Elastic and nonelastic deformation of greensand

Hossain, Zakir; Fabricius, Ida Lykke; Christensen, H.F.

doi:10.1190/1.3064151

Cited by 10 publications

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“…(b) Cemented greensand model shows micro crystalline quartz cement (QC) on quartz (Q) grains and berthierine (B) cementation within large pores. (c) Glauconite (G) grain of greensand with complex pore structure (Hossain et al 2009). porosity, pore geometry and saturation (Archie 1942) while the elastic properties depend on porosity (Mavko 1980, Murphy 1984, saturation history (Mavko and Mukerji 1995), pore geometry (Mavko 1980;Mavko and Nur 1978), mineralogy and fluids types (Mavko et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Relationship among porosity, permeability, electrical and elastic properties

Hossain¹,

Cohen²

2012

SEG Technical Program Expanded Abstracts 2012

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Electrical resisivity is usually easier to measure in the laboratory and in-situ than permeability. Therefore, a method of combination between permeability and electrical resistivity might be used to define the fluid flow of reservoir rocks from resistivity data. However, estimating permeability from resistivity has been a problem examined by different authors. Furthermore, neither electrical nor elastic data seldom allow us to accurately quantify the hydrocarbon saturation. Hence, a combination of elastic and electrical properties could offer a powerful means of solving the problem of hydrocarbon saturation production. The objective of this study is to experimentally and theoretically revise the relations among the electrical properties, porosity, permeability, and elastic wave velocity. A data set of laboratory measured petrophysical properties, electrical properties and elastic properties of glauconitic greensand from the North Sea Nini Field was used for this study. A linear relationship between laboratory measured electrical properties and permeability could be established if the diagenesis of greensand is know. By combing Archie's relation and Kozeny's equation, the greensand diagenesis may be described by the specific surface area of pores. A linear relationship between laboratory measured electrical and elastic properties could be established if the effect of micro structure of greensand is known. Rock physics modeling results show that quartz cementation has a larger effect on elastic properties than electrical properties, while berthierine cementation has a similar effect on elastic and electrical properties. Selfconsistent modeling results show that pore aspect ratios are more sensitive for electrical properties than elastic properties.

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Section: Introductionmentioning

confidence: 99%

Relationship among porosity, permeability, electrical and elastic properties

Hossain¹,

Cohen²

2012

SEG Technical Program Expanded Abstracts 2012

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“…1). Greensand petroleum reservoirs occur worldwide, e.g., the Mid‐Cretaceous Safaniya Sandstone Member in Saudi Arabia (Cagatay et al 1996), a Lower Cretaceous Glauconitic Sandstone in Alberta, Canada (Tilley and Longstaffe 1984), the Upper Cretaceous Shannon Sandstone in Wyoming, USA (Ranganathan and Tye 1986), a Lower Cretaceous Greensand offshore Ireland (Winn 1994) and a Late Paleocene Greensand in a central part of the North Sea (Solymar 2002; Solymar, Fabricus and Middleton 2003; Hossain, Fabricius and Christensen 2009; Stokkendal et al 2009; Hossain, Mukerji and Fabricius 2010; Hossain et al 2011). However, evaluation of greensand reservoirs has challenged geologists, engineers and petrophysicists.…”

Section: Introductionmentioning

confidence: 99%

V_p‐V_s relationship and amplitude variation with offset modelling of glauconitic greensand^‡

Hossain

Mukerji

Fabricius

2011

Geophysical Prospecting

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The relationship between Vp and Vs may be used to predict Vs where only Vp is known. Vp/Vs is also used to identify pore fluids from seismic data and amplitude variation with offset analysis. Theoretical, physical, as well as statistical empirical Vp‐Vs relationships have been proposed for reservoir characterization when shear‐wave data are not available. In published work, the focus is primarily on the Vp‐Vs relationship of quartzitic sandstone. In order to broaden the picture we present Vp‐Vs relationships of greensand composed of quartz and glauconite by using data from the Paleocene greensand Nini oil field in the North Sea. A Vp‐Vs relationship derived from modelling is compared with empirical Vp‐Vs regressions from laboratory data as well as from log data. The accuracy of Vs prediction is quantified in terms of root‐mean‐square error. We find that the Vp‐Vs relationship derived from modelling works well for greensand shear‐wave velocity prediction. We model the seismic response of glauconitic greensand by using laboratory data from the Nini field. Our studies here reveal that brine‐saturated glauconitic greensand can have a similar seismic response to that from oil‐saturated quartzitic sandstone and that oil‐saturated strongly cemented greensand can have a similar amplitude variation with offset response to that from brine‐saturated weakly cemented greensand.

