Slide 1

AVO analysis & rock physics based AVO inversion Stud. MSc Asger Johansen Supervisors: Thomas Mejer Hansen, IMM DTU Ida Lykke Fabricius, BYG DTU 1/46Thesis defence 14/5-2012

Slide 2

Presenting Objectives of the thesis Part I-III Method Results Conclusions Thesis: Discussion Thesis: Conclusion 2/46Thesis defence 14/5-2012

Slide 3

3/46 (picture: Schiler et. al) Nini-1 Area of seismic data Thesis defence 14/5-2012

Slide 4

Objectives 4/46 Investigate and assess the AVO response of North Sea oil and brine saturated greensand from the Hermod formation Investigate the possibility of identifying oil reservoirs from seismic data Investigate the prospects of predicting the physical properties of greensand from seismic data by a rock physics based non-linear AVO waveform inversion AVO response AVO analysis AVO inversion Thesis defence 14/5-2012

Slide 5

Workflow 5/46 AVO response Prospects of inverting seismic data AVO analysis Where to invert AVO inversion Predicting physical properties Thesis defence 14/5-2012

Slide 6

Part I: AVO response of greensand Forward model the AVO response Estimate elastic properties Oil and brine sat. greensand Of an upper and lower reflecting layer Observe the AVO response from seismic data 6/46Thesis defence 14/5-2012

Slide 7

7/46 (picture: Kearey, P. (2002) AVO (Amplitude variation with offset) Thesis defence 14/5-2012

Slide 8

Identified greensand (Oil saturated) 8/46 Thesis defence 14/5-2012

Slide 9

9/46Thesis defence 14/5-2012

Slide 10

10/46 Greensand Balder Ekofisk Thesis defence 14/5-2012

Slide 11

AVO response 11/46 Observed from the seismic data at the Nini-1a well location Thesis defence 14/5-2012

Slide 12

AVO response From seismic data 12/46Thesis defence 14/5-2012

Slide 13

Conclusion - Part I: AVO response of oil sat. greensand AVO response of oil sat. greensand different from brine sat. greensand Oil saturated characterized by: a top reflector which amplitude increases negatively with offset A bottom reflector which amplitude increases positively with offset 13/46Thesis defence 14/5-2012

Slide 14

Part II: Identifying possible oil reservoirs Method of identifying the seismic attribute of oil Visualize the possible oil reservoirs 14/46Thesis defence 14/5-2012

Slide 15

15/46 B (slope) 0 B (slope)= big negative A A Thesis defence 14/5-2012

Slide 16

16/46 Brine sat. Oil sat. Thesis defence 14/5-2012

Slide 17

17/46 Greensand Balder Ekofisk Thesis defence 14/5-2012

Slide 18

18/46Thesis defence 14/5-2012

Slide 19

19/46 Brine sat. Oil sat. Thesis defence 14/5-2012

Slide 20

20/46 Nini-1a location Thesis defence 14/5-2012

Slide 21

21/46 Greatest distance Thesis defence 14/5-2012

Slide 22

Ekofisk 22/46Thesis defence 14/5-2012

Slide 23

23/46Thesis defence 14/5-2012

Slide 24

24/46Thesis defence 14/5-2012

Slide 25

25/46Thesis defence 14/5-2012

Slide 26

Conclusions from part II Method of identifying possible oil reservoirs verified The oil reservoir around Nini-1a and Nini-4 identified Another known oil reservoir identified A third possible oil reservoir identified 26/46Thesis defence 14/5-2012

Slide 27

Part III: AVO inversion Predicting physical properties of greensand from seismic data non-linear AVO waveform inversion Metropolis inversion 27/46Thesis defence 14/5-2012

Slide 28

Principle of the algorithm Iteratively Sampling a realization of the posterior distribution 28/46 Propose model Forward model Misfit to data Accept / reject model Thesis defence 14/5-2012

Slide 29

Forward model Non-linear rock physics model Non-linear reflectivity model Convolution model 29/46Thesis defence 14/5-2012

Slide 30

The rock physics model Hertz-Mindlin grain contact model Modelling: K dry and Estimating: Poisson ratio Glauconite bulk and shear moduli Gassmann fluid substitution Estimating: Mineral modulus 30/46Thesis defence 14/5-2012

Slide 31

Illustrate forward model 31/46Thesis defence 14/5-2012

Slide 32

Sampling a posterior distribution Accept model by: Likelihood of a proposed model Accept: If: L(m_propose) >= L(m_current) Else if: L(m_proposed) / L(m_current) > rand([0:1]) m_current = m_propose Measure of how well the accepted models fits data relative to each other Number of iterations between accepted models SPE meeting 28/2-201232/46

Slide 33

Illustrate sampling method 33/46Thesis defence 14/5-2012

Slide 34

Synthetic reference model Different prior scenarios The waveform inversion requires the elastic properties of the 1. and / or 3. layer to be known Inversion using the Hertz-Mindlin rock physics model is found to require the P eff, C and glauconite to be known 34/46Thesis defence 14/5-2012

Slide 35

Inverting seismic data 35/46 = 0.25 glau = 0.4 F glau = 0.3 C=15 P eff = 22 MPa Oil sat = 0.9 Thesis defence 14/5-2012

Slide 36

Prior distribution 36/46Thesis defence 14/5-2012

Slide 37

37/46Thesis defence 14/5-2012

Slide 38

38/46Thesis defence 14/5-2012

Slide 39

39/46Thesis defence 14/5-2012

Slide 40

Probabilistic estimates on: Porosity Glauconite fraction 40/46 Oil saturation Thesis defence 14/5-2012

Slide 41

Modeling greensand Estimating the: Mineral modulus Poisson ratio Glauconite bulk and shear moduli Investigating these estimates by inversion of seismic data The estimates proposed by Zakir Hossain are verified from seismic data 41/46Thesis defence 14/5-2012

Slide 42

Inverting seismic data Nini-1a A discrepancy observed Seismic data Forward model Elastic properties above the greensand Inversion by a 3-layer model 42/46Thesis defence 14/5-2012

Slide 43

Conclusion part III Feasible to invert the physical properties of greensand from seismic data Requires prior information on both the greensand and the elastic properties above and/ or below Challenge describing the seismic data by a 3- layer model 43/46Thesis defence 14/5-2012

Slide 44

Discussion Thesis: The assessed AVO response depends on the geological setting The method of identifying possible oil reservoirs only indicates a possible seismic anomaly Challenge of inverting seismic data at locations without information from a well log Describing the seismic data by a 3-layer model 44/46Thesis defence 14/5-2012

Slide 45

Conclusion Thesis: The results of part I supported: the possibility of identifying possible oil reservoirs from seismic data by AVO analysis An the possibility of inverting physical properties of greensand by AVO inversion Two possible oil reservoirs identified Inversion of physical properties are feasible however a challenge is encountered Thesis defence 14/5-201245/46

Slide 46

Conclusion Thesis: Elastic properties and the physical properties of greensand are required to be known Inverting the physical properties at the two unknown possible reservoirs was not possible 46/46Thesis defence 14/5-2012