Advanced seismic characterization of a geothermal carbonate reservoir – insight into the structure and diagenesis of a reservoir in the German Molasse Basin

The quality of geothermal carbonate reservoirs is controlled by, for instance, depositional environment, lithology, diagenesis, karstification, fracture networks, and tectonic deformation. Carbonatic rock formations are thus often extremely heterogeneous, and reservoir parameters and their spatial distribution difficult to predict. Using a 3D seismic dataset combined with well data from Munich, Germany, we demonstrate how a comprehensive seismic attribute analysis can significantly improve the understanding of a complex carbonate reservoir. We deliver an improved reservoir model concept and identify possible exploitation targets within the Upper Jurassic carbonates. We use seismic attributes and different carbonate lithologies from well logs to identify parameter correlations. From this, we obtain a supervised neural-network-based 3D lithology model of the geothermal reservoir. Furthermore, we compare fracture orientations measured in seismic (ant-tracking analysis) and well scale (image log analysis) to address scalability. Our results show that, for example, acoustic impedance is suitable to identify reefs and karst-related dolines, and sweetness proves useful to analyse the internal reef architecture, whereas frequency- and phase-related attributes allow the detection of karst. In addition, reef edges, dolines, and fractures, associated with high permeabilities, are characterized by strong phase changes. Fractures are also identified using variance and ant tracking. Morphological characteristics, like dolines, are captured using the shape index. Regarding the diagenetic evolution of the reservoir and the corresponding lithology distribution, we show that the Upper Jurassic carbonate reservoir experienced a complex evolution, consisting of at least three dolomitization phases, two karstification phases, and a phase of tectonic deformation. We observe spatial trends in the degree of dolomitization and show that it is mainly facies-controlled and that karstification is facies- and fault-controlled. Karstification improves porosity and permeability, whereas dolomitization can either increase or decrease porosity. Therefore, reservoir zones should be exploited that experienced only weak diagenetic alteration, i.e. the dolomitic limestone in the upper part of the Upper Jurassic carbonates. Regarding the fracture scalability across seismic and well scales, we note that a general scalability is, due to a combination of methodological limitations and geological reasons, not possible. Nevertheless, both methods provide an improved understanding of the fracture system and possible fluid pathways. By integrating all the results, we are able to improve and adapt recent reservoir concepts, to outline the different phases of the reservoir's structural and diagenetic evolution, and to identify high-quality reservoir zones in the Munich area. These are located southeast at the Ottobrunn Fault and north of the Munich Fault close to the Nymphenburg Fault.</p

Biotic and abiotic controls on carbon storage in aggregates in calcareous alpine and prealpine grassland soils

Alpine and prealpine grasslands provide various ecosystem services and are hotspots for the storage of soil organic C (SOC) in Central Europe. Yet, information about aggregate-related SOC storage and its controlling factors in alpine and prealpine grassland soils is limited. In this study, the SOC distribution according to the aggregate size classes large macroaggregates (> 2000 μm), small macroaggregates (250–2000 μm), microaggregates (63–250 μm), and silt-/clay-sized particles (< 63 μm) was studied in grassland soils along an elevation gradient in the Northern Limestone Alps of Germany. This was accompanied by an analysis of earthworm abundance and biomass according to different ecological niches. The SOC and N stocks increased with elevation and were associated with relatively high proportions of water-stable macroaggregates due to high contents of exchangeable Ca$^{2+}$ and Mg$^{2+}$. At lower elevations, earthworms appeared to act as catalyzers for a higher microaggregate formation. Thus, SOC stabilization by aggregate formation in the studied soils is a result of a joined interaction of organic matter and Ca$^{2+}$ as binding agents for soil aggregates (higher elevations), and the earthworms that act as promoters of aggregate formation through the secretion of biogenic carbonates (low elevation). Our study highlights the importance of aggregate-related factors as potential indices to evaluate the SOC storage potential in other mountainous grassland soils

Classification across gene expression microarray studies

<p>Abstract</p> <p>Background</p> <p>The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive) and histological grade (low/high) of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM), predictive analysis of microarrays (PAM), random forest (RF) and k-top scoring pairs (kTSP). Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV) aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing.</p> <p>Results</p> <p>For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In particular, the better predictive results of DV in across platform classification indicate higher robustness of the classifier when trained on single channel data and applied to gene expression ratios.</p> <p>Conclusions</p> <p>We present a systematic evaluation of strategies for the integration of independent microarray studies in a classification task. Our findings in across studies classification may guide further research aiming on the construction of more robust and reliable methods for stratification and diagnosis in clinical practice.</p

Endogenous mouse Dicer is an exclusively cytoplasmic protein

Dicer is a large multi-domain protein responsible for the ultimate step of microRNA and short-interfering RNA biogenesis. In human and mouse cell lines, Dicer has been shown to be important in the nuclear clearance of dsRNA as well as the establishment of chromatin modifications. Here we set out to unambiguously define the cellular localization of Dicer in mice to understand if this is a conserved feature of mammalian Dicer in vivo. To this end, we utilized an endogenously epitope tagged Dicer knock-in mouse allele. From primary mouse cell lines and adult tissues, we determined with certainty by biochemical fractionation and confocal immunofluorescence microscopy that endogenous Dicer is exclusively cytoplasmic. We ruled out the possibility that a fraction of Dicer shuttles to and from the nucleus as well as that FGF or DNA damage signaling induce Dicer nuclear translocation. We also explored Dicer localization during the dynamic and developmental context of embryogenesis, where Dicer is ubiquitously expressed and strictly cytoplasmic in all three germ layers as well as extraembryonic tissues. Our data exclude a direct role for Dicer in the nuclear RNA processing in the mouse