Elastic impedance

An integrated innovative multidisciplinary approach has been used to estimate effective porosity (PHIE), shale volume (V sh ), and sand probability from prestack angle gathers and petrophysical well logs within the Lower Triassic Havert Formation in the Goliat field, Southwest Barents Sea. A rock-physics feasibility study revealed the optimum petrofacies discriminating ability of extended elastic impedance (EEI) tuned for PHIE and V sh . We then combined model-based prestack inversion outputs from a simultaneous inversion and an EEI inversion into a multilinear attribute regression analysis to estimate absolute V sh and PHIE seismic attributes. The quality of the V sh and PHIE prediction is shown to increase by integrating the EEI inversion in the workflow. Probability distribution functions and a priori petrofacies proportions extracted from the well data are then applied to the V sh and PHIE volumes to obtain clean and shaly sand probabilities. A tectonic-controlled point-source depositional model for the Havert Formation sands is then inferred from the extracted sand bodies and the seismic geomorphological character of the different attributes. IntroductionThe past two decades have seen a significant increase in the use of quantitative seismic interpretation methods to characterize the subsurface. Quantitative seismic interpretation techniques are increasingly being implemented into reservoir characterization schemes to minimize hydrocarbon exploitation risks. The measured seismic data respond to the contrasts in the effective elastic properties in the subsurface area of investigation. However, the main goal is usually aimed at characterizing the different lithofacies, porosity distribution, and fluid content responsible for the effective elastic response. These underlying properties are only indirectly measured using the available proxies in the seismic data, which are then transformed to the geologic variables of interest using rock physics.Direct hydrocarbon indicators (DHIs) from seismic data are not always successful because the seismic amplitude is a composite response of the saturated rock. Therefore, it is important to spend as much time characterizing the lithology response before fluid anomaly hunting. Reservoir quality assessment from seismic, well log, and laboratory data requires an integrated approach involving geology, petrophysics, rock physics,

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“…The concept of elastic impedance (EI) was first introduced by Connolly (1999). EI is the equivalence of AI for nonzero incidence angles.…”

Section: Eei Inversionmentioning

confidence: 99%

Prestack inversion and multiattribute analysis for porosity, shale volume, and sand probability in the Havert Formation of the Goliat field, southwest Barents Sea

et al. 2017

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“…2) The definition of an AVA classification scheme that predicts the likely character of a reflective interface from relative variations in reflectivity (Rutherford and Williams, 1989;Castagna and Swan, 1997). 3) Attributes derived from I and G can be diagnostic indicators of variations in fluid-related properties, including porosity, pressure, and saturation (Fatti et al, 1994;Connolly, 1999;Landrø, 2001). …”

Section: Approximations To the Knott-zoeppritz Equationsmentioning

confidence: 99%

Approximations to seismic AVA responses: Validity and potential in glaciological applications

Booth

Emir²,

Diez

2016

GEOPHYSICS

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Amplitude-variation-with-angle (AVA) methods establish the seismic properties of material either side of a reflective interface, and their use is growing in glaciology. The AVA response of an interface is defined by the complex Knott-Zoeppritz (K-Z) equations, numerous approximations to which we typically assume weak interface contrasts and isotropic propagation, inconsistent with the strong contrasts at glacier beds and the vertically transverse isotropic (VTI) fabrics were associated with englacial reflectivity. We considered the validity of a suite of approximate K-Z equations for the exact P-wave reflectivity R P of ice overlying bedrock, sediment and water, and englacial interfaces between isotropic and VTI ice. We found that the approximations of Aki-Richards, Shuey, and Fatti match exact glacier bed reflectivity to within R P AE 0.05, smaller than the uncertainty in typical glaciological AVA analyses, but only for maximum incident angle θ i limited to 30°. A stricter limit of θ i ≤ 20°offered comparable accuracy to a hydrocarbon benchmark case of shale overlying gas-charged sand. The VTI-compliant Rüger approximation accurately described englacial reflectivity, to within R P AE 0.01, and it can be modified to give a quadratic expression in sin 2 ðθ i Þ suitable for curve-matching operations. Having shown the circumstances under which AVA approximations were valid for glaciological applications, we have suggested that their interpretative advantages can be exploited in the future AVA interpretations.

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“…Therefore, the attention paid by specialists to technologies that are aimed to study anisotropy of properties of the section becomes understandable [20,[25][26][27][28][29][30][31].…”

Section: Azimuth Processing Of Seismic Data To Overcome Geological Chmentioning

confidence: 99%

Chayandinskoye field is the project of new technologies implementation in East Siberia

Davydov¹,

Pogretckii²,

Smirnov³

et al. 2017

Вестник ПНИПУ. Геология. Нефтегазовое и горное дело

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Elastic impedance

Abstract: Figure 1. Comparison of an AI curve with a 30°EI curve for the Foinaven discovery well 204/24a-2.

Cited by 519 publications

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Prestack inversion and multiattribute analysis for porosity, shale volume, and sand probability in the Havert Formation of the Goliat field, southwest Barents Sea

Prestack inversion and multiattribute analysis for porosity, shale volume, and sand probability in the Havert Formation of the Goliat field, southwest Barents Sea

Approximations to seismic AVA responses: Validity and potential in glaciological applications

Chayandinskoye field is the project of new technologies implementation in East Siberia

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