2 Physical Properties of Marine Sedimentsblogs.unpad.ac.id/myawaludin/files/2011/09/kel_6.pdf2...

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Generally, physical properties of marine sedi-ments are good indicators for the composition,microstructure and environmental conditionsduring and after the depositional process. Theirstudy is of high interdisciplinary interest andfollows various geoscientific objectives.

Physical properties provide a lithologicaland geotechnical description of the sediment.Questions concerning the composition of a de-positional regime, slope stability or nature ofseismic reflectors are of particular interest withinthis context. Parameters like P- and S-wave velo-city and attenuation, elastic moduli, wet bulkdensity and porosity contribute to their solution.

As most physical properties can be mea-sured very quickly in contrast to parameters likecarbonate content, grain size distribution oroxygen isotope ratio, they often serve as proxyparameters for geological or paleoceanogra-phical processes and changes in the environ-mental conditions. Basis for this approach arecorrelations between different parameters whichallow to derive regression equations of regionalvalidity. Highly resolved physical properties areused as input parameters for such equations tointerpolate coarsely sampled geological, geo-chemical or sedimentological core logs. Examplesare the P-wave velocity, attenuation and wetbulk density as indices for the sand content ormean grain size and the magnetic susceptibilityas an indicator for the carbonate content oramount of terrigenous components. Additional-ly, highly resolved physical property core logsare often used for time series analysis to derivequaternary stratigraphies by orbital tuning.

In marine geochemistry, physical parameterswhich quantify the amount and distribution ofpore space or indicate alterations due to diage-nesis are important. Porosities are necessary to

2 Physical Properties of Marine SedimentsMONIKA BREITZKE

calculate flow rates, permeabilities describe howeasy a fluid flows through a porous sedimentand increased magnetic susceptibilities can beinterpreted by an increased iron content or,more generally, by a high amount of magneticparticles within a certain volume.

This high interdisciplinary value of physicalproperty measurements results from the diffe-rent effects of changed environmental condi-tions on sediment structure and composition.Apart from anthropogeneous influences varia-tions in the environmental conditions resultfrom climatic changes and tectonic eventswhich affect the ocean circulation and relatedproduction and deposition of biogenic andterrigenous components. Enhanced or reducedcurrent intensities during glacial or interglacialstages cause winnowing, erosion and redepo-sition of fine-grained particles and directlymodify the sediment composition. These effectsare subject of sedimentological and paleoce-anographical studies. Internal processes likeearly diagenesis, newly built authigenic sedi-ments or any other alterations of the solid andfluid constituents of marine sediments are ofgeochemical interest. Gravitational mass trans-ports at continental slopes or turbidites in largesubmarine fan systems deposit as coarse-grained chaotic or graded beddings. They canbe identified in high-resolution physical proper-ty logs and are often directly correlated with sealevel changes, results valuable for sedimento-logical, seismic and sequence stratigraphicinvestigations. Generally, any changes in thesediment structure which modify the elasticproperties of the sediment influence the reflec-tion characteristics of the subsurface and canbe imaged by remote sensing seismic or echo-sounder surveys.

2 Physical Properties of Marine Sediments

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Fig. 2.1 Components of marine sediments. The singleparticles are the sediment grains. The voids betweenthese particles – the pores – are filled with pore fluid,usually sea water. Welded particles and sediment grains inclose contact build the sediment frame.

Fig. 2.2 Two types of sediment models. (a) The layered, volume-oriented model for bulk parameters only depends onthe relative amount of solid and fluid components. (b) The microstructure-oriented model for acoustic and elasticparameters takes the complicated shape and geometry of the particle and pore size distribution into account and con-siders interactions between the solid and fluid constituents during wave propagation.

2.1 Introduction

Physical properties of marine sediments dependon the properties and arrangement of the solidand fluid constituents. To fully understand theimage of geological and paleoceanographicalprocesses in physical property core logs it ishelpful to consider the single components indetail (Fig. 2.1).

By most general definition a sediment is acollection of particles - the sediment grains -which are loosely deposited on the sea floor andclosely packed and consolidated under increasinglithostatic pressure. The voids between the sedi-ment grains - the pores - form the pore space. In

water-saturated sediments it is filled with porewater. Grains in close contact and welded particlesbuild the sediment frame. Shape, arrangement,grain size distribution and packing of particlesdetermine the elasticity of the frame and therelative amount of pore space.

Measurements of physical properties usuallyencompass the whole, undisturbed sediment. Twotypes of parameters can be distinguished: (1) bulkparameters and (2) acoustic and elastic para-meters. Bulk parameters only depend on therelative amount of solid and fluid componentswithin a defined sample volume. They can beapproximated by a simple volume-oriented model(Fig. 2.2a). Examples are the wet bulk density andporosity. In contrast, acoustic and elastic para-meters depend on the relative amount of solid andfluid components and on the sediment frameincluding arrangement, shape and grain sizedistribution of the solid particles. Viscoelasticwave propagation models simulate thesecomplicated structures, take the elasticity of theframe into account and consider interactionsbetween solid and fluid constituents. (Fig. 2.2b).Examples are the velocity and attenuation of P-and S-waves. Closely related parameters whichmainly depend on the distribution and capillarityof the pore space are the permeability andelectrical resistivity.

Various methods exist to measure the differentphysical properties of marine sediments. Someparameters can be measured directly, others

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2.2 Porositiy and Wet Bulk Density

indirectly by determining one or several relatedparameters and computing the desired property byempirical or model-based equations. For consoli-dated sedimentary, igneous and metamorphicrocks Schön (1996) described a large variety ofsuch methods for all common physical properties.Some of these methods can also be applied tounconsolidated, water-saturated sediments, othershave to be modified or are completely inapprop-riate. Principally, if empirical relations or sedimentmodels are used, the implicit assumptions have tobe checked carefully. An example is Archie’s law(Archie 1942) which combines the electrical resis-tivities of the pore fluid and saturated sedimentand with its porosity. An exponent and multiplierin this equation depend on the sediment type andcomposition and change from fine- to coarse-grained and from terrigenous to biogenic sedi-ments. Another example is Wood’s equation(Wood 1946) which relates P-wave velocities toporosities. This model approximates the sedimentby a dilute suspension and neglects the sedimentframe, any interactions between particles orparticles and pore fluid and assumes a ‘zero’frequency for acoustic measurements. Suchassumptions are only valid for a very limited set ofhigh porosity sediments so that for any compari-sons these limitations should be kept in mind.

Traditional measuring techniques use smallchunk samples taken from the split core. Thesetechniques are rather time-consuming and couldonly be applied at coarse sampling intervals. Thenecessity to measure high-resolution physicalproperty logs rapidly on a milli- to centimeterscale for a core-to-core or core-to-seismic datacorrelation, and the opportunity to use high-resolution physical property logs for stratigraphicpurposes (e.g. orbital tuning) forced the deve-lopment of non-destructive, automated loggingsystems. They record one or several physicalproperties almost continuously at arbitrary smallincrements under laboratory conditions. The mostcommon tools are the multi sensor track (MST)system for P-wave velocity, wet bulk density andmagnetic susceptibility core logging onboard ofthe Ocean Drilling Program research vesselJOIDES Resolution (e.g. Shipboard ScientificParty 1995), and the commercially available multisensor core logger (MSCL) of GEOTEK™(Schultheiss and McPhail 1989; Weaver andSchultheiss 1990; Gunn and Best 1998).Additionally, other core logging tools have simul-taneously been developed for special research

interests which for instance record electrical resis-tivities (Bergmann 1996) or full waveform trans-mission seismograms on sediment cores (Breitzkeand Spieß 1993). They are particularly discussedin this paper.

While studies on sediment cores only provideinformation on the local core position, lateralvariations in physical properties can be imaged byremote sensing methods like high-resolution seis-mic or sediment echosounder profiling. Theyfacilitate core-to-core correlations over large dis-tances and allow to evaluate physical propertylogs within the local sedimentation environment.

In what follows the theoretical background ofthe most common physical properties and theirmeasuring tools are described. Examples for thewet bulk density and porosity can be found inSection 2.2. For the acoustic and elastic para-meters first the main aspects of Biot-Stoll’sviscoelastic model which computes P- and S-wavevelocities and attenuations for given sedimentparameters (Biot 1956a, b, Stoll 1974, 1977, 1989)are summarized. Subsequently, analysis methodsare described to derive these parameters fromtransmission seismograms recorded on sedimentcores, to compute additional properties like elasticmoduli and to derive the permeability as a relatedparameter by an inversion scheme (Sect. 2.4).

Examples from terrigenous and biogenicsedimentation provinces are presented (1) toillustrate the large variability of physicalproperties in different sediment types and (2) toestablish a sediment classification which is onlybased on physical properties, in contrast togeological sediment classifications which mainlyuses parameters like grain size distribution ormineralogical composition (Sect. 2.5).

Finally, some examples from high-resolutionnarrow-beam echosounder recordings presentremote sensing images of terrigenous and bioge-nic sedimentation environments (Sect. 2.6).

2.2 Porosity and Wet Bulk Density

Porosity and wet bulk density are typical bulkparameters which are directly associated with therelative amount of solid and fluid components inmarine sediments. After definition of both para-meters this section first describes their traditionalanalysis method and then focuses on recentlydeveloped techniques which determine porosities


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and wet bulk densities by gamma ray attenuationand electrical resistivity measurements.

The porosity (φ) characterizes the relativeamount of pore space within a sample volume. It isdefined by the ratio

VV

volumesampletotalspaceporeofvolume f==φ (2.1)

Equation 2.1 describes the fractional porositywhich ranges from 0 in case of none pore volumeto 1 in case of a water sample. Multiplication with100 gives the porosity in percent. Depending onthe sediment type porosity occurs as inter- andintraporosity. Interporosity specifies the porespace between the sediment grains and is typicalfor terrigenous sediments. Intraporosity includesthe voids within hollow sediment particles likeforaminifera in calcareous ooze. In such sedimentsboth inter- and intraporosity contribute to thetotal porosity.

The wet bulk density (ρ) is defined by themass (m) of a water-saturated sample per samplevolume (V)

Vm

volumesampletotalsamplewetofmass

==ρ (2.2)

Porosity and wet bulk density are closelyrelated, and often porosity values are derived fromwet bulk density measurements and vice versa.Basic assumption for this approach is a two-component model for the sediment with uniformgrain and pore fluid densities (ρg) and (ρf). The wetbulk density can then be calculated using theporosity as a weighing factor

( ) gf ρφρφρ ⋅−+⋅= 1 (2.3)

If two or several mineral components withsignificantly different grain densities contributeto the sediment frame their densities are ave-raged in (ρg).

2.2.1 Analysis by Weight and Volume

The traditional way to determine porosity and wetbulk density is based on weight and volumemeasurements of small sediment samples. Usuallythey are taken from the centre of a split core by asyringe which has the end cut off and a definitevolume of e.g. 10 ml. While weighing can be donevery accurately in shore-based laboratories mea-

surements onboard of research vessels requirespecial balance systems which compensate theshipboard motions (Childress and Mickel 1980).Volumes are measured precisely by Helium gaspycnometers. They mainly consist of a sample celland a reference cell and employ the ideal gas lawto determine the sample volume. In detail, thesediment sample is placed in the sample cell, andboth cells are filled with Helium gas. After a valveconnecting both cells are closed, the sample cell ispressurized to (P1). When the valve is opened thepressure drops to (P2) due to the increased cellvolume. The sample volume (V) is calculated fromthe pressure ratio (P1/P2) and the volumes of thesample and reference cell, (Vs) and (Vref) (Blum1997).

