ALBERT

Description: A correction to this paper has been published: 10.1140/epjc/s10052-021-09344-w

Description: The results of a search for gluino and squark pair production with the pairs decaying via the lightest charginos into a final state consisting of two W bosons, the lightest neutralinos ($$ilde{chi }^0_1$$ χ ~ 1 0 ), and quarks, are presented: the signal is characterised by the presence of a single charged lepton ($$e^{pm }$$ e ± or $$mu ^{pm }$$ μ ± ) from a W boson decay, jets, and missing transverse momentum. The analysis is performed using 139 fb$$^{-1}$$ - 1 of proton–proton collision data taken at a centre-of-mass energy $$sqrt{s}=13$$ s = 13   delivered by the Large Hadron Collider and recorded by the ATLAS experiment. No statistically significant excess of events above the Standard Model expectation is found. Limits are set on the direct production of squarks and gluinos in simplified models. Masses of gluino (squark) up to 2.2  (1.4 ) are excluded at 95% confidence level for a light $$ilde{chi }^0_1$$ χ ~ 1 0 .

Description: Determining thin layer thickness is very important for reservoir characterization and CO2 quantification. Given its high time-frequency resolution and robustness, the complex spectral decomposition method was applied on time-lapse 3D seismic data from the Ketzin pilot site for CO2 storage to evaluate the frequency-dependent characteristics of thin layers at the injection level. Higher temporal resolution and more stratigraphic details are seen in the all-frequency and monochromatic reflectivity amplitude sections obtained by complex spectral decomposition compared to the stacked sections. The mapped geologic discontinuities within the reservoir are consistent with the preferred orientation of CO2 propagation. Tuning frequency mapping shows the thicknesses of the reservoir sandstone and gaseous CO2 is consistent with the measured thickness of the sandstone unit from well logging. An attempt to discriminate between pressure effects and CO2 saturation using the extracted tuning frequency indicates that CO2 saturation is the main contributor to the amplitude anomaly at the Ketzin site. On the basis of determined thickness of gaseous CO2 in the reservoir, quantitative analysis of the amount of CO2 was performed and shows a discrepancy between the injected and calculated CO2 mass. This may be explained by several uncertainties, like structural reservoir heterogeneity, a limited understanding of the complex subsurface conditions, error of determined tuning frequency, the presence of ambient noise and ongoing CO2 dissolution.

Description: Spectral decomposition is a powerful tool that can provide geological details dependent upon discrete frequencies. Complex spectral decomposition using inversion strategies differs from conventional spectral decomposition methods in that it produces not only frequency information but also wavelet phase information. This method was applied to a time-lapse three-dimensional seismic dataset in order to test the feasibility of using wavelet phase changes to detect and map injected carbon dioxide within the reservoir at the Ketzin carbon dioxide storage site, Germany. Simplified zero-offset forward modelling was used to help verify the effectiveness of this technique and to better understand the wavelet phase response from the highly heterogeneous storage reservoir and carbon dioxide plume. Ambient noise and signal-to-noise ratios were calculated from the raw data to determine the extracted wavelet phase. Strong noise caused by rainfall and the assumed spatial distribution of sandstone channels in the reservoir could be correlated with phase anomalies. Qualitative and quantitative results indicate that the wavelet phase extracted by the complex spectral decomposition technique has great potential as a practical and feasible tool for carbon dioxide detection at the Ketzin pilot site. © 2016 European Association of Geoscientists & Engineers.

Description: Full waveform inversion is an effective tool for velocity model building. Recently it has been introduced as a complementary method for interpreting time-lapse seismic data as it can be used to detect velocity changes in reservoirs. There are already some successful applications in the fields of oil/gas production and CO2 injection monitoring. We present a case study of data pre-processing of time-lapse data from the Ketzin CO2 geological storage site. Ketzin is a well-known onshore CO2 geological storage pilot site. Due to the restriction of the acquisi- tion geometry, the time-lapse seismic data sets here have limited maximum offset which makes direct inversion for reservoir velocity difficult. As shown by experiences from other case studies, the double difference full waveform inversion method is the best choice here. The success of double difference time-lapse full waveform inversion is highly dependent upon data pre-processing. This is because it only inverts the difference between the baseline and repeat shot gathers. In order to get the correct velocity change in the reservoir, it is important to apply some pre-processing steps to remove the time-lapse noise above the reservoir. In this study we apply cross equalization and time-lapse difference static corrections to remove the time-lapse noise in the shot gathers. We test our methods by using synthetic data sets. The results show that these methods can effectively remove the time-lapse noise in the shot gathers. We also apply these methods to the real time-lapse shot gathers from the Ketzin site. The time-lapse differences above the reservoir time sections are significantly reduced after pre-processing.

