IMPEDANCE MICROSTRUCTURE OF KEROGEN SHALES
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1 IMPEDANCE MICROSTRUCTURE OF KEROGEN SHALES Manika Prasad Rock Abuse Laboratory Colorado School of Mines Presented at the 27th Oil Shale Symposium at CSM on October 17, 2007
2 OUTLINE Motivation Working Principles Quantitative Studies Ultrasonic Impedance Analyses Impedance Microstructure Conclusions October 17, th Oil Shale Symposium at CSM
3 MOTIVATION Microstructural investigations based on impedance changes Quantitative impedance mapping Mapping with μm resolution quantify textures as impedance values quantify textural changes with maturation Non-destructive evaluation October 17, th Oil Shale Symposium at CSM
4 POROSITY - VELOCITY RELATION Vp (km/s) Low porosity shales High porosity shales sandstones Fractional porosity Data from Vernik and Liu, 1997 Increasing shaliness Sandstones 27th Oil Shale Symposium at CSM High porosity kerogen shales resemble sandstones Low porosity kerogen shales require different approach
5 MATURATION - VELOCITY RELATION 7 6 high porosity Vp increases with maturity in low porosity kerogen shales Vp (km/s) Stage II III - IVa IV V - VI Maturity stage
6 ACOUSTIC MICROSCOPY circulator HF pulse generator Receiver Image storage sample Scanning system Monitor Y C-scan transducer X water Z A-scan B-scan Rayleigh waves
7 QUANTITATIVE INFORMATION Gray scale calibration with materials of known impedance. Gray color in image of unknown sample gives its AI values μm 200 μm October 17, th Oil Shale Symposium at CSM
8 MATURITY GRADE: II 62.5 μm Bakken Formation October 17, μm 7.4 Elongated grains Very low acoustic impedance 27th Oil Shale Symposium at CSM 1000 μm
9 MATURITY GRADE: II 100 μm Woodford Formation October 17, μm 27th Oil Shale Symposium at CSM Elongated grains Very low acoustic impedance 200 μm 13-19
10 MATURITY GRADE: III Bazhenov Formation October 17, μm 1000 μm Fine grained, elongated grains Low acoustic impedance 27th Oil Shale Symposium at CSM 1000 μm 23
11 MATURITY GRADE: III 7.7 Bakken Formation 1000 μm 200 μm μm Elongated grains, connected textures Low acoustic impedance
12 MATURITY GRADE: IVa 10 Bazhenov Formation October 17, μm 1000 μm Coarser grained Higher acoustic impedance 27th Oil Shale Symposium at CSM
13 MATURITY GRADE: IVb μm 312 μm Bakken Formation 312 μm Coarser grained, elongated texture Higher acoustic impedance October 17, th Oil Shale Symposium at CSM
14 MATURITY GRADE: V μm 312 μm 312 μm Woodford Formation Coarser grained, elongated texture Higher acoustic impedance
15 HYDROGEN INDEX - ACOUSTIC TEXTURE Transition from kerogen loadbearing (immature) to grain supported (mature) 1 mm Bakken Shales
16 HYDROGEN INDEX - ACOUSTIC TEXTURE Transition from kerogen loadbearing (immature) to grain supported (mature) 62 µm Bakken Shales
17 HYDROGEN INDEX - Vp RELATION Vp(km/s) mature Fast Slow immature Hydrogen Index Vp increases with increasing shale maturity Bakken Shales
18 HYDROGEN INDEX - IMPEDANCE Impedance (Mrayls) mature Bulk Impedance Hydrogen Index Micro-Impedance immature Impedance increases with increasing shale maturity. Ultrasonic values match well with AM values Bakken Shales
19 MICRO- AND MACRO IMPEDANCE Bulk impedance increases with maturation Microstructural changes Micro-impedance increases with maturation Remote detection of kerogen maturity October 17, th Oil Shale Symposium at CSM
20 Statistical tools for texture analysis Heterogeneity Coeff. of variation (CV) Mukerji and Prasad, 2005 CV = std. dev{i(x,y)} / mean{i(x,y)} Autocovariance function (ACF) R( m, n) {[ I( x, y) m ][ I( x + m, y + n ]} = E ) I m I Fourier transform Iˆ( kx, k y ) = I( x, y)exp{ i( xkx + yky )} dxdy Power spectrum S( k x, k y ) = Iˆ Iˆ S R
21 Autocovariance Function & Textures From Mukerji and Prasad, 2005
22 Textural anisotropy ratio (AR) ACF 1/e ~ 0.37 lag a min a max a r = a max/a min From Mukerji and Prasad, 2005
23 Texture analysis Textural Heterogeneity Coeff. of variation CV Larger contrast of heterogeneity leads to high values of CV Textural Anisotropy Anisotropy Ratio AR Textural anisotropy leads to a directional dependence of the ACF Textural Scale Mean correlation length Larger sized heterogeneities lead to larger correlation lengths From Mukerji and Prasad, 2005
24 Textural anisotropy & scales DEEP Increasing Maturity SHALLOW Textural anisotropy (AR) increases with increasing correlation length With depth (= maturity), textural anisotropy increase is lower while the mean correlation length increase is larger Deeper samples have lower anisotropy but larger heterogeneities From Mukerji and Prasad, 2005
25 Textural heterogeneity and scales - depth dependence Increasing Maturity DEEP Mean correlation length decreases as textural heterogeneity (CV) increases deeper samples have larger heterogeneities with higher contrast SHALLOW From Mukerji and Prasad, 2005
26 Textural heterogeneity & shale maturity Coef. of variability TOC (%) Increasing maturity From Mukerji and Prasad, 2005 Coef. of variability Volumetric kerogen content Increasing maturity Bakken
27 Textural anisotropy and maturity -depth & scale dependence 1000 µm 100 µm From Mukerji and Prasad, 2005 Mean Anisotropy Bakken µm µm Volumetric kerogen content Increasing maturity
28 Results from SAM Image Analysis The coefficient of variation (CV) (a measure of impedance heterogeneity) ranges from 7% to about 12%. The mean correlation length tends to increase with increasing heterogeneity. Textural heterogeneity, elastic impedance, velocity, and density increase with increasing shale maturity. The textural spatial correlation length varies with direction. The textural anisotropy (AR) ranges from 10% to about 70% and tends to decrease with increasing depth & maturity. Quantifiable and consistent patterns linking - Texture, - Shale maturity, and - Wave propagation properties
29 CONCLUSIONS Acoustic impedance in kerogen shales increases with shale maturity Bulk impedance matches well with impedance measured on a micrometer scale With increasing maturity, there is a transition from kerogen supported to grain supported framework October 17, th Oil Shale Symposium at CSM
30 ACKNOWLEDGEMENTS The experimental work was done at the Frauenhofer Institute, Saarbrücken in Germany This research is supported by NSF, PRF, and the Fluids Consortium. October 17, th Oil Shale Symposium at CSM
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