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Magnitude estimation for microseismicity induced during the KTB 2004/2005 injection experiment
(2011)
We determined the magnitudes of 2540 microseismic events measured at one single 3C borehole geophone at the German Deep Drilling Site (known by the German acronym, KTB) during the injection phase 2004/2005. For this task we developed a three-step approach. First, we estimated local magnitudes of 104 larger events with a standard method based on amplitude measurements at near-surface stations. Second, we investigated a series of parameters to characterize the size of these events using the seismograms of the borehole sensor, and we compared them statistically with the local magnitudes. Third, we extrapolated the regression curve to obtain the magnitudes of 2436 events that were only measured at the borehole geophone. This method improved the magnitude of completeness for the KTB data set by more than one order down to M = -2.75. The resulting b-value for all events was 0.78, which is similar to the b-value obtained from taking only the greater events with standard local magnitude estimation from near-surface stations, b = 0.86. The more complete magnitude catalog was required to study the magnitude distribution with time and to characterize the seismotectonic state of the KTB injection site. The event distribution with time was consistent with prediction from theory assuming pore pressure diffusion as the underlying mechanism to trigger the events. The value we obtained for the seismogenic index of -4 suggested that the seismic hazard potential at the KTB site is comparatively low.
Most 2.5D controlled-source electromagnetic (CSEM) modeling algorithms presented to date explicitly consider only sources that are point dipoles oriented parallel or perpendicular to the direction of constant conductivity. This makes simulations of complex source geometries expensive, requiring separate evaluations of many point dipole fields, and thus limits the practical applicability of such schemes for simulating and interpreting field data. We present a novel 2.5D CSEM modeling scheme that overcomes this limitation and permits efficient simulations of sources with general shape and orientation by evaluating fields for the entire source at once. We accommodate general sources by using a secondary field approach, in which primary fields are computed for the general source and a 1D background conductivity model. To carry out the required Fourier transforms between space and wavenumber domain using the same fast cosine and sine transform filters as in conventional algorithms, we split the primary and secondary fields into their symmetric and antisymmetric parts. For complex 3D source geometries, this approach is significantly more efficient than previous 2.5D algorithms. Our finite-difference algorithm also includes novel approaches for divergence correction at low frequencies and EM field interpolation across conductivity discontinuities. We describe the modeling scheme and demonstrate its accuracy and efficiency by comparisons of 2.5D-simulated data with 1D and 3D results.
This study investigates spatial patterns and temporal dynamics of aquifer-river exchange flow at a reach of the River Leith, UK. Observations of sub-channel vertical hydraulic gradients at the field site indicate the dominance of groundwater up-welling into the river and the absence of groundwater recharge from surface water. However, observed hydraulic heads do not provide information on potential surface water infiltration into the top 0-15 cm of the streambed as these depths are not covered by the existing experimental infrastructure. In order to evaluate whether surface water infiltration is likely to occur outside the 'window of detection', i.e. the shallow streambed, a numerical groundwater model is used to simulate hydrological exchanges between the aquifer and the river. Transient simulations of the successfully validated model (Nash and Sutcliff efficiency of 0.91) suggest that surface water infiltration is marginal and that the possibility of significant volumes of surface water infiltrating into non-monitored shallow streambed sediments can be excluded for the simulation period. Furthermore, the simulation results show that with increasing head differences between river and aquifer towards the end of the simulation period, the impact of streambed topography and hydraulic conductivity on spatial patterns of exchange flow rates decreases. A set of peak flow scenarios with altered groundwater-surface water head gradients is simulated in order to quantify the potential for surface water infiltration during characteristic winter flow conditions following the observation period. The results indicate that, particularly at the beginning of peak flow conditions, head gradients are likely to cause substantial increase in surface water infiltration into the streambed. The study highlights the potential for the improvement of process understanding of hyporheic exchange flow patterns at the stream reach scale by simulating aquifer-river exchange fluxes with a standard numerical groundwater model and a simple but robust model structure and parameterization. Copyright
The amount and composition of subduction zone fluids and the effect of fluid-rock interaction at a slab-mantle interface have been constrained by thermodynamic and trace element modelling of partially overprinted blueschist-facies rocks from the Sesia Zone (Western Alps). Deformation-induced differences in fluid flux led to a partial preservation of pristine mineral cores in weakly deformed samples that were used to quantify Li, B, Stand Pb distribution during mineral growth, -breakdown and modification induced by fluid-rock interaction. Our results show that Li and 13 budgets are fluid-controlled, thus acting as tracers for fluid-rock interaction processes, whereas Stand Pb budgets are mainly controlled by the fluid-induced formation of epidote. Our calculations show that fluid-rock interaction caused significant Li and B depletion in the affected rocks due to leaching effects, which in turn can lead to a drastic enrichment of these elements in the percolating fluid. Depending on available fluid-mineral trace element distribution coefficients modelled fluid rock ratios were up to 0.06 in weakly deformed samples and at least 0.5 to 4 in shear zone mylonites. These amounts lead to time integrated fluid fluxes of up to 1.4-10(2) m(3) m(-2) in the weakly deformed rocks and 1-8-10(3) m(3) m(-2) in the mylonites. Combined thermodynamic and trace element models can be used to quantify metamorphic fluid fluxes and the associated element transfer in complex, reacting rock systems and help to better understand commonly observed fluid-induced trace element trends in rocks and minerals from different geodynamic environments.
