Common‐shot Fresnel beam migration based on wave‐field approximation in effective vicinity under complex topographic conditions

Gaussian beam migration is a versatile imaging method for geologically complex land areas, which overcomes the limitation of Kirchhoff migration in imaging multiple arrivals and has no steep‐dip limits of one‐way wave‐equation migration. However, its imaging accuracy depends on the geometry of Gaussian beam that is determined by the initial parameter of dynamic ray tracing. As a result, its applications in exploration areas with strong variations in topography and near‐surface velocity are limited. Combined with the concept of Fresnel zone and the theory of wave‐field approximation in effective vicinity, we present a more robust common‐shot Fresnel beam imaging method for complex topographic land areas in this paper. Compared with the conventional Gaussian beam migration for irregular topography, our method improves the beam geometry by limiting its effective half‐width with Fresnel zone radius. Moreover, through a quadratic travel‐time correction and an amplitude correction that is based on the wave‐field approximation in effective vicinity, it gives an accurate method for plane‐wave decomposition at complex topography, which produces good imaging results in both shallow and deep zones. Trials of two typical models and its application in field data demonstrated the validity and robustness of our method.     

Incorporating velocity shear into the magneto-Boussinesq approximation

Motivated by consideration of the solar tachocline, we derive, via an asymptotic procedure, a new set of equations incorporating velocity shear and magnetic buoyancy into the Boussinesq approximation. We demonstrate, by increasing the magnetic field scale height, how these equations are linked to the magneto-Boussinesq equations of Spiegel and Weiss (Magnetic buoyancy and the Boussinesq approximation. Geophys. Astrophys. Fluid Dyn. 1982, 22, 219–234).     

Seismic inversion with generalized Radon transform based on local second-order approximation of scattered field in acoustic media

Sound velocity inversion problem based on scattering theory is formulated in terms of a nonlinear integral equation associated with scattered field. Because of its nonlinearity, in practice, linearization algorisms (Born/single scattering approximation) are widely used to obtain an approximate inversion solution. However, the linearized strategy is not congruent with seismic wave propagation mechanics in strong perturbation (heterogeneous) medium. In order to partially dispense with the weak perturbation assumption of the Born approximation, we present a new approach from the following two steps: firstly, to handle the forward scattering by taking into account the second-order Born approximation, which is related to generalized Radon transform (GRT) about quadratic scattering potential; then to derive a nonlinear quadratic inversion formula by resorting to inverse GRT. In our formulation, there is a significant quadratic term regarding scattering potential, and it can provide an amplitude correction for inversion results beyond standard linear inversion. The numerical experiments demonstrate that the linear single scattering inversion is only good in amplitude for relative velocity perturbation ( \( \delta_{c}/c_{0} \) ) of background media up to 10 %, and its inversion errors are unacceptable for the perturbation beyond 10 %. In contrast, the quadratic inversion can give more accurate amplitude-preserved recovery for the perturbation up to 40 %. Our inversion scheme is able to manage double scattering effects by estimating a transmission factor from an integral over a small area, and therefore, only a small portion of computational time is added to the original linear migration/inversion process.     

Time-domain identification of dynamic properties of layered soil by using extended Kalman filter and recorded seismic data

A novel time-domain identification technique is developed for the seismic response analysis of soil-structure interaction. A two-degree-of-freedom (2DOF) model with eight lumped parameters is adopted to model the frequency-dependent behavior of soils. For layered soil, the equivalent eight parameters of the 2DOF model arc identified by the extended Kalman filter (EKF) method using recorded seismic data. The polynomial approximations for derivation of state estimators are applied in the EKF procedure. A realistic identification example is given for the layered-soil of a building site in Anchorage, Alaska in the United States. Results of the example demonstrate the feasibility and practicality of the proposed identification technique. The 2DOF soil model and the identification technique can be used for nonlinear response analysis of soil-structure interaction in the time-domain for layered of complex soil conditions. The identified parameters can be stored in a database for use in other similar soil conditions. If a universal database that covers information related to most soil conditions is developed in the future, engineers could conveniently perform time history analyses of soil-structural interaction.     

深部咸水层CO2地质储存工程场地选址技术方法

CO₂地质储存作为环保型工程项目,其合理的工程场址是实现长期、安全封存CO₂的首要前提。我国CO₂地质储存工作刚刚起步,尚未形成成熟的选址技术方法体系。CO₂地质储存工程场地选址应遵循目标储层有效储存量大、安全、经济、符合一般建设项目环境保护选址条件、不受外部不良地质因素影响的原则,选址技术宜采用多尺度目标逼近法,选址程序包括规划选址和工程选址两大阶段。规划选址包括国家级、盆地级和目标区级潜力评价3个阶段;工程选址旨在通过目标靶区确定、综合地质调查、钻探及灌注试验和选定场地多因子排序综合评价,最终选出良好的工程场址。深部咸水层CO₂地质储存工程场地多尺度目标逼近选址技术方法对我国批量开展CO₂地质储存工程场地选址具有一定的指导意义。     

一种基于模糊正域类的模糊属性约简方法

为了实现模糊信息系统属性约简问题,探讨一种基于正域类的模糊属性约简方法。利用模糊二元相似关系建立模糊相似类的方法,进而定义决策属性关于条件属性的模糊正域类,得到正域类属性的重要度。结果表明:一方面,实现模糊信息系统属性约简;另一方面,通过取不同的相似精度,得到不同属性约简集。     

Stationary phase approximation in the ambient noise method revisited

The method of extracting Green's function between stations from cross correlation has proven to be effective theoretically and experimentally.It has been widely applied to surface wave tomography of the crust and upmost mantle.However,there are still controversies about why this method works.Snieder employed stationary phase approximation in evaluating contribution to cross correlation function from scatterers in the whole space,and concluded that it is the constructive interference of waves emitted by the scatterers near the receiver line that leads to the emergence of Green's function.His derivation demonstrates that cross correlation function is just the convolution of noise power spectrum and the Green's function.However,his derivation ignores influence from the two stationary points at infinities,therefore it may fail when attenuation is absent.In order to obtain accurate noise-correlation function due to scatters over the whole space,we compute the total contribution with numerical integration in polar coordinates.Our numerical computation of cross correlation function indicates that the incomplete stationary phase approximation introduces remarkable errors to the cross correlation function,in both amplitude and phase,when the frequency is low with reasonable quality factor Q.Our results argue that the distance between stations has to be beyond several wavelengths in order to reduce the influence of this inaccuracy on the applications of ambient noise method,and only the station pairs whose distances are above several (5) wavelengths can be used.     

Point- and curve-based geometric conflation

Geometric conflation is the process undertaken to modify the coordinates of features in dataset A in order to match corresponding ones in dataset B. The overwhelming majority of the literature considers the use of points as features to define the transformation. In this article we present a procedure to consider one-dimensional curves also, which are commonly available as Global Navigation Satellite System (GNSS) tracks, routes, coastlines, and so on, in order to define the estimate of the displacements to be applied to each object in A. The procedure involves three steps, including the partial matching of corresponding curves, the computation of some analytical expression, and the addition of a correction term in order to satisfy basic cartographic rules. A numerical example is presented.