Bridging the gap: Using AVO to detect changes in fundamental elastic constants

Gray, David; Goodway, Bill; Chen, Taiwen

doi:10.1190/1.1821163

Cited by 95 publications

(40 citation statements)

References 3 publications

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“…This elastic parameters have been linked to the rock properties (such as lithology, porosity and pore fluids), which can be further used for reservoir characterization and fluids identification (Avseth et al 2005;Fatti et al 1994;Gray et al 1999;He et al 2011;Xu and Payne 2009). Integrating core data, well log and seismic data, the rock physics analysis aims to study the effects of rock physical parameter changes (such as lithologic character, porosity, pore texture, fluid type and saturation) on rock elastic properties (He et al 2011).…”

Section: Objectivesmentioning

confidence: 99%

Rock physics template (RPT) analysis of well logs and seismic data for lithology and fluid classification in Cambay Basin

Gupta¹,

Chatterjee

Farooqui³

2012

Int J Earth Sci (Geol Rundsch)

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The Cambay Basin is 450-km-long north-southtrending graben with an average width of 50 km, having maximum depth of about 7 km. The origin of the Cambay and other Basins on the western margin of India are related to the break up of the Gondwana super-continent in the LateTriassic to Early-Jurassic (215 ma). The structural disposition of the Pre-Cambrian basement-a complex of igneous and metamorphic rocks exposed in the vicinity of the Cambay Basin-controls its architecture. The principal lineaments in the Basin are aligned towards NE-SE, ENE-WSW and NNW-SSE, respectively. Rock physics templates (RPTs) are charts and graphs generated by using rock physics models, constrained by local geology, that serve as tools for lithology and fluid differentiation. RPT can act as a powerful tool in validating hydrocarbon anomalies in undrilled areas and assist in seismic interpretation and prospect evaluation. However, the success of RPT analysis depends on the availability of the local geological information and the use of the proper model. RPT analysis has been performed on well logs and seismic data of a particular study area in mid Cambay Basin. Rock physics diagnostic approach is adopted in the study area placed at mid Cambay Basin to estimate the volume in the reservoir sands from 6 wells (namely; A, B, C, D, E and F) where oil was already encountered in one well, D.In the study area, hydrocarbon prospective zone has been marked through compressional (P wave) and shear wave (S wave) impedance only. In the RPT analysis, we have plotted different kinds of graphical responses of Lame's parameters, which are the function of P-wave velocity, S-wave velocity and density. The discrete thin sand reservoirs have been delineated through the RPT analysis. The reservoir pay sand thickness map of the study area has also been derived from RPT analysis and fluid characterization. Through this fluid characterization, oil-bearing thin sand layers have been found in well E including well D. The sand distribution results prove that this methodology has able to perform reservoir characterization and seismic data interpretation more quantitatively and efficiently.

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Section: Objectivesmentioning

confidence: 99%

Rock physics template (RPT) analysis of well logs and seismic data for lithology and fluid classification in Cambay Basin

Gupta¹,

Chatterjee

Farooqui³

2012

Int J Earth Sci (Geol Rundsch)

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“…Cross-plots of elastic moduli can not only effectively extract lithology information but also better distinguish pore fluids. The Gray et al (1999) approximation provides different approximations for the exact solution of reflectivity carried out using elastic moduli. Gray et al (1999) re-expressed the Aki-Richards (1980) Zoeppritz equation approximation in terms of the parameters ∆l/l , ∆m/m , and ∆r/r ; that is, the Lamé constant, shear modulus, and density reflectivities, respectively: …”

Section: Elastic Impedance Equation With Lamé Parametersmentioning

confidence: 99%

Lamé parameters inversion based on elastic impedance and its application

2006

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parameter data volumes. The Connolly (1999) elastic impedance equation is a function of P-wave velocity, S-wave velocity, and density. Based on this equation, P-wave velocity, S-wave velocity, and density can be extracted from elastic impedance inversion directly but other rock physical parameters such as l and m can only be calculated using the extracted parameters indirectly (Connolly, 1999;Yin et al., 2004) which increases calculation errors. In order to obtain more accurate results and reduce the cumulative errors, it is hoped that these rock physical parameters can be extracted directly.In this paper, we start from the fundamental elastic impedance equation expressed using the shear modulus m, density r, and Lamé parameter l. Using this new elastic impedance equation for inversion, the shear modulus, density, and Lamé parameter data can be extracted from elastic impedance data directly.

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“…However, these equations are very complex; therefore many other geoscientists (Bortfeld 1961;Aki and Richards 1980;Shuey 1985;Smith and Gidlow 1987;Fatti et al 1994;Verm and Hilterman 1995;Gray et al 1999) gave linearized approximations of these. These linearized equations give more intuitive AVO attributes that help to discriminate the fluids and lithologies.…”

mentioning

confidence: 99%

“…These linearized equations give more intuitive AVO attributes that help to discriminate the fluids and lithologies. Shuey (1985) proposed intercept-gradient methods, fluid factor (Smith and Gidlow 1987), impedances (Fatti et al 1994), Poisson reflectivity (Verm and Hilterman 1995), elastic impedance (Connolly 1999), Poisson impedance (Quakenbush et al 2006), elastic parameters (Goodway et al 1997;Chen et al 1998;Berryman et al 2002;Gray et al 1999;Khalid et al 2014b), the pore space modulus (Hedlin 2000) and generalized fluid method (Russell et al 2003). A large number of AVO derived attributes are in practice to discriminate hydrocarbon and non-hydrocarbon saturated reservoir rocks (Swan 1993;Castagna and Smith 1994;Thaper 2012).…”

mentioning

confidence: 99%

AVO forward modeling and attributes analysis for fluid’s identification: a case study

et al. 2015

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Since the four decades amplitude versus offset (AVO) analysis is used extensively in hydrocarbon exploration to discriminate the hydrocarbon fluids from background geology. Conventionally AVO analysis involves calculation of intercept and gradient from a linear fit of compressional wave reflection coefficient to the sine square of the angle of incidence. Mississauga formation of early cretaceous is the reservoir rock in the study area, contains hydrocarbons and condensates in the middle part. It is very difficult to discriminate hydrocarbon fluids from non pay zones due to small thickness and low quality of pay zone. AVO forward modeling is done to estimate and analyze various AVO derived attributes for the discrimination of hydrocarbon from background sand. After calculating the AVO attributes, appropriate pairs of these attributes are crossplotted so that the hydrocarbon and non-hydrocarbon facies cluster together for quick identification and interpretation. In intercept/gradient crossplot the top of the gas zone falls in quadrant II and show clear deviation from background trend. The analysis reveals that oil and gas sand attributes are strongly different from water sand attributes. Among various attributes, the fluid factor and intercept are more promising attribute for fluid discrimination.

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Bridging the gap: Using AVO to detect changes in fundamental elastic constants

Cited by 95 publications

References 3 publications

Rock physics template (RPT) analysis of well logs and seismic data for lithology and fluid classification in Cambay Basin

Rock physics template (RPT) analysis of well logs and seismic data for lithology and fluid classification in Cambay Basin

Lamé parameters inversion based on elastic impedance and its application

AVO forward modeling and attributes analysis for fluid’s identification: a case study

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