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VVV ref

s−

+= (2.4)

While weights are measured on wet and drysamples having used an oven or freeze drying,volumes are preferentially determined on drysamples. A correction for the mass and volume ofthe salt precipitated from the pore water duringdrying must additionally be applied (Hamilton1971; Gealy 1971) so that the total sample volume(V) consists of

fsaltdry VVVV +−= (2.5)

The volumes (Vf) and (Vsalt) of the pore space andsalt result from the masses of the wet and drysample, (m) and (mdry), from the densities of the porefluid and salt (ρf =1.024 g cm-3 and ρsalt = 2.1 g cm-3)and from the fractional salinity (s)

( ) f

dry

f

ff s

mmmV

ρρ ⋅−−

==1

(2.6)

with :s

mmm dry

f −−

=1

( )salt

dryf

salt

saltsalt

mmmmV

ρρ−−

== (2.7)

with : ( )dryfsalt mmmm −−=

Together with the mass (m) of the wet sampleequations 2.5 to 2.7 allow to compute the wet bulkdensity according to equation 2.2.

Wet bulk density computations according toequation 2.3 require the knowledge of grain

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densities (ρg). They can also be determined fromweight and volume measurements on wet and drysamples (Blum 1997)

saltdry

saltdry

g

gg VV

mmVm

−−

==ρ (2.8)

Porosities are finally computed from the volumesof the pore space and sample as defined by theequations above.

2.2.2 Gamma Ray Attenuation

The attenuation of gamma rays passing radiallythrough a sediment core is a widely used effect toanalyze wet bulk densities and porosities by anon-destructive technique. Often 137Cs is used assource which emits gamma rays of 662 keV energy.They are mainly attenuated by Comptonscattering (Ellis 1987). The intensity I of theattenuated gamma ray beam depends on thesource intensity (I0), the wet bulk density (ρ) ofthe sediment, the ray path length (d) and thespecific Compton mass attenuation coefficient (µ)

deII µρ−⋅= 0 (2.9)

To determine the source intensity in practiceand to correct for the attenuation in the liner wallsfirst no core and then an empty core liner areplaced between the gamma ray source anddetector to measure the intensities (Iair) and (Iliner).The difference (Iair - Iliner) replaces the sourceintensity (I0), and the ray path length (d) issubstituted by the measured outer core diameter(doutside) minus the double liner wall thickness(2dliner). With these corrections the wet bulkdensity (ρ) can be computed according to

( ) ⎟⎟

⎠

⎞

⎜⎜

⎝

⎛

−⋅

−⋅−=

linerairlineroutside III

ddln

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µρ (2.10)

Porosities are derived by rearranging equation2.3 and assuming a grain density (ρg).

The specific Compton mass attenuationcoefficient (µ) is a material constant. It dependson the energy of the gamma rays and on the ratio(Z/A) of the number of electrons (Z) to the atomicmass (A) of the material (Ellis 1987). For mostsediment and rock forming minerals this ratio isabout 0.5, and for a 137Cs source the correspon-ding mass attenuation coefficient (µg) for sedimentgrains is 0.0774 cm2 g-1. However, for the hydro-

gen atom (Z/A) is close to 1.0 leading to a signi-ficantly different mass attenuation coefficient (µf)in sea water of 0.0850 cm2 g-1 (Gerland andVillinger 1995). So, in water-saturated sedimentsthe effective mass attenuation coefficient (µ)results from the sum of the mass weightedcoefficients of the solid and fluid constituents(Bodwadkar and Reis 1994)

( ) gg

ff µ

ρρ

φµρ

ρφµ ⋅⋅−+⋅⋅= 1 (2.11)

The wet bulk density (ρ) in the denominator isdefined by equation 2.3. Unfortunately, equations2.3 and 2.11 depend on the porosity (φ), aparameter which should actually be determined bygamma ray attenuation. Gerland (1993) used anaverage ‘processing porosity’ of 50% for terrige-nous, 70% for biogenic and 60% for cores of mixedmaterial to estimate the effective mass attenuationcoefficient for a known grain density. Whitmarsh(1971) suggested an iterative scheme whichimproves the mass attenuation coefficient. Itstarts with an estimated ‘processing porosity’ andmass attenuation coefficient (eq. 2.11) to calculatethe wet bulk density from the measured gamma rayintensity (eq. 2.10). Subsequently, an improvedporosity (eq. 2.3) and mass attenuation coefficient(eq. 2.11) can be calculated for a given graindensity. Using these optimized values in a seconditeration wet bulk density, porosity and massattenuation coefficient are re-evaluated. Gerland(1993) and Weber et al. (1997) showed that afterfew iterations (< 5) the values of two successivesteps differ by less than 0.1‰ even if a ‘processingporosity’ of 0 or 100% and a mass attenuationcoefficient of 0.0774 cm2 g-1 or 0.0850 cm2 g-1 for apurely solid or fluid ‘sediment’ are used asstarting values.

Gamma ray attenuation is usually measured byautomated logging systems, e.g. onboard of theOcean Drilling Program research vessel JOIDESResolution (Boyce 1973, 1976) by the multisensorcore logger of GEOTEK™ (Schultheiss andMcPhail 1989; Weaver and Schultheiss 1990; Gunnand Best 1998) or by specially developed systems(Gerland 1993; Bodwadkar and Reis 1994; Gerlandand Villinger 1995). The emission of gamma rays isa random process which is quantified in countsper second, and which are converted to wet bulkdensities by appropriate calibration curves(Weber et al. 1997). To get a representative value



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Fig. 2.3 Gamma counts for a 1 m long core section of gravity core PS2557-1 used to illustrate the influence of variousintegration times and measuring increments. Curve A is recorded with an increment of 1 cm and an integration time of10 s, curve B with an increment of 1 cm and an integration time of 20 s, curve C with an increment of 0.5 cm and anintegration time of 60 s and curve D with an increment of 0.2 cm and an integration time of 120 s. To facilitate thecomparison each curve is set off by 800 counts. Modified after Weber et al. (1997).

for the gamma ray attenuation gamma counts mustbe integrated over a sufficiently long time interval.How different integration times and measuringincrements influence the quality, resolution andreproducibility of gamma ray logs illustratesFigure 2.3. A 1 m long section of gravity corePS2557-1 from the South African continentalmargin was repeatedly measured with incrementsfrom 1 to 0.2 cm and integration times from 10 to120 s. Generally, the dominant features, which canbe related to changes in the lithology, arereproduced in all core logs. The prominent peaksare more pronounced and have higher amplitudesif the integration time increases (from A to D).Additionally, longer integration times reduce thescatter (from A to B). Fine-scale lithologicalvariations are best resolved by the shortestmeasuring increment (D).

A comparison of wet bulk densities derivedfrom gamma ray attenuation with those measuredon discrete samples is shown in Figure 2.4a fortwo gravity cores from the Arctic (PS1725-2) andAntarctic Ocean (PS1821-6). Wet bulk densities,

porosities and grain densities of the discretesamples were analyzed by their weight and volume.These grain densities and a constant ‘processingporosity’ of 50% were used to evaluate the gammacounts. Displayed versus each other both data setsessentially differ by less than ±5% (dashed lines).The lower density range (1.20 - 1.65 g cm-3) ismainly covered by the data of the diatomaceousand terrigenous sediments of core PS1821-6 whilethe higher densities (1.65 - 2.10 g cm-3) arecharacteristic for the terrigenous core PS1725-2.According to Gerland and Villinger (1995) thescatter in the correlation of both data sets probab-ly results from (1) a slight shift in the depthscales, (2) the fact that both measurements do notconsider identical samples volumes, and (3)artefacts like drainage of sandy layers due to corehandling, transportation and storage.

A detailed comparison of both data sets isshown in Figure 2.4b for two segments of corePS1725-2. Wet bulk densities measured on discretesamples agree very well with the density logderived from gamma ray attenuation. Additionally,

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Fig. 2.4 Comparison of wet bulk densities determined on discrete samples by weight and volume measurements andcalculated from gamma ray attenuation. (a) Cross plot of wet bulk densities of gravity cores PS1821-6 from theAntarctic and PS1725-2 from the Arctic Ocean. The dashed lines indicate a difference of ±5% between both data sets.(b) Wet bulk density logs derived from gamma ray attenuation for two 1 m long core sections of gravity core PS1725-2.Superimposed are density values measured on discrete samples. Modified after Gerland and Villinger (1995).



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the striking advantage of the almost continuouswet bulk density log clearly becomes obvious.Measured with an increment of 5 mm a lot of fine-scale variations are defined, a resolution whichcould never be reached by the time-consuminganalysis of discrete samples (Gerland 1993;Gerland and Villinger 1995).

The precision of wet bulk densities can beslightly improved, if the iterative scheme for themass attenuation coefficient is applied (Fig. 2.5a).For core PS1725-2 wet bulk densities computedwith a constant mass attenuation coefficient arecompared with those derived from the iterativeprocedure. Below 1.9 g cm-3 the iteration producesslightly smaller densities than are determined witha constant mass attenuation coefficient and are

thus below the dotted 1:1 line. Above 1.9 g cm-3

densities based on the iterative procedure areslightly higher.

If both data sets are plotted versus the wetbulk densities of the discrete samples theoptimization essentially becomes obvious for highdensities (>2.0 g cm-3, Fig. 2.5b). After iterationdensities are slightly closer to the dotted 1:1 line.

While this improvement is usually small andhere only on the order of 1.3% (≈0.02 g cm-3), diffe-rences between assumed and true grain densityaffect the iteration more distinctly (Fig. 2.5c). Asan example wet bulk densities of core PS1725-2were calculated with constant grain densities of2.65, 2.75 and 2.10 g cm-3, values which are typicalfor calcareous, terrigenous and diatomaceous

Fig. 2.5 Influence of an iterative mass attenuation coef-ficient determination on the precision of wet bulk densi-ties. The gamma ray attenuation log of gravity corePS1725-2 was used as test data set. (a) Wet bulk densitiescalculated with a constant mass attenuation coefficient('processing porosity' =50%) are displayed versus the dataresulting from the iteration. A pore fluid density of 1.024 g cm-3

and a constant grain density of 2.7 g cm-3 were used, andthe iteration was stopped if densities of two successivesteps differed by less than 0.1‰ (b) Cross plot of wetbulk densities measured on discrete samples versus wetbulk densities calculated from gamma ray attenuationwith a constant mass attenuation coefficient ( ) andwith the iterative scheme (+). (c) Influence of grain den-sity on iteration. Three grain densities of 2.65, 2.75 and2.1 g cm-3 were used to calculate wet bulk densities. Modi-fied after Gerland (1993).

