Alex Rinehart

Pore networks in continental and marine mudstones: characteristics and controls on sealing behavior.

Mudstone pore networks are strong modifiers of sedimentary basin fluid dynamics and have a critical role in the distribution of hydrocarbons and containment of injected fluids. Using core samples from continental and marine mudstones, we investigate properties of pore types and networks from a variety of geologic environments, together with estimates of capillary breakthrough pressures by mercury intrusion porosimetry. Analysis and interpretation of quantitative and qualitative three-dimensional (3D) observations, obtained by dual focused ion beam–scanning electron microscopy, suggest seven dominant mudstone pore types distinguished by geometry and connectivity. A dominant planar pore type occurs in all investigated mudstones and generally has high coordination numbers (i.e., number of neighboring connected pores). Connected networks of pores of this type contribute to high mercury capillary pressures due to small pore throats at the junctions of connected pores and likely control most matrix transport in these mudstones. Other pore types are related to authigenic (e.g., replacement or pore-lining precipitation) clay minerals and pyrite nodules; pores in clay packets adjacent to larger, more competent clastic grains; pores in organic phases; and stylolitic and microfracture-related pores. Pores within regions of authigenic clay minerals often form small isolated networks (

Variation of hydrometeorological conditions along a topographic transect in Northwestern Mexico during the North American monsoon

Abstract Relatively little is currently known about the spatiotemporal variability of land surface conditions during the North American monsoon, in particular for regions of complex topography. As a result, the role played by land–atmosphere interactions in generating convective rainfall over steep terrain and sustaining monsoon conditions is still poorly understood. In this study, the variation of hydrometeorological conditions along a large-scale topographic transect in northwestern Mexico is described. The transect field experiment consisted of daily sampling at 30 sites selected to represent variations in elevation and ecosystem distribution. Simultaneous soil and atmospheric variables were measured during a 2-week period in early August 2004. Transect observations were supplemented by a network of continuous sampling sites used to analyze the regional hydrometeorological conditions prior to and during the field experiment. Results reveal the strong control exerted by topography on the spatial and tem...

Fracture propagation in Indiana Limestone interpreted via linear softening cohesive fracture model

We examine the use of a linear softening cohesive fracture model (LCFM) to predict single-trace fracture growth in short-rod (SR) and notched 3-point-bend (N3PB) test configurations in Indiana Limestone. The broad goal of this work is to (a) understand the underlying assumptions of LCFM and (b) use experimental similarities and deviations from the LCFM to understand the role of loading paths of tensile fracture propagation. Cohesive fracture models are being applied in prediction of structural and subsurface fracture propagation in geomaterials. They lump the inelastic processes occurring during fracture propagation into a thin zone between elastic subdomains. LCFM assumes that the cohesive zone initially deforms elastically to a maximum tensile stress (σmax) and then softens linearly from the crack opening width at σmax to zero stress at a critical crack opening width w1. Using commercial finite element software, we developed LCFMs for the SR and N3PB configurations. After fixing σmax with results from cylinder splitting tests and finding an initial Youngs modulus (E) with unconfined compressive strength tests, we manually calibrate E and w1 in the SR model against an envelope of experimental data. We apply the calibrated LCFM parameters in the N3PB geometry and compare the model against an envelope of N3PB experiments. For accurate simulation of fracture propagation, simulated off-crack stresses are high enough to require inclusion of damage. Different elastic moduli are needed in tension and compression. We hypothesize that the timing and location of shear versus extensional micromechanical failures control the qualitative macroscopic force-versus-displacement response in different tests. For accurate prediction, the LCFM requires a constant style of failure, which the SR configuration maintains until very late in deformation. The N3PB configuration does not maintain this constancy. To be broadly applicable between geometries and failure styles, the LCFM would require additional physics, possibly including elastoplastic damage in the bulk material and more complicated cohesive softening models.

Using Wavelet Covariance Models for Simultaneous Picking of Overlapping P‐ and S‐Wave Arrival Times in Noisy Single‐Component Data

We present a method for automatically identifying overlapping elastice‐waveelastice‐wave phase arrivals in single‐component data. The algorithm applies to traditional near‐source seismic, microseismicity and picoseismicity monitoring, and acoustic emission monitoring; we use acoustic emissions examples as a worst‐case demonstration. These signals have low signal‐to‐noise and, because of small geometric dimensions, overlapping P ‐ and S ‐wave arrivals. Our method uses the statistics of temporal covariance across many wavelet scales. We use a nonnormalized rectilinity function of the scale covariance. The workflow begins by denoising signals and making a rough first‐arrival estimate. We then perform a continuous Daubechies wavelet transform over tens to hundreds of scales on the signal and find a moving covariance across transform scales. The nonnormalized rectilinity is calculated for each of the covariance matrices, and we sharpen changes in the rectilinity values with a maximization filter. We then estimate phase arrival times using thresholds of the filtered rectilinity. Overall, we have a high success rate for both P ‐ and S ‐wave arrivals. Remaining challenges include estimation of arrival times of long duration, cigar‐shape events, and culling complex high‐magnitude electrical noise. By using higher‐order Daubechies wavelet transforms, the scale covariance metric reflects variations in higher‐moment statistics (skewness and kurtosis) and changes in short‐term versus long‐term means, as well as the covariance across timescales of the signal. For single‐component data, it is necessary to preserve both amplitude and correlation information of the signal; this necessitates using the nonnormalized rectilinity function.