Microseismic Full Waveform Modeling in Anisotropic Media with Moment Tensor Implementation

Seismic anisotropy which is common in shale and fractured rocks will cause travel-time and amplitude discrepancy in different propagation directions. For microseismic monitoring which is often implemented in shale or fractured rocks, seismic anisotropy needs to be carefully accounted for in source location and mechanism determination. We have developed an efficient finite-difference full waveform modeling tool with an arbitrary moment tensor source. The modeling tool is suitable for simulating wave propagation in anisotropic media for microseismic monitoring. As both dislocation and non-double-couple source are often observed in microseismic monitoring, an arbitrary moment tensor source is implemented in our forward modeling tool. The increments of shear stress are equally distributed on the staggered grid to implement an accurate and symmetric moment tensor source. Our modeling tool provides an efficient way to obtain the Green’s function in anisotropic media, which is the key of anisotropic moment tensor inversion and source mechanism characterization in microseismic monitoring. In our research, wavefields in anisotropic media have been carefully simulated and analyzed in both surface array and downhole array. The variation characteristics of travel-time and amplitude of direct P- and S-wave in vertical transverse isotropic media and horizontal transverse isotropic media are distinct, thus providing a feasible way to distinguish and identify the anisotropic type of the subsurface. Analyzing the travel-times and amplitudes of the microseismic data is a feasible way to estimate the orientation and density of the induced cracks in hydraulic fracturing. Our anisotropic modeling tool can be used to generate and analyze microseismic full wavefield with full moment tensor source in anisotropic media, which can help promote the anisotropic interpretation and inversion of field data.     

Carbon Stores, Sinks, and Sources in Forests of Northwestern Russia: Can We Reconcile Forest Inventories with Remote Sensing Results?

Forest inventories and remote sensing are the two principal data sources used to estimate carbon (C) stocks and fluxes for large forest regions. National governments have historically relied on forest inventories for assessments but developments in remote sensing technology provide additional opportunities for operational C monitoring. The estimate of total C stock in live forest biomass modeled from Landsat imagery for the St. Petersburg region was consistent with estimates derived from forest inventory data for the early 1990s (272 and 269 TgC, respectively). The estimates of mean C sink in live forest biomass also agreed well (0.36 and 0.34 Mg C ha^–1 yr^–1). Virtually all forest lands were accumulating C in live biomass, however when the net change in total ecosystem C stock was considered, 19% of the forest area were a net source of C. The average net C sink in total ecosystem biomass is quite weak (0.08 MgC ha^–1 yr^–1 and could be reversed by minor increases in harvest rates or a small decline in biomass growth rates.     

Separation of incident and reflected waves in wave–current flumes

A technique is developed to separate the incident and reflected waves propagating on a known current in a laboratory wave–current flume by analyzing wave records measured at two or more locations using a least squares method. It can be applied to both regular and irregular waves. To examine its performance, numerical tests are made for waves propagating on quiescent or flowing water. In some cases, to represent the signal noise and measurement error, white noise is superimposed on the numerically generated wave signal. For all the cases, good agreement is observed between target and estimation.     

Stall markets in metropolitan Sydney

Stall markets on open air, suburban sites are an important new form of retailing in Sydney. The existing literature on petty commodity forms of production argues that stall markets are conserved in underdeveloped economies for a variety of reasons but the relevance of these ideas to the markets in many cities in advanced economies has not been considered. This paper identifies the basic types of stall markets in Sydney, establishes that these markets are not ephemeral and shows that they have characteristics and parameters which are similar to those of conventional shopping centres. Thus the way is open to compare stall markets with conventional retailing, to assess the role of stall markets in post‐industrial societies and to investigate the reasons for their recent appearance in Sydney.     