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sediments. Displayed as cross-plot, calculationswith grain densities of 2.65 and 2.75 g cm-3 almostcoincide and follow the dotted 1:1 line. However,computations with a grain density of 2.10 g cm-3

differ by 1.3 - 3.6% (0.02 - 0.08 g cm-3) from thosewith a grain density of 2.65 g cm-3. This result isparticularly important for cores composed of terri-genous and biogenic material of significantlydifferent grain densities like the terrigenous and dia-tomaceous components in core PS1821-6. Here, aniteration with a constant grain density of 2.65 g cm-3

would give erroneous wet bulk densities in thediatomaceous parts. In such cores a depthdepen-dent grain density profile should be applied incombination with the iterative procedure, or other-wise wet bulk densities would better be calculatedwith a constant mass attenuation coefficient.However, if the grain density is almost constantdowncore the iterative scheme could be appliedwithout any problems.

2.2.3 Electrical Resistivity(Galvanic Method)

The electrical resistivity of water-saturated sedi-ments depends on the resistivity of its solid andfluid constituents. However, as the sedimentgrains are poor conductors an electrical currentmainly propagates in the pore fluid. The dominanttransport mechanism is an electrolytic conductionby ions and molecules with an excess or deficien-cy of electrons. Hence, current propagation inwater-saturated sediments actually transportsmaterial through the pore space, so that theresistivity depends on both the conductivity ofthe pore water and the microstructure of thesediment. The conductivity of pore water varieswith its salinity, and mobility and concentration ofdissolved ions and molecules. The microstructureof the sediment is controlled by the amount anddistribution of pore space and its capillarity andtortuosity. Thus, the electrical resistivity cannotbe considered as a bulk parameter which strictlyonly depends on the relative amount of solid andfluid components, but as shown below, it can beused to derive porosity and wet bulk density asbulk parameters after calibration to a ‘typical’sediment composition of a local sedimentationenvironment.

Several models were developed to describecurrent flow in rocks and water-saturated sedi-ments theoretically. They encompass simple planelayered models (Waxman and Smits 1968) as well

as complex approximations of pore space by selfsimilar models (Sen et al. 1981), effective mediumtheories (Sheng 1991) and fractal geometries(Ruffet et al. 1991). In practice these models are ofminor importance because often only few of therequired model parameters are known. Here, anempirical equation is preferred which relates theresistivity (Rs) of the wet sediment to its fractionalporosity (φ) (Archie 1942)

m

f

s aRR

F −⋅== φ (2.12)

The ratio of the resistivity (Rs) in sediment tothe resistivity (Rf) in pore water defines theformation (resistivity) factor (F). (a) and (m) areconstants which characterize the sedimentcomposition. As Archie (1942) assumed that (m)indicates the consolidation of the sediment it isalso called cementation exponent (cf. Sect. 3.2.2).Several authors derived different values for (a)and (m). For an overview please refer to Schön(1996). In marine sediments often Boyce’s (1968)values (a = 1.3, m = 1.45), determined by studieson diatomaceous, silty to sandy arctic sediments,are applied. Nevertheless, these values can onlybe rough estimates. For absolutely correct porosi-ties both constants must be calibrated by anadditional porosity measurement, either ondiscrete samples or by gamma ray attenuation.Such calibrations are strictly only valid for thatspecific data set but, with little loss of accuracy,can be transferred to regional environments withsimilar sediment compositions. Wet bulk densitiescan then be calculated using equation 2.3 andassuming a grain density (cf. also section 3.2.2).

Electrical resistivities can be measured on splitcores by a half-automated logging system (Berg-mann 1996). It measures the resistivity (Rs) andtemperature (T) by a small probe which is manu-ally inserted into the upper few millimeters of thesediment. The resistivity (Rf) of the interstitialpore water is simultaneously calculated from acalibration curve which defines the temperature-conductivity relation of standard sea water (35‰salinity) by a fourth power law (Siedler and Peters1986).

The accuracy and resolution that can be achie-ved compared to measurements on discretesamples were studied on the terrigenous squarebarrel kastenlot core PS2178-5 from the ArcticOcean. If both data sets are displayed as crossplots porosities mainly range within the dashed10% error lines, while densities mainly differ by



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Fig. 2.6 Comparison of porosities and wet bulk densities measured on discrete samples and by electrical resistivities.Boyce’s (1968) values for the coefficients (a) and (m) and pore fluid and grain densities of 1.024 g cm-3 and 2.67 g cm-3

were used to convert formation factors into porosities and wet bulk densities. Wet and dry weights and volumes wereanalyzed on discrete samples. (a) Cross plots of both data sets for square barrel kastenlot core PS2178-5. The dashedlines indicate an error of 10% for the porosity and 5% for the density data. (b) Porosity and wet bulk density logs ofcore PS2178-5 derived from resistivity measurements. Superimposed are porosity and density values measured ondiscrete samples. Data from Bergmann (1996).

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Fig. 2.7 Formation factor versus porosity for six gravity cores retrieved from different sedimentation provinces inthe South Atlantic. Porosities were determined on discrete samples by wet and dry weights and volumes, formationfactors by resistivity measurements. The dashed lines indicate Archie’s law for a = 1 and cementation exponents (m)between 1 and 5. For a description of the sedimentation provinces, core numbers, coring locations, sedimentcompositions, water depths and constants (a) and (m) derived from linear least square fits please refer to Table 2.1.Unpublished data from M. Richter, University Bremen, Germany.

less than 5% (Fig. 2.6a). The core logs illustratethat the largest differences occur in the laminatedsandy layers, particularly between 1.5 and 3.5 mand between 4.3 and 5.1 m depth (Fig. 2.6b). Adrainage of the sandy layers, slight differences inthe depth scale and different volumes consideredby both methods probably cause this scatter.Nevertheless, in general both data sets agree verywell having used Boyce’s (1968) values for (a) and(m) and a typical terrigenous grain density of2.67 g/cm3 for porosity and wet bulk densitycomputations. This is valid because the sedimen-tation environment of core PS2178-5 from theArctic Ocean is rather similar to the Bering Seastudied by Boyce (1968).

The influence of the sediment composition onthe formation factor-porosity relation illustratesFigure 2.7 for six provinces in the South Atlantic.For each core porosities and formation factorswere evaluated at the same core depths by wetand dry weights and volumes of discrete samples

and by electrical resistivities. Displayed as a crossplot on a log-log scale the data sets of each coreshow different trends and thus different cemen-tation exponents. Jackson et al. (1978) tried torelate such variations in the cementation exponentto the sphericity of sediment particles. Based onstudies on artificial samples they found highercementation exponents if particles become lessspherical. For natural sediments incorporating alarge variety of terrigenous and biogenic particlesizes and shapes, it is difficult to verify similarrelations. It is only obvious that coarse-grainedcalcareous foraminiferal oozes from the HunterGap show the lowest and fine-grained, diatom-bearing hemipelagic mud from the Congo Fanupwelling the highest cementation exponent.Simultaneously, the constant (a) decreases withincreasing cementation exponent (Tab. 2.1). Possibly,in natural sediments the amount and distributionof pore space are more important than the par-ticle shape. Generally, cementation exponent (m),



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Table 2.1 Geographical coordinates, water depth, core length, region and composition of the sediment coresconsidered in Figure 2.7. The cementation exponent (m) and the constant (a) are derived from the slope andintercept of a linear least square fit to the log-log display of formation factors versus porosities.

constant (a) and formation factor (F) togethercharacterize a specific environment. Table 2.1summarizes the values of (a) and (m) derived froma linear least square fit to the log-log display ofthe data sets and shortly describes the sedimentcompositions.

With these values for (a) and (m) calibratedporosity logs are calculated which agree well withporosities determined on discrete samples (Fig.2.8, black curves). The error in porosity that mayresult from using the ‘standard’ Boyce’s (1968)values for (a) and (m) instead of those derivedfrom the calibration appears in two different ways(gray curves). (1) The amplitude of the downcoreporosity variations might be too large, as isillustrated by core GeoB2110-4 from the BrazilianContinental Margin. (2) The log might be shiftedto higher or lower porosities, as is shown by coreGeoB1517-1 from the Ceará Rise. Only if linearregression results in values for (a) and (m) closeto Boyce’s (1968) coefficients the error in theporosity log is negligible (core GeoB1701-4 fromthe Niger Mouth).

In order to compute absolutely correct wet bulkdensities from calibrated porosity logs a graindensity must be assumed. For most terrigenous andcalcareous sediment cores this parameter is notvery critical as it often only changes by fewpercent downcore (e.g. 2.6 - 2.7 g cm-3). However, incores from the Antarctic Polar Frontal Zone where

an interlayering of diatomaceous and calcareousoozes indicates the advance and retreat of theoceanic front during glacial and interglacial stagesgrain densities may vary between about 2.0 and2.8 g cm-3. Here, depth-dependent values musteither be known or modeled in order to get correctwet bulk density variations from resistivitymeasurements. An example for this approach areresistivity measurements on ODP core 690C fromthe Maud Rise (Fig. 2.9). While the carbonate log(b) clearly indicates calcareous layers with highand diatomaceous layers with zero CaCO3percentages (O’Connell 1990), the resistivity-based porosity log (a) only scarcely reflects theselithological changes. The reason is thatcalcareous and diatomaceous oozes are characte-rized by high inter- and intraporosities incorpora-ted in and between hollow foraminifera and diatomshells. In contrast, the wet bulk density logmeasured onboard of JOIDES Resolution by gammaray attenuation ((c), gray curve) reveals pronouncedvariations. They obviously correlate with the CaCO3-content and can thus only be attributed to downcorechanges in the grain density. So, a grain densitymodel (d) was developed. It averages the densitiesof carbonate (ρcarb = 2.8 g cm-3) and biogenic opal(ρopal = 2.0 g cm-3) (Barker, Kennnett et al. 1990)according to the fractional CaCO3-content (C),ρmodel = C×ρcarb + (1 - C)×ρopal. Based on this modelwet bulk densities ((c), black curve) were derived from

Core Coordinates Water Core Region Sediment Factor CementationDepth Length Composition (a) Exponent (m)

GeoB 35°12.4'S 4058 m 6.97 m Hunter foram.-nannofossil 1,6 1,31306-2 26°45.8'W Gap ooze, sandy

GeoB 04°44.2'N 4001 m 6.89 m Ceará nannofossil-foram. 1,3 2,11517-1 43°02.8'W Rise ooze

GeoB 01°57.0'N 4162 m 7.92 m Niger clayey mud, foram. 1,4 1,41701-4 03°33.1'E Mouth bearing

GeoB 29°58.2'S 5084 m 7.45 m Cape red clay 1,0 2,81724-2 08°02.3'E Basin

GeoB 28°38.8'S 3011 m 8.41 m Braz. Cont. pelagic clay. Foram. 0,8 3,32110-4 45°31.1'W Margin bearing

GeoB 05°06.4'S 1830 m 14.18 m Congo hemipelagic mud, 0,8 5,32302-2 10°05.5'E Fan diatom bearing, H2S

39

Fig. 2.8 Porosity logs determined by resistivity measurements on three gravity cores from the South Atlantic (seealso Fig. 2.7 and Table 2.1). Gray curve: Boyce’s (1968) values were used for the constants (a) and (m). Black curve:(a) and (m) were derived from the slope and intercept of a linear least square fit. These values are given at the topof each log. Superimposed are porosities determined on discrete samples by weight and volume measurements(unpublished data from P. Müller, University Bremen, Germany).

the porosity log which agree well with the gammaray attenuation densities ((c), gray curve) andshow less scatter.

