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doi:10.2204/iodp.proc.341.202.2017

Methods

Permeability tests

The methods for permeability testing are similar to those of previous studies (e.g., James and Screaton, 2015) and were based on American Society for Testing and Materials (ASTM) designation D5084-90 (ASTM International, 1990). Permeability tests used Trautwein Soil Testing Equipment Company’s DigiFlow K, which consisted of a cell to contain the sample and provide isostatic effective stress and three pumps (Fig. F2). Deionized water was used as the fluid in the pumps, and a solution of 33 g NaCl per liter of water permeated the sample. Pressure was transmitted from the deionized water to the permeant across a rubber membrane in an interface chamber (Fig. F2).

The retrieved core samples from Expedition 341 were stored in plastic core liners and sealed bags to prevent moisture loss and refrigerated at 4°C until immediately before sample preparation. All tests were conducted with flow in the vertical direction (along the axis of the core) using the whole-round core. To provide freshly exposed surfaces, cores were trimmed on both ends using a cutting tool or wire saw, depending on core properties. Visual inspection was used to select portions of the core that were relatively uniform in composition and not disturbed or fractured. After trimming the ends of the sample, diameters of the trimmed whole-round cores ranged from 5.2 to 6.3 cm, and sample heights ranged from 6.2 to 9.0 cm. The sample was then placed in a rubber membrane and fitted with saturated porous disks and end caps. The membrane-encased sample was placed in the cell, which was then filled with deionized water. Fluid exchange occurs only through the flows lines connecting the end caps to the top and bottom pumps. A small confining pressure of ~0.03 MPa (5 psi) was applied to the water in the cell, and flow lines were flushed to remove any trapped air bubbles. After flushing the flow lines, the sample was backpressured to either ~0.28 MPa (40 psi) or ~0.41 MPa (60 psi) by concurrently ramping the cell pressure and the sample pressure to maintain a constant effective stress of 0.03 MPa (5 psi). Backpressure was maintained at least 24 h. Subsequently, the cell fluid pressure was increased while the sample backpressure was maintained, thus increasing the effective stress on the sample. This effective stress both consolidated the sample and pushed the flexible membrane against the sample to prevent flow bypassing the sample.

Because the whole-round samples were sealed immediately after cutting the core liner, the samples were expected to be near saturation prior to testing. Backpressuring at 0.28 MPa (40 psi) for ~24 h is sufficient to ensure full saturation under these conditions (ASTM International, 1990). A B-test on each sample was used to check saturation. In a B-test, the cell confining pressure was instantaneously increased by 10 psi and the sample response was measured. The ratio of sample pressure change to cell pressure change is the Skempton B-coefficient, which is typically near 1 for soft to medium clays (Wang, 2000), and a B-test result 0.95 is typically used to indicate saturation for soft to medium clays. This criterion is not applicable for more consolidated materials because compiled B-coefficients for mudstone, sandstone, and limestone are 0.95, 0.50 to 0.88, and 0.25, respectively (Wang, 2000). Samples below 0.95 were given additional time for saturation or backpressure was increased. Saturation was assumed if the B-value did not change with increased time.

For each sample location, in situ effective stress was estimated using the shipboard bulk density measurements of the overlying sediments. Effective stress increments between depths of shipboard measurements were calculated assuming hydrostatic fluid pressures and summed. The estimated in situ effective stress is generally much greater than what was reached in the laboratory testing. Although these permeability values should not be assumed to reflect in situ conditions, they can be used to construct permeability-porosity relationships for use in fluid-flow modeling (e.g., Daigle and Screaton, 2015).

For every sample, flow tests were performed at two different effective stress steps. Once the target effective stress was achieved for each step, cell pressure and backpressure were maintained. The sample was allowed to equilibrate for at least 12 h and generally for 24 h. Throughout testing, inflows and outflows to the cell fluid were monitored to assess changes in sample volume, and sample data were recorded every minute. Because fluid pressure in the closed hydraulic system was affected by temperature changes, testing was conducted within a closed cabinet to keep the internal temperature uniform. Testing temperatures were 28° ± 1°C. Two or more flow tests were performed at each effective stress level, with flow direction varied between tests. Flow tests were run at specific pressures of the top and bottom pump while recording flow rates into and out of the sample.

The pressure difference (ΔP) from the top and bottom pumps were converted to hydraulic head difference (Δh):

where

• ρ_w = fluid density (1021 kg/m³), and
• g = acceleration due to gravity (9.81 m/s²).

