Compressibility and permeability data for kaolin: a comparison between 1-dimensional oedometers and a high-stress permeameter [Data set]

Samples analyzed and the data presented are associated with kaolinite purchased from a retailer and the data resulting from their analysis do not have site-specific implications. The geographic extent for the data in this data release is thus described as global.

High-Stress Permeameter – Correction Factors: The custom-designed high stress permeameter (HSP) requires two correction factors: 1) a correction factor for deriving the true specimen height, and 2) a correction factor for the permeability of the porous stones that sit above and below a specimen and factor into the overall measured permeability.

Correction #1) The specimen height is calculated from the height of the piston protruding above the chamber (see figure 9 in the HSP Specimen Height Example tab). To connect that measurable length to the specimen height, the system was set up with no specimen (specimen height = 0), and the system was cycled through the range of applied vertical stresses (0 to 16 MPa) at two different chamber pressures. This yields an offset we can subtract from the piston protrusion that, for a given applied stress and chamber pressure, yields the specimen height. An example of this calculation is given in the HSP Specimen Height Example tab.

Correction #2) Permeability of the porous stones was measured during the specimen height calibration tests while there was no specimen. Based on the linear relationship between the differential pressure and the fluid flow rate, the permeability of the porous stones could be calculated for the range of applied stresses in a standard test (0 to 16 MPa). Results of this measurement, and an example of how the porous stone permeability can be accounted for when trying to measure permeability in a sediment specimen, are presented in the Direct Permeability Example tab.

Consolidation: In this study, kaolin taken from a single batch ("Peerless2" air-floated kaolin from Vanderbilt Minerals) was used for 1-dimensional consolidation testing. Specifically, the tests were run to obtain the compression index, Cc, and the recompression index, Cr, for kaolin across three types of devices: The custom designed high-stress permeameter (HSP), two identical industry-standard oedometers with a servo-controlled load (GeoTac) and an industry-standard oedometer with a dead-weight load (ELE International). These compression index data are measured on kaolin in deionized water. For the HSP, the procedure followed the methods described for the Effective Stress Cell (ESC) in Santamarina and others (2015) and Jang and others (2019). For the oedometers, the consolidation procedures were based on the methods described in Jang and others (2018) and the American Society for Testing and Materials standard D2435 (ASTM, 2011). The specific process steps used for this study are detailed in Garcia and Waite (2026).
References:
ASTM, D2435/D2435M-11-Standard Test Methods for One-Dimensional Consolidation Properties of Soils Using Incremental Loading, 2011, ASTM International, West Conshohocken, PA, https://www/doi.org/10.1520/D2435_D2435M-11.
Garcia, A.V., and Waite, W.F., 2026, Establishing the equivalence of compressibility and permeability data from a High-Stress Permeameter (HSP) with standard oedometer consolidation results: Geotechnical Testing Journal, https://www.doi.org/10.1520/GTJ20250043.
Jang, J., Cao, S.C., Stern, L.A., Jung, J., and Waite, W.F., 2018, Impact of pore fluid chemistry on fine-grained sediment fabric and compressibility: Journal of Geophysical Research - Solid Earth, v. 123, p. 5495-514, https://doi.org/10.1029/2018JB015872.
Jang, J., Dai, S., Yoneda, J., Waite, W.F., Stern, L.A., Boze, L.-G., Collett, T.S., and Kumar, P., 2019, Pressure core analysis of geomechanical and fluid flow properties of seals associated with gas hydrate-bearing reservoirs in the Krishna-Godavari Basin, offshore India: Marine and Petroleum Geology, v. 108, p. 537-550, https://doi.org/10.1016/j.marpetgeo.2018.08.015.
Santamarina, J.C., Dai, S., Terzariol, M., Jang, J., Waite, W.F., Winters, W.J., Nagao, J., Yoneda, J., Konno, Y., Fujii, T., and Suzuki, K., 2015, Hydro-bio-geomechanical properties of hydrate-bearing sediments from Nankai Trough: Marine and Petroleum Geology, v. 66, p. 434-450, https://doi.org/10.1016/j.marpetgeo.2015.02.033.

