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James G Berryman

Publications and source records attributed to James G Berryman.

5 recordsLinked to original sources

Dispersion of waves in porous cylinders with patchy saturation: formulation and torsional waves.

Laboratory experiments on wave propagation through saturated and partially saturated porous media have often been conducted on porous cylinders that were initially fully saturated and then allowed to dry while continuing to acquire data on the wave behavior. Since it is known that drying typically progresses from outside to inside, a sensible physical model of this process is concentric cylinders having different saturation levels-the simplest example being a fully dry outer cylindrical shell together with a fully wet inner cylinder. We use this model to formulate the equations for wave dispersion in porous cylinders for patchy saturation (i.e., drainage) conditions. In addition to multiple modes of propagation obtained numerically from these dispersion relations, we find two distinct analytical expressions for torsional wave modes. We solve the resulting torsional wave dispersion relation for two examples: Massillon sandstone and Sierra White granite. One essential fact that comes to light during the analysis is that the effective shear moduli of the gas- and liquid-saturated regions must differ, otherwise it is impossible to account for the laboratory torsional wave data. Furthermore, the drainage analysis appears to give improved qualitative and quantitative agreement with the data for both of the materials considered.

Journal Article↗

Time-reversal analysis for scatterer characterization.

A new application of time-reversal processing of wave scattering data permits characterization of scatterers by analyzing the number and nature of the singular functions (or eigenfunctions) associated with individual scatterers when they have multiple contributions from monopole, dipole, and/or quadrupole scattering terms. We discuss acoustic, elastic, and electromagnetic scattering problems for low frequencies. Specific examples for electromagnetic scattering from one of a number of small conducting spheres show that each sphere can have up to six distinct time-reversal eigenfunctions associated with it.

Journal Article↗

Linear dynamics of double-porosity dual-permeability materials. I. Governing equations and acoustic attenuation.

The equations governing the linear acoustics of composites with two isotropic porous constituents are derived from first principles using volume-averaging arguments. The theory is designed for modeling acoustic propagation through heterogeneous porous structures. The only restriction placed on the geometry of the two porous phases is that the overall composite remains isotropic. The theory determines the macroscopic fluid response in each porous phase in addition to the combined bulk response of the grains and fluid in the composite. The complex frequency-dependent macroscopic compressibility laws that are obtained allow for fluid transfer between the porous constituents. Such mesoscopic fluid transport between constituents within each averaging volume provides a distinct attenuation mechanism from the losses associated with the net Darcy flux within individual constituents as is quantified in the examples.

Journal Article↗

Linear dynamics of double-porosity dual-permeability materials. II. Fluid transport equations.

For the purpose of understanding the acoustic attenuation of double-porosity composites, the key macroscopic equations are those controlling the fluid transport. Two types of fluid transport are present in double-porosity dual-permeability materials: (1) a scalar transport that occurs entirely within each averaging volume and that accounts for the rate at which fluid is exchanged between porous phase 1 and porous phase 2 when there is a difference in the average fluid pressure between the two phases and (2) a vector transport that accounts for fluid flux across an averaging region when there are macroscopic fluid-pressure gradients present. The scalar transport that occurs between the two phases can produce large amounts of wave-induced attenuation. The scalar transport equation is derived using volume-averaging arguments and the frequency dependence of the transport coefficient is obtained. The dual-permeability vector Darcy law that is obtained allows for fluid flux across each phase individually and is shown to have a symmetric permeability matrix. The nature of the cross coupling between the flow in each phase is also discussed.

Journal Article↗

Statistically stable ultrasonic imaging in random media.

Analysis of array data from acoustic scattering in a random medium with a small number of isolated targets is performed in order to image and, thereby, localize the spatial position of each target. Because the host medium has random fluctuations in wave speed, the background medium is itself a source of scattered energy. It is assumed, however, that the targets are sufficiently larger and/or more reflective than the background fluctuations so that a clear distinction can be made between targets and background scatterers. In numerical simulations nonreflective boundary conditions are used so as to isolate the effects of the host randomness from those of the spatial boundaries, which can then be treated in a separate analysis. It is shown that the key to successful imaging is finding statistically stable functionals of the data whose extreme values provide estimates of scatterer locations. The best ones are related to the eigenfunctions and eigenvalues of the array response matrix, just as one might expect from prior work on array data processing in complex scattering media having homogeneous backgrounds. The specific imaging functionals studied include matched-field processing and linear subspace methods, such as MUSIC (MUtiple SIgnal Classification). But statistical stability is not characteristic of the frequency domain, which is often the province of these methods. By transforming back into the time domain after first diagonalizing the array data in the frequency domain, one can take advantage of both the time-domain stability and the frequency-domain orthogonality of the relevant eigenfunctions.

Models, Statistical↗