Experimental support for a predictive osmotic model of clay membranes

Osmosis has been cited as a mechanism for explaining anomalously high fluid pressures in the subsurface. Clays and shales act as membranes, and osmotic flux across these units may result in pressures sufficiently high to explain these anomalies. The theoretical osmotic pressures as calculated solely from solution properties can be quite large; however, it is not yet resolved whether these geologic membranes are sufficiently ideal to generate such pressures.Osmotic efficiencies of a Na-bentonite membrane were measured by a series of hyperfiltration experiments using various molarities of NaCl at two different porosities. The highest osmotic efficiency (0.8912) occurred at the lower porosity and the lowest NaCl input solution. The lowest measured osmotic efficiency (0.0423) occurred at the high porosity and the highest NaCl input concentration.The osmotic efficiencies obtained from the hyperfiltration experiments correlate very favorably with the Fritz-Marine Membrane Model. This model predicts that the maximum osmotically-induced hydraulic pressures in the subsurface should occur across shales having low porosities and high cation exchange capacities in which the unit separates solutions of brackish waters.     

The Probability Perturbation Method: A New Look at Bayesian Inverse Modeling

Building of models in the Earth Sciences often requires the solution of an inverse problem: some unknown model parameters need to be calibrated with actual measurements. In most cases, the set of measurements cannot completely and uniquely determine the model parameters; hence multiple models can describe the same data set. Bayesian inverse theory provides a framework for solving this problem. Bayesian methods rely on the fact that the conditional probability of the model parameters given the data (the posterior) is proportional to the likelihood of observing the data and a prior belief expressed as a prior distribution of the model parameters. In case the prior distribution is not Gaussian and the relation between data and parameters (forward model) is strongly non-linear, one has to resort to iterative samplers, often Markov chain Monte Carlo methods, for generating samples that fit the data likelihood and reflect the prior model statistics. While theoretically sound, such methods can be slow to converge, and are often impractical when the forward model is CPU demanding. In this paper, we propose a new sampling method that allows to sample from a variety of priors and condition model parameters to a variety of data types. The method does not rely on the traditional Bayesian decomposition of posterior into likelihood and prior, instead it uses so-called pre-posterior distributions, i.e. the probability of the model parameters given some subset of the data. The use of pre-posterior allows to decompose the data into so-called, “easy data” (or linear data) and “difficult data” (or nonlinear data). The method relies on fast non-iterative sequential simulation to generate model realizations. The difficult data is matched by perturbing an initial realization using a perturbation mechanism termed “probability perturbation.” The probability perturbation method moves the initial guess closer to matching the difficult data, while maintaining the prior model statistics and the conditioning to the linear data. Several examples are used to illustrate the properties of this method.     

Stable isotopic fingerprint of a hyporheic–hypolentic boundary in a reservoir

Stable isotopes of H₂O are used to define the hyporheic–hypolentic boundary in Ledbetter Creek as it discharges to Kentucky Lake, a constructed reservoir in western Kentucky, USA. High-resolution (centimeter-scale) sample collection and analysis were utilized to determine one-dimensional variations in δ²H and δ¹⁸O of H₂O and chloride (Cl⁻) across the boundary. During reservoir low stand in winter, the hyporheic–hypolentic zone contains water from Ledbetter Creek and groundwater separated by an interface at ~10 cm below the channel bottom. Following reservoir-stage increase in spring and summer, water from Kentucky Lake infiltrates into the hyporheic–hypolentic zone to a depth of at least 18 cm below the channel bottom. Reservoir-stage decline in autumn causes source-water mixing, largely obscuring the hyporheic–hypolentic boundary. Stable isotopes provide an effective complement to conventional tracers for delineation of water masses within the hyporheic–hypolentic zone.

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Resumen Se han utilizado isótopos estables del agua para definir el límite hiporreico-hipoléntico en Ledbetter Creek, que constituye una zona de descarga del lago Kentucky, una presa construida al Oeste de Kentucky, USA. Se ha llevado a cabo una recogida de muestras de alta resolución (a escala centimétrica) y se utilizaron los resultados para determinar las variaciones unidimensionales en δ²H y δ¹⁸O del H₂O y los cloruros (Cl⁻) alrededor del límite. Durante la época de niveles bajos en invierno, la zona hiporreica-hipolentica tiene agua procedente de Ledbetter Creek y de agua subterránea separada por una interfase de ~10 cm debajo del límite del canal. Siguiendo el incremento de los niveles en la presa en primavera y verano, el agua del Lago Kentucky se infiltra en la zona hiporreica-hipoléntica hasta una profundidad de, al menos, 18 cm bajo el límite hiporreico-hipoléntico. Los isótopos estables aportan un complemento efectivo a los trazadores convencionales para la delimitación de masas de agua dentro de la zona hiporreica-hipoléntica.

