2
Physical Properties of Marine Sediments
42
The low-pass filtering effect particularly becomes
obvious if resistivity logs measured by the galvanic
and inductive method are compared. Figure 2.11
displays such an example for a terrigenous core
from the Weddell Sea (PS1635-1) and a biogenic
foraminiferal and diatomaceous core from the
Maud Rise (PS1836-3) in the Antarctic Ocean.
Resistivities differ by maximum 15% (Fig. 2.11a), a
rather high value which mainly results from core
PS1635-1. Here, the downcore logs illustrate that
the inductive methods produces lower resistivities
than the galvanic method (Fig. 2.11b). In detail,
the galvanic resistivity log reveals a lot of pronounced, fine-scale variations which cannot be
resolved by induction measurements but are
smeared along the core depth. For the biogenic
core PS1836-3 this smoothing is not so important
because lithology changes more gradually.
2.3
Permeability
Permeability describes how easy a fluid flows
through a porous medium. Physically it is defined
by Darcy’s law
x
p
q
∂
∂
η
κ ⋅
=
(2.14)
which relates the flow rate (q) to the permeability
(κ) of the pore space, the viscosity (η) of the pore
fluid and the pressure gradient ( ∂ ∂
p x
/ ) causing
the fluid flow. Simultaneously, permeability
depends on the porosity (φ) and grain size distribution of the sediment, approximated by the mean
grain size (d m ). Assuming that fluid flow can be
simulated by an idealized flow through a bunch of
capillaries with uniform radius (d m /2) (Hagen
Poiseuille’s flow) permeabilities can for instance
be estimated from Kozeny-Carman’s equation
(Carman 1956; Schopper 1982)
( )
2
3
2
1
36
φ
φ
κ
−
⋅
= k
d m
(2.15)
This relation is approximately valid for unconsolidated sediments of 30 - 80% porosity (Carman
1956). It is used for both geotechnical applications
to estimate permeabilities of soil (Lambe and
Whitman 1969) and seismic modeling of wave
propagation in water-saturated sediments (Biot
1956a, b; Hovem and Ingram 1979; Hovem 1980;
Ogushwitz 1985). (κ) is a constant which depends
on pore shape and tortuosity. In case of parallel,
cylindrical capillaries it is about 2, for spherical
sediment particles about 5, and in case of high
porosities ≥ 10 (Carman 1956).
However, this is only one approach to estimate
permeabilities from porosities and mean grain
sizes. Other empirical relations exist, particularly
for regions with hydrocarbon exploration (e.g.
Gulf of Mexico, Bryant et al. 1975) or fluid venting
(e.g. Middle Valley, Fisher et al. 1994) which
compute depth-dependent permeabilities from
porosity logs or take the grain size distribution
and clay content into account.
Direct measurements of permeabilities in unconsolidated marine sediments are difficult, and
only few examples are published. They confine to
measurements on discrete samples with a specially
developed tool (Lovell 1985), to indirect estimations by resistivity measurements (Lovell 1985),
and to consolidation tests on ODP cores using a
modified medical tool (Olsen et al. 1985). These
measurements are necessary to correct for the
elastic rebound (MacKillop et al. 1995) and to
determine intrinsic permeabilities at the end of
each consolidation step (Fisher et al. 1994). In
Section 2.4.2 a numerical modeling and inversion
scheme is described which estimates permeabilities from P-wave attenuation and dispersion
curves (c.f. also section 3.6).
2.4
Acoustic and Elastic Properties
Acoustic and elastic properties are directly concerned with seismic wave propagation in marine
sediments. They encompass P- and S-wave velocity and attenuation and elastic moduli of the
sediment frame and wet sediment. The most
important parameter which controls size and
resolution of sedimentary structures by seismic
studies is the frequency content of the source
signal. If the dominant frequency and bandwidth
are high, fine-scale structures associated with
pore space and grain size distribution affect the
elastic wave propagation. This is subject of ultrasonic transmission measurements on sediment
cores (Sects. 2.4 and 2.5). At lower frequencies
larger scale features like interfaces with different
physical properties above and below and bedforms like mud waves, erosion zones and channel
levee systems are the dominant structures imaged
Physical Properties of Marine Sediments
42
The low-pass filtering effect particularly becomes
obvious if resistivity logs measured by the galvanic
and inductive method are compared. Figure 2.11
displays such an example for a terrigenous core
from the Weddell Sea (PS1635-1) and a biogenic
foraminiferal and diatomaceous core from the
Maud Rise (PS1836-3) in the Antarctic Ocean.
