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Results and discussion

The quality of the dry density and porosity logs generated from the high-resolution MSCL data is dependent on the quality of the MSCL bulk density data. Despite the high linear correlation coefficient between the MAD and uncorrected MSCL ρB, MSCL-derived values are generally higher than depth-equivalent MAD measurements. The overprediction is greater at higher sediment ρB (Fig. F4). The correction procedure developed here reduces both the overall offset and the scatter that arises from variability in the core quality (Fig. F4).

The complete downhole corrected MSCL ρB data set shows close agreement with the MAD data (Fig. F5). Similar agreement is seen in the derived ρD and ϕ data. The only core that showed significant deviation between the corrected MSCL and the MAD ρB was 302-M0002A-23X. Here a single MAD measurement from Section 302-M0002A-23X-2 was used to develop the correction factor and provided a much better fit than the average correction factor from lithologic Subunit 1.3. Increased divergence between the MAD and MSCL predictions of ρD and ϕ data is introduced by using the average grain density for lithologic units/subunits in Equations 6 and 7. This assumption overlooks any natural variability in sediment composition. Between Subunits 1.1 and 1.5, this natural variability would include proportional changes in the sand, silt, and clay contents of the sediments, as well as the presence of authigenic iron-manganese minerals (see the “Sites M0001–M0004” chapter) that characteristically have a higher ρG than generic silty clays.

Beneath Subunit 1.5, increased variability in the occurrence and quantity of total organic carbon and authigenic minerals such as pyrite (Stein et al., 2006) make the use of the average ρG more problematic. For instance, although quartz has a ρG of 2.65 g/cm3, pyrite has a grain density of 5.02 g/cm3, introducing large variability in the ρB logs from the MSCL. This variability is not adequately sampled in the discrete MAD data nor is it accounted for by employing average ρG. Below Core 302-M0004A-28X (Fig. F2), there are no MAD measurements to correct the MSCL data. The average correction factors for lithologic Unit 3 and ρG from petrophysical Subunit 3b were used to correct the ρB and generate the ρD and ϕ logs for these cores.

The ρB, ρD, and ϕ data from this study are available in Table T4. The MSCL data include measurements that were made on sediments described as disturbed in Table T24 in the “Sites M0001–M0004” chapter. How the results from this study are applied to future research depends on the nature and resolution of the work. To a first order, the use of average grain densities for lithologic units and subunits in Equations 6 and 7 introduces an error into the dry density and porosity data. This error may exaggerate absolute differences between units and subunits but does not diminish the significance of the variability within them. Through sections where sediments are believed to be relatively homogeneous, a depth-dependent relationship for dry density can be derived and used in mass accumulation rate calculations (e.g., see Moran, 1997). Filtering of the data to remove sections with known core disturbances is certainly recommended (e.g., see caption for Fig. F5). Once cleaned, artificial variability in the data can be reduced by applying a generous smoothing function, the size of which should depend on the resolution of the study.