Though resistivities are only measured half-automatically including a manual insertion andremoval of the probe, increments of 1 - 2 cm canbe realized within an acceptable time so that morefine-scale structures can be resolved than byanalysis of discrete samples. However, the realadvantage compared to an automated gamma rayattenuation logging is that the resistivity measure-ment system can easily be transported, e.g.

onboard of research vessels or to core reposi-tories, while the transport of radioactive sourcesrequires special safety precautions.

2.2.4 Electrical Resistivity(Inductive Method)

A second, non-destructive technique to determineporosities by resistivity measurements uses a coilas sensor. A current flowing through the coilinduces an electric field in the unsplit sedimentcore while it is automatically transported through



40

Fig. 2.9 Model based computation of a wet bulk density log from resistivity measurements on ODP core 690C. (a)Porosity log derived from formation factors having used Boyce’s (1968) values for (a) and (m) in Archie’s law. (b)Carbonate content (O’Conell 1990). (c) Wet bulk density log analyzed from gamma ray attenuation measurementsonboard of JOIDES Resolution (gray curve). Superimposed is the wet bulk density log computed from electricalresistivity measurements on archive halves of the core (black curve) having used the grain density model shown in(d). Unpublished data from B. Laser and V. Spieß, University Bremen, Germany.

41

Fig. 2.10 Impulse response function of a thin metal plate measured by the inductive method with a coil of about 14 cmdiameter. Modified after Gerland et al. (1993).

the centre of the coil (Gerland et al. 1993). Thisinduced electric field contains information on themagnetic and electric properties of the sediment.

Generally, the coil characteristic is defined bythe quality value(Q)

( )( )ωωω

RLQ ⋅= (2.13)

(L(ω)) is the inductance, (R(ω)) the resistance and(ω) the (angular) frequency of the alternatingcurrent flowing through the coil (Chelkowski1980). The inductance (L(ω)) depends on the num-ber of windings, the length and diameter of thecoil and the magnetic permeability of the coilmaterial. The resistance (R(ω)) is a superpositionof the resistance of the coil material and losses ofthe electric field induced in the core. It increaseswith decreasing resistivity in the sediment.Whether the inductance or the resistance is ofmajor importance depends on the frequency of thecurrent flowing through the coil. Changes in theinductance (L(ω)) can mainly be measured ifcurrents of some kilohertz frequency or less areused. They simultaneously indicate variations inthe magnetic susceptibility while the resistance(R(ω)) is insensitive to changes in the resistivityof the sediment. In contrast, operating withcurrents of several megahertz allows to measurethe resistivity of the sediment by changes of thecoil resistance (R(ω)) while variations in the

magnetic susceptibility do not affect the induc-tance (L(ω)). The examples presented here weremeasured with a commercial system (Scintrex CTU 2)which produces an output voltage that is pro-portional to the quality value (Q) of the coil at afrequency of 2.5 MHz, and after calibration isinversely proportional to the resistivity of thesediment.

The induced electric field is not confined tothe coil position but extends over some sedimentvolume. Hence, measurements of the resistance(R(ω)) integrate over the resistivity distribution onboth sides of the coil and provide a smoothed,low-pass filtered resistivity record. The amount ofsediment volume affected by the inductionprocess increases with larger coil diameters. Theshape of the smoothing function can be measuredfrom the impulse response of a thin metal plateglued in an empty plastic core liner. For a coil ofabout 14 cm diameter this gaussian-shapedfunction has a half-width of 4 cm (Fig. 2.10), sothat the effect of an infinitely small resistivityanomaly is smeared over a depth range of 10 - 15 cm.This smoothing effect is equivalent to convo-lution of a source wavelet with a reflectivity func-tion in seismic applications and can accordinglybe removed by deconvolution algorithms. How-ever, only few applications from longcore paleo-magnetic studies are known up to now (Constableand Parker 1991; Weeks et al. 1993).



42

The low-pass filtering effect particularly becomesobvious if resistivity logs measured by the galvanicand inductive method are compared. Figure 2.11displays such an example for a terrigenous corefrom the Weddell Sea (PS1635-1) and a biogenicforaminiferal and diatomaceous core from theMaud Rise (PS1836-3) in the Antarctic Ocean.Resistivities differ by maximum 15% (Fig. 2.11a), arather high value which mainly results from corePS1635-1. Here, the downcore logs illustrate thatthe inductive methods produces lower resistivitiesthan the galvanic method (Fig. 2.11b). In detail,the galvanic resistivity log reveals a lot of pro-nounced, fine-scale variations which cannot beresolved by induction measurements but aresmeared along the core depth. For the biogeniccore PS1836-3 this smoothing is not so importantbecause lithology changes more gradually.

2.3 Permeability

Permeability describes how easy a fluid flowsthrough a porous medium. Physically it is definedby Darcy’s law

xpq

∂∂

ηκ ⋅= (2.14)

which relates the flow rate (q) to the permeability(κ) of the pore space, the viscosity (η) of the porefluid and the pressure gradient ( ∂ ∂p x/ ) causingthe fluid flow. Simultaneously, permeabilitydepends on the porosity (φ) and grain size distri-bution of the sediment, approximated by the meangrain size (dm). Assuming that fluid flow can besimulated by an idealized flow through a bunch ofcapillaries with uniform radius (dm/2) (HagenPoiseuille’s flow) permeabilities can for instancebe estimated from Kozeny-Carman’s equation(Carman 1956; Schopper 1982)

( )2

32

136 φφκ−

⋅=k

dm (2.15)

This relation is approximately valid for uncon-solidated sediments of 30 - 80% porosity (Carman1956). It is used for both geotechnical applicationsto estimate permeabilities of soil (Lambe andWhitman 1969) and seismic modeling of wavepropagation in water-saturated sediments (Biot1956a, b; Hovem and Ingram 1979; Hovem 1980;

Ogushwitz 1985). (κ) is a constant which dependson pore shape and tortuosity. In case of parallel,cylindrical capillaries it is about 2, for sphericalsediment particles about 5, and in case of highporosities ≥ 10 (Carman 1956).

However, this is only one approach to estimatepermeabilities from porosities and mean grainsizes. Other empirical relations exist, particularlyfor regions with hydrocarbon exploration (e.g.Gulf of Mexico, Bryant et al. 1975) or fluid venting(e.g. Middle Valley, Fisher et al. 1994) whichcompute depth-dependent permeabilities fromporosity logs or take the grain size distributionand clay content into account.

Direct measurements of permeabilities in un-consolidated marine sediments are difficult, andonly few examples are published. They confine tomeasurements on discrete samples with a speciallydeveloped tool (Lovell 1985), to indirect estima-tions by resistivity measurements (Lovell 1985),and to consolidation tests on ODP cores using amodified medical tool (Olsen et al. 1985). Thesemeasurements are necessary to correct for theelastic rebound (MacKillop et al. 1995) and todetermine intrinsic permeabilities at the end ofeach consolidation step (Fisher et al. 1994). InSection 2.4.2 a numerical modeling and inversionscheme is described which estimates permeabi-lities from P-wave attenuation and dispersioncurves (c.f. also section 3.6).

2.4 Acoustic and Elastic Properties

Acoustic and elastic properties are directly con-cerned with seismic wave propagation in marinesediments. They encompass P- and S-wave veloci-ty and attenuation and elastic moduli of thesediment frame and wet sediment. The mostimportant parameter which controls size andresolution of sedimentary structures by seismicstudies is the frequency content of the sourcesignal. If the dominant frequency and bandwidthare high, fine-scale structures associated withpore space and grain size distribution affect theelastic wave propagation. This is subject of ultra-sonic transmission measurements on sedimentcores (Sects. 2.4 and 2.5). At lower frequencieslarger scale features like interfaces with differentphysical properties above and below and bed-forms like mud waves, erosion zones and channellevee systems are the dominant structures imaged

43

Fig. 2.11 Comparison of electrical resistivities (galv.) measured with the small hand-held probe and determined bythe inductive method (ind.) for the gravity cores PS1635-1 and PS1836-3. (a) Cross plots of both data sets. Thedashed lines indicate a difference of 15%. (b) Downcore resistivity logs determined by both methods. Modified afterGerland et al. (1993).



44

by sediment echosounder and multi-channelseismic surveys (Sect. 2.6).

In this section first Biot’s viscoelastic model issummarized which simulates high- and low-frequency wave propagation in water-saturatedsediments by computing phase velocity andattenuation curves. Subsequently, analysistechniques are introduced which derive P-wavevelocities and attenuation coefficients fromultrasonic signals transmitted radially acrosssediment cores. Additional physical properties likeS-wave velocity, elastic moduli and permeabilityare estimated by an inversion scheme.

2.4.1 Biot-Stoll Model

To describe wave propagation in marine sedimentsmathematically, various simple to complex modelshave been developed which approximate thesediment by a dilute suspension (Wood 1946) oran elastic, water-saturated frame (Gassmann 1951;Biot 1956a, b). The most common model whichconsiders the microstructure of the sediment andsimulates frequency-dependent wave propagationis based on Biot’s theory (Biot 1956a, b). It includesWood’s suspension and Gassmann’s elastic framemodel as low-frequency approximations andcombines acoustic and elastic parameters - P- andS-wave velocity and attenuation and elastic moduli- with physical and sedimentological parameterslike mean grain size, porosity, density and permea-bility.

Based on Biot’s fundamental work Stoll (e.g.1974, 1977, 1989) reformulated the mathematicalbackground of this theory with a simplifieduniform nomenclature. Here, only the main physi-cal principles and equations are summarized. For adetailed description please refer to one of Stoll’spublications or Biot’s original papers.

The theory starts with a description of themicrostructure by 11 parameters. The sedimentgrains are characterized by their grain density (ρg)and bulk modulus (Kg), the pore fluid by itsdensity (ρf), bulk modulus (Kf) and viscosity (η).The porosity (φ) quantifies the amount of porespace. Its shape and distribution are specified bythe permeability (κ), a pore size parametera=dm/3⋅φ/(1-φ), dm = mean grain size (Hovem andIngram 1979; Courtney and Mayer 1993), andstructure factor a’=1-r0(1-φ-1) (0 ≤ r0 ≤ 1) indicatinga tortuosity of the pore space (Berryman 1980).The elasticity of the sediment frame is consideredby its bulk and shear modulus (Km and µm).

An elastic wave propagating in water-satura-ted sediments causes different displacements ofthe pore fluid and sediment frame due to theirdifferent elastic properties. As a result (global)fluid motion relative to the frame occurs and canapproximately be described as Poiseuille’s flow.The flow rate follows Darcy’s law and depends onthe permeability and viscosity of the pore fluid.Viscous losses due to an interstitial pore waterflow are the dominant damping mechanism. Inter-granular friction or local fluid flow can additio-nally be included but are of minor importance inthe frequency range considered here.

