The Using of Vp/Vs Ratio and P-Impedance for Differentiate Both Fluid Sand Lithology Depending on Rock Physics Templates Model of Mishrif and Nahr Umr Formations in Kumait and Dujaila Oil Fields Sothern Iraq

Nssir, Nowfal A.; Al-Banna, Ahmed S.; Al-Sharaa, Ghazi H.

doi:10.5958/2320-3234.2020.00025.6

Cited by 3 publications

(4 citation statements)

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“…Conversely, the cross-plot of Vp/Vs ratio against Acoustic Impedance, Lambda-Rho (λρ) against Vp/Vs, Mu-Rho against Density and Lambda-Rho (λρ) against Mu-Rho (μρ) distinguished reservoir R_5500 into three zones namely hydrocarbon bearing zone, brine sand zone and shale zone using the water saturation has colour indicator for wells HAX 01, 02, 03, and 04 indicative of both lithology and fluid discrimination. From these cross-plots the clusters with the least water saturation correspond to highly charged hydrocarbon saturation sand while clusters with maximum water saturation correspond to non-hydrocarbon zone (brine sand and shale) [32,33].…”

Section: Discussionmentioning

confidence: 99%

“…The results also show that the hydrocarbon bearing sand density colour-code is lower than water saturated sand for hydrocarbon bearing sand because water is denser than oil while water saturated sand has a lower density than shale [36,37]. Therefore, clusters with higher density values coloured black represent shale, while the low density clusters coloured (orange and purple) represent hydrocarbon bearing [32][33][34][35][36][37]. This cross-plot shows better lithology and fluid discrimination along the acoustic impedance axis, indicating that the acoustic impedance attribute will better describe the R_5500 reservoir conditions in terms of lithology and fluid content than Vp/Vs ratio.…”

Section: P /V S Ratio Versus P-impedancementioning

confidence: 96%

“…14(A-D) distinguishes the reservoir of interest into four zones namely; shale zone (black ellipse), brine sand (blue ellipse), oil (orange ellipse) and gas sands (purple ellipse). The Vp/Vs ratio is lower in hydrocarbon bearing sand than shale since shear waves cannot propagate during fluids [32,33]. The results show shale having high values in each Vp/Vs and AI than hydrocarbon bearing sand with low values of AI and Vp/Vs ratio [32][33][34][35][36].…”

Section: P /V S Ratio Versus P-impedancementioning

confidence: 99%

“…The Vp/Vs ratio is lower in hydrocarbon bearing sand than shale since shear waves cannot propagate during fluids [32,33]. The results show shale having high values in each Vp/Vs and AI than hydrocarbon bearing sand with low values of AI and Vp/Vs ratio [32][33][34][35][36]. The results also show that the hydrocarbon bearing sand density colour-code is lower than water saturated sand for hydrocarbon bearing sand because water is denser than oil while water saturated sand has a lower density than shale [36,37].…”

Section: P /V S Ratio Versus P-impedancementioning

confidence: 99%

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Fluid and Lithology Discrimination for Reservoir Characterization of HAX Field, Offshore Niger Delta