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Résumé L’utilisation des isotopes stables de la molécule d’eau a permis de définir l’interface hyporhéique-hypolentique dans la Ledbetter Creek, au point de déversement dans le réservoir artificiel que constitue le Kentucky Lake (Ouest du Kentucky, Etats-Unis). Une campagne de prélèvements à haute résolution (échelle centimétrique) a contribué à déterminer les variations unidimensionnelles des valeurs de δ2H et de δ18O de la molécule d’eau et de la concentration en chlorures (Cl⁻) de part et d’autre de l’interface. En hiver, lorsque le niveau du réservoir est minimal, la zone hyporhéique-hypolentique contient de l’eau de la Ledbetter Creek et de l’eau souterraine, séparées par un interface situé environ 10 cm sous le fond du chenal. Suite aux recharges printanières et estivales, l’eau du Kentucky Lake envahit la zone hyporhéique-hypolentique sur plus de 18 cm sous le fond du chenal. En automne, la baisse de niveau dans le réservoir occasionne un mélange des eaux, rendant diffus l’interface hyporhéique-hypolentique. Les isotopes stables constituent ainsi un complément efficace aux traceurs conventionnels pour la délimitation des masses d’eau dans la zone hyporhéique-hypolentique.

     

GPS-derived strain in northwestern California: Termination of the San Andreas fault system and convergence of the Sierra Nevada–Great Valley block contribute to southern Cascadia forearc contraction

GPS-derived velocities (1993–2002) in northwestern California show that processes other than subduction are in part accountable for observed upper-plate contraction north of the Mendocino triple junction (MTJ) region. After removing the component of elastic strain accumulation due to the Cascadia subduction zone from the station velocities, two additional processes account for accumulated strain in northern California. The first is the westward convergence of the Sierra Nevada–Great Valley (SNGV) block toward the coast and the second is the north–northwest impingement of the San Andreas fault system from the south on the northern California coastal region in the vicinity of Humboldt Bay. Sierra Nevada–Great Valley block motion is northwest toward the coast, convergent with the more northerly, north–northwest San Andreas transform fault-parallel motion. In addition to the westward-converging Sierra Nevada–Great Valley block, San Andreas transform-parallel shortening also occurs in the Humboldt Bay region. Approximately 22 mm/yr of distributed Pacific–SNGV motion is observed inland of Cape Mendocino across the northern projections of the Maacama and Bartlett Springs fault zones but station velocities decrease rapidly north of Cape Mendocino. The resultant 6–10 mm/yr of San Andreas fault-parallel shortening occurs above the southern edge of the subducted Gorda plate and at the latitude of Humboldt Bay. Part of the San Andreas fault-parallel shortening may be due to the viscous coupling of the southern edge of the Gorda plate to overlying North American plate. We conclude that significant portions of the upper-plate contraction observed north of the MTJ region are not solely a result of subduction of the Gorda plate but also a consequence of impingement of the western edge of the Sierra Nevada–Great Valley block and growth of the northernmost segments of the San Andreas fault system.     

Lessons learned in remediation and restoration in the Oklahoma prairie: A review

For almost a decade the Tallgrass Prairie Preserve in Oklahoma has been used as a field laboratory for the investigation of aspects of the remediation and restoration of oil and brine spills. Objectives of this work have included: (1) simplification of the remediation process and lowering the cost of remediation; (2) the development of methods to accelerate or jump-start the restoration process; and (3) determining appropriate metrics for assessing the status of soil ecosystem recovery. This research has resulted in a number of lessons learned that will be presented here which can be exported to other exploration and production sites, especially sites located in sensitive ecosystems. Key observations have included the role of a fertilizer amendment in linking the remediation and restoration process at an oil-impacted site, the use of nematodes as ecological indicators in the restoration of oil- and brine-impacted sites, and the development of a two-stage process for remediation of brine impacted sites that does not include significant use of gypsum.     

A Case Study of Soil-Gas Sampling in Silt and Clay-Rich (Low-Permeability) Soils

Soil-gas sampling and analysis is a common tool used in vapor intrusion assessments; however, sample collection becomes more difficult in fine-grained, low-permeability soils because of limitations on the flow rate that can be sustained during purging and sampling. This affects the time required to extract sufficient volume to satisfy purging and sampling requirements. The soil-gas probe tubing or pipe and sandpack around the probe screen should generally be purged prior to sampling. After purging, additional soil gas must be extracted for chemical analysis, which may include field screening, laboratory analysis, occasional duplicate samples, or analysis for more than one analytical method (e.g., volatile organic compounds and semivolatile organic compounds). At present, most regulatory guidance documents do not distinguish between soil-gas sampling methods that are appropriate for high- or low-permeability soils. This paper discusses permeability influences on soil-gas sample collection and reports data from a case study involving soil-gas sampling from silt and clay-rich soils with moderate to extremely low gas permeability to identify a sampling approach that yields reproducible samples with data quality appropriate for vapor intrusion investigations for a wide range of gas-permeability conditions.     

