Simulation–Regression Approximations for Value of Information Analysis of Geophysical Data

Value of information analysis is useful for helping a decision maker evaluate the benefits of acquiring or processing additional data. Such analysis is particularly beneficial in the petroleum industry, where information gathering is costly and time-consuming. Furthermore, there are often abundant opportunities for discovering creative information gathering schemes, involving the type and location of geophysical measurements. A consistent evaluation of such data requires spatial modeling that realistically captures the various aspects of the decision situation: the uncertain reservoir variables, the alternatives and the geophysical data under consideration. The computational tasks of value of information analysis can be daunting in such spatial decision situations; in this paper, a regression-based approximation approach is presented. The approach involves Monte Carlo simulation of data followed by linear regression to fit the conditional expectation expression that is needed for value of information analysis. Efficient approximations allow practical value of information analysis for the spatial decision situations that are typically encountered in petroleum reservoir evaluation. Applications are presented for seismic amplitude data and electromagnetic resistivity data, where one example includes multi-phase fluid flow simulations.     

Ongoing research on seismic safety assessment

Research on seismic safety assessment has been the centre of great interest among the scientific community in recent years. Although the devastating impact of earthquakes on current society should be incentive enough to increase research, the development of more realistic mechanical behaviour models and the continuous enhancement of computation capabilities are paramount factors contributing a great deal to the increase of such interest. In this context, three research areas can be identified as currently leading to important developments: code related research, especially in Europe where new design codes are in the implementation process; risk analysis, namely concerning the definition of methodologies for safety assessment that involve the evaluation of the failure probability and could be included in future generations of codes; and experimental characterization of constitutive laws which provides support for the development and calibration of accurate and realistic numerical models for seismic analysis and for the adequate characterization of limit state capacities. The paper will present some of the current scientific research trends on these three seismic safety assessment related topics. Studies addressing the seismic safety assessment of structures, either probabilistically or based on code provisions, and that consider realistic nonlinear mechanical behaviour models will be focussed. Reference will also be made to experimental research on the seismic behaviour of structural elements, emphasizing its crucial role to support the development of numerical models simulating the effects of different seismic strengthening techniques. Finally, given the development of studies leading to new trends and perspectives for performance based earthquake engineering, a possible scenario for seismic design in the future is presented, emphasizing the key issues for its implementation.     

Production of oxalates In Vitro by Microbes Isolated from Rock Surfaces with prehistoric paints in the Lower Pecos Region,Texas

Calcium oxalate‐rich rock coatings are ubiquitous on limestone inside dry rock shelters and under bluff overhangs along canyon walls in southwestern Texas. Prehistoric pictographs occur in more than 250 such sites, and the ancient paints are encapsulated within the natural rock coating. Previous studies suggest lichens were the source of the oxalate; however, we report here that microbes cultured and isolated from samples of the coating produce oxalate in vitro. Twenty different bacteria species have been identified in samples from eight different sites, with Bacillus the most common genus, represented by five species. HPLC analyses of inoculated R2B medium after eight months of bacterial growth revealed the presence of oxalate ions in the solid phase of the growth medium. © 2008 Wiley Periodicals, Inc.     

Evaluating disturbance on mediterranean karst areas: the example of Sardinia (Italy)

Evaluating the human disturbance on karst areas is a difficult task because of the complexity of these peculiar and unique environments. The human impact on karstic geo-ecosystems is increasingly important and there is an increasing need for multidisciplinary tools to assess the environmental changes in karst areas. Many disciplines, such as biology, geomorphology, hydrology and social-economical sciences are to be considered to sufficiently evaluate the impact on these intrinsically vulnerable areas. This article gives an overview of the evolution of environmental impact on karst areas of the island Sardinia (Italy). For this particular case, the most important impacts in the past 50 years are derived from the following activities, in decreasing importance: (1) mining and quarrying; (2) deforestation, agriculture and grazing; (3) building (widespread urbanisation, isolated homes, etc.) and related infrastructures (roads, sewer systems, aqueducts, waste dumps, etc.); (4) tourism; (5) military activities. To evaluate the present environmental state of these areas the Disturbance Index for Karst environments [Van Beynen and Townsend (Environ Manage 36:101–116)] is applied in a slightly modified version. Instead of considering the indicators of environmental disturbances used in the original method, this slightly modified index evaluates the disturbances causing the deterioration of the environmental attributes. In the Sardinian case study, 27 disturbances have been evaluated, giving rise to the definition of a Disturbance Index ranging between 0 (Pristine) and 1 (highly disturbed). This Disturbance Index simplifies the original KDI method, appears to adequately measure disturbance on Mediterranean karst areas and could be applied with success to other similar regions.     