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“…The mineralogical composition has been determined by point counting of thin sections (Solymar, 2002). We estimate the glauconite grain bulk modulus to be about 7 GPa and shear modulus to be about 5 GPa (Hossain et al, 2009). The effective mineral moduli are then calculated by using the Voigt-Reuss-Hill average (Mavko et al, 2009), and the effective density is calculated using the arithmetic average.…”

Section: Geological Setting Of Nini Field and Data Availablementioning

confidence: 99%

“…Glauconite affects the elastic properties, porosity, and permeability of reservoir rocks (Diaz et al, 2003). Glauconite is also ductile (Ranganathan and Tye, 1986), so it can cause nonelastic deformation of greensand (Hossain et al, 2009) and, hence, can affect reservoir quality. Greensands generally show low resistivity in the reservoir zone due to the large amount of bound water in the glauconite, yet free hydrocarbons can be produced because rather than being pore-filling, glauconite is part of the sand-size grains of the framework (Slot-Petersen et al, 1998).models are particularly useful for testing multiple possible geological scenarios using well logs, and, when integrated with rock texture properties, can be useful for interpreting observed seismic amplitudes away from well control.…”

Section: Introductionmentioning

confidence: 99%

“…Porosity in this sediment is found at two scales: macroporosity between grains and microporosity within grains (Figure 1). Greensand petroleum reservoirs occur world-wide, e.g., the mid-Cretaceous Safaniya Sandstone Member in Saudi Arabia (Cagatay et al, 1996), the Lower Cretaceous Glauconitic sandstone in Alberta, Canada (Tilley and Longstaffe, 1984), the Upper Cretaceous Shannon sandstone in Wyoming, USA (Ranganathan and Tye, 1986), a Lower Cretaceous Greensand offshore Ireland (Winn, 1994) and a late Paleocene Greensand in central part of the North Sea (Solymar, 2002;Solymar et al, 2003;Hossain et al, 2009;Hossain et al, 2011a, b;Stokkendal et al, 2009). However, evaluation of greensand reservoirs has challenged geologists, engineers and petrophysicsts.…”

Section: Introductionmentioning

confidence: 99%

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Rock physics model of glauconitic greensand from the North Sea

et al. 2011

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The objective of this study was to establish a rock physics model of North Sea Paleogene greensand. The Hertz-Mindlin contact model is widely used to calculate elastic velocities of sandstone as well as to calculate the initial sand-pack modulus of the soft-sand, stiff-sand, and intermediate-stiff-sand models. When mixed minerals in rock are quite different, e.g., mixtures of quartz and glauconite in greensand, the Hertz-Mindlin contact model of single type of grain may not be enough to predict elastic velocity. Our approach is first to develop a Hertz-Mindlin contact model for a mixture of quartz and glauconite. Next, we use this Hertz-Mindlin contact model of two types of grains as the initial modulus for a soft-sand model and a stiff-sand model. By using these rock physics models, we examine the relationship between elastic modulus and porosity in laboratory and logging data and link rock-physics properties to greensand diagenesis. Calculated velocity for mixtures of quartz and glauconite from the Hertz-Mindlin contact model for two types of grains are higher than velocity calculated from the HertzMindlin single mineral model using the effective mineral moduli predicted from the Hill's average. Results of rock-physics modeling and thin-section observations indicate that variations in the elastic properties of greensand can be explained by two main diagenetic phases: silica cementation and berthierine cementation. These diagenetic phases dominate the elastic properties of greensand reservoir. Initially, greensand is a mixture of mainly quartz and glauconite; when weakly cemented, it has relatively low elastic modulus and can be modeled by a Hertz-Mindlin contact model of two types of grains. Silica-cemented greensand has a relatively high elastic modulus and can be modeled by an intermediate-stiff-sand or a stiff-sand model. Berthierine cement has different growth patterns in different parts of the greensand, resulting in a soft-sand model and an intermediate-stiff-sand model.

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Elastic and nonelastic deformation of greensand

Cited by 10 publications

References 0 publications

Relationship among porosity, permeability, electrical and elastic properties

Relationship among porosity, permeability, electrical and elastic properties

V_p‐V_s relationship and amplitude variation with offset modelling of glauconitic greensand^‡

Rock physics model of glauconitic greensand from the North Sea

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Elastic and nonelastic deformation of greensand

Cited by 10 publications

References 0 publications

Relationship among porosity, permeability, electrical and elastic properties

Relationship among porosity, permeability, electrical and elastic properties

Vp‐Vs relationship and amplitude variation with offset modelling of glauconitic greensand‡

Rock physics model of glauconitic greensand from the North Sea

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Product

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V_p‐V_s relationship and amplitude variation with offset modelling of glauconitic greensand^‡