Darcy’s law was used to calculate the hydraulic conductivity:

where

• Q = measured flow rate (in cubic meters per second),
• K = hydraulic conductivity (in meters per second),
• A = the cross-sectional area of the sample (in square meters),
• Δh = the difference in head across the sample (in meters), and
• Δl = the length of the sample (in meters).

The hydraulic conductivity values (k) were then converted to permeability (in square meters) using the following equation:

where

• ρ = fluid density (1021 kg/m³),
• g = acceleration due to gravity (9.81 m/s²), and
• μ = viscosity (0.000893 Pa·s).

For the laboratory temperature (averaging 28°C) and fluid salinity (33 g/L), a fluid density of 1021 kg/m³ and viscosity of 0.000893 Pa·s were calculated based on relationships compiled by Sharqawy et al. (2010). Assuming reasonable water compressibility, density change caused by the applied pressure was minor (<0.1%). A 1 h interval of stable flow rates was averaged for the permeability calculations, and the standard deviation of the permeability during that interval was calculated to assess uncertainty. The fluctuations in the calculated permeability are likely caused by slight temperature variations. The resulting volume changes would cause temporary changes in measured flow rates. The time interval was selected based on where inflow best matched outflow, indicating steady-state conditions, and where the standard deviation was minimized.

The corresponding porosity for each effective stress was calculated using the change in volume of fluid (milliliters) contained in the cell during each consolidation step. The volume change during consolidation was assumed to be solely a result of changes in sample porosity. Influences of material and apparatus stiffness were assumed to be negligible. Total sample volume (V_T(0)) was calculated using πr²h, where r is the radius of the core sample and h is the height of the sample. Initial porosities (n₀) for volume calculations were obtained from the shipboard moisture and density results (see the "Expedition 341 summary" chapter [Jaeger et al., 2014]). The two nearest shipboard measurements were averaged for each sample. We assumed that the porosity of the sample at the end of backpressure is similar to the initial porosity (n₀) of the sample because of the small change in effective stress (0.03 MPa).

Using the initial porosity (n₀), the volume of voids before the testing (V_v(0)) was calculated:

Volume of solids (V_s) was calculated using

The change in volume of water in the cell (ΔV_T(1)) was calculated using the difference of cell volumes between two consecutive steps (e.g., cell volume at backpressure and cell volume at first consolidation). The new total volume of the sample (V_T(1)) after pore spaces were reduced during the consolidation process was determined by subtracting the change in cell volume at the end of the consolidation step (ΔV_T(1)) from the total sample volume (V_T(0)):

Using the calculated new total volume of the sample (V_T(1)), the new porosity at the end of the consolidation (n₁) was calculated as

Grain size analyses

Subsamples were extracted in 1.5 cm thick intervals from the permeability sample after completion of the permeability tests. Because the cores used for permeability testing were relatively consistent in composition, the subsamples were assumed to be representative. The subsamples were homogenized and used for grain size, biogenic silica, and clay mineral analyses.

For grain size analyses, the samples were disaggregated in a solution of sodium hexametaphosphate to inhibit clay flocculation. Subsamples were also immersed in an ultrasonic bath for a minimum of 2 h to assist disaggregation. A small aliquot of the homogenized sample was dried to determine water content, which was then used to establish the equivalent dry mass used in the particle size analysis. Once disaggregated, a subsample was wet sieved at 63 µm to determine the sand-size fraction. A separate subsample was wet sieved at 53 µm, and material smaller than 53 µm was analyzed on a 5100 Micrometrics SediGraph (Coakley and Syvitski, 1991). The SediGraph emits X-rays that record the settling rates of particles suspended in a sodium hexametaphosphate solution. The principle of Stoke’s law was used to calculate grain sizes. The SediGraph data were combined with the wet-sieved results to normalize the mud and sand fraction to their relative masses to determine the proportion of sand-, silt-, and clay-size particles. Clay-size particles were defined as smaller than 4 µm based on the Wentworth grain-size classification.

Silica analyses

To determine the amount of biogenic silica in each sample, an alkaline leaching method was used, as outlined by DeMaster (1981) and Spinelli and Underwood (2004). As noted by Spinelli and Hutton (2013), this method can include other amorphous silica in addition to biogenic opal. The subsamples were digested in 40 mL of 0.0316 M NaOH at 85°C. Biogenic opal and other amorphous silica digests more rapidly in alkaline solution than clay minerals, resulting in a rapid increase in silica concentration in the alkaline solution (Spinelli and Underwood, 2004). However, this signal can be overprinted by dissolution of silicate clay minerals. Thus, continuous dissolution of the samples was monitored over a total of 5 h. DeMaster (1981) found that alumino-silicates from clay dissolution release silica linearly over time. Most of the silica is dissolved within 2 h of digestion (Grasshoff et al., 1983). The concentration of silica (milligrams of SiO₂ per gram) in the leachate after 0, 1, 2, 3, 4, and 5 h was determined by spectrophotometry. The intercept of the regression through the 3–5 h measurements was used to calculate the concentration of amorphous silica (Saccone et al., 2006).

