带粒子滤波约束的PP-PS联合反演的稀疏解算法

随着地震勘探目标从构造型油气藏向岩性油气藏的转变,地震勘探难度日益增大,这就要求从地震数据中获得更多可靠且具有明确地质含义的属性信息,并充分利用这些属性信息来对储层的岩性、岩相进行分析.AVO三参数反演能够从振幅随炮检距的变化信息中直接提取纵波速度、横波速度以及密度来估计岩石和流体的性质,进而对储层进行预测.然而,AVO反演本身是一个不适定的问题,加上地震纵波反射系数对横波速度和密度的不敏感,会造成单纯利用纵波地震数据进行反演的结果误差大.随着地震接收和数据处理技术的发展,越来越多的学者对PP-PS联合反演方法进行了研究并在实际资料中得以运用.融合转换横波地震数据的联合反演在一定程度上提高了反演的精度,降低了解的不稳定性.但是在信噪比较低的情况下,联合反演的效果受到了限制.本文从优化理论出发,提出了基于粒子滤波提供先验知识的l₁范数约束极小化问题的稀疏解算法.并将上述方法运用到了不同的模型中,通过比较分析,证实了该方法在不同信噪比资料中的有效性和在信噪比较低情况下的优势.     

Optimization of laboratory illumination in optical dating

As part of the development of new laboratory lighting, we present a methodological approach applicable to the characterization of any light source intended for illumination in optical dating laboratories. We derive optical absorption cross-sections for quartz and feldspar from published data and compare these with the human eye response. The optimum peak wavelength giving the best clarity for non-dark adapted vision for the least trapped charge loss lies within the wavelength range 590–630 nm; we argue that it is unnecessary to consider dark-adapted vision. The predicted relative decay rates of quartz optically stimulated luminescence (OSL) and feldspar infrared stimulated luminescence (IRSL) signals by an incandescent light bulb and a compact fluorescent lamp (CFL) through an ILFORD 902 filter are first derived. These predicted decay rates are then compared with those of three relevant light-emitting diodes (LEDs); this comparison demonstrates the significant advantage of the LED sources over the filtered light sources, because essentially all of the reduction of both OSL and IRSL signals by the LEDs occurs at wavelengths to which the human eye is most sensitive. We conclude that exposure of quartz and feldspar extracts from various samples to the light from an LED with emission peak at 594 nm results in a ≤1% OSL or IRSL signal loss for a 48-h exposure at a power density of ∼0.2 μW.cm⁻².     

Generalized algorithms for particle motion and collision with streambeds

Recent theoretical and numerical models for the motion of saltating particles close to stream beds are constituted of three sub-models: a) a set of equations describing the particle “free flight”, b) a sub-model to calculate the post-collision particle velocity, and c) a mathematical representation of the bed roughness. In this paper, a comprehensive three-dimensional (3-D), theoretical/numerical model for bedload motion at large Reynolds numbers is presented. By using geometric considerations and stochastic parameters to characterize collisions with the wall, five new sub-models for representation of bed roughness are, for the first time to the best of our knowledge, proposed and implemented. The emphasis of this paper is on the particle model, for which Basset, Magnus, drag, submerged weight, virtual mass, and lift forces are included. For the range of particle sizes (sands) analyzed herein, it is found that the stream-wise contribution of the Basset force, compared to other forces, may be as large as 60%. Whereas in the wall-normal direction, the Basset force is equally important as the drag force, and it is exceeded only by the submerged weight. It is also found that the best agreement between numerical and experimental results in terms of jump length, jump height, and stream-wise particle velocity is achieved for restitution and friction coefficients of 0.65 and 0.1, respectively. Important conclusions are obtained regarding the lack of realistic prediction with available “roughness” models with small ranges of angles.     

Determination of the particle load based on detailed suspended sediment measurements at a hydropower plant

Suspended sediment particles contained in inflows of water systems of hydropower plants (HPPs) cause hydro-abrasive erosion of the hydraulic turbines and structures leading to significant maintenance costs, efficiency reductions, and downtime. Relevant parameters such as suspended sediment concentration (SSC), particle size distribution (PSD), shape, and mineralogical composition were measured with an online multi-frequency acoustic instrument and based on manually taken samples from the end of the sand trap of the Toss HPP in the Himalayan region, India. In the laboratory, the samples were analyzed using the gravimetric method, laser diffraction, turbidity, dynamic digital image processing, scanning electron microscope, petrography analysis, energy-dispersive X-ray spectroscopy, and X-ray diffraction. The online instrument and the samples provided measurement results at a single point. To investigate vertical gradients in concentration and particle sizes, additional samples were collected 9 times at 7 relative water depths. The SSC, most particle sizes, and particle shape were found to be evenly distributed over depth except d90, i.e. the diameter which is not exceeded by 90% of the particle mass. d90 measured at 76% of the water depth was in the range of fine sand and was multiplied by 1.05 to obtain an average value representative for the entire depth. Improved methodologies to quantify both particle shape and size in an analytical model for hydro-abrasive erosion are proposed. Also, the PSD measuring performance of laser diffraction and dynamic imaging was studied and similar values of the median particle sizes were obtained from both instruments. Further, multi-frequency acoustic, turbidity and laser diffraction techniques were found suitable for SSC measurement at the test case HPP.     

