Optimization of sub-band coding method for seismic data compression

Seismic data volumes, which require huge transmission capacities and massive storage media, continue to increase rapidly due to acquisition of 3D and 4D multiple streamer surveys, multicomponent data sets, reprocessing of prestack seismic data, calculation of post‐stack seismic data attributes, etc. We consider lossy compression as an important tool for efficient handling of large seismic data sets. We present a 2D lossy seismic data compression algorithm, based on sub‐band coding, and we focus on adaptation and optimization of the method for common‐offset gathers. The sub‐band coding algorithm consists of five stages: first, a preprocessing phase using an automatic gain control to decrease the non‐stationary behaviour of seismic data; second, a decorrelation stage using a uniform analysis filter bank to concentrate the energy of seismic data into a minimum number of sub‐bands; third, an iterative classification algorithm, based on an estimation of variances of blocks of sub‐band samples, to classify the sub‐band samples into a fixed number of classes with approximately the same statistics; fourth, a quantization step using a uniform scalar quantizer, which gives an approximation of the sub‐band samples to allow for high compression ratios; and fifth, an entropy coding stage using a fixed number of arithmetic encoders matched to the corresponding statistics of the classified and quantized sub‐band samples to achieve compression. Decompression basically performs the opposite operations in reverse order. We compare the proposed algorithm with three other seismic data compression algorithms. The high performance of our optimized sub‐band coding method is supported by objective and subjective results.     

Particulate carbon content in rain at various temperate and tropical locations

Particulate organic and black carbon concentrations in rain were determined in various source or remote regions, in order to gain information on the incorporation of atmospheric carbonaceous particles in hydrometeors. The analyses of rainwaters indicate that all the samples contained particles derived from combustion. Data obtained on a sample basis, show an important areal and temporal variability of the composition of rain carbonaceous particles, a variability which is reported to that of the black carbon to total carbon ratio, Cb/Ct, ranging from 10 to 72%. In addition to the fluctuations of the aerosol atmospheric burden, these variations may be related to alterations of the organic fraction of the particles or their involvement in in-cloud nucleation processes during atmospheric transport. Also, a comparison of the mean relative abundance of black carbon in aerosols and in rainwaters, gives evidence of a partial disappearance of the organic particles, a phenomenon which could be due to their dissolution when incorporated in the hydrometeors. Precipitation scavenging ratio values of black carbon particles, which range from 100 to 370, are similar to those found for sulphate anthropogenic aerosols. Due to their hygroscopic properties and mean size, black carbon aerosols could possibly trace the physico-chemical processes involved in the incorporation of fine combustion particles into hydrometeors. It is also suggested that smoke particles may act as cloud condensation nuclei (CCN). Consequently, emissions of particulates derived from combustion in some tropical or industrial regions could result locally in alteration of cloud albedo and precipitation regimes.     

Pitch-angle distributions in and near the loss cone of (100–350) keV protons

The pitch-angle distributions in and near the loss cone, of ～ (100–200) and ～ (200–350) keV protons observed by the ESRO IB satellite during the period 7–15 October 1969 are presented. The data include periods of relative quiet as well as more disturbed geomagnetic conditions. Spatial characteristics and dynamics of the protons, both on the night-and dayside of the Earth are described. The actual pitch-angle distribution is interpreted as produced by wave-particle interactions, and the diffusion coefficient and lifetime against pitch angle scattering have been estimated from existing theories. During slightly disturbed conditions, the observations suggest an average random walk in pitch angle made by a particle during a crossing of the diffusion region of about one half of the loss cone half angle for 4 ? L ? 6. The lifetime against pitch angle scattering into the loss cone is found to be somewhat less than the charge exchange lifetime for these (100–350) keV protons. The spectral density of interacting waves is tentatively estimated to about 0·1 $\text{γ}{}^2\text{Hz}$, and compares with estimates arrived at from completely different approaches.     

Stochastic inversion of pressure and saturation changes from time-lapse multi component data

Knowledge about saturation and pressure distributions in a reservoir can help in determining an optimal drainage pattern, and in deciding on optimal well designs to reduce risks of blow‐outs and damage to production equipment. By analyzing time‐lapse PP AVO or time‐lapse multicomponent seismic data, it is possible to separate the effects of production related saturation and pressure changes on seismic data. To be able to utilize information about saturation and pressure distributions in reservoir model building and simulation, information about uncertainty in the estimates is useful. In this paper we present a method to estimate changes in saturation and pressure from time‐lapse multicomponent seismic data using a Bayesian estimation technique. Results of the estimations will be probability density functions (pdfs), giving immediate information about both parameter values and uncertainties. Linearized rock physical models are linked to the changes in saturation and pressure in the prior probability distribution. The relationship between the elastic parameters and the measured seismic data is described in the likelihood model. By assuming Gaussian distributed prior uncertainties the posterior distribution of the saturation and pressure changes can be calculated analytically. Results from tests on synthetic seismic data show that this method produces more precise estimates of changes in effective pressure than a similar methodology based on only PP AVO time‐lapse seismic data. This indicates that additional information about S‐waves obtained from converted‐wave seismic data is useful for obtaining reliable information about the pressure change distribution.     

Seasonal to decadal predictions of regional Arctic sea ice by assimilating sea surface temperature in the Norwegian Climate Prediction Model

Climate Dynamics - The version of the Norwegian Climate Prediction Model (NorCPM) that only assimilates sea surface temperature (SST) with the Ensemble Kalman Filter has been used to investigate...