2020
DOI: 10.1007/s13202-020-00833-4
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Estimation of reservoir porosity using analysis of seismic attributes in an Iranian oil field

Abstract: The most commonly used data for reservoir description are well and seismic data. Well data such as logs typically provide sufficient vertical resolution but leave a large space between the wells. Three-dimensional seismic data, on the other hand, can provide more detailed reservoir characterization between wells. However, the vertical resolution of seismic data is poor compared with that of well data. Conventionally, seismic data have been used to delineate reservoir structure; however, seismic data can be use… Show more

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Cited by 15 publications
(8 citation statements)
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“…It follows that the variability of acoustic impedance has underlying dependency on porosity. Acoustic impedance attributes and others, derived from seismic data are often used to estimate subsurface porosity distribution (Hampson et al 2001;Na'imi et al 2014;Soleimani et al 2020). In a stochastic reservoir modeling study presented in (Coburn et al 2006, p. 253), acoustic impedance is used to derive porosity trend maps for a carbonate reservoir.…”
Section: Discussionmentioning
confidence: 99%
“…It follows that the variability of acoustic impedance has underlying dependency on porosity. Acoustic impedance attributes and others, derived from seismic data are often used to estimate subsurface porosity distribution (Hampson et al 2001;Na'imi et al 2014;Soleimani et al 2020). In a stochastic reservoir modeling study presented in (Coburn et al 2006, p. 253), acoustic impedance is used to derive porosity trend maps for a carbonate reservoir.…”
Section: Discussionmentioning
confidence: 99%
“…It follows that the variability of acoustic impedance has underlying dependency on porosity. Acoustic impedance attributes and others, derived from seismic data are often used to estimate subsurface porosity distribution (Hampson et al, 2001;Na'imi et al, 2014;Soleimani et al, 2020). Most applications rely on very high correlation between attributes and well log data in order to directly derive porosity values.…”
Section: Discussionmentioning
confidence: 99%
“…A zero-phase seismic wavelet of 200 ms and 18 HZ frequency is extracted from the cube to convert seismic reflection into acoustic impedance. After extracting the seismic wavelet, seismic data are correlated with the synthetic trace produced at the well location . The RMS error and correlation coefficient are calculated, and 82% correlation value is achieved.…”
Section: Materials and Methodsmentioning
confidence: 99%