Resistivities differ by maximum 15% (Fig. 2.11a), a
rather high value which mainly results from core
PS1635-1. Here, the downcore logs illustrate that
the inductive methods produces lower resistivities
than the galvanic method (Fig. 2.11b). In detail,
the galvanic resistivity log reveals a lot of pronounced, fine-scale variations which cannot be
resolved by induction measurements but are
smeared along the core depth. For the biogenic
core PS1836-3 this smoothing is not so important
because lithology changes more gradually.
2.3
Permeability
Permeability describes how easy a fluid flows
through a porous medium. Physically it is defined
by Darcy’s law
x
p
q
∂
∂
η
κ ⋅
=
(2.14)
which relates the flow rate (q) to the permeability
(κ) of the pore space, the viscosity (η) of the pore
fluid and the pressure gradient ( ∂ ∂
p x
/ ) causing
the fluid flow. Simultaneously, permeability
depends on the porosity (φ) and grain size distribution of the sediment, approximated by the mean
grain size (d m ). Assuming that fluid flow can be
simulated by an idealized flow through a bunch of
capillaries with uniform radius (d m /2) (Hagen
Poiseuille’s flow) permeabilities can for instance
be estimated from Kozeny-Carman’s equation
(Carman 1956; Schopper 1982)
( )
2
3
2
1
36
φ
φ
κ
−
⋅
= k
d m
(2.15)
This relation is approximately valid for unconsolidated sediments of 30 - 80% porosity (Carman
1956). It is used for both geotechnical applications
to estimate permeabilities of soil (Lambe and
Whitman 1969) and seismic modeling of wave
propagation in water-saturated sediments (Biot
1956a, b; Hovem and Ingram 1979; Hovem 1980;
Ogushwitz 1985). (κ) is a constant which depends
on pore shape and tortuosity. In case of parallel,
cylindrical capillaries it is about 2, for spherical
sediment particles about 5, and in case of high
porosities ≥ 10 (Carman 1956).
However, this is only one approach to estimate
permeabilities from porosities and mean grain
sizes. Other empirical relations exist, particularly
for regions with hydrocarbon exploration (e.g.
Gulf of Mexico, Bryant et al. 1975) or fluid venting
(e.g. Middle Valley, Fisher et al. 1994) which
compute depth-dependent permeabilities from
porosity logs or take the grain size distribution
and clay content into account.
Direct measurements of permeabilities in unconsolidated marine sediments are difficult, and
only few examples are published. They confine to
measurements on discrete samples with a specially
developed tool (Lovell 1985), to indirect estimations by resistivity measurements (Lovell 1985),
and to consolidation tests on ODP cores using a
modified medical tool (Olsen et al. 1985). These
measurements are necessary to correct for the
elastic rebound (MacKillop et al. 1995) and to
determine intrinsic permeabilities at the end of
each consolidation step (Fisher et al. 1994). In
Section 2.4.2 a numerical modeling and inversion
scheme is described which estimates permeabilities from P-wave attenuation and dispersion
curves (c.f. also section 3.6).
2.4
Acoustic and Elastic Properties
Acoustic and elastic properties are directly concerned with seismic wave propagation in marine
sediments. They encompass P- and S-wave velocity and attenuation and elastic moduli of the
sediment frame and wet sediment. The most
important parameter which controls size and
resolution of sedimentary structures by seismic
studies is the frequency content of the source
signal. If the dominant frequency and bandwidth
are high, fine-scale structures associated with
pore space and grain size distribution affect the
elastic wave propagation. This is subject of ultrasonic transmission measurements on sediment
cores (Sects. 2.4 and 2.5). At lower frequencies
larger scale features like interfaces with different
physical properties above and below and bedforms like mud waves, erosion zones and channel
levee systems are the dominant structures imaged