Based on generalized Hooke’s law andNewton’s 2. Axiom two equations of motions arenecessary to quantify the different displacementsof the sediment frame and pore fluid. For P-wavesthey are (Stoll 1989)

( ) ( )ζρρ∂∂ζ ⋅−⋅=⋅−⋅∇ fe

tCeH

2

22

(2.16a)

( ) ( )t

met

MeC f ∂∂ζ

κηζρ

∂∂ζ ⋅−⋅−⋅=⋅−⋅∇

2

22

(2.16b)

Similar equations for S-waves are given byStoll (1989). Equation 2.16a describes the motionof the sediment frame and Equation 2.16b the mo-tion of the pore fluid relative to the frame.

)(udive

= (2.16c)and

)( Uudiv

−⋅=φζ (2.16d)

are the dilatations of the frame and between porefluid and frame (

u = displacement of the frame,

U = displacement of the pore fluid). The term( t∂∂ζκη ⋅ ) specifies the viscous losses due toglobal pore fluid flow, and the ratio ( κη ) the vis-cous flow resistance.

The coefficients (H), (C), and (M) define the elas-tic properties of the water-saturated model. They areassociated with the bulk and shear moduli of thesediment grains, pore fluid and sediment frame (Κg),(Κf), (Κm), (µm) and with the porosity (φ) by

Η = (Κg - Km)2 / (D - Km) + Km + 4/3 · µm (2.17a)

C = (Kg · (Kg - Km)) / (D - Km) (2.17b)

45

Μ = Κg2 / (D - Km) (2.17c)

D = Kg · (1 + φ · ( Kg/Kf - 1)) (2.17d)

The apparent mass factor m = a’⋅ρf /φ (a’ ≥ 1) inEquation 2.16b considers that not all of the porefluid moves along the maximum pressure gradientin case of tortuous, curvilinear capillaries. As a re-sult the pore fluid seems to be more dense, withhigher inertia. (a’) is called structure factor and isequal to 1 in case of uniform parallel capillaries.

In the low frequency limit H - 4/3µm (Eq. 2.17a)represents the bulk modulus computed by Gass-mann (1951) for a ‘closed system’ with no porefluid flow. If the shear modulus (µm) of the frame isadditionally zero, the sediment is approximated bya dilute suspension and Equation 2.17a reduces tothe reciprocal bulk modulus of Wood’s equation for‘zero’ acoustic frequency, (K-1 = φ/Kf + (1-φ)/Kg;Wood 1946).

Additionally, Biot (1956a, b) introduced acomplex correction function (F) which accountsfor a frequency-dependent viscous flow resis-tance (η/κ). In fact, while the assumption of anideal Poiseuille flow is valid for lower frequencies,deviations of this law occur at higher frequencies.For short wavelengths the influence of pore fluidviscosity confines to a thin skin depth close tothe sediment frame, so that the pore fluid seems tobe less viscous. To take these effects into accountthe complex function (F) modifies the viscous flowresistance (η/κ) as a function of pore size, porefluid density, viscosity and frequency. A completedefinition of (F) can be found in Stoll (1989).

The equations of motions 2.16 are solved by aplane wave approach which leads to a 2 x 2determinant for P-waves

0det22

22

22

22

=⎟

⎟

⎠

⎞

−⋅−

⋅−⎜

⎜

⎝

⎛

−⋅

−⋅

κηωω

ωρ

ωρ

ρω

FikMm

kC

kC

kH f

f

(2.18)

and a similar determinant for S-waves (Stoll 1989).The variable k(ω) = kr(ω) + iki(ω) is the complexwavenumber. Computations of the complex zeroesof the determinant result in the phase velocityc(ω) = ω/kr(ω) and attenuation coefficient α(ω) =ki(ω) as real and imaginary parts. Generally, thedeterminant for P-waves has two and that for S-

waves one zero representing two P- and one S-wave propagating in the porous medium. The firstP-wave (P-wave of first kind) and the S-wave arewell known from conventional seismic wavepropagation in homogeneous, isotropic media.The second P-wave (P-wave of second kind) issimilar to a diffusion wave which is exponentiallyattenuated and can only be detected by speciallyarranged experiments (Plona 1980).

An example of such frequency-dependent phasevelocity and attenuation curves presents Figure 2.12for P- and S-waves together with the slope (power (n))of the attenuation curves (α = k ⋅ f n). Three sets ofphysical properties representing typical sand, siltand clay (Table 2.2) were used as model para-meters. The attenuation coefficients show a signi-ficant change in their frequency dependence.They follow an α∼f2 power law for low and anα∼√f law for high frequencies and indicate acontinuously decreasing power (n) (from 2 to 0.5)near a characteristic frequency fc = (ηφ)/(2πκρf ).This characteristic frequency depends on themicrostructure (porosity (φ), permeability (κ)) andpore fluid (viscosity (η), density (ρf)) of the sedi-ment and is shifted to higher frequencies ifporosity increases and permeability decreases.Below the characteristic frequency the sedimentframe and pore fluid moves in phase and couplingbetween solid and fluid components is at maxi-mum. This behaviour is typical for clayey sedi-ments in which low permeability and viscousfriction prevent any relative movement betweenpore fluid and frame up to several MHz, in spite oftheir high porosity. With increasing permeabilityand decreasing porosity the characteristicfrequency diminishes so that in sandy sedimentsmovements in phase only occur up to about 1 kHz.Above the characteristic frequency wavelengthsare short enough to cause relative motionsbetween pore fluid and frame.

Phase velocities are characterized by a low-and high-frequency plateau with constant valuesand a continuous velocity increase near the cha-racteristic frequency. This dispersion is difficult todetect because it is confined to a small frequencyband. Here, dispersion could only be detectedfrom 1 - 10 kHz in sand, from 50 - 500 kHz in siltand above 100 MHz in clay. Generally, velocities incoarse-grained sands are higher than in fine-grained clays.

S-waves principally exhibit the same attenua-tion and velocity characteristics as P-waves.However, at the same frequency attenuation is



46

Fig. 2.12 Frequency-dependent attenuation and phase velocity curves and power (n) of the attenuation law α = k ⋅ f n

computed for P-and S-waves in typical sand, silt and clay. The gray-shaded areas indicate frequency bands typical forultrasonic measurements on sediment cores (50 - 500 kHz) and sediment echosounder surveys (0.5 - 10 kHz). Modifiedafter Breitzke (1997).

47

Table 2.2 Physical properties of sediment grains, pore fluid and sediment frame used for the computation ofattenuation and phase velocity curves according to Biot-Stoll’s sediment model (Fig. 2.12).

about one magnitude higher, and velocities aresignificantly lower than for P-waves. The conse-quence is that S-waves are very difficult to recorddue to their high attenuation, though they are ofgreat value for identifying fine-scale variations inthe elasticity and microstructure of marine sedi-ments. This is even valid if the low S-wave veloci-ties are taken into account and lower frequenciesare used for S-wave measurements than for P-wave recordings.

The two gray-shaded areas in Figure 2.12 marktwo frequency bands typical for ultrasonic studieson sediment cores (50 - 500 kHz) and sedimentechosounder surveys (0.5 - 10 kHz). They aredisplayed in order to point to one characteristic ofacoustic measurements. Attenuation coefficientsanalyzed from ultrasonic measurements on sedi-ment cores cannot directly be transferred to

sediment echosounder or seismic surveys. Prima-rily they only reflect the microstructure of thesediment. Rough estimates of the attenuation inseismic recordings from ultrasonic core measure-ments can be derived if ultrasonic attenuation ismodeled, and attenuation coefficients are extrapo-lated to lower frequencies by such model curves.

2.4.2 Full Waveform Ultrasonic CoreLogging

To measure the P-wave velocity and attenuationillustrated by Biot-Stoll’s model an automated, PC-controlled logging system was developed whichrecords and stores digital ultrasonic P-waveformstransmitted radially across marine sediment cores(Breitzke and Spieß 1993). These transmissionmeasurements can be done at arbitrary small depth


Parameter Sand Silt Clay

Sediment Grains Bulk Modulus Κ g [109 Pa] 38 38 38

Density ρ g [g cm-3] 2.67 2.67 2.67

Pore Fluid

Bulk Modulus Κ f [109 Pa] 2.37 2.37 2.37

Density ρ f [g cm-3] 1.024 1.024 1.024

Viscosity η [10-3 Pa⋅s] 1.07 1.07 1.07

Sediment Frame

Bulk Modulus Κ m [106 Pa] 400 150 20

Shear Modulus µ m [106 Pa] 240 90 12

Poisson Ratio σ m 0.25 0.25 0.25

Pore Space

Porosity φ [%] 50 60 80

Mean Grain Size d m [10-6 m] 70 30 2

Permeability κ [m2] 5.4·10-11 2.3·10-12 7.1·10-15

Pore Size Parameter a = d m / 3 φ /(1-φ ) [10-6 m] 23 15 2.7

Ratio κ / a2 0.1 0.01 0.001

Structure Factor a' = 1-r 0 (1-φ -1) 1.5 1.3 1.1

Constant r 0 0.5 0.5 0.5


48

Fig.

2.1

3Fu

ll w

avef

orm

ultr

ason

ic c

ore

logg

ing,

fro

m l

ithol

ogy

cont

rolle

d si

ngle

tra

ces

to t

he g

ray

shad

ed p

ixel

gra

phic

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tran

smis

sion

sei

smog

ram

s, a

nd P

-wav

eve

loci

ty a

nd a

ttenu

atio

n lo

gs d

eriv

ed f

rom

the

tra

nsm

issi

on d

ata.

The

sin

gle

trac

es o

n th

e le

ft-h

and

side

ref

lect

tru

e am

plitu

des

whi

le t

he w

iggl

e tr

aces

of

the

core

segm

ent

and

the

pixe

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aphi

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ized

to

max

imum

val

ues.

Dat

a fr

om B

reitz

ke e

t al

. (1

996)

.

49

increments so that the resulting seismogram sec-tions can be combined to an ultrasonic image of thecore.

Figure 2.13 displays the most prominent effectsinvolved in full waveform ultrasonic core logging.Gravity core GeoB1510-2 from the westernequatorial South Atlantic serves as an example. Thelithology controlled single traces and amplitudespectra demonstrate the influence of increasinggrain sizes on attenuation and frequency contentof transmission seismograms. Compared to areference signal in distilled water, the signal shaperemains almost unchanged in case of wavepropagation in fine-grained clayey sediments (1stattenuated trace). With an increasing amount ofsilty and sandy particles the signal amplitudes arereduced due to an enhanced attenuation of high-frequency components (2nd and 3rd attenuatedtrace). This attenuation is accompanied by achange in signal shape, an effect which isparticularly obvious in the normalized wiggle tracedisplay of the 1 m long core segment. While theupper part of this segment is composed of fine-grained nannofossil ooze, a calcareous foramini-feral turbidite occurs in the lower part. The down-ward coarsening of the graded bedding causessuccessively lower-frequency signals which caneasily be distinguished from the high-frequencytransmission seismograms in the upper fine-grainedpart. Additionally, first arrival times are lower in thecoarse-grained turbidite than in fine-grainednannofossil oozes indicating higher velocities insilty and sandy sediments than in the clayey part.A conversion of the normalized wiggle traces to agray-shaded pixel graphic allows us to present thefull transmission seismogram information on ahandy scale. In this ultrasonic image of thesediment core lithological changes appear assmooth or sharp phase discontinuities resultingfrom the low-frequency waveforms in silty andsandy layers. Some of these layers indicate agraded bedding by downward prograding phases(1.60 - 2.10 m, 4.70 - 4.80 m, 7.50 - 7.60 m). The P-wave velocity and attenuation log analyzed fromthe transmission seismograms support theinterpretation. Coarse-grained sandy layers arecharacterized by high P-wave velocities and atte-nuation coefficients while fine-grained parts reveallow values in both parameters. Especially, atte-nuation coefficients reflect lithological changesmuch more sensitively than P-wave velocities.