The Upper Cretaceous La Cova limestones (southern Pyrenees, Spain) host a rich and diverse larger foraminiferal fauna, which represents the first diversification of K-strategists after the mass extinction at the Cenomanian-Turonian boundary.
The stratigraphic distribution of the main taxa of larger foraminifera defines two assemblages. The first assemblage is characterised by the first appearance of lacazinids (Pseudolacazina loeblichi) and mean-dropsinids (Eofallotia simplex), by the large agglutinated Montsechiana montsechiensis, and by several species of complex rotalids (Rotorbinella campaniola, Iberorotalia reicheli, Orbitokhatina wondersmitti and Calcarinella schaubi). The second assemblage is defined by the appearance of Lacazina pyrenaica, Palandrosina taxyae and Martiguesia cyclamminiformis.
A late Coniacian-early Santonian age was so far accepted for the La Cova limestones, based on indirect correlation with deep-water fades bearing planktic foraminifers of the Dicarinella concavata zone. Strontium isotope stratigraphy, based on many samples of pristine biotic calcite of rudists and ostreids, indicates that the La Cova limestones span from the early Coniacian to the early-middle Santonian boundary. The first assemblage of larger foraminifera appears very close to the early-middle Coniacian boundary and reaches its full diversity by the middle Coniacian. The originations defining the second assemblage are dated as earliest Santonian: they represent important bioevents to define the Coniacian-Santonian boundary in the shallow-water facies of the South Pyrenean province.
By means of the calibration of strontium isotope stratigraphy to the Geological Time Scale, the larger foraminiferal assemblages of the La Cova limestones can be correlated to the standard biozonal scheme of ammonites, planktonic foraminifers and calcareous nannoplankton. This correlation is a first step toward a larger foraminifera standard biozonation for Upper Cretaceous carbonate platform facies.
The public promotion of renewable energies is expected to increase the number of biogas plants and stimulate energy crops cultivation (e. g. maize) in Germany. In order to assess the indirect effects of the resulting land-use changes on biodiversity, we developed six land-use scenarios and simulated the responses of six farmland wildlife species with the spatially explicit agent-based model system ALMaSS. The scenarios differed in composition and spatial configuration of arable crops. We implemented scenarios where maize for energy production replaced 15% and 30% of the area covered by other cash crops. Biogas maize farms were either randomly distributed or located within small or large aggregation clusters. The animal species investigated were skylark (Alauda arvensis), grey partridge (Perdix perdix), European brown hare (Lepus europaeus), field vole (Microtus agrestis), a linyphiid spider (Erigone atra) and a carabid beetle (Bembidion lampros). The changes in crop composition had a negative effect on the population sizes of skylark, partridge and hare and a positive effect on the population sizes of spider and beetle and no effect on the population size of vole. An aggregated cultivation of maize amplified these effects for skylark. Species responses to changes in the crop composition were consistent across three differently structured landscapes. Our work suggests that with the compliance to some recommendations, negative effects of biogas-related land-use change on the populations of the six representative farmland species can largely be avoided.
In this study, Nuclear Magnetic Resonance (NMR), a non-destructive measurement technique, has been applied for investigation of iron turn-over processes. In non-invasive laboratory experiments, iron dissolution and precipitation reactions in saturated natural sands were observed spatially and temporally. These processes play an important role in groundwater with varying redox and pH conditions. Redox reactions turning Fe2+ into Fe3+ and Fe3+ into Fe2+ were detected in aqueous solution by the difference in magnetic relaxation times. Furthermore, the spatial distribution of the iron reduction reaction, the consumption and diffusive transfer to and from the reaction sites, was observed in a 1D set-up with natural sands. The achieved spatial resolution was less than one millimetre while repeating measurements every half an hour. It showed the system changing from diffusion-limited to reaction-limited.
