Quantifying ecospace utilization and ecosystem engineering during the early Phanerozoic-The role of bioturbation and bioerosion.

The Cambrian explosion (CE) and the great Ordovician biodiversification event (GOBE) are the two most important radiations in Paleozoic oceans. We quantify the role of bioturbation and bioerosion in ecospace utilization and ecosystem engineering using information from 1367 stratigraphic units. An increase in all diversity metrics is demonstrated for the Ediacaran-Cambrian transition, followed by a decrease in most values during the middle to late Cambrian, and by a more modest increase during the Ordovician. A marked increase in ichnodiversity and ichnodisparity of bioturbation is shown during the CE and of bioerosion during the GOBE. Innovations took place first in offshore settings and later expanded into marginal-marine, nearshore, deep-water, and carbonate environments. This study highlights the importance of the CE, despite its Ediacaran roots. Differences in infaunalization in offshore and shelf paleoenvironments favor the hypothesis of early Cambrian wedge-shaped oxygen minimum zones instead of a horizontally stratified ocean.

Mapping of compositional properties of coal using isometric log-ratio transformation and sequential Gaussian simulation - A comparative study for spatial ultimate analyses data.

Chemical properties of coal largely determine coal handling, processing, beneficiation methods, and design of coal-fired power plants. Furthermore, these properties impact coal strength, coal blending during mining, as well as coal's gas content, which is important for mining safety. In order for these processes and quantitative predictions to be successful, safer, and economically feasible, it is important to determine and map chemical properties of coals accurately in order to infer these properties prior to mining. Ultimate analysis quantifies principal chemical elements in coal. These elements are C, H, N, S, O, and, depending on the basis, ash, and/or moisture. The basis for the data is determined by the condition of the sample at the time of analysis, with an "as-received" basis being the closest to sampling conditions and thus to the in-situ conditions of the coal. The parts determined or calculated as the result of ultimate analyses are compositions, reported in weight percent, and pose the challenges of statistical analyses of compositional data. The treatment of parts using proper compositional methods may be even more important in mapping them, as most mapping methods carry uncertainty due to partial sampling as well. In this work, we map the ultimate analyses parts of the Springfield coal from an Indiana section of the Illinois basin, USA, using sequential Gaussian simulation of isometric log-ratio transformed compositions. We compare the results with those of direct simulations of compositional parts. We also compare the implications of these approaches in calculating other properties using correlations to identify the differences and consequences. Although the study here is for coal, the methods described in the paper are applicable to any situation involving compositional data and its mapping.

Decoupled evolution of soft and hard substrate communities during the Cambrian Explosion and Great Ordovician Biodiversification Event.

Contrasts between the Cambrian Explosion (CE) and the Great Ordovician Biodiversification Event (GOBE) have long been recognized. Whereas the vast majority of body plans were established as a result of the CE, taxonomic increases during the GOBE were manifested at lower taxonomic levels. Assessing changes of ichnodiversity and ichnodisparity as a result of these two evolutionary events may shed light on the dynamics of both radiations. The early Cambrian (series 1 and 2) displayed a dramatic increase in ichnodiversity and ichnodisparity in softground communities. In contrast to this evolutionary explosion in bioturbation structures, only a few Cambrian bioerosion structures are known. After the middle to late Cambrian diversity plateau, ichnodiversity in softground communities shows a continuous increase during the Ordovician in both shallow- and deep-marine environments. This Ordovician increase in bioturbation diversity was not paralleled by an equally significant increase in ichnodisparity as it was during the CE. However, hard substrate communities were significantly different during the GOBE, with an increase in ichnodiversity and ichnodisparity. Innovations in macrobioerosion clearly lagged behind animal-substrate interactions in unconsolidated sediment. The underlying causes of this evolutionary decoupling are unclear but may have involved three interrelated factors: (i) a Middle to Late Ordovician increase in available hard substrates for bioerosion, (ii) increased predation, and (iii) higher energetic requirements for bioerosion compared with bioturbation.

Stochastic reservoir simulation for the modeling of uncertainty in coal seam degasification.