While P-wave velocities are determined onlineduring core logging using a cross-correlation

technique for the first arrival detection (Breitzkeand Spieß 1993)

liner

lineroutsideP tt

ddv

22

−−

= (2.19)

(doutside= outer core diameter, 2 dliner = doubleliner wall thickness, t = detected first arrival,2t liner = travel time across both liner walls),attenuation coefficients are analyzed by a post-processing routine. Several notches in the ampli-tude spectra of the transmission seismogramscaused by the resonance characteristics of theultrasonic transducers required a modification ofstandard attenuation analysis techniques (e.g.Jannsen et al. 1985; Tonn 1989, 1991). Here, amodification of the spectral ratio method isapplied (Breitzke et al. 1996). It defines a windowof bandwidth (bi = fui - fli) in which the spectralamplitudes are summed (Fig. 2.14a).

( ) ( )∑

==

ui

lii

f

ffimi xfAxfA ,, (2.20)

The resulting value ( A f xmi( , ) ) is related tothat part of the frequency band which predo-minantly contributes to the spectral sum, i.e. to thearithmetic mean frequency (fmi) of the spectralamplitude distribution within the ith band. Sub-sequently, for a continuously moving window aseries of attenuation coefficients (α(fmi)) is com-puted from the natural logarithm of the spectralratio of the attenuated and reference signal

( ) ( )( )

n

miref

mimi fkx

xfAxfA

f ⋅=⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

=,

,lnα (2.21)

Plotted in a log α - log f diagram the power (n)and logarithmic attenuation factor (log k) can bedetermined from the slope and intercept of a linearleast square fit to the series of (fmi,α(fmi)) pairs(Fig. 2.14b). Finally, a smoothed attenuationcoefficient α(f) = k ⋅ f n is calculated for thefrequency (f) using these values for (k) and (n).

Figure 2.14b shows several attenuation curves(α(fmi)) analyzed along the turbidite layer of coreGeoB1510-2. With downward-coarsening grainsizes attenuation coefficients increase. Each linearregression to one of these curves provide a power(n) and attenuation factor (k), and thus one valueα = k ⋅ f n on the attenuation log of the completecore (Fig. 2.14c).



50

Fig. 2.14 Attenuation analysis by the smoothed spectral ratio method. (a) Definition of a moving window ofbandwidth bi=fui-fli, in which the spectral amplitudes are summed. (b) Seven attenuation curves analyzed from theturbidite layer of gravity core GeoB1510-2 and linear regression to the attenuation curve in 1.82 m depth. (c)Attenuation log of gravity core GeoB1510-2 for 400 kHz frequency. Data from Breitzke et al. (1996).

51

Fig. 2.15 (a) Attenuation coefficients (at 400 kHz) of gravity core GeoB1510-2 versus mean grain sizes. The solidline indicates a second degree polynomial used to predict mean grain sizes from attenuation coefficients. (b)Comparison of the predicted mean grain size log (gray shaded) with the data measured on discrete samples (soliddots). Mean grain sizes are given in Φ = -log2 d, d = grain diameter in mm. Modified after Breitzke et al. (1996).

As the P-wave attenuation coefficientobviously depends on the grain size distributionof the sediment it can be used as a proxy para-meter for the mean grain size, i.e. for a sedi-mentological parameter which is usually onlymeasured at coarse increments due to the time-consuming grain size analysis methods. Forinstance, this can be of major importance incurrent controlled sedimentation environmentswhere high-resolution grain size logs mightindicate reduced or enhanced current intensities.

If the attenuation coefficients and mean grainsizes analyzed on discrete samples of coreGeoB1510-2 are displayed as a cross plot a secondorder polynomial can be derived from a leastsquare fit (Fig. 2.15a). This regression curve thenallows to predict mean grain sizes using theattenuation coefficient as proxy parameter. Theaccuracy of the predicted mean grain sizes illus-

trates the core log in Figure 2.15b. The predictedgray shaded log agrees well with the superim-posed dots of the measured data.

Similarly, P-wave velocities can also be used asproxy parameters for a mean grain size prediction.However, as they cover only a small range (1450 -1650 m/s) compared to attenuation coefficients (20- 800 dB/m) they reflect grain size variations lesssensitively.

Generally, it should be kept in mind, that theregression curve in Figure 2.15 is only an example.Its applicability is restricted to that range ofattenuation coefficients for which the regressioncurve was determined and to similar sedimentationenvironments (calcareous foraminiferal andnannofossil ooze). For other sediment compo-sitions new regression curves must be determined,which are again only valid for that specificsedimentological setting.



52

Table 2.3 Geographical coordinates, water depth, core length, region and composition of the sediment coresconsidered for the sediment classification in Section 2.5.

Biot-Stoll’s theory allows us to model P-wavevelocities and attenuation coefficients analyzed fromtransmission seismograms. As an example Figure 2.16displays six data sets for the turbidite layer of coreGeoB1510-2. While attenuation coefficients wereanalyzed as described above frequency dependent P-wave velocities were determined from successivebandpass filtered transmission seismograms (Court-ney and Mayer 1993; Breitzke 1997). Porosities andmean grain sizes enter the modeling computations viathe pore size parameter (a) and structure factor (a’).Physical properties of the pore fluid and sedimentgrains are the same as given in Table 2.2. A bulk andshear modulus of 10 and 6 MPa account for theelasticity of the frame. As the permeability is theparameter which is usually unknown but has thestrongest influence on attenuation and velocitydispersion, model curves were computed for threeconstant ratios κ/a2 = 0.030, 0.010 and 0.003 ofpermeability (κ) and pore size parameter (a). Theresulting permeabilities are given in each diagram.These theoretical curves show that the attenuationand velocity data between 170 and 182 cm depth canconsistently be modeled by an appropriate set ofinput parameters. Viscous losses due to a global porewater flow through the sediment are sufficient to ex-plain the attenuation in these sediments. Only if theturbidite base is approached (188 - 210 cm depth) theattenuation and velocity dispersion data succes-sively deviate from the model curves probably dueto an increasing amount of coarse-grained fora-minifera. An additional damping mechanism which

might either be scattering or resonance within thehollow foraminifera must be considered.

Based on this modeling computations aninversion scheme was developed which auto-matically iterates the permeability and minimizesthe difference between measured and modeledattenuation and velocity data in a least squaresense (Courtney and Mayer 1993; Breitzke 1997).As a result S-wave velocities and attenuationcoefficients, permeabilities and elastic moduli ofwater-saturated sediments can be estimated. Theyare strictly only valid if attenuation and velocitydispersion can be explained by viscous losses. Incoarse-grained parts deviations must be takeninto account for the estimated parameters, too.Applied to the data of core GeoB1510-2 in 170, 176and 182 cm depth S-wave velocities of 67, 68 and74 m/s and permeabilities of 5·10-13, 1·10-12 and3·10-12 m2 result from this inversion scheme.

2.5 Sediment Classification

Full waveform ultrasonic core logging was appliedto terrigenous and biogenic sediment cores toanalyze P-wave velocities and attenuation coef-ficients typical for the different settings. Togetherwith the bulk parameters and the physical proper-ties estimated by the inversion scheme they formthe data base for a sediment classification whichidentifies different sediment types from their

Core Coordinates Water Core Region SedimentDepth Length Composition

40KL 07°33.1'N 3814 m 8.46 m Bengal terrigenous clay, silt, sand85°29.7'E Fan

47KL 11°10.9'N 3293 m 10.00 m Bengal terrigenous clay, silt, sand;88°24.9'E Fan foram. and nannofossil ooze

GeoB 30°27.1'S 3941 m 8.19 m Rio Grande foram. and nannofossil ooze2821-1 38°48.9'W Rise

PS 46°56.1'S 4102 m 17.65 m Meteor diatomaceous mud/ooze; few2567-2 06°15.4'E Rise foram. and nannofossil layers

53

Fig. 2.16 Comparison of P-wave attenuation and velocity dispersion data derived from ultrasonic transmission seismogramswith theoretical curves based on Biot-Stoll’s model for six traces of the turbidite layer of gravity core GeoB1510-2.Permeabilities vary in the model curves according to constant ratios κ/a2 = 0.030, 0.010, 0.003 (κ = permeability, a = pore sizeparameter). The resulting permeabilities are given in each diagram. Modified after Breitzke et al. (1996).



54

acoustic and elastic properties. Table 2.3 summa-rizes the cores used for this sediment classifica-tion.

2.5.1 Full Waveform Core Logs asAcoustic Images

That terrigenous, calcareous and biogenic sili-ceous sediments differ distinctly in their acousticproperties is shown by four transmission seismo-gram sections in Figure 2.17. Terrigenoussediments from the Bengal Fan (40KL, 47KL) arecomposed of upward-fining sequences of turbi-dites characterized by upward decreasing attenu-ations and P-wave velocities. Coarse-grainedbasal sandy layers can easily be located by low-frequency waveforms and high P-wave velocities.

Calcareous sediments from the Rio Grande Rise(GeoB2821-1) in the western South Atlantic alsoexhibit high- and low-frequency signals whichscarcely differ in their P-wave velocities. In thesesediments high-frequency signals indicate fine-grained nannofossil ooze while low-frequencysignals image coarse-grained foraminiferal ooze.

The sediment core from the Meteor Rise(PS2567-2) in the Antarctic Ocean is composed ofdiatomaceous and foraminiferal-nannofossil oozedeposited during an advance and retreat of thePolar Frontal Zone in glacial and interglacialstages. Opal-rich, diatomaceous ooze can be iden-tified from high-frequency signals while foramini-feral-nannofossil ooze causes higher attenuationand low-frequency signals. P-wave velocitiesagain only show smooth variations.

Acoustic images of the complete core litho-logies present the colour-encoded graphics of thetransmission seismograms, in comparison to thelithology derived from visual core inspection (Fig.2.18). Instead of normalized transmission seismo-grams instantaneous frequencies are displayedhere (Taner et al. 1979). They reflect the dominantfrequency of each transmission seismogram astime-dependent amplitude, and thus directlyindicate the attenuation. Highly attenuated low-frequency seismograms appear as warm red towhite colours while parts with low attenuation andhigh-frequency seismograms are represented bycool green to black colours.