The seismicity pattern along the San Andreas fault near Parkfield and Cholame, California, varies distinctly over a length of only fifty kilometres. Within the brittle crust, the presence of frictionally weak minerals, fault-weakening high fluid pressures and chemical weakening are considered possible causes of an anomalously weak fault northwest of Parkfield(1-4). Non-volcanic tremor from lower-crustal and upper-mantle depths(5-7) is most pronounced about thirty kilometres southeast of Parkfield and is thought to be associated with high pore-fluid pressures at depth(8). Here we present geophysical evidence of fluids migrating into the creeping section of the San Andreas fault that seem to originate in the region of the uppermost mantle that also stimulates tremor, and evidence that along-strike variations in tremor activity and amplitude are related to strength variations in the lower crust and upper mantle. Interconnected fluids can explain a deep zone of anomalously low electrical resistivity that has been imaged by magnetotelluric data southwest of the Parkfield-Cholame segment. Near Cholame, where fluids seem to be trapped below a high-resistivity cap, tremor concentrates adjacent to the inferred fluids within a mechanically strong zone of high resistivity. By contrast, sub-vertical zones of low resistivity breach the entire crust near the drill hole of the San Andreas Fault Observatory at Depth, northwest of Parkfield, and imply pathways for deep fluids into the eastern fault block, coincident with a mechanically weak crust and the lower tremor amplitudes in the lower crust. Fluid influx to the fault system is consistent with hypotheses of fault-weakening high fluid pressures in the brittle crust.
Enhancing the resolution and accuracy of surface ground-penetrating radar (GPR) reflection data by inverse filtering to recover a zero-phased band-limited reflectivity image requires a deconvolution technique that takes the mixed-phase character of the embedded wavelet into account. In contrast, standard stochastic deconvolution techniques assume that the wavelet is minimum phase and, hence, often meet with limited success when applied to GPR data. We present a new general-purpose blind deconvolution algorithm for mixed-phase wavelet estimation and deconvolution that (1) uses the parametrization of a mixed-phase wavelet as the convolution of the wavelet's minimum-phase equivalent with a dispersive all-pass filter, (2) includes prior information about the wavelet to be estimated in a Bayesian framework, and (3) relies on the assumption of a sparse reflectivity. Solving the normal equations using the data autocorrelation function provides an inverse filter that optimally removes the minimum-phase equivalent of the wavelet from the data, which leaves traces with a balanced amplitude spectrum but distorted phase. To compensate for the remaining phase errors, we invert in the frequency domain for an all-pass filter thereby taking advantage of the fact that the action of the all-pass filter is exclusively contained in its phase spectrum. A key element of our algorithm and a novelty in blind deconvolution is the inclusion of prior information that allows resolving ambiguities in polarity and timing that cannot be resolved using the sparseness measure alone. We employ a global inversion approach for non-linear optimization to find the all-pass filter phase values for each signal frequency. We tested the robustness and reliability of our algorithm on synthetic data with different wavelets, 1-D reflectivity models of different complexity, varying levels of added noise, and different types of prior information. When applied to realistic synthetic 2-D data and 2-D field data, we obtain images with increased temporal resolution compared to the results of standard processing.
While several empirical and theoretical studies have clearly shown the negative effects of climate or landscape changes on population and species survival only few of them addressed combined and correlated consequences of these key environmental drivers. This also includes positive landscape changes such as active habitat management and restoration to buffer the negative effects of deteriorating climatic conditions. In this study, we apply a conceptual spatial modelling approach based on functional types to explore the effects of both positive and negative correlations between changes in habitat and climate conditions on the survival of spatially structured populations. We test the effect of different climate and landscape change scenarios on four different functional types that represent a broad spectrum of species characterised by their landscape level carrying capacity, the local population turnover rates at the patch level (K-strategies vs. r-strategies) and dispersal characterstics. As expected, simulation results show that correlated landscape and climatic changes can accelerate (in case of habitat loss or degradation) or slow down (in case of habitat gain or improvement) regional species extinction. However, the strength of the combined changes depends on local turnover at the patch level, the overall landscape capacity of the species, and its specific dispersal characteristics. Under all scenarios of correlated changes in habitat and climate conditions we found the highest sensitivity for functional types representing species with a low landscape capacity but a high population growth rate and a strong density regulation causing a high turnover at the local patch level.
The relative importance of habitat loss or habitat degradation, in combination with climate deterioration, differed among the functional types. However, an increase in regional capacity revealed a similar response pattern: For all types, habitat improvement led to higher survival times than habitat gain, i.e. the establishment of new habitat patches. This suggests that improving local habitat quality at a regional scale is a more promising conservation strategy under climate change than implementing new habitat patches. This conceptual modelling study provides a general framework to better understand and support the management of populations prone to complex environmental changes.
In the Aconcagua basin the modernization and intensification of land use have resulted both in an agricultural conversion, and the increase in area cultivated. This process has been very intense as far that have entered new areas beyond the limits of the valley and towards sloping ground. This signals changes in land use over the vegetation coverage models. The analysis of the geomorphology of the coastline in detail, accounts for the occurrence of transformations on the beach and dunes that are spatially less significant, but evolutionarily important, since they show a sediment feeding, which could be correlated with changes in vegetation cover in the basin