Coal seam degasification improves coal mine safety by reducing the gas content of coal seams and also by generating added value as an energy source. Coal seam reservoir simulation is one of the most effective ways to help with these two main objectives. As in all modeling and simulation studies, how the reservoir is defined and whether observed productions can be predicted are important considerations. Using geostatistical realizations as spatial maps of different coal reservoir properties is a more realistic approach than assuming uniform properties across the field. In fact, this approach can help with simultaneous history matching of multiple wellbores to enhance the confidence in spatial models of different coal properties that are pertinent to degasification. The problem that still remains is the uncertainty in geostatistical simulations originating from the partial sampling of the seam that does not properly reflect the stochastic nature of coal property realizations. Stochastic simulations and using individual realizations, rather than E-type, make evaluation of uncertainty possible. This work is an advancement over Karacan et al. (2014) in the sense of assessing uncertainty that stems from geostatistical maps. In this work, we batched 100 individual realizations of 10 coal properties that were randomly generated to create 100 bundles and used them in 100 separate coal seam reservoir simulations for simultaneous history matching. We then evaluated the history matching errors for each bundle and defined the single set of realizations that would minimize the error for all wells. We further compared the errors with those of E-type and the average realization of the best matches. Unlike in Karacan et al. (2014), which used E-type maps and average of quantile maps, using these 100 bundles created 100 different history match results from separate simulations, and distributions of results for in-place gas quantity, for example, from which uncertainty in coal property realizations could be evaluated. The study helped to determine the realization bundle that consisted of the spatial maps of coal properties, which resulted in minimum error. In addition, it was shown that both E-type and the average of realizations that gave the best match for invidual approximated the same properties resonably. Moreover, the determined realization bundle showed that the study field initially had 151.5 million m3 (cubic meter) of gas and 1.04 million m3 water in the coal, corresponding to Q90 of the entire range of probability for gas and close to Q75 for water. In 2013, in-place fluid amounts decreased to 138.9 million m3 and 0.997 million m3 for gas and water, respectively.

Sequential Gaussian co-simulation of rate decline parameters of longwall gob gas ventholes.

Gob gas ventholes (GGVs) are used to control methane inflows into a longwall mining operation by capturing the gas within the overlying fractured strata before it enters the work environment. Using geostatistical co-simulation techniques, this paper maps the parameters of their rate decline behaviors across the study area, a longwall mine in the Northern Appalachian basin. Geostatistical gas-in-place (GIP) simulations were performed, using data from 64 exploration boreholes, and GIP data were mapped within the fractured zone of the study area. In addition, methane flowrates monitored from 10 GGVs were analyzed using decline curve analyses (DCA) techniques to determine parameters of decline rates. Surface elevation showed the most influence on methane production from GGVs and thus was used to investigate its relation with DCA parameters using correlation techniques on normal-scored data. Geostatistical analysis was pursued using sequential Gaussian co-simulation with surface elevation as the secondary variable and with DCA parameters as the primary variables. The primary DCA variables were effective percentage decline rate, rate at production start, rate at the beginning of forecast period, and production end duration. Co-simulation results were presented to visualize decline parameters at an area-wide scale. Wells located at lower elevations, i.e., at the bottom of valleys, tend to perform better in terms of their rate declines compared to those at higher elevations. These results were used to calculate drainage radii of GGVs using GIP realizations. The calculated drainage radii are close to ones predicted by pressure transient tests.

Time-Lapse Analysis of Methane Quantity in the Mary Lee Group of Coal Seams Using Filter-Based Multiple-Point Geostatistical Simulation.

Coal seam degasification and its success are important for controlling methane, and thus for the health and safety of coal miners. During the course of degasification, properties of coal seams change. Thus, the changes in coal reservoir conditions and in-place gas content as well as methane emission potential into mines should be evaluated by examining time-dependent changes and the presence of major heterogeneities and geological discontinuities in the field. In this work, time-lapsed reservoir and fluid storage properties of the New Castle coal seam, Mary Lee/Blue Creek seam, and Jagger seam of Black Warrior Basin, Alabama, were determined from gas and water production history matching and production forecasting of vertical degasification wellbores. These properties were combined with isotherm and other important data to compute gas-in-place (GIP) and its change with time at borehole locations. Time-lapsed training images (TIs) of GIP and GIP difference corresponding to each coal and date were generated by using these point-wise data and Voronoi decomposition on the TI grid, which included faults as discontinuities for expansion of Voronoi regions. Filter-based multiple-point geostatistical simulations, which were preferred in this study due to anisotropies and discontinuities in the area, were used to predict time-lapsed GIP distributions within the study area. Performed simulations were used for mapping spatial time-lapsed methane quantities as well as their uncertainties within the study area. The systematic approach presented in this paper is the first time in literature that history matching, TIs of GIPs and filter simulations are used for degasification performance evaluation and for assessing GIP for mining safety. Results from this study showed that using production history matching of coalbed methane wells to determine time-lapsed reservoir data could be used to compute spatial GIP and representative GIP TIs generated through Voronoi decomposition. Furthermore, performing filter simulations using point-wise data and TIs could be used to predict methane quantity in coal seams subjected to degasification. During the course of the study, it was shown that the material balance of gas produced by wellbores and the GIP reductions in coal seams predicted using filter simulations compared very well, showing the success of filter simulations for continuous variables in this case study. Quantitative results from filter simulations of GIP within the studied area briefly showed that GIP was reduced from an initial ~73 Bcf (median) to ~46 Bcf (2011), representing a 37 % decrease and varying spatially through degasification. It is forecasted that there will be an additional ~2 Bcf reduction in methane quantity between 2011 and 2015. This study and presented results showed that the applied methodology and utilized techniques can be used to map GIP and its change within coal seams after degasification, which can further be used for ventilation design for methane control in coal mines.