Umeadi

Balogun

2023

AJR2P

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Fluid and lithology discrimination for reservoir characterization of HAX field, offshore Niger Delta was carried out in this study. Three reservoir intervals, R_4500, R_5500, and R_6500 were picked, identified, and correlated across the four wells; but only the R_5500 reservoir was analyzed. The cross-plot analysis of elastic rock properties with reservoir properties such as Vp/Vs ratio against Acoustic Impedance, Lambda-Rho against Vp/Vs, Mu-Rho against Density, and Lambda-Rho against Mu-Rho colour-coded by gamma ray, water saturation, and density respectively was carried out for fluid and lithology discrimination. The result of these elastic rock properties when colour-coded with gamma ray distinguished reservoir R_5500 into the sand zone and shale zone for the four wells, these results depict lithology discrimination as predominantly found in the Niger Delta basin. Consequently, when colour–coded by water saturation reservoir R_5500 was distinguished into three zones namely the hydrocarbon bearing zone, brine sand zone and shale zone indicative of both lithology and fluid discrimination. From these cross-plots, the clusters with the least water saturation correspond to highly charged hydrocarbon saturation sand while clusters with maximum water saturation correspond to non-hydrocarbon zone (brine sand and shale). Finally, when colour–coded by density reservoir R_5500 was distinguished into four zones namely gas sand zone and oil sand zone, brine sand zone, and shale zone indicating fluid types. The result shows relatively lower Acoustic Impedance, Vp/Vs ratio, lambda-rho, mu-rho, and density (as the colour-code) values indicating hydrocarbon bearing sand while the relatively higher Acoustic Impedance, Vp/Vs ratio, lambda-rho, mu-rho and density (as the colour-code) values are associated with non-hydrocarbon zone (shale and brine sand). This study has been able to discriminate hydrocarbon reservoirs using the cross-plots of elastic rock properties in the zone of interest and proven that the HAX field is viable in terms of hydrocarbon prospects and highly economical for production.

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Section: Discussionmentioning

confidence: 99%

Section: P /V S Ratio Versus P-impedancementioning

confidence: 96%

Section: P /V S Ratio Versus P-impedancementioning

confidence: 99%

Section: P /V S Ratio Versus P-impedancementioning

confidence: 99%

See 2 more Smart Citations

Fluid and Lithology Discrimination for Reservoir Characterization of HAX Field, Offshore Niger Delta

Umeadi

Balogun

2023

AJR2P

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Identification and modeling of the hydrocarbon-bearing Ghar sand using seismic attributes, wireline logs and core information, a case study on Asmari Formation in Hendijan Field, southwest part of Iran

Abdolahi

Chehrazi

Kadkhodaie

et al. 2022

Model. Earth Syst. Environ.

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Lithofacies discrimination using seismic anisotropic attributes from logging data in Muglad Basin, South Sudan

Deng¹,

Hwang

Jang

2022

Open Geosciences

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The identification of formations in anisotropic reservoirs using seismic reflection data and logging data may lead to misrepresentations of the actual formations. Lithofacies discrimination intrinsically has ambiguity, and the depositional sequences of the study area comprise shales, fine-grained sands, and silts. So it needs to reduce the uncertainty of the lithofacies discrimination using anisotropic parameters. This study proposes an approach involving seismic anisotropic parameters to discriminate between different lithofacies. We calculate four anisotropic parameters (ε, δ, γ, η) from logging data (V p, V s, and density) and then employ these for lithofacies discrimination. We compared our results to lithofacies discrimination based on traditional parameters such as V p/V s ratio, clay volume, and water saturation. Using field data from Muglad Basin in South Sudan, we show how the suggested parameters could be used to identify eleven zones with distinct lithofacies. According to the anisotropic parameters, the lithofacies discrimination results are similar to other logging data, and it is easier to separate the lithofacies than petrophysical data. Furthermore, we introduce a new parameter, i.e., the difference between the normalized anisotropic δ parameter and clay volume, which can be used as a possible indicator for heavy oil reservoirs. The new parameter matches well with water saturation in the field data application.

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The Using of Vp/Vs Ratio and P-Impedance for Differentiate Both Fluid Sand Lithology Depending on Rock Physics Templates Model of Mishrif and Nahr Umr Formations in Kumait and Dujaila Oil Fields Sothern Iraq

Cited by 3 publications

References 0 publications

Fluid and Lithology Discrimination for Reservoir Characterization of HAX Field, Offshore Niger Delta

Fluid and Lithology Discrimination for Reservoir Characterization of HAX Field, Offshore Niger Delta

Identification and modeling of the hydrocarbon-bearing Ghar sand using seismic attributes, wireline logs and core information, a case study on Asmari Formation in Hendijan Field, southwest part of Iran

Lithofacies discrimination using seismic anisotropic attributes from logging data in Muglad Basin, South Sudan

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