J. Carlos Santamarina

FABRIC MAP FOR KAOLINITE: EFFECTS OF pH AND IONIC CONCENTRATION ON BEHAVIOR

The behavior of fine-grained mineral systems is dependent on pore-fluid characteristics. The systematic analysis of previously published studies supports the development of a fabric map in the pH and ionic concentration space as a working hypothesis. This conceptual study is complemented with an extensive battery of tests where surface charge and particle interactions are controlled through pore-fluid characteristics. The macro-scale tests include sedimentation, viscosity and liquid limit, and involve a wide range of solid volume fractions (suspension to sediment) and strain levels. Experimental results permit the development of an updated fabric map on the pH-ionic concentration space which takes into consideration all experimental results. The fabric map is structured around a critical pH level and a threshold ionic concentration beyond which van der Waals attraction prevails.

Discrete Signals and Inverse Problems: An Introduction for Engineers and Scientists

Preface. Brief Comments on Notation. 1. Introduction. 1.1 Signals, Systems, and Problems. 1.2 Signals and Signal Processing -- Application Examples. 1.3 Inverse Problems -- Application Examples. 1.4 History -- Discrete Mathematical Representation. 1.5 Summary. Solved Problems. Additional Problems. 2. Mathematical Concepts. 2.1 Complex Numbers and Exponential Functions. 2.2 Matrix Algebra. 2.3 Derivatives -- Constrained Optimization 2.4 Summary. Further Reading. Solved Problems. Additional Problems. 3. Signals and Systems. 3.1 Signals: Types and Characteristics. 3.2 Implications of Digitization -- Aliasing 3.3 Elemental Signals and Other Important Signals. 3.4 Signal Analysis with Elemental Signals. 3.5 Systems: Characteristics and Properties. 3.6 Combination of Systems 3.7 Summary. Further Reading. Solved Problems. Additional Problems. 4. Time Domain Analyses of Signals and Systems. 4.1 Signals and Noise. 4.2 Cross- and Autocorrelation: Identifying Similarities. 4.3 The Impulse Response -- System Identification. 4.4 Convolution: Computing the Output Signal. 4.5 Time Domain Operations in Matrix Form. 4.6 Summary. Further Reading. Solved Problems. Additional Problems. 5. Frequency Domain Analysis of Signals (Discrete Fourier Transform). 5.1 Orthogonal Functions -- Fourier Series. 5.2 Discrete Fourier Analysis and Synthesis. 5.3 Characteristics of the Discrete Fourier Transform. 5.4 Computation in Matrix Form. 5.5 Truncation, Leakage, and Windows. 5.6 Padding. 5.7 Plots. 5.8 The Two-dimensional Discrete Fourier Transform. 5.9 Procedure for Signal Recording. 5.10 Summary. Further Reading and References. Solved Problems. Additional Problems. 6. Frequency Domain Analysis of Systems. 6.1 Sinusoids and Systems - Eigenfunctions. 6.2 Frequency Response. 6.3 Convolution. 6.4 Cross-spectral and Autospectral Densities. 6.5 Filters in the Frequency Domain -- Noise Control. 6.6 Determining H with Noiseless Signals (Phase Unwrapping). 6.7 Determining H with Noisy Signals (Coherence). 6.8 Summary. Further Reading and References. Solved Problems. Additional Problems. 7. Time Variation and Nonlinearity. 7.1 Nonstationary Signals: Implications. 7.2 Nonstationary Signals: Instantaneous Parameters. 7.3 Nonstationary Signals: Time Windows. 7.4 Nonstationary Signals: Frequency Windows. 7.5 Nonstationary Signals: Wavelet Analysis. 7.6 Nonlinear Systems: Detecting Nonlinearity. 7.7 Nonlinear Systems: Response to Different Excitations. 7.8 Time-varying Systems. 7.9 Summary. Further Reading and References Solved Problems. Additional Problems. 8. Concepts in Discrete Inverse Problems. 8.1 Inverse Problems -- Discrete Formulation. 8.3 Data-driven Solution -- Error Norms. 8.4 Model Selection -- Ockhams Razor. 8.5 Information. 8.6 Data and Model Errors. 8.7 Nonconvex Error Surfaces. 8.8 Discussion on Inverse Problems. 8.9 Summary. Further Reading and References. Solved Problems. Additional Problems. 9. Solution by Matrix Inversion. 9.1 Pseudoinverse. 9.2 Classification of Inverse Problems. 9.3 Least Squares Solution (LSS). 9.4 Regularized Least Squares Solution (RLSS). 9.5 Incorporating Additional Information. 9.6 Solution Based on Singular Value Decomposition. 9.7 Nonlinearity. 9.8 Statistical Concepts -- Error Propagation. 9.9 Experimental Design for Inverse Problems. 9.10 Methodology for the Solution of Inverse Problems. 9.11 Summary. Further Reading. Solved Problems. Additional Problems. 10. Other Inversion Methods. 10.1 Transformed Problem Representation. 10.2 Iterative Solution of System of Equations. 10.3 Solution by Successive Forward Simulations. 10.4 Techniques from the Field of Artificial Intelligence. 10.5 Summary. Further Reading. Solved Problems. Additional Problems. 11. Strategy for Inverse Problem Solving. 11.1 Step 1: Analyze the Problem. 11.2 Step 2: Pay Close Attention to Experimental Design. 11.3 Step 3: Gather High-quality Data. 11.4 Step 4: Pre-process the Data. 11.5 Step 5: Select an Adequate Physical Model. 11.6 Step 6: Explore Different Inversion Methods. 11.7 Step 7: Analyze the Final Solution. 11.8 Summary. Solved Problems. Additional Problems. Index.