Gravity data as a tool for landfill study

This paper shows the potential of gravity data to map a buried landfill bottom topography. To this end, a gravity inversion method is presented for estimating the landfill’s bottom depths at discrete points assuming a decrease of the density contrast with depth according to a hyperbolic law. The method’s efficiency was tested using synthetic data from simulated waste landfills, producing estimated bottom topographies very close to the true ones. The method’s potentiality has been further evaluated in applying it to the gravity data from the abandoned Thomas Farm Landfill site, Indiana, USA, whose bottom topography is known. The estimated topography showed close agreement with the known Thomas Farm Landfill’s bottom topography.     

Concluding remarks and perspectives on the evolution and seismic tools activity (ESTA) of the CoRoT community

A first part gives a summary of the main conclusions stemmed from the different comparisons reported in this book. One main conclusion is: with some care in the computations, one is able to obtain frequency differences between different computations which are smaller than required by Corot challenges. This is true for high frequency modes. Small frequency differences are much less easily obtained for low frequencies around the fundamental radial mode frequency. Care here means: having the same physics, same constants of physics, same input stellar parameters, computing models and oscillations with enough self numerical consistent accuracy. The ESTA group has built reference grids of models and associated oscillation frequencies and made them available to the community. In a second part of the present paper, a study case is considered in order to show the need and the use of such reference grids. Finally some perspectives concerning the remaining tasks are suggested.     

Spectral filtering as a method of visualising and removing striped artefacts in digital elevation data

Spectral filtering was compared with traditional mean spatial filters to assess their ability to identify and remove striped artefacts in digital elevation data. The techniques were applied to two datasets: a 100 m contour derived digital elevation model (DEM) of southern Norway and a 2 m LiDAR DSM of the Lake District, UK. Both datasets contained diagonal data artefacts that were found to propagate into subsequent terrain analysis. Spectral filtering used fast Fourier transformation (FFT) frequency data to identify these data artefacts in both datasets. These were removed from the data by applying a cut filter, prior to the inverse transform. Spectral filtering showed considerable advantages over mean spatial filters, when both the absolute and spatial distribution of elevation changes made were examined. Elevation changes from the spectral filtering were restricted to frequencies removed by the cut filter, were small in magnitude and consequently avoided any global smoothing. Spectral filtering was found to avoid the smoothing of kernel based data editing, and provided a more informative measure of data artefacts present in the FFT frequency domain. Artefacts were found to be heterogeneous through the surfaces, a result of their strong correlations with spatially autocorrelated variables: landcover and landsurface geometry. Spectral filtering performed better on the 100 m DEM, where signal and artefact were clearly distinguishable in the frequency data. Spectrally filtered digital elevation datasets were found to provide a superior and more precise representation of the landsurface and be a more appropriate dataset for any subsequent geomorphological applications. Copyright © 2007 John Wiley & Sons, Ltd.     

Comparison of pelagic and nepheloid layer marine snow: implications for carbon cycling

Marine snow from upper and mid-water (i.e., pelagic) depths on the California margin is texturally and compositionally different from that traveling in the nepheloid layer. Transmission electron microscopy shows that pelagic marine snow consists primarily of bioclasts (e.g., diatom frustules, foram tests), organic matter, and microbes. These components are entrained as discrete particles or small aggregates μm in diameter) in a loose network of exocellular, muco-polysaccharide material. Clays are infrequent but, when present, are constituents of comparatively compact organic-rich microaggregates. Microbes are abundant and appear to decrease in number with increasing water depth. In contrast, marine snow aggregates collected from just above the sea floor in the nepheloid layer are assemblages of clay particles, clay flocs, and relatively dense clay–organic-rich microaggregates in an exocellular organic matrix. Bioclasts and microorganisms occur only rarely. The prevalence of clay–organic-rich aggregates in the nepheloid layer suggests that, prior to final deposition and burial, marine snow from the pelagic zone is subject to disaggregation and recombination with terrigenous detrital material near or at the sea floor. Results have significant implications for the accumulation and burial rates of organic carbon on continental margins and the aging and bioavailability of sedimentary organic matter. Samples examined were collected offshore of northern and central California.