In these attenuation images the sandy turbi-dite bases in the terrigenous cores from theBengal Fan (40KL, 47KL) can easily be distin-guished. Graded beddings can also be identifiedfrom slightly prograding phases and continuously

decreasing travel times. In contrast, the transitionto calcareous, pelagic sediments in the upper part(> 5.6 m) of core 47KL is rather difficult to detect.Only above 3.2 m depth a slightly increasedattenuation can be observed by slightly warmercolours at higher transmission times (> 140 µs). Inthis part of the core (> 3.2 m) sediments are mainlycomposed of coarse-grained foraminiferal ooze,while farther downcore (3.2 - 5.6 m) fine-grainednannofossils prevail in the pelagic sediments.

The acoustic image of the calcareous core fromthe Rio Grande Rise (GeoB2821-1) shows muchmore lithological changes than the visual coredescription. Cool colours between 1.5 - 2.5 mdepth indicate unusually fine grain sizes (Breitzke1997). Alternately yellow/red and blue/blackcolours in the lower part of the core (> 6.0 m)reflect an interlayering of fine-grained nannofossiland coarse-grained foraminiferal ooze. Dating byorbital tuning shows that this interlayering coin-cides with the 41 ky cycle of obliquity (vonDobeneck and Schmieder 1999) so that fine-grained oozes dominate during glacial and coarse-grained oozes during interglacial stages.

The opal-rich diatomaceous sediments in corePS2567-2 from the Meteor Rise are characterizedby a very low attenuation. Only 2 - 3 calcareouslayers with significantly higher attenuation(yellow and red colours) can be identified asprominent lithological changes.

2.5.2 P- and S-Wave Velocity,Attenuation, Elastic Moduli andPermeability

As the acoustic properties of water-saturatedsediments are strongly controlled by the amountand distribution of pore space, cross plots of P-wave velocity and attenuation coefficient versusporosity clearly indicate the different bulk andelastic properties of terrigenous and biogenicsediments and can thus be used for an acousticclassification of the lithology. Additional S-wavevelocities (and attenuation coefficients) andelastic moduli estimated by least-square inversionspecify the amount of bulk and shear moduliwhich contribute to the P-wave velocity (Breitzke2000).

The cross plots of the P-wave parameters ofthe four cores considered above illustrate thatterrigenous, calcareous and diatomaceoussediments can uniquely be identified from theirposition in both diagrams (Fig. 2.19). In terri-

55

Fig.

2.

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56

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57

2.6 Sediment Echosounding

genous sediments (40KL, 47KL) P-wave velocitiesand attenuation coefficients increase with decrea-sing porosities. Computed S-wave velocities arevery low (≈ 60 - 65 m s-1) and almost independentof porosity (Fig. 2.20a) whereas computed S-waveattenuation coefficients (at 400 kHz) vary stronglyfrom 4·103 dB m-1 in fine-grained sediments to1.5·104 dB m-1 in coarse-grained sediments (Fig.2.20b). Accordingly, shear moduli are also low anddo not vary very much (Fig. 2.21b) so that higherP-wave velocities in terrigenous sediments mainlyresult from higher bulk moduli (Fig. 2.21a).

If calcareous, particularly foraminiferal compo-nents (FNO) are added to terrigenous sedimentsporosities become higher (≈ 70 - 80%, 47KL). P-wave velocities slightly increase from their mini-mum of 1475 m s-1 at 70% porosity to 1490 m s-1 at80% porosity (Fig. 2.19a) mainly due to an increasein the shear moduli from about 6.5 to 8.5 MPawhereas bulk moduli remain almost constant atabout 3000 MPa (Fig. 2.21b). However, a muchmore pronounced increase can be observed in theP-wave attenuation coefficients (Fig. 2.19b). Forporosities of about 80% they reach the samevalues (about 200 dB m-1) as terrigenous sedi-ments of about 55% porosity, but can easily bedistinguished because of higher P-wave velocitiesin terrigenous sediments. S-wave attenuationcoefficients increase as well in these hemipelagicsediments from about 1·105 dB m-1 at 65% porosityto about 2.5·105 dB m-1 at 80% porosity (Fig.2.20b), and are thus even higher than interrigenous sediments.

Calcareous foraminiferal and nannofossil oozes(NFO) show similar trends in both P-wave and S-wave parameters as terrigenous sediments, but areshifted to higher porosities due to their additionalintraporosities (GeoB2821-1; Figs. 2.19, 2.20).

In diatomaceous oozes P- and S-wave wavevelocities increase again though porosities arevery high (>80%, PS2567-2; Figs. 2.19, 2.20). Here,the diatom shells build a very stiff frame whichcauses high shear moduli and S-wave velocities(Fig. 2.21). It is this increase in the shear moduliwhich only accounts for the higher P-wavevelocities while the bulk moduli remain almostconstant and are close to the bulk modulus of seawater (Fig. 2.21). P-wave attenuation coefficientsare very low in these high-porosity sediments(Fig. 2.19b) whereas S-wave attenuation coeffici-ents are highest (Fig. 2.20b).

Permeabilities estimated from the least squareinversion mainly reflect the attenuation charac-

teristics of the different sediment types (Fig. 2.22).They reach lowest values of about 5·10-14 m2 infine-grained clayey mud and nannofossil ooze.Highest values of about 5·10-11 m2 occur in diato-maceous ooze due to their high porosities.Nevertheless, it should be kept in mind that thesepermeabilities are only estimates based on theinput parameters and assumptions incorporated inBiot-Stoll’s model. For instance one of theseassumptions is that only mean grain sizes areused, but the influence of grain size distributionsis neglected. Additionally, the total porosity isusually used as input parameter for the inversionscheme without differentiation between inter- andintraporosities. Comparisons of these estimatedpermeabilities with direct measurements unfortu-nately do not exist up to know.


While ultrasonic measurements are used to studythe structure and composition of sediment cores,sediment echosounders are hull-mounted acousticsystems which image the upper 10-200 m of sedimentcoverage by remote sensing surveys. They operatewith frequencies around 3.5-4.0 kHz. The examplespresented here were digitally recorded with thenarrow-beam Parasound echosounder andParaDIGMA recording system (Spieß 1993).

2.6.1 Synthetic Seismograms

Figure 2.23 displays a Parasound seismogramsection recorded across an inactive channel of theBengal Fan. The sediments of the terrace weresampled by a 10 m long piston core (47KL). Itsacoustic and bulk properties can either be directlycompared to the echosounder recordings or bycomputations of synthetic seismograms. Suchmodeling requires P-wave velocity and wet bulkdensity logs as input parameters. From theproduct of both parameters acoustic impedances I= vP·ρ are calculated. Changes in the acousticimpedance cause reflections of the normallyincident acoustic waves. The amplitude of suchreflections is determined by the normal incidencereflection coefficient R = (I2-I1 ) / (I2+I1 ), with (I1)and (I2) being the impedances above and belowthe interface. From the series of reflectioncoefficients the reflectivity can be computed asimpulse response function, including all internal


58

Fig. 2.19 (a) P-wave velocities and (b) attenuation coefficients (at 400 kHz) versus porosities for the foursediment cores 40KL, 47KL, GeoB2821-1, and PS2567-2. NFO is nannofossil foraminiferal ooze, FNO isforaminiferal nannofossil ooze (nomenclature after Mazullo et al. (1988)). Modified after Breitzke (2000).

59

Fig. 2.20 (a) S-wave velocities and (b) attenuation coefficients (at 400 kHz) derived from least square inversionbased on Biot-Stoll’s theory versus porosities for the four sediment cores 40KL, 47KL, GeoB2821-1, and PS2567-2.NFO and FNO as in Figure 2.19. Modified after Breitzke (2000).



60

Fig. 2.21 (a) S-wave velocity versus P-wave velocity and (b) shear modulus versus bulk modulus derived from leastsquare inversion based on Biot-Stoll’s theory for the four sediment cores 40KL, 47KL, GeoB2821-1, and PS2567-2.The dotted line indicates an asymptote parallel to the shear modulus axis which crosses the value for the bulkmodulus of seawater Kf = 2370 MPa on the bulk modulus axis. NFO and FNO as in Figure 2.19. Modified afterBreitzke (2000).

61

Fig. 2.22 Permeabilities derived from least square inversion based on Biot-Stoll’s theory versus porosities for thefour sediment cores 40KL, 47KL, GeoB2821-1, and PS2567-2. The regular spacing of the permeability values is dueto the increment (10 permeability values per decade) used for the optimization process in the inversion scheme.NFO and FNO as in Figure 2.19. Modified after Breitzke (2000).

multiples. Convolution with a source waveletfinally provides the synthetic seismogram. Inpractice, different time- and frequency domainmethods exist for synthetic seismogram compu-tations. For an overview, please refer to books antheoretical seismology (e.g. Aki and Richards,2002). Here, we used a time domain method called‘state space approach’ (Mendel et al. 1979).

Figure 2.24 compares the synthetic seismogramcomputed for core 47KL with the Parasoundseismograms recorded at the coring site. The P-wave velocity and wet bulk density logs used asinput parameters are displayed on the right-handside, together with the attenuation coefficient logas grain size indicator, the carbonate content andan oxygen isotope (δ18O-) stratigraphy. Anenlarged part of the gray shaded Parasoundseismogram section is shown on the left-handside. The comparison of synthetic and Parasounddata indicates some core deformations. If thesynthetic seismograms are leveled to the pro-minent reflection caused by the Toba Ash in 1.6 mdepth about 95 cm sediment are missing in theoverlying younger part of the core. Deeper reflec-

tions, particularly caused by the series of turbi-dites below 6 m depth, can easily be correlatedbetween synthetic and Parasound seismograms,though single turbidite layers cannot be resolveddue to their short spacing. Slight core stretchingor shortening are obvious in this lower part of thecore, too.

From the comparison of the gray shadedParasound seismogram section and the wiggletraces on the left-hand side with the syntheticseismogram, core logs and stratigraphy on theright-hand side the following interpretation can bederived. The first prominent reflection below seafloor is caused by the Toba Ash layer depositedafter the explosion of volcano Toba (Sumatra)75,000 years ago. The underlying series of reflec-tion horizons (about 4 m thickness) result from aninterlayering of very fine-grained thin terrigenousturbidites and pelagic sediments. They areyounger than about 240,000 years (oxygen isotopestage 7). At that time the channel was alreadyinactive. The following transparent zone between4.5 - 6.0 m depth indicates the transition to thetime when the channel was active, more than



62

Fig.

2.2

3Pa

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63

Fig.

2.2

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g si

te o

f 47

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Fro

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. W

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om (

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rass

199

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96).

Mod

ifie

d af

ter

Bre

itzke

(19

97).



64

300,000 years ago. Only terrigenous turbiditescausing strong reflections below 6 m depth weredeposited.

Transferred to the Parasound seismogram sec-tion in Figure 2.23 this interpretation means thatthe first prominent reflection horizon in the leveescan also be attributed to the Toba Ash layer (75 ka).The following transparent zone indicates completelypelagic sediments deposited on the levees duringthe inactive time of the channel (< 240 ka). Thesuspension cloud was probably trapped betweenthe channel walls so that only very thin, fine-grained terrigenous turbidites were deposited onthe terrace but did not reach the levee crests. Thehigh reflectivity part below the transparent zone inthe levees is probably caused by terrigenousturbidites deposited here more than 300,000 yearsago during the active time of the channel.