Thermal conductivity of hydrate‐bearing sediments

[1] A thorough understanding of the thermal conductivity of hydrate-bearing sediments is necessary for evaluating phase transformation processes that would accompany energy production from gas hydrate deposits and for estimating regional heat flow based on the observed depth to the base of the gas hydrate stability zone. The coexistence of multiple phases (gas hydrate, liquid and gas pore fill, and solid sediment grains) and their complex spatial arrangement hinder the a priori prediction of the thermal conductivity of hydrate-bearing sediments. Previous studies have been unable to capture the full parameter space covered by variations in grain size, specific surface, degree of saturation, nature of pore filling material, and effective stress for hydrate-bearing samples. Here we report on systematic measurements of the thermal conductivity of air dry, water- and tetrohydrofuran (THF)-saturated, and THF hydrate-saturated sand and clay samples at vertical effective stress of 0.05 to 1 MPa (corresponding to depths as great as 100 m below seafloor). Results reveal that the bulk thermal conductivity of the samples in every case reflects a complex interplay among particle size, effective stress, porosity, and fluid-versus-hydrate filled pore spaces. The thermal conductivity of THF hydrate-bearing soils increases upon hydrate formation although the thermal conductivities of THF solution and THF hydrate are almost the same. Several mechanisms can contribute to this effect including cryogenic suction during hydrate crystal growth and the ensuing porosity reduction in the surrounding sediment, increased mean effective stress due to hydrate formation under zero lateral strain conditions, and decreased interface thermal impedance as grain-liquid interfaces are transformed into grain-hydrate interfaces.

Mechanical limits to microbial activity in deep sediments

The observed decline in microbial abundance with increasing depth has been associated to various environmental factors. Meanwhile, the role of geometrical constraints and soil-bacteria mechanical interactions remains poorly analyzed. Pore and pore-throat sizes may restrict habitable pore space and traversable interconnected porosity, and sediment-cell interaction may cause puncture or tensile failure of the cell membrane. In this study we compile published evidence on the presence of bacteria in deep sediments as well as pore and pore-throat size data in sediments at different depths to establish possible geometrical conditions for the sediment-cell complex. Compiled data are complemented with experimental results gathered through controlled axial compression experiments that reproduce the mechanical consolidation of deep sediment sequences. Then, we analyze the mechanical interaction between bacteria and sediments that may cause cell death. Finally, we combine data and model predictions to define the main regions in a particle-size versus depth space that characterize the fate of bacteria: “active and motile,” “trapped inside pores,” and “dead or dormant.” These regions constrain hypotheses related to the role of biological activity in deep sediments, research protocols and sampling methods, the viability of bioremediation strategies for contaminated sites, and the potential development of bioengineered sediments.

Electrical Conductivity in Soils: Underlying Phenomena

Electrical conductivity can be accurately and readily measured in the laboratory and in the field, with minimal electrode effects even in high specific surface soils and∕or high ionic concentration pore fluids. Electrical conductivity combines the contributions of particle conduction, surface conduction and pore fluid conduction, and the effects of particle shape and fabric. The interplay between participating soil parameters is often obscured in typical empirical equations, such as Archie’s law. New experimental results show that surface conduction is an important contributor to global soil conduction in high specific surface soils that are saturated with low-ionic concentration pore fluids; the relevance of surface conduction increases with decreasing porosity. On the other hand, pore fluid conduction prevails as the conductivity of the electrolyte and the porosity of the soil increase. Furthermore, low frequency conductivity anisotropy increases with increasing ionic concentration. Simple yet robust mi...

