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.     

Optimizing fixed observational assets in a coastal observatory

Proliferation of coastal observatories necessitates an objective approach to managing of observational assets. In this article, we used our experience in the coastal observatory for the Columbia River estuary and plume to identify and address common problems in managing of fixed observational assets, such as salinity, temperature, and water level sensors attached to pilings and moorings. Specifically, we addressed the following problems: assessing the quality of an existing array, adding stations to an existing array, removing stations from an existing array, validating an array design, and targeting of an array toward data assimilation or monitoring.     

Weathering: Toward a Fractal Quantifying

Weathering occurs over a wide range of scales. To link features through these scales is a major challenge for interdisciplinary weathering studies. Fractal approach seems to be specially useful for this purpose. We introduce a multistep fractal weathering assessment scheme devoted to extract fractal weathering classifiers from texture analysis of the mineral's image. Our scheme enables to quantitatively estimate the global and local information about the geometry of the weathering pattern. This information is basic to develop geometrical indices of weathering, which can significantly enrich the common qualitative and semiquantitative weathering assessment schemes. To justify the fractal approach, a strong statistical self-similarity has been documented for both the weathering and fresh features of two common silica minerals: quartz and biogenic A-opal (phytolith) over four orders of length scales. The procedure is fast, drastically reduces thresholding bias, promises to be universal, it is valid for genetically different minerals and rock types, scale independent, and specially useful for monitoring the changes in the mineral's roughness during the alteration. Two of the proposed classifiers seem to be potentially useful for direct application in the field and be used by nonspecialist.     

Eddy formation in the bays of Kamchatka and fluxes to the open ocean

Ocean Dynamics - The Eastern Kamchatka Current (EKC) is the western boundary current of the North Pacific subpolar gyre. Southeast of the Kamchatka Peninsula lies a large anticyclonic eddy, the...     

High-order kernels for Riemannian wavefield extrapolation

Riemannian wavefield extrapolation is a technique for one‐way extrapolation of acoustic waves. Riemannian wavefield extrapolation generalizes wavefield extrapolation by downward continuation by considering coordinate systems different from conventional Cartesian ones. Coordinate systems can conform with the extrapolated wavefield, with the velocity model or with the acquisition geometry. When coordinate systems conform with the propagated wavefield, extrapolation can be done accurately using low‐order kernels. However, in complex media or in cases where the coordinate systems do not conform with the propagating wavefields, low order kernels are not accurate enough and need to be replaced by more accurate, higher‐order kernels. Since Riemannian wavefield extrapolation is based on factorization of an acoustic wave‐equation, higher‐order kernels can be constructed using methods analogous to the one employed for factorization of the acoustic wave‐equation in Cartesian coordinates. Thus, we can construct space‐domain finite‐differences as well as mixed‐domain techniques for extrapolation. High‐order Riemannian wavefield extrapolation kernels improve the accuracy of extrapolation, particularly when the Riemannian coordinate systems does not closely match the general direction of wave propagation.     

Iterative resolution estimation in least‐squares Kirchhoff migration

We apply iterative resolution estimation to least‐squares Kirchhoff migration. Reviewing the theory of iterative optimization uncovers the common origin of different optimization methods. This allows us to reformulate the pseudo‐inverse, model resolution and data resolution operators in terms of effective iterative estimates. When applied to Kirchhoff migration, plots of the diagonal of the model resolution matrix reveal low illumination areas on seismic images and provide information about image uncertainties. Synthetic and real data examples illustrate the proposed technique and confirm the theoretical expectations.     

Structure and tectonic evolution of the Southern Eurasia Basin, Arctic Ocean

Multichannel seismic reflection data acquired by Marine Arctic Geological Expedition (MAGE) of Murmansk, Russia in 1990 provide the first view of the geological structure of the Arctic region between 77–80°N and 115–133°E, where the Eurasia Basin of the Arctic Ocean adjoins the passive-transform continental margin of the Laptev Sea. South of 80°N, the oceanic basement of the Eurasia Basin and continental basement of the Laptev Sea outer margin are covered by 1.5 to 8 km of sediments. Two structural sequences are distinguished in the sedimentary cover within the Laptev Sea outer margin and at the continent/ocean crust transition: the lower rift sequence, including mostly Upper Cretaceous to Lower Paleocene deposits, and the upper post-rift sequence, consisting of Cenozoic sediments. In the adjoining Eurasia Basin of the Arctic Ocean, the Cenozoic post-rift sequence consists of a few sedimentary successions deposited by several submarine fans. Based on the multichannel seismic reflection data, the structural pattern was determined and an isopach map of the sedimentary cover and tectonic zoning map were constructed. A location of the continent/ocean crust transition is tentatively defined. A buried continuation of the mid-ocean Gakkel Ridge is also detected. This study suggests that south of 78.5°N there was the cessation in the tectonic activity of the Gakkel Ridge Rift from 33–30 until 3–1 Ma and there was no sea-floor spreading in the southernmost part of the Eurasia Basin during the last 30–33 m.y. South of 78.5°N all oceanic crust of the Eurasia Basin near the continental margin of the Laptev Sea was formed from 56 to 33–30 Ma.     

The international conference “Vortices and coherent structures: from ocean to microfluids”, Vladivostok,Russia, 28–31 August 2017

The international conference “Vortices and coherent structures: from ocean to microfluids” was held at the Pacific Oceanological Institute of the Russian Academy of Sciences in Vladivostok (Russia) from August 28 to August 31, 2017. The event gathered experimentalists and theoreticians, oceanographers and physicists, with a common interest in observing and modelling fluid flows in different media, from the ocean to laboratory flows. It was a fruitful idea to bring together researchers from a variety of backgrounds to benefit from a vigorous discussion of concepts across different disciplines in oceanography and hydrodynamics.

     

Atlas of Japan (East) Sea hydrographic properties in summer, 1999

Hydrographic properties from CTD and discrete bottle sample profiles covering the Japan (East) Sea in summer, 1999, are presented in vertical sections, maps at standard depths, maps on isopycnal surfaces, and as property–property distributions. This data set covers most of the Sea with the exception of the western boundary region and northern Tatar Strait, and includes nutrients, pH, alkalinity, and chlorofluorocarbons, as well as the usual temperature, salinity, and oxygen observations.