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Methods and materials

Sampling and sample handling

This project was allocated four whole-round (WR) specimens for constant-flow permeability tests. The objective was to test interbeds of clayey siltstone and fine sand to siltstone turbidites. The samples are from lithostratigraphic Unit V (accreted trench or Shikoku Basin deposits) over a depth of 2174.98 to 2209.64 mbsf (Fig. F2). The WR samples were capped and taped in their plastic core liners on board the D/V Chikyu, sealed with wet sponges in aluminum vacuum bags to prevent moisture loss, and stored at ~4°C until immediately prior to trimming. The specimens we tested are texturally and compositionally heterogeneous, with siltstone laminae and black bands of pyrite. Steep bedding dips are also obvious in the specimens (Fig. F3).

The specimens were indurated and easy to extract without cutting the liners open. Unfortunately, one section (348-C0002P-2R-2) fell into pieces, so only three were tested in the vertical (along core) direction. In addition, the WR intervals were too small to allow trimming of companion specimens in the horizontal (cross core) direction, thereby precluding an assessment of the anisotropy of permeability. Each cylindrical specimen was trimmed along the sides, top, and bottom using a razor blade and knife. Their lengths after trimming ranged from 3.6 to 7.8 cm and averaged 5.46 cm, as measured by caliper to a resolution of 0.02 mm. The diameters were 3.8 to 4.5 cm and averaged 4.0 cm.

For most samples, we calculated values of initial (pretest) and post-test porosity from measurements of gravimetric water content (Table T1). This was done by oven-drying the trimmings at 105°C in accordance with shipboard protocols (see the “Methods” chapter [Tobin et al., 2015b]) and by assuming 100% pore water saturation. However, the material dried out quickly during the trimming, so some of the values of pretest porosity may be inaccurate. Comparable values of grain density and porosity were imported from shipboard measurements of the closest adjacent specimen (see the “Site C0002” chapter [Tobin et al., 2015c]). A correction for pore water salt content was applied using:

Wc = (MtMd)/(MdrMt),


  • Wc = corrected dry weight,
  • Mt = total mass of saturated specimen,
  • Md = mass of dried specimen, and
  • r = salinity (permil).

For salt corrections on pretest trimmings, we assumed an average interstitial salinity value of 35‰. For post-test trimmings, we assumed a salinity value of 25‰ to approximate the simulated seawater that was used to saturate specimens.

Constant-flow apparatus

Yue et al. (2012) provided a thorough description of the instrumentation and procedures for testing permeability at the University of Missouri (USA). To summarize, the system consists of an acrylic confining cell, porous stones between the specimen and end caps, a constant-flow syringe pump, one differential pressure transducer to measure hydraulic head difference between the specimen top cap and bottom cap, and an air/water interface panel for regulating the confining fluid pressure and backpressure (Fig. F4). Signals from the differential pressure transducer permit calculations of hydraulic head difference (Δh) at a precision of ±1 cm H2O over a range of ±1000 cm H2O. A digital interface also records values of effective isotropic confining stress and elapsed time. A syringe pump (KDS Scientific, Model 260) simultaneously injects and extracts pore fluid from opposite ends of the specimen. The flow pump holds one syringe (Hamilton GasTight Series 1000) to infuse pore fluid into one end while another syringe withdraws an equal volume of fluid from the other end at the same rate. During the tests described here, volumetric flow rate (Q) ranged from 2.0 × 10–4 cm3/min to 8.0 × 10–4 cm3/min.

Backpressure saturation

Prior to each test, all permeant lines and porous stones were saturated with simulated seawater (25 g NaCl to 1 L tap water). After placing a specimen on the pedestal, the top cap was attached, and a latex membrane was added to encase the cylinder using a vacuum membrane expander. The confining chamber was then sealed, and the cell was filled with tap water. Saturation was achieved by ramping pore-fluid backpressure to 0.48 MPa (70 psi) using the panel board (air/water interface) while also ramping the confining pressure to maintain an effective isotropic confining stress of 0.034 MPa (5 psi). The elevated backpressure was maintained for at least 24 h. We confirmed saturation by increasing the confining pressure to 0.55 MPa (80 psi) and measuring the corresponding pore pressure (u) response over the change in stress (σ), which yields Skempton’s B-value (B = Δu/Δσ). Following the precedent of Yue et al. (2012), we judged the specimen to be saturated if either B ≥ 0.95 (Table T1) or a B value < 0.95 remained constant for >48 h. After saturation, the cell pressure was increased to consolidate the specimen at an isotropic effective stress of 0.28 MPa (40 psi). Pore water drained during consolidation from both the top and bottom of the specimen by opening valves on the confining cell. The volume of expelled pore water was measured using the backpressure pipette and monitored for equilibrium to calculate the corresponding volume change of the specimen. After finishing tests at 0.28 MPa, the specimen was consolidated further and tested again at an effective stress of 0.55 MPa (80 psi).