2.6.2 Narrow-Beam ParasoundEchosounder Recordings

Finally, some examples of Parasound echosounderrecordings from different terrigenous and biogenicprovinces are presented to illustrate that charac-teristic sediment compositions can already berecognized from such remote sensing surveysprior to the sediment core retrieval.

The first example was recorded on the RioGrande Rise in the western South Atlantic duringRV Meteor cruise M29/2 (Bleil et al. 1994) and istypical for a calcareous environment (Fig. 2.25a).It is characterized by a strong sea bottom reflectorcaused by coarse-grained foraminiferal sands.Signal penetration is low and reaches only about20 m.

In contrast, the second example from theConrad Rise in the Antarctic Ocean, recordedduring RV Polarstern cruise ANT XI/4 (Kuhn, pers.communication), displays a typical biogenicsiliceous environment (Fig. 2.25b). The diatoma-ceous sediment coverage seems to be verytransparent, and the Parasound signal penetratesto about 160 m depth. Reflection horizons arecaused by calcareous foraminiferal and nanno-fossil layers deposited during a retreat of thePolar Frontal Zone during interglacial stages.

The third example recorded in the Weddell Sea/Antarctic Ocean during RV Polarstern cruise ANTXI/4 as well (Kuhn, pers. communication) indi-cates a deep sea environment with clay sediments(Fig. 2.25c). Signal penetration again is high(about 140 m), and reflection horizons are very

sharp and distinct. Zones with upward curvedreflection horizons might possibly be indicatorsfor pore fluid migrations.

The fourth example from the distal BengalFan (Hübscher et al. 1997) was recorded duringRV Sonne cruise SO125 and displays terrigenousfeatures and sediments (Fig. 2.25d). Active andolder abandoned channel levee systems are cha-racterized by a diffuse reflection pattern whichindicates sediments of coarse-grained turbidites.Signal penetration in such environments is ratherlow and reaches about 30 - 40 m.

Acknowledgment

We thank the captains, crews and scientists on-board of RV Meteor, RV Polarstern and RV Sonnefor their efficient cooperation and help during thecruises in the South Atlantic, Antarctic and IndianOcean. Additionally, special thanks are to M.Richter who provided a lot of unpublished elec-trical resistivity data and to F. Pototzki, B. Piochand C. Hilgenfeld who gave much technicalassistance and support during the development ofthe full waveform logging system. V. Spießdeveloped the ParaDIGMA data acquisitionsystem for digital recording of the Parasoundechosounder data and the program system fortheir processing and display. His help is greatlyappreciated, too. H. Villinger critically read anearly draft and improved the manuscript by manyhelpful discussions. The research was funded bythe Deutsche Forschungsgemeinschaft (SpecialResearch Project SFB 261 at Bremen University,contribution no. 251 and project no. Br 1476/2-1+2)and by the Federal Minister of Education, Science,Research and Technology (BMBF), grant no.03G0093C.

Appendix

A: Physical Properties of SedimentGrains and Sea Water

The density (ρg) and bulk modulus (Kg) of thesediment grains are the most important physicalproperties which characterize the sediment type -terrigenous, calcareous and siliceous - andcomposition. Additionally, they are required asinput parameters for wave propagation modeling,

65

Fig. 2.25 a, b Parasound seismogram sections representing typical calcareous (Rio Grande Rise) and opal-richdiatomaceous (Conrad Rise) environments. Lengths and heights of both profiles amount to 50 km and 300 m,respectively. Vertical exaggeration (VE) is 111. The Parasound seismogram section from the Conrad Rise was kindlyprovided by G. Kuhn, Alfred-Wegener-Institute for Polar- and Marine Research, Bremerhaven, Germany and is anunpublished data set recorded during RV Polarstern cruise ANT IX/4. Modified after Breitzke (1997).

Appendix


66

Fig. 2.25 c, d Parasound Seismogram sections representing typical deep sea clay (Weddell Sea) and terrigenoussediments (Bengal Fan). Lengths and heights of both profiles amount to 50 km and 300 m, respectively. Verticalexaggeration (VE) is 111. The Parasound seismogram section from the Weddell Sea was kindly provided by G. Kuhn,Alfred-Wegener-Institute for Polar- and Marine Research, Bremerhaven, Germany and is an unpublished data setrecorded during RV Polarstern cruise ANT IX/4. Modified after Breitzke (1997).

67

Table 2A-1 Physical properties of sediment forming minerals, at laboratory conditions (20°C temperature, 1 atpressure). After 1Wohlenberg (1982) and 2Gebrande (1982).

Table 2A-2 Physical properties of sea water, at laboratory conditions (20°C temperature, 1 at pressure, 35 ‰salinity). After 1Wille (1986) and 2Siedler and Peters (1986).

e.g. with Biot-Stoll’s sediment model (Sect. 2.4.1).Table 2A-1 provides an overview on densities andbulk moduli of some typical sediment formingminerals.

Density (ρf), bulk modulus (Kf), viscosity (η),sound velocity (vP), sound attenuation coefficient(α) and electrical resistivity (Rf) of sea waterdepend on salinity, temperature and pressure.Table 2A-2 summarizes their values at laboratory

conditions, i.e. 20°C temperature, 1 at pressureand 35‰ salinity.

B: Corrections to Laboratory and InSitu Conditions

Measurements of physical properties are usuallycarried out under laboratory conditions, i.e. roomtemperature (20°C) and atmospheric pressure (1 at).

Mineral Density1 ρg [g cm-3] Bulk Modulus2 Κg [109 Pa]

terrigenous sediments quartz 2.649 - 2.697 37.6 - 38.1 (trigonal) biotite 2.692 - 3.160 42.0 - 60.0 muscovite 2.770 - 2.880 43.0 - 62.0 hornblende 3.000 - 3.500 84.0 - 90.0

calcareous sediments calcite 2.699 - 2.882 70.0 - 76.0

siliceous sediments opal 2.060 - 2.300 no data

Appendix

Parameter Value

sound velocity1 vP [m s-1] 1521 m s-1

sound attenuation coefficient1 α [10-3 dB m-1] 4 kHz ∼0.25

10 kHz ∼0.80

100 kHz ∼ 40

400 kHz ∼ 120

1000 kHz ∼ 300

density2 ρf [g/cm-3] 1.024

bulk modulus2 Κf [109 Pa] 2.37

viscosity2 η [10-3 Pa⋅s] 1.07

electrical resistivity2 Rf [Ω⋅m] 0.21


68

In order to correct for slight temperature varia-tions in the laboratory and to transfer laboratorymeasurements to in situ conditions, usuallytemperature and in situ corrections are applied.Temperature variations mainly affect the porefluid. Corrections to in situ conditions shouldconsider both the influence of reduced tempe-rature and increased hydrostatic pressure at thesea floor.

Porosity and Wet Bulk Density

In standard sea water of 35‰ salinity densityincreases by maximum 0.3·10-3 g cm-3 per °C(Siedler and Peters 1986), i.e. by less than 0.1%per °C. Hence, temperature corrections can usu-ally be neglected.

Differences between laboratory and in-situporosities are less than 0.001% (Hamilton 1971)and can thus be disregarded, too. Sea floor wetbulk densities are slightly higher than the cor-responding laboratory values due to the hydro-static pressure and the resulting higher density ofthe pore water. For Central Pacific sediments of75 - 85% porosity Hamilton (1971) estimated adensity increase of maximum 0.01 g cm-3 for waterdepths between about 500 - 3000 m and ofmaximum 0.02 g cm-3 for water depths betweenabout 3000 - 6000 m. Thus, corrections to sea floorconditions are usually of minor importance, too.However, for cores of several hundred meter lengththe effect of an increasing lithostatic pressure hasto be taken into account.

Electrical Resistivity

If porosities and wet bulk densities are determinedby galvanic resistivity measurements (Sect. 2.2.3)varying sediment temperatures are considered bycomputation of the formation factor (F) (see Eq.2.12). While the resistivity (Rs) of the sediment isdetermined by the small hand-held probe (cf. Sect.2.2.3) the resistivity (Rf) of the pore fluid is deri-ved from a calibration curve which describes thetemperature (T) - conductivity (c) relation by afourth power law (Siedler and Peters 1986)

44

33

221

1 TcTcTcTccR of ++++=− (2.22)

The coefficients (c0) to (c4) depend on thegeometry of the probe and are determined by aleast square fit to the calibration measurements instandard sea water.

P-wave velocity and attenuation

Bell and Shirley (1980) demonstrated that the P-wave velocity of marine sediments increasesalmost linearly by about 3 m s-1 per °C while theattenuation is independent of sediment tempe-rature, similar to the temperature dependence ofsound velocity and attenuation in sea water.Hence, to correct laboratory P-wave velocity mea-surements to a reference temperature of 20°CSchultheiss and McPhail’s (1989) equation

( )Tvv T −⋅+= 20320 (2.23)

can be applied, with (v20) = P-wave velocity at20°C (in m s-1), (T) = sediment temperature (in °C)and (vT) = P-wave velocity measured at tempera-ture (T) (in m s-1).

To correct laboratory P-wave velocity measu-rements to in situ conditions a modified time-ave-rage equation (Wyllie et al. 1956) can be used(Shipboard Scientific Party 1995)

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

−⋅+=labsituinlabsituin ccvv1111 φ (2.24)

(vlab) and (vin-situ) are the measured laboratory(20°C, 1 at) and the corrected in situ P-wavevelocities, (clab) and (cin-situ) the sound velocity insea water at laboratory and in situ conditions and(φ) the porosity. If laboratory and sea floorpressure, temperature and salinity are known fromtables or CTD measurements (clab) and (cin-situ) canbe computed according to Wilson’s (1960)equation

STPPT cccccS

++++= 14.1449 (2.25)

(cT), (cP), (cS) are higher order polynomials whichdescribe the influence of temperature (T), pressure(P) and salinity (S) on sound velocity. (cSTP)depends on all three parameters. Completeexpressions for (cT), (cP), (cS), (cSTP) can be foundin Wilson (1960). For T = 20°C, P = 1 at and S =0.035 Wilson’s equation results in a sound veloci-ty of 1521 m s-1.

69

2.7 Problems

Problem 1

What is the difference between bulk parametersand acoustic/elastic parameters concerning thedistribution of pore fluid and sediment grains ?

Problem 2

Which direct and which indirect methods do youknow to determine the porosity and wet bulkdensity of marine sediment, which of both para-meters is primarily determined by each method,and how can porosity values be converted todensity values and vice versa ?

Problem 3

Assume that you have recovered a sediment corein the Antarctic Ocean close to the Polar FrontalZone. The core is composed of an interlayering ofcalcareous and siliceous sediments. You wouldlike to determine the downcore porosity and wetbulk density logs by electrical resitivity measu-rements. What do you have to consider duringconversion of porosities to wet bulk densities ?

Problem 4

Which sediment property mainly influences theultrasonic acoustic wave propagation (50 - 500 kHz),and how affects it the P-wave velocity andattenuation in terrigenous and calcareous sedi-ments ?

Problem 5

Which parameter determines the amplitude orstrength of reflection horizons during sedimentechosounding, and which are the two physicalproperties that contribute to it ?

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