Structure-oriented edge-preserving smoothing based on accurate estimation of orientation and edges

In this paper, we present a new method for reducing seismic noise while preserving structural and stratigraphic discontinuities. Structure-oriented edge-preserving smoothing requires information such as the local orientation and edge of the reflections. The information is usually estimated from seismic data with full frequency bandwidth. When the data has a very low signal to noise ratio （SNR）, the noise usually reduces the estimation accuracy. For seismic data with extremely low SNR, the dominant frequency has higher SNR than other frequencies, so it can provide orientation and edge information more reliably than other frequencies. Orientation and edge are usually described in terms of apparent reflection dips and coherence differences, respectively. When frequency changes, both dip and coherence difference change more slowly than the seismogram itself. For this reason, dip and coherence estimated from dominant frequency data can approximately represent those of other frequency data. Ricker wavelet are widely used in seismic modeling. The Marr wavelet has the same shape as Ricker wavelets in both time and frequency domains, so the Marr wavelet transform is selected to divide seismic data into several frequency bands. Reflection apparent dip as well as the edge information can be obtained by scanning the dominant frequency data. This information can be used to selectively smooth the frequency bands （dominant, low, and high frequencies） separately by structure-oriented edge-preserving smoothing technology. The ultimate noise-suppressed seismic data is the combination of the smoothed frequency band data. Application to synthetic and real data shows the method can effectively reduce noise, preserve edges, improve trackable reflection continuity, and maintain useful information in seismic data.

Calculation method of the signal-to-noise ratio attribute of seismic data based on structural orientation

At present,most signal-to-noise ratio(SNR)estimation methods can only calculate the global and not the local SNR of seismic data.This paper proposes a calculation method of a structure-oriented-based seismic SNR attribute.The purpose is to characterize the temporal and spatial variation of the seismic data SNR.First,the local slope parameters of the seismic events are calculated using a plane wave decomposition filter.Then,the singular value decomposition method is used to calculate the local seismic data SNR,thereby obtaining it in time and space.The proposed method overcomes the insufficiency of a conventional global SNR to characterize any local seismic data features and uses the SNR as an attribute of seismic data to more accurately describe the signal-noise energy distribution characteristics of seismic data in time and space.The results of a theoretical model test and real data processing show that the SNR attribute can be used not only for seismic data quality evaluation but also for analysis and evaluation of denoising methods.

Bimetal-organic framework-derived carbon nanocubes with 3D hierarchical pores as highly efficient oxygen reduction reaction electrocatalysts for microbial fuel cells

Noble metal-free and highly efficient electrocatalytic materials with hierarchically porous structures continue to be studied for the oxygen reduction reaction(ORR) in microbial fuel cells(MFCs). We report bimetal-organic framework(bi-MOF)-derived nanocubic Swiss cheese-like carbons with a novel three-dimensional hierarchically porous structure(3D Co-N-C) prepared by utilizing cetyltrimethylammonium bromide(CTAB) as a structure-directing agent to control the formation of a nanocubic skeleton, and silica spheres as a template to form a mesoporous structure. The elemental composition and chemical morphology of this material can be tuned through the Zn/Co ratio to optimize its ORR catalytic activity. The optimized 3D Co-N-C displays excellent ORR catalytic performance(half-wave potential as high as 0.754 V vs. reversible hydrogen electrode and diffusion-limiting current density of 5.576 mA cm^(-2)) in 0.01 mol L^(-1) phosphate-buffered saline(PBS electrolyte),showing it can compete with the commercial 20 wt% Pt/C catalysts. The catalytic capability and long-term durability of 3D Co-N-C as an air-filled cathode electrocatalyst in an MFC device are tested, showing that the 3D CoNC-MFC can reach a high power density of 1257 mW m^(-2) and provide a competitive voltage during a periodic feeding operation for 192 h;these values are much higher than those of the Pt/C-MFC.