Permeability - Direct Flow Method: During the 1-dimensional consolidation testing on kaolin, the custom designed high-stress permeameter (HSP) was used at the end of certain consolidation steps to measure permeability by directly flowing water through the specimen while measuring the relationship between flow rate and pressure gradient. This method follows the description for the Effective Stress Cell (ESC) in Santamarina and others (2015) and Jang and others (2019). The specific process steps used for this study are detailed in Garcia and Waite (2026), and the "Direct Permeability Example" tab contains a template for deriving permeability estimates from flow and pressure gradient data.
References:
Garcia, A.V. and Waite, W.F., 2026, Establishing the equivalence of compressibility and permeability data from a High-Stress Permeameter (HSP) with standard oedometer consolidation results: Geotechnical Testing Journal, https://www.doi.org/10.1520/GTJ20250043.
Jang, J., Dai, S., Yoneda, J., Waite, W.F., Stern, L.A., Boze, L.-G., Collett, T.S., and Kumar, P., 2019, Pressure core analysis of geomechanical and fluid flow properties of seals associated with gas hydrate-bearing reservoirs in the Krishna-Godavari Basin, offshore India: Marine and Petroleum Geology, v. 108, p. 537-550, https://doi.org/10.1016/j.marpetgeo.2018.08.015.
Santamarina, J.C., Dai,S., Terzariol, M., Jang, J., Waite, W.F., Winters, W.J., Nagao, J., Yoneda, J., Konno, Y., Fujii, T., and Suzuki, K., 2015, Hydro-bio-geomechanical properties of hydrate-bearing sediments from Nankai Trough: Marine and Petroleum Geology, v. 66, p. 434-450, https://doi.org/10.1016/j.marpetgeo.2015.02.033.

Permeability - Log-time Method: During the 1-dimensional consolidation testing on kaolin, the three oedometers yielded consolidation versus time curves that can be analyzed via Terzaghi’s Log-Time method to estimate permeability. Following the method in Budhu (2011), these calculations were used in this study and contrasted with the direct-flow results from the HSP. The specific process steps used for this study are detailed in Garcia and Waite (2026), and the "Log Time Permeability Example" tab contains a template for deriving permeability estimates from consolidation data.
References:
Budhu, M., 2011, Soil Mechanics and Foundations (3rd Edition): John Wiley and Sons, Inc., Hoboken, NJ.
Garcia, A.V. and Waite, W.F., 2026, Establishing the equivalence of compressibility and permeability data from a High-Stress Permeameter (HSP) with standard oedometer consolidation results: Geotechnical Testing Journal, https://www.doi.org/10.1520/GTJ20250043.

Note: The number of significant figures displayed in a given cell depends on the source of the information. Imported values are given as measured in the example tabs. Results data for compressibility and permeability are limited to three significant figures for consolidation and permeability data (or to the nearest 0.01 MPa for stresses).

Grain Size: Samples submitted to the Sediment Laboratory for grain size analysis using the Horiba laser diffraction unit (LA-960) and divided into batches of no more than 30 samples. Each batch is entered into a Microsoft Excel data entry spreadsheet (e.g., LD Worksheet Template_####.xlsx, where #### is the identifier assigned to the sample submission) to record the initial and dried sample weights. Each batch is also is entered into macro-enabled Microsoft Excel data entry spreadsheets (####_GrainSizeWorksheet_LD1-30.xlsm or ####_GrainSizeWorksheet_LD31-60.xlsm, where #### is the identifier assigned to the sample submission, "LD1-30" and "LD31-60" refer to the pre-labeled and weighed glass laser diffraction vials the samples will be run in) to record the measurement data coming from the laser diffraction unit and incorporate the initial sample weights.

Fine fractions ready for analysis by the Horiba laser diffraction unit are rehydrated with distilled water. Fifteen (15) ml of pre-mixed 40 g/l sodium hexametaphosphate [(NaPO3)6] are added to each sample. If the height of the fluid in the laser diffraction vial is less than 5 cm, more distilled water is added to raise the level to no more than 8 cm in the vial. The samples are gently stirred, covered, and allowed to soak for at least 1 hour (for samples that were not dried) up to 24 hours (for samples that were dried). Soaked vials are placed into an ultrasonic bath and run for 10 minutes at a frequency of 37 Hz with a power level of 100. If the samples appear to be fully disaggregated, they are placed into pre-determined autosampler locations and are run using the Horiba LA-960 for Windows software to get the fine fraction grain size distributions. The fine fraction distribution data are added to the appropriate data entry spreadsheets. The spreadsheet is used to calculate a continuous phi class distribution from the original fractions. Data from this submission were processed using version 2.1 of the data entry spreadsheet. Grain size distribution statistics are calculated according to the methods of Collias and others (1963).
Reference:
Collias, E. E., Rona, M. R., McMannus, D. A., and Creager, J. S., 1963, Machine processing of technical data: University of Washington, Technical report #87, https://apps.dtic.mil/sti/tr/pdf/AD0423746.pdf.