Constant-flow tests

Two samples were tested under the two isotropic effective stresses of 0.28 MPa (40 psi) and 0.55 MPa (80 psi). The third sample was tested only under 0.28 MPa because the cylinder fell apart during loading to 0.55 MPa (Table T1). The normal protocol consists of two runs from top to bottom (denoted as a negative flow value) and two runs from bottom to top (denoted as a positive flow value) (Fig. F5). We monitored the transient response from the differential pressure transducer. Plots of applied discharge velocity (v) and steady-state hydraulic gradient (is) allow for visual assessments of consistency and linearity (see Appendix Figs. AF1, AF2, and AF3). Yue et al. (2012) regarded such data as “reliable” if the coefficient of determination (R2), calculated by least-squared linear regression of those values, is >0.9835.

Data reduction

We calculated the value of hydraulic conductivity (K, in meters per second) for each specimen using Darcy’s Law:

Q = KisA = K (Δhs /ΔL) A,


  • Q = applied volumetric flow rate (cm3/s),
  • is = steady-state hydraulic gradient,
  • Δhs = steady-state head difference,
  • ΔL = length over which head difference occurs (initial height of the specimen), and
  • A = cross-sectional flow area (initial specimen area).

The corresponding value of discharge velocity was computed using v = Q/A. Conversion of hydraulic conductivity to values of intrinsic permeability (k, in square meters) takes the permeant properties into account:

k = (Kµ)/(ρg),


  • µ = viscosity of permeant at room temperature (0.001 Pa·s),
  • ρ = density of permeant (1027 kg/m3), and
  • g = gravitational acceleration (9.81 m/s2).

Room temperature was typically set at 72°F (22°C).

Imaging microfabric

Yue et al. (2012) provided a thorough description of the procedures used at the University of Missouri (USA) to image and characterize the preferred orientation of microfabric. To summarize, oriented specimens were cut using a razor blade after the flow-through tests were finished (Fig. F6). Wet, uncoated, and unfixed surfaces were imaged using an FEI Quanta 600 FEG scanning electron microscope (SEM), which operates in environmental mode (ESEM) at 20 kV with the specimen chamber pressure set at 400 Pa. Water vapor (~98% humidity) from a built-in reservoir keeps specimens from losing moisture with the cooling stage set to 2°C. We used a gaseous backscattered electron detector, spot = 3.0, and a working distance of ~10 mm. That combination generates an imaging resolution of ~4 nm, and the field of view is ~150 mm across with 1000× magnification (Fig. F7).

Each gray-mode TIF image from the ESEM was processed for statistical analysis using ImageJ software (, which isolates the apparent dimensions of objects in a two-dimensional image. We generally counted between 600 and 800 grains per image (depending on particle size) to calculate statistics for preferred grain orientation (Table T2). Each particle orientation (azimuth of the apparent long axis) is assigned to an angle between 0° and 180°. For the vertical cut surface, the core axis is oriented at 90°. Rose diagrams were constructed using Rozeta software (, which automatically assigns azimuths to bins at 10° intervals. We plotted cumulative frequency curves to obtain graphical solutions of standard deviation (d) according to Folk and Ward (1957) statistics:

d = [(φ84 – φ16)/4] + [(φ95 – φ5)/6.6],

where φ84, φ16, φ95, and φ5 represent the azimuth (in degrees) at the 84th, 16th, 95th, and 5th percentiles. In this context, the largest possible value of d is 72.3° (i.e., a case in which φ16 and φ5 = 0° and φ84 and φ95 = 180°). To compare each standard deviation to this maximum d value we calculated the “index of microfabric orientation” (i) as

i = 1 – (d/72.3).

With random arrangements of particles, the cumulative curve is relatively flat (slope < 0.75) near the median, d > 35°, and i < 0.5. As particles attain better parallel alignment, azimuths cluster more tightly, the slope of the cumulative curve steepens (slope > 1.00) near the median, d < 25°, and i > 0.65 (Yue et al., 2012).

Energy dispersive X-ray spectroscopy

Energy dispersive X-ray spectroscopy (EDS) was used to compare relative elemental proportions from measuring spots on selected SEM images. The SEM is equipped with a Bruker QUANTAX 200 high-speed silicon drift detector. A representative example of the spectrum for typical silicate minerals is shown in Figure F8 (Sample 348-C0002P-4R-2, 98 cm).