Estimating instantaneous concentration of suspended sediment using acoustic backscatter from an ADV

The measurement of instantaneous sediment concentration remains a challenging task. In this study, a three-step procedure is proposed to estimate instantaneous sediment concentration using acoustic backscatter from Acoustic Doppler Velocimeter (ADV). The influences of acoustic noise and particle diameter on an ADV's performance was first tested in the laboratory, then the three-step procedure was verified based on field measurements in the Zhongxian and Fengjie reaches in the Three Gorges Reservoir. The first step involves reconstructing the backscatter signal time series. Due to contamination from both the noise floor and spurious spikes, the denoising-despiking method was applied instead of the traditional velocity-despiking methods, and this approach performed well based on spectrum ana-lysis. The second step involves calibrating the sediment concentration against the backscatter signal. A linear relation, whose slope and intercept were calibrated to be dependent on particle diameter, is proposed in double logarithmic coordinates. The third step involves calculating the instantaneous sediment concentration using reconstructed instantaneous backscatter based on the proposed relation. The accuracy of the proposed method was evaluated through consideration of the concentration spec-trum and sediment flux, indicating that the proposed three-step procedure is effective for the mea-surement of instantaneous sediment concentration.     

Reflection-constrained 2D and 3D non-hyperbolic moveout analysis using particle swarm optimization

The objective of moveout parameter inversion is to derive sets of parameter models that can be used for moveout correction and stacking at each common midpoint location to increase the signal-to-noise ratio of the data and to provide insights into the kinematic characteristics of the data amongst other things. In this paper, we introduce a data-driven user-constrained optimization scheme that utilizes manual picks at a point on each reflector within a common midpoint gather to constrain the search space in which an optimization procedure can search for the optimal parameter sets at each reflection. The picks are used to create boundary curves which can be derived approximately via an optimization technique or analytically via the derivation of an analytical bounds function. In this paper, we derive analytical forms of bounds functions for four different moveout cases. These are normal moveout, non-hyperbolic moveout, azimuthally dependent normal moveout and azimuthally dependent non-hyperbolic moveout. The optimization procedure utilized here to search for the optimal moveout parameters is the particle swarm optimization technique. However, any metaheuristic optimization procedure could be modified to account for the constraints introduced in this paper. The technique is tested on two-layer synthetic models based on three of the four moveout cases discussed in this paper. It is also applied to an elastic forward modelled synthetic model called the HESS model, and finally to real 2D land data from Alaska. The resultant stacks show a marked improvement in the signal-to-noise ratio compared to the raw stacks. The results for the normal moveout, non-hyperbolic moveout and azimuthally dependent normal moveout tests suggest that the method is viable for said models. Results demonstrate that our method offers potential as an alternative to conventional parameter picking and inversion schemes, particularly for some cases where the number of parameters in the moveout approximation is 2 or greater.     

Artificial contradiction between cosmology and particle physics: the Λ problem

It is shown that the usual choice of units obtained by taking G=c=ℏ=1, giving the Planck’s units of mass, length and time, introduces an artificial contradiction between cosmology and particle physics: the lambda problem that we associate with ℏ. We note that the choice of ℏ=1 does not correspond to the scale of quantum physics. For this scale we prove that the correct value is ℏ≈1/10¹²², while the choice of ℏ=1 corresponds to the cosmological scale. This is due to the scale factor of 10⁶¹ that converts the Planck scale to the cosmological scale. By choosing the ratio G/c ³=constant=1, which includes the choice G=c=1, and the momentum conservation mc=constant, we preserve the derivation of the Einstein field equations from the action principle. Then the product Gm/c ²=r _g , the gravitational radius of m, is constant. For a quantum black hole we prove that ℏ≈r _g ²≈(mc)². We also prove that the product Λℏ is a general constant of order one, for any scale. The cosmological scale implies Λ≈ℏ≈1, while the Planck scale gives Λ≈1/ℏ≈10¹²². This explains the Λ problem. We get two scales: the cosmological quantum black hole (QBH), size ∼10²⁸ cm, and the quantum black hole (qbh) that includes the fundamental particles scale, size ∼10⁻¹³ cm, as well as the Planck’ scale, size ∼10⁻³³ cm.      

Optimization of nutrient component for diesel oil degradation by Rhodococcus erythropolis

A novel bacterium T7-2 was isolated from the oil-polluted sea-bed mud of Bohai Sea, northern China, which can degrade diesel oil at 15 °C. This bacterium was identified as a strain of Rhodococcus erythropolis according to its 16S rDNA gene. In order to enhance degradation efficiency, a five-level, three-factor central composite design was employed to optimize the nutrition supplied to artificial seawater. The results indicate that a supplement of 2.53 g (NH₄)₂SO₄ L⁻¹, 2.75 g Na₂HPO₄ L⁻¹ and 0.01 g yeast extract L⁻¹ to artificial seawater increases the degradation rate from 12.61% to 75% within 7 d.