A Compilation of Statistics for VOCs from Post-1990 Indoor Air Concentration Studies in North American Residences Unaffected by Subsurface Vapor Intrusion

This paper provides a summary of a number of indoor air quality studies reporting concentrations of volatile organic compounds (VOCs) in indoor air samples collected from residential properties in North America and provides average values for certain statistics (percentiles, detection frequency, maximum). This compilation includes several VOCs that are commonly assessed in studies of subsurface vapor intrusion to indoor air, but may also be attributable to consumer products, building materials, or even outdoor air (ambient) sources, specifically benzene, carbon tetrachloride, chloroform, 1,1-dichloroethane, 1,1-dichloroethene, 1,2-dichloroethane, cis and trans-1,2-dichloroethene, ethylbenzene, methyl tert-butyl ether, methylene chloride, tetrachloroethene, trichloroethene, toluene, trichloro-1,2,2-trifluoroethane, 1,1,1-trichloroethane, vinyl chloride, and meta, para, and ortho-xylene. In studies spanning 1990 through 2005, eleven of these compounds were detected in more than 50% of samples collected, and for several compounds (benzene, carbon tetrachloride, chloroform, ethylbenzene, and tetrachloroethene) the lower and upper quintiles of the indoor air concentrations are within the range of typical risk-based target levels. These summary statistics may help interpret data collected during a vapor intrusion investigation and communicate the findings of indoor air quality studies to building occupants and other stakeholders. Similar studies have been published in the past, but there has been a gradual change in indoor air quality over time and a large amount of new data has been collected, so this paper provides more relevant information for current use than previous compilations.     

Patterns of Seismicity Associated with USGS Identified Areas of Potentially Induced Seismicity

A systematic review across U.S. Geological Survey (USGS) identified potentially induced seismic locations was conducted to discover seismic distance patterns and trends over time away from injection disposal wells. Previous research indicates a 10 km (6 miles) average where the majority of induced seismicity is expected to occur within individual locations, with some areas reporting a larger radius of 35 km (22 miles) to over 70 km (43 miles). This research analyzed earthquake occurrences within nine USGS locations where specified wells were identified as contributors to induced seismicity to determine distance patterns from disposal wells or outward seismic migration over time using established principles of hydrogeology. Results indicate a radius of 31.6 km (20 miles) where 90% of felt earthquakes occur among locations, with the closest proximal felt seismic events, on average, occurring 3 km (1.9 miles) away from injection disposal wells. The results of this research found distance trends across multiple locations of potentially induced seismicity.     

Flare Prediction Using Photospheric and Coronal Image Data

The precise physical process that triggers solar flares is not currently understood. Here we attempt to capture the signature of this mechanism in solar-image data of various wavelengths and use these signatures to predict flaring activity. We do this by developing an algorithm that i) automatically generates features in 5.5 TB of image data taken by the Solar Dynamics Observatory of the solar photosphere, chromosphere, transition region, and corona during the time period between May 2010 and May 2014, ii) combines these features with other features based on flaring history and a physical understanding of putative flaring processes, and iii) classifies these features to predict whether a solar active region will flare within a time period of \(T\) hours, where \(T = 2 \mbox{ and }24\). Such an approach may be useful since, at the present time, there are no physical models of flares available for real-time prediction. We find that when optimizing for the True Skill Score (TSS), photospheric vector-magnetic-field data combined with flaring history yields the best performance, and when optimizing for the area under the precision–recall curve, all of the data are helpful. Our model performance yields a TSS of \(0.84 \pm0.03\) and \(0.81 \pm0.03\) in the \(T = 2\)- and 24-hour cases, respectively, and a value of \(0.13 \pm0.07\) and \(0.43 \pm0.08\) for the area under the precision–recall curve in the \(T=2\)- and 24-hour cases, respectively. These relatively high scores are competitive with previous attempts at solar prediction, but our different methodology and extreme care in task design and experimental setup provide an independent confirmation of these results. Given the similar values of algorithm performance across various types of models reported in the literature, we conclude that we can expect a certain baseline predictive capacity using these data. We believe that this is the first attempt to predict solar flares using photospheric vector-magnetic field data as well as multiple wavelengths of image data from the chromosphere, transition region, and corona, and it points the way towards greater data integration across diverse sources in future work.