Description: In this study, we explored the capability of coda wave interferometry (CWI) for monitoring CO2 storage by estimating the seismic velocity changes caused by CO2 injection. Given that the CWI method is highly efficient, the primary aim of this study was to provide a quick detection tool for the long-term monitoring of CO2 storage safety. In particular, we looked at monitoring with a cross-well geometry. We also expected that CWI could help to reduce the inversion errors of existing methods. Time-lapse upgoing waves and downgoing waves from two-component datasets were utilized to efficiently monitor the area between the wells and provide a quick indication of possible CO2 leakage. The resulting mean velocity changes versus the depth indicated the depth where velocity changes occurred. Combining the upgoing and downgoing wavefields provided a more specific indication of the depth range for changes. The calculated velocity changes were determined using the time shift between the time-lapse wavefields caused by CO2 injection/leakage. Hence, the resulting velocity changes were closely related to the ratio of propagation path length through the CO2 injection/leakage layer over the length of the entire travel path. The results indicated that the noise level and repeatability of the time-lapse datasets significantly influenced the results generated using CWI. Therefore, denoising and time-lapse processing were very important for improving the detectability of any change. Applying CWI to time-lapse cross-well surveys can be an effective tool for monitoring CO2 in the subsurface at a relatively low computational cost. As a highly efficient monitoring method, it is sensitive to changes in the seismic response caused by velocity changes in the subsurface and provides additional constraints on the inversion results from conventional travel time tomography and full waveform inversion.

Description: The Laiwu Fe deposit is the largest skarn‐type deposit in West Shandong in China, with an estimated reserve of 290 Mt of iron ore. Here, we investigate the occurrence and chemical composition of amphiboles in altered dioritic rocks of this deposit. Three generations of amphibole group minerals were identified in these rocks. The first type (Type 1) is a hornblende with a generally euhedral crystal shape, 150–500 μm in size, and dominantly occurs in the host monzonite. The second type (Type 2) of hornblende occurs as fine grains (〈100 μm) or concentric rims, less than 50 μm in thickness, around the Type 1 hornblende. The third type (Type 3) of amphibole is anhedral actinolite occurring along the boundary or the cracks of the Type 1 or 2 hornblende grains. The Type 1 hornblende has higher FeO (12.5–15.6 wt.%) and lower MgO contents (11.2–14.6 wt.%) than the Type 2 hornblende, which has an FeO content ranging from 8.8 to 10.5 wt.% and MgO content ranging from 14.2 to 17.1 wt.%. The Type 3 actinolite shows the lowest FeO (4.6–6.4 wt.%) and highest MgO (19.8–21.2 wt.%) contents. We infer that the Type 2 hornblende formed from Fe‐rich hydrothermal fluids released during rapid upwelling of the crystallizing magma. The fluids were relatively reduced and enriched in Fe. The Type 3 actinolite formed by coupled dissolution and reprecipitation, and its formation is one of the features denoting Fe‐enrichment events. Our study of these types of amphibole provides insights into the ore formation process.

Description: In the permafrost domain, hydrological processes are expected to be altered by warming-induced permafrost degradation, mainly through changing the connections between surface and subsurface systems. However, due to the lack of groundwater observations in the permafrost domain, key processes that control subsurface dynamics are not well understood. Nevertheless, as a consequence of frozen ground during the cold season, the winter river discharge is only recharged by groundwater and thus can reflect the changes in groundwater dynamics. In this contribution, we investigate the magnitude and timing of the occurrence of miniflow, as well as their relations to the corresponding groundwater dynamics during 1950-2010 in large river catchments (with various permafrost coverages) in southern Siberia. Based on daily discharge records, we found that the lowflow in all the catchments increased during 1950-2010, with the most considerable rise being noticed since 1980. Particularly, in the catchments where discontinuous permafrost prevails, there is a clear shift in the occurrence of miniflow from late winter to early winter. In continuous permafrost catchments, though the miniflow always occurs in late winter, it also exhibits a potential shift of the regime in the miniflow. Given strong correlations between winter flow and climate variables in the warm season, these significant changes in both magnitude and timing of low flow could be triggered by the degrading permafrost and associated alterations in surface water-groundwater interactions. Overall, our results highlight the potential evolutions in the long-timescale groundwater dynamics over varied temporal and spatial distributions of permafrost under a warming climate.

Description: As a fundamental physical property of snowpack, snow density is used to describe many essential features of snowpack behaviour. However, the variability in snow density across the Northern Hemisphere (NH) is largely unknown. Here, we investigate snow density variability in conjunction with snow classes and geographic elements in the NH based on 6,954 snow sites from 1909 to 2019. Precipitation, air temperature, and snowfall based on meteorological sites, as well as the aridity index (AI) and wind speed from reanalysis data, are also applied to describe the effect of climate on snow density. The results present that the long-term mean snow density is 246 ± 70 kg/m3 considering all in-situ measurement sites. Considerable spatial heterogeneity in snow density exists with contrasting snow densities among differing snow classes. The values range from 198 ± 79 kg/m3 for ephemeral snow to 363 ± 63 kg/m3 for maritime snow. For the seasonal evolution of snow density, the different snow classes share a general characteristic with the overall NH, a slight decrease from October to September, followed by a sustained increase. Moreover, the densification rate in the snow stable period varies over a much smaller range than that during the snowmelt period. Furthermore, the longitudinal trends in the variability of snow density are more pronounced compared to altitudinal and latitudinal trends. High snow densities are typically associated with adequate precipitation, warm air temperature, large aridity index, a long snow season, and heavy snowfall for different snow classes. The results will deepen the understanding of the snow density distribution at hemispherical scale, and provide basic data for the remote sensing of snow water equivalent and parameterization of snow models.