Gas emissions, minerals, and tars associated with three coal fires, Powder River Basin, USA.

Ground-based surveys of three coal fires and airborne surveys of two of the fires were conducted near Sheridan, Wyoming. The fires occur in natural outcrops and in abandoned mines, all containing Paleocene-age subbituminous coals. Diffuse (carbon dioxide (CO(2)) only) and vent (CO(2), carbon monoxide (CO), methane, hydrogen sulfide (H(2)S), and elemental mercury) emission estimates were made for each of the fires. Additionally, gas samples were collected for volatile organic compound (VOC) analysis and showed a large range in variation between vents. The fires produce locally dangerous levels of CO, CO(2), H(2)S, and benzene, among other gases. At one fire in an abandoned coal mine, trends in gas and tar composition followed a change in topography. Total CO(2) fluxes for the fires from airborne, ground-based, and rate of fire advancement estimates ranged from 0.9 to 780mg/s/m(2) and are comparable to other coal fires worldwide. Samples of tar and coal-fire minerals collected from the mouth of vents provided insight into the behavior and formation of the coal fires.

Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation.

Determination of the size of the gas emission zone, the locations of gas sources within, and especially the amount of gas retained in those zones is one of the most important steps for designing a successful methane control strategy and an efficient ventilation system in longwall coal mining. The formation of the gas emission zone and the potential amount of gas-in-place (GIP) that might be available for migration into a mine are factors of local geology and rock properties that usually show spatial variability in continuity and may also show geometric anisotropy. Geostatistical methods are used here for modeling and prediction of gas amounts and for assessing their associated uncertainty in gas emission zones of longwall mines for methane control. This study used core data obtained from 276 vertical exploration boreholes drilled from the surface to the bottom of the Pittsburgh coal seam in a mining district in the Northern Appalachian basin. After identifying important coal and non-coal layers for the gas emission zone, univariate statistical and semivariogram analyses were conducted for data from different formations to define the distribution and continuity of various attributes. Sequential simulations performed stochastic assessment of these attributes, such as gas content, strata thickness, and strata displacement. These analyses were followed by calculations of gas-in-place and their uncertainties in the Pittsburgh seam caved zone and fractured zone of longwall mines in this mining district. Grid blanking was used to isolate the volume over the actual panels from the entire modeled district and to calculate gas amounts that were directly related to the emissions in longwall mines. Results indicated that gas-in-place in the Pittsburgh seam, in the caved zone and in the fractured zone, as well as displacements in major rock units, showed spatial correlations that could be modeled and estimated using geostatistical methods. This study showed that GIP volumes may change up to 3 MMscf per acre and, in a multi-panel district, may total 9 Bcf of methane within the gas emission zone. Therefore, ventilation and gas capture systems should be designed accordingly. In addition, rock displacements within the gas emission zone are spatially distributed. From an engineering and practical point of view, spatial distributions of GIP and distributions of rock displacements should be correlated with in-mine emissions and gob gas venthole productions.

Navajo coal combustion and respiratory health near Shiprock, New Mexico.

Indoor air pollution has been identified as a major risk factor for acute and chronic respiratory diseases throughout the world. In the sovereign Navajo Nation, an American Indian reservation located in the Four Corners area of the USA, people burn coal in their homes for heat. To explore whether/how indoor coal combustion might contribute to poor respiratory health of residents, this study examined respiratory health data, identified household risk factors such as fuel and stove type and use, analyzed samples of locally used coal, and measured and characterized fine particulate airborne matter inside selected homes. In twenty-five percent of homes surveyed coal was burned in stoves not designed for that fuel, and indoor air quality was frequently found to be of a level to raise concerns. The average winter 24-hour PM2.5 concentration in 20 homes was 36.0 µg/m³. This is the first time that PM2.5 has been quantified and characterized inside Navajo reservation residents' homes.

Duration of urban mortality for the 14th-century Black Death epidemic.

The Black Death epidemic of 1347-1351 was one of the most serious catastrophes in human history, yet it continues to be imperfectly described because of the small and often uncertain amount of information recorded and preserved. Analysis of data from 53 cities, with 200 to 120,000 residents, shows a relationship between urban population at the beginning of the epidemic and duration of the epidemic, thus throwing some light on the characteristics of the pestilence. A further relevance of the finding is its utility for estimating and resolving contradictory information. On a first application, we show that the population and fatalities of London in all likelihood were higher than the most widely accepted estimates and that those of Florence and Paris must have been smaller.