Clay mineral analyses

Quantitative X-ray clay mineralogy followed methods described in Underwood et al. (2003). The method uses normalization factors determined after measuring the X-ray diffraction peak area produced by standard mineral mixtures with known weight percentages of each component. The total content of clay minerals was determined using the X-ray diffractogram of the bulk sediment samples, whereas clay mineralogy of the <2 μm fraction was studied using preferentially oriented mounts (Moore and Reynolds, 1997).

Standard mineral mixtures (Table T1) and splits of freeze-dried bulk sediment samples were gently disaggregated using a mortar and pestle, mixed with distilled water, and ground in a McCrone micronizing mill for 5 min to homogenize the samples. Each sample was oven-dried at 40°C overnight and sieved at 125 μm. Standard mixtures and bulk samples were side-loaded in aluminum sample holders to ensure random orientation and analyzed in a Rigaku Ultima X-ray diffraction system at 40kV, 35 mA, incidence angle from 3° to 35°2θ, 0.01°2θ step size, and scan speed of 1°2θ/min.

A portion of each bulk sediment sample (3–4 g) was mixed with 0.05% sodium hexametaphosphate and placed in an ultrasonic bath for 60 min to facilitate particle disaggregation. After >24 h, samples were wet-sieved at 63 μm to remove the sand fraction. The <63 μm fraction of each sample was centrifuged for 36 s to extract the fraction finer than 2 μm. This procedure was repeated 4–5 times per sample to ensure extraction of all <2 μm particles from the sediment. Oriented samples were mounted in glass slides following Moore and Reynolds (1997). Each sample was analyzed in the X-ray diffractometer with the incidence angle varying from 3° to 23°2θ at a 0.01°2θ step with a scan speed of 1 s/step. To evaluate the presence of smectite in the clay fraction of the sediment, the sample slides were put in a sealed desiccator with an ethylene glycol bath at 60°–65°C for ~18 h, after which they were analyzed in the X-ray diffractometer under the previous conditions.

The diffractograms of the mineral standard mixtures, bulk samples, and clay mineral slides were processed in MacDiff (version 4.2.6; http://www.ccp14.ac.uk/ccp/web-mirrors/krumm/macsoftware/macdiff/MacDiff.html). Normalization factors used to semi-quantify the mineralogy were calculated using the diffractograms of the standard mixtures and using the normalization factor technique proposed by Fisher and Underwood (1995). The area of the basal peaks used to estimate the normalization factors were calculated using the Pearson VII pattern fit:

• Composite clay mineral at ~19.8°2θ (d= 4.49 Å);
• Quartz (101) at 26.65°2θ (d= 3.34 Å);
• Double peak for plagioclase at 27.77°–28.02°2θ (d= 3.21–3.18 Å); and
• Calcite (104) at 29.42°2θ (d= 3.04 Å).

These factors were used to semiquantify total clays, quartz, plagioclase, and calcite in the bulk sediment samples (Fig. F3).

For the <2 μm fraction, quantification of smectite (15–17 Å), illite (10 Å), and chlorite/kaolinite (7 Å) was done following Biscaye (1965), using the diffractograms of the glycolated clay mineral slides (Spinelli and Underwood, 2004) (Fig. F3). This method considers the area under the basal peaks corrected by weighing factors: 1× for smectite, 41× for illite, and 21× for chlorite/kaolinite. Semiquantification results were obtained after normalization of the peak areas (% smectite + % illite + % chlorite/kaolinite = 100%). Based on these results, the proportion of each clay mineral in the bulk sample was calculated using the total clay mineral content (weight percent), and the total biogenic opal (weight percent) measured in the bulk sample following Spinelli and Underwood (2004). Underwood et al. (2003) reports that the Biscaye peak area method underestimates the amount of smectite by 7–17 wt% and overestimates illite and chlorite by as much as 16 and 8 wt%, respectively. However, we used the Biscaye (1965) method because it is a readily available method to determine relative variations in clay mineralogy in the absence of clay mineral standards (e.g., Underwood et al., 2003).

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