Mineral Dissolution and the Evolution of k0

Adequate knowledge of the in situ state of stress can be essential to the analysis of geotechnical systems. However, the measurement and prediction of k0 remain difficult. In particular, limited attention has been given to the evolution of k0 during the formation history of the soil and diagenetic processes such as mineral dissolution. Experimental and numerical results show that grain mass loss due to mineral dissolution produces a pronounced horizontal stress drop under zero lateral strain conditions; the state of stress may reach the active shear failure ka condition and internal shear planes may develop. While horizontal stress recovery often follows upon further dissolution, marked differences in fabric are observed between the pre and postdissolution soil structures.

Mechanical Effects of Biogenic Nitrogen Gas Bubbles in Soils

The fluid bulk stiffness of a soil is very sensitive to the presence of gas, and a small volume of bubbles can significantly affect the pore pressure response to loading, including Skempton’s B parameter, P-wave velocity, and liquefaction resistance. Biologically mediated processes can lead to the production of gases in soils; nitrogen is particularly advantageous because it is not a greenhouse gas, it is not combustible, and it has low solubility in water. Sands, silts, and clayey sands inoculated with Paracoccus denitrificans were monitored to assess the effects of nutrient availability, fines content, and pressure-diffusion on the evolution of nitrogen gas generation and bulk stiffness. Results show clear evidence of biogas bubble formation, earlier gas generation and entrapment in specimens with higher fines content, and a strong correlation between biogas volume and P-wave velocity. The volume of gas is correlated with specific surface, suggesting that biogas bubble formation develops as heterogeneou...

Contraction-driven shear failure in compacting uncemented sediments

Shear failure in sediments is universally linked with active boundary conditions, such as those imposed by tectonic stresses. Under conditions of no lateral strain, and in the absence of tectonic stress, soil mechanics theories predict a simple one-dimensional compaction in which sediment particles displace vertically without shear failure during pressure diffusion. Conflicting with this theory, shear failure planes are often found in sediments that formed under near-horizontal burial conditions. We investigated the effect of particle-scale volume contraction as a potential cause of shear failure in uncemented particulate materials and found that loss of particle volume under confined conditions (no external loading) resulted in pronounced lateral stress reduction, often reaching Coulomb frictional failure conditions. Shear strain localization was analytically predicted and modeled numerically, due entirely to volume loss at the grain scale. We define this mode of internally driven shear failure as “contractile” to distinguish it from that caused by external loading, and show that it can explain many natural fracture systems without invoking regional tectonics.

Particle Clogging in Radial Flow: Microscale Mechanisms

Summary Fluid-flow-driven particle migration through porous networks reflects the interplay between various particle-level forces, the relative size between migrating particles and pore constrictions, and the spatial variability of the velocity field. Experimental evidence shows that particle migration in radial fluid flow results in selfstabilizing annular clogging patterns when the particle size approaches the constriction size. Conversely, flow localization and flushing instability are observed when the particle size is significantly smaller than the pore-throat size.

Evolution of gas saturation and relative permeability during gas production from hydrate-bearing sediments: Gas invasion vs. gas nucleation

Capillarity and both gas and water permeabilities change as a function of gas saturation. Typical trends established in the discipline of unsaturated soil behavior are used when simulating gas production from hydrate-bearing sediments. However, the evolution of gas saturation and water drainage in gas invasion (i.e., classical soil behavior) and gas nucleation (i.e., gas production) is inherently different: micromodel experimental results show that gas invasion forms a continuous flow path while gas nucleation forms isolated gas clusters. Complementary simulations conducted using tube networks explore the implications of the two different desaturation processes. In spite of their distinct morphological differences in fluid displacement, numerical results show that the computed capillarity-saturation curves are very similar in gas invasion and nucleation (the gas-water interface confronts similar pore throat size distribution in both cases); the relative water permeability trends are similar (the mean free path for water flow is not affected by the topology of the gas phase); and the relative gas permeability is slightly lower in nucleation (delayed percolation of initially isolated gas-filled pores that do not contribute to gas conductivity). Models developed for unsaturated sediments can be used for reservoir simulation in the context of gas production from hydrate-bearing sediments, with minor adjustments to accommodate a lower gas invasion pressure Po and a higher gas percolation threshold.