reservoir dynamic model

Why do we want to perform 4D seismic inversion?


History matching Production forecasting

Production history data

History matching Production forecasting

Production history data

Dynamic properties changes

With 4D Seismic

Without 4D Seismic

Seismic data have been mainly used as a reservoir monitoring tool, but if the quality of the

repeatability is sufficiently good it can be used to determine changes related to reservoir

production. For that reason, this data have been recently used as an additional set of data for

history matching in reservoir applications.

Why do we want to perform 4D seismic inversion?


1. What?

2. Why?

3. How?


Step 2: Estimation of reservoir properties

Step 1: Estimation of elastic properties

This type of problems can be divided in two smaller problems. The first comprises the estimation

of relative changes in elastic properties from seismic differences. The second comprises the

estimation and pressure changes from elastic property changes.

Seismic Response

Elastic properties

Reservoir

properties

Inversion

Rock

Physics

How do we propose to do it?


Based on Soares (2007) work, the Global Stochastic Inversion methodology was first presented

by Caetano (2009). This iterative geostatistical seismic inversion methodology is based on a

direct sequential simulation and co-simulation approaches, multi-point simulation and global

perturbation method.

How do we propose to do it? – Global Stochastic

Inversion



Inversion

However, this method has some limitations.

METHOD LIMITATIONS:

• The uncertainty is only related with the random path/seed of the stochastic simulation

– local uncertainty in the impedance models.

• A spatial continuity pattern is assumed known – no uncertainty.

• A prior AI global distribution is assumed known

– no uncertainty.


To address these limitations, Azevedo (2014) proposed an updated algorithm to enable multi-

scale uncertainty assessment using adaptive stochastic and Bayesian inference algorithms.


Inversion


AI / EI simulated

x Ns

Reflection Coefficients

Synthetic Seismic

Wavelet

Correlation Coefficient

Real Seismic

Best Correlation Cube

x Ns

x Ns

x Ns

Best AI Cube

Well Data

Variograms

START!

Prior Distribution

START!

Particle

Swarm

Optimisation

Co-Simulation

Simulation - DSS

Convolution


Inversion


Hard data Hard data Hard data

AI /EI

Dynamic

properties

changes

AI /EI

Dynamic

properties

changes

DSS / Co-DSS

x Ns

x Ns x Ns

x Ns

Best AI

model

Best AI

model START! START! START!

B C D

Prior

Distribution

Variograms

A

Particle

Swarm

Optimisation

Δ Y0 – Y10 Δ Y10 – Y20

Year 20 Year 10 Year 0



Year 20 Year 10 Year 0

Synt

hetic

Seis

mic

Real

Seism

ic

x Ns x q

Δ Y0 – Y10 Δ Y10 – Y20

B C D A

Correlation Coefficients


x Ns x q

x q x q x q x q x q


How do we propose to do it? – Case Study

To proposed methodology will be tested in a cropped area of the synthetic seismic dataset

Stanford VI-E.


Independent geostatistical acoustic inversion

REA

L

SY

NTH

ETIC

BASE SURVEY 10 YEARS 20 YEARS 30 YEARS


Independent geostatistical acoustic inversion

BASE - 10 10 -20 YEARS 20 - 30 YEARS

REA

L

SY

NTH

ETIC


Thank you!

Geostatistical Inversion of Time-Lapse Seismic Data Inversion of...We have two ways to analyze...

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