Time‐lapse pre‐stack seismic data registration and inversion for CO2 sequestration study at Cranfield

Pre‐stack seismic data are indicative of subsurface elastic properties within the amplitude versus offset characteristic and can be used to detect elastic rock property changes caused by injection. We perform time‐lapse pre‐stack 3‐D seismic data analysis for monitoring sequestration at Cranfield. The time‐lapse amplitude differences of Cranfield datasets are found entangled with time‐shifts. To disentangle these two characters, we apply a local‐correlation‐based warping method to register the time‐lapse pre‐stack datasets, which can effectively separate the time‐shift from the time‐lapse seismic amplitude difference without changing the original amplitudes. We demonstrate the effectiveness of our registration method by evaluating the inverted elastic properties. These inverted time‐lapse elastic properties can be reliably used for monitoring plumes.     

Lagrangian study of temporal changes of a surface flow through the Kamchatka Strait

Using Lagrangian methods, we analyze a 20-year-long estimate of water flux through the Kamchatka Strait in the northern North Pacific based on AVISO velocity field. It sheds new light on the flux pattern and its variability on annual and monthly time scales. Strong seasonality in surface outflow through the strait could be explained by temporal changes in the wind stress over the northern and western Bering Sea slopes. Interannual changes in a surface outflow through the Kamchatka Strait correlate significantly with the Near Strait inflow and Bering Strait outflow. Enhanced westward surface flow of the Alaskan Stream across the 174°E section in the northern North Pacific is accompanied by an increased inflow into the Bering Sea through the Near Strait. In summer, the surface flow pattern in the Kamchatka Strait is determined by the passage of anticyclonic and cyclonic mesoscale eddies. The wind stress over the Bering basin in winter–spring is responsible for eddy generation in the region.     

Open and coastal seas interactions south of Japan represented by an ensemble Kalman filter

We investigated the feasibility of the ensemble Kalman filter (EnKF) to reproduce oceanic conditions south of Japan. We have adopted the local ensemble transformation Kalman filter algorithm based on 20 members’ ensemble simulations of the parallelized Princeton Ocean Model (the Stony Brook Parallel Ocean Model) with horizontal resolution of 1/36°. By assimilating satellite sea surface height anomaly, satellite sea surface temperature, and in situ temperature and salinity profiles, we reproduced the Kuroshio variation south of Japan for the period from 8 to 28 February 2010. EnKF successfully reproduced the Kuroshio path positions and the water mass property of the Kuroshio waters as observed. It also detected the variation of the steep thermohaline front in the Kii Channel due to the intrusion of the Kuroshio water based on the observation, suggesting efficiency of EnKF for detection of open and coastal seas interactions with highly complicated spatiotemporal variability.     

Estimation of methane fluxes from bottom sediments of Lake Baikal

Methane bubble fluxes in gas flares from bottom sediments in Lake Baikal were estimated for the first time using hydroacoustic methods. Earlier work has demonstrated the occurrence of gas seeps both inside and outside of areas where bottom simulating reflectors were identified in seismic profiles. Fluxes ranged from 14 to 216 tons per year, with the flux for the entire area of the central and southern basins ranging from 1,400 to 2,800 tons per year. Comparison with other water bodies showed that fluxes from the most intensive Baikal flares were similar to those in the Norwegian and Okhotsk seas. Gas hydrates decompose at the lower boundary of the gas hydrate stability zone due to sedimentation. Calculation of the amount of methane produced due to sedimentation gave a total of between 2,600 and 14,000 tons per year for the central and southern basins of the lake. Based on rough estimation, the total flux from shallow- and deep-water gas seeps is similar to the amount of methane produced due to sedimentation. This suggests that gas hydrates possibly occupy much more than 10?% of the pore volume near the base of the gas hydrate stability zone, or that there are other reasons for gas hydrate dissociation and bubble flux from these bottom sediments.     

Batisite,Na2BaTi2(Si4O12)O2, from Inagli massif,Aldan, Russia: crystal-structure refinement and high-temperature X-ray diffraction study

Mineralogy and Petrology - The crystal structure of batisite, Na2BaTi2 (Si4O12)O2, from the Inagli massif (Aldan, Yakutia, Russia) was refined to R 1 = 0.032 for 1449 unique...     

Geomorphologic map of the 1<Superscript>st</Superscript> Mutnaya River,Southeastern Kamchatka,Russia

The Kamchatka Peninsula–situated in the Pacific “Ring of Fire”–has 29 active and over 400 extinct volcanoes. Since it is situated in the northeastern extremity of Russia, in subarctic climate, the volcanic landforms are overprinted by the 446 glaciers. This research focuses on the 1^stMutnaya catchment which drains the southern slopes of two active volcanoes: Avachinsky and Koryaksky. Those volcanoes are a permanent threat for the cities of Petropavlovsk and Elizovo, which are the 2 of 3 cities of the peninsula. Hence, most of the studies carried out in the area dealt with the natural hazards and only few focus on landscape evolution. Thus, the purpose of this study was to elaborate a cartographic approach which integrates classic geomorphology with state of the art GIS and remote sensing techniques. As result, different landforms and related processes have been analysed and included in the first general geomorphologic map of the 1^stMutnaya catchment.     

Genotoxic potential of copper oxide nanoparticles in the bivalve mollusk <Emphasis Type="Italic">Mytilus trossulus</Emphasis>

Copper oxide nanoparticles (CuO-NPs) are among the most widely used metal oxide nanoparticles, which increases the chance of their being released into the marine environment. As the applications of these particles have increased in recent years, their potential impact on the health of marine biota has also increased. However, the toxicological effects of these NPs in the marine environment are poorly known. In the present study, the DNA damaging potential of CuO-NPs in the marine eastern mussel Mytilus trossulus was evaluated and compared to that of dissolved copper exposures. Genotoxicity was assessed by the single cell gel electrophoresis (comet) assay in mussel gill and digestive gland cells. The results showed that copper in both forms (CuO-NPs and dissolved copper) was accumulated to different extents in mussel tissues. The mussel exposed to the dissolved copper attained higher concentrations of copper in the gills than in the digestive gland. In contrast to these results, it was found that CuO-NPs could induce much higher copper accumulation in the digestive gland than in the gills. A clear and statistically significant increase in DNA damage was found in both tissues of the Cu-exposed group compared to the control mussels. Our results indicated that the CuO-NP exposure produced remarkable effects and increased DNA damage significantly in mussel gill cells only. It should be noted that the digestive gland cells were prone to accumulation following CuO-NPs when compared to the gill cells, while the gill cells were more sensitive to the genotoxic effects of CuO-NPs. These results also suggested the need for a complete risk assessment of engineered particles before its arrival in the consumer market.     

Nonlinear structure‐enhancing filtering using plane‐wave prediction*

Attenuation of random noise and enhancement of structural continuity can significantly improve the quality of seismic interpretation. We present a new technique, which aims at reducing random noise while protecting structural information. The technique is based on combining structure prediction with either similarity‐mean filtering or lower‐upper‐middle filtering. We use structure prediction to form a structural prediction of seismic traces from neighbouring traces. We apply a non‐linear similarity‐mean filter or an lower‐upper‐middle filter to select best samples from different predictions. In comparison with other common filters, such as mean or median, the additional parameters of the non‐linear filters allow us to better control the balance between eliminating random noise and protecting structural information. Numerical tests using synthetic and field data show the effectiveness of the proposed structure‐enhancing filters.