Elastic Inversion

8/8/2019 Elastic Inversion

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Elastic Inversion Using Partial

Stack Seismic Data: Case

Histories in China



OutlineOutline

Introduction

Work FlowCase Histories

Conclusions

Introduction



Background of Elastic Parameter Inversion

),,;,,,(222111 S pS p P P

V V V V f R ρ ρ θ =

( )

[ ] )sin(tansin)(

:

sinsin1)(

:&

22

212

)1(0

24

cos2

124

21

2

2

2

22

2

θ θ θ θ

θ θ θ

σ

σ

θ ρ

ρ

−+++≈

−++−≈

∆

−

∆

∆∆∆

P

P

s

s

p

s

P

P

P

S

V

V

P P

V

V

V

V

V

V

V

V

NI A NI RC

Shuey

RC

Richards Aki




Comparison of elastic impedance and acoustic impedance on recognizing of reservoir lithology

(According to Connolly.Patrick,1999)




Result of AcousticImpedance

Inversion

Result of Elastic

Impedance

Inversion

(According to Connolly.

Patrick,1999)

Oil-bearing reservoir

Unidentified

Oil-bearing reservoir

identified clearly



OutlineOutline

Introduction


Conclusions



Seismic data processing

Petrophysical modeling

Elastic impedance generation

Wavelet estimation and horizon calibration

AVA Constrained Sparse Spike Inversion

Work Flow of Elastic Parameter Inversion



Seismic Data Processing Flow

INPUT COMMON-SHOT GATHERS

Amplitude Recovery

Filtering

Spiking Deconvolution

Bandpass Filter

CMP Sorting

Residual Statics

Velocity Analysis

Kirchhoff Pre-stack Time Migration

Common-angle Gather Extraction

Limited-angle Stacking

OUTPUT MIGRATED COMMON-ANGLE DATA

3-D Random Noise Attenuation



0-10 deg 10-20 deg

Full stack20-30 deg

Seismic Data Volume of Partial Angle Gather Stack



Shale volume Total porosity Temperature , pressure, fluid type & density

Vp&Vs modeling of brine-bearing reservoirs

Vp&Vs modeling of oil & gas-bearing reservoirs

Cross-plot analysis of elastic parameters of lithologies & fluids

Petrophysical model： Xu&White (DEM) & SCA

Petrophysical Modeling

Calculation of elastic parameters

Guide to identifying reservoirs & fluids



Petrophysical Modeling

A plot of petrophysical modeling of borehole logging data

Vsh Density M-PVp Sw M-PVsShear

modulusLambda Poisson’s

ratio

Vp/Vs S-imp P-imp Total porosity



Cross-plot Analysis of Elastic Parameters

sh

Sw

Sand

Shale

Oil sand

Brine sand Brine sand

Oil sand

S-impedance

P -i m p e d an c e

Lambda

V p / V s

P -i m p e d an c e

Vp / Vs

S-impedanceP-impedanceVp / VsSwTotal-ProVsh



Wavelet & synthetic seismogram

(0-10deg angle gathers stack)

Wavelet Estimation and Horizon Calibration

Various wavelets are extracted from near, middle and far offset angle gather stack

seismic data using elastic impedance curves corresponding with angle series of seismic data.







Wavelet analysis of different angle gathers

0-10deg

10-20deg

20-30deg

Wavelet Estimation and Horizon Calibration

Interpolated wavelet

& interpolation weights

Wavelet amplitude spectrum, phase spectrum, and time-frequency analysis



OutlineOutline

Introduction


Conclusions

Case Histories



0-10

deg

10-20

deg

20-30

deg

Case 1. Changqing Oilfield

Coal bed



S-impedance

P-impedance


Gas sandstone

Sandstone existence




Lambda

Gas sandstone

Well BWell A

Gas sandstone

Vp/Vs



0-12deg 12-24deg

fullstack24-36deg

Case 2. Zhunger Oilfield



P-impedance of post-stack acoustic inversion


P-impedance of pre-stack elastic inversion



Poisson’s ratio


S-impedance



Vp/Vs

S-impedance





Red and yellow colorsshow the favorable

distribution of

oil-bearing reservoirs

Favorable area :

40 Km2

Dry well

Oil well

Proposed well



OutlineOutline

Introduction


Conclusions Conclusions



Elastic inversion is more powerful than conventional post-stack

acoustic inversion, which provides more petro-physical parameters

used in identifying lithology and fluid distribution in a reservoir.

Our elastic inversion result fits very well with drilling results.

Elastic inversion obviously is a major direction in reservoir

characterization.

Conclusions



Thank you for

your attention!

Elastic Inversion

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