Iron titanium oxides in equilibrium with metallic iron

The iron titanium oxide phases ulvite, ilmenite and ferropseudobrookite were synthesized in equilibrium with metallic iron at 1000 ° C, 1130 ° C and 1300 ° C in CO₂/H₂ gas mixtures.The composition of the phases were determined by wet chemical and electron microprobe analyses and by direct oxygen determination.The chemical composition of the Fe-Ti oxide phases in equilibrium with metallic iron is sensitively influenced by temperature and by bulk composition.Ulvite in equilibrium with wüstite does not contrivalent titanium in the whole temperature range up to the eutectic temperature at 1312 °C.Ulvite+ilmenite phase assemblages contain trivalent titanium only at temperatures above 1200 ° C.A ferropseudobrookite phase is stable under the given conditions at temperatures above 1068 °C (Ender and Woermann, 1977).Ferropseudobrookite in equilibrium with metallic iron always contains trivalent titanium.Deviations from stoichiometric compositions of the solid solution phases are generally small. Thus recalculation of microprobe data to stoichiometric solid solutions does not involve a major error.From: Bruno Simons, Diplomarbeit Aachen, October 1974     

GIS Methodology for Characterizing Historical Conditions of the Willamette River Flood Plain, Oregon

Recent environmental developments have stimulated an interest in conservation and restoration of the historical Willamette River flood plain, both to protect against flooding and to provide wildlife habitat. In order to best utilize scarce resources, we characterized historical and modern river channel and flood‐plain conditions to evaluate changes and help prioritize restoration sites. Using cartographic and photographic data sources, we developed a Geographic Information System (GIS) to map active channels, side channels, islands and tributaries for four separate dates, as well as riparian and flood‐plain vegetation characteristics for pre‐European settlement and modern time periods. Coverages based on flood records and other boundaries were used to partition the flood plain into spatial subsets for analysis. The GIS allowed comparisons between historical and present conditions for a variety of environmental factors. Much of the pre‐settlement channel complexity has been removed. Total channel length in 1995 was 26% less than in 1850, with almost 58% of the river's side channels disconnected from the system. In addition, we found a 72% loss of flood‐plain forest from 1850 to 1995, since it was converted to agricultural and urban land uses. Selected river and flood‐plain variables were made available for a spatial model to prioritize potential locations for flood‐plain restoration.     

Can bottom-up procedures improve the performance of stream classifications?

Top-down methods for defining stream classifications are based on a conceptual model or expert-defined rules, whereas bottom-up methods use biological training data and statistical modelling. We compared the performance of six classification methods for explaining the taxonomic composition of invertebrate and fish assemblages recorded at 327 and 511 sites, respectively, distributed throughout France. Classification 1 and 2 were top-down classifications; The European Water Framework System A (WFDa,) and the French Hydro-ecoregions (HER 2). Four bottom-up classification procedures of increasing complexity were defined based on 11 variables that included watershed characteristics describing climate, topography, and geology, and site characteristics including elevation, bed slope and temperature. Classification 3 was defined using matrix correlation (MC) to select a combination of variable categories that produced the best discrimination of the observed taxonomic composition. Classification 4 and 5 were defined by clustering the sites based on their taxonomic data and then using linear discriminant analysis (LDA) and Random forests (RF) to discriminate the clusters based on the environmental variables. Classification 6 was defined using generalized dissimilarity modelling (GDM). Our hypothesis was that the bottom-up classifications would perform better because they flexibly accommodate complex relationships between compositional and environmental variation. We tested the classifications using the classification strength statistic (CS). The RF-based classification fitted the taxonomic patterns better than GDM or LDA and these latter classifications generally fitted better than the MC, WFDa or HER classifications. Cross validation analysis showed that differences in predictive CS (i.e. the CS statistics produced from sites not used in defining the classifications) were often significant. However, these differences were generally small. Gains in predictive performance of classifications appear to be small relative to the increase in complexity in the manner in which environmental variables are combined to define classes.     

Carbon Stores,Sinks, and Sources in Forests of Northwestern Russia: Can We Reconcile Forest Inventories with Remote Sensing Results?

Forest inventories and remote sensing are the two principal data sources used to estimate carbon (C) stocks and fluxes for large forest regions. National governments have historically relied on forest inventories for assessments but developments in remote sensing technology provide additional opportunities for operational C monitoring. The estimate of total C stock in live forest biomass modeled from Landsat imagery for the St. Petersburg region was consistent with estimates derived from forest inventory data for the early 1990s (272 and 269 TgC, respectively). The estimates of mean C sink in live forest biomass also agreed well (0.36 and 0.34 Mg C ha^–1 yr^–1). Virtually all forest lands were accumulating C in live biomass, however when the net change in total ecosystem C stock was considered, 19% of the forest area were a net source of C. The average net C sink in total ecosystem biomass is quite weak (0.08 MgC ha^–1 yr^–1 and could be reversed by minor increases in harvest rates or a small decline in biomass growth rates.