三角网格剖分下速度与反射界面的同时反演

为了解决复杂速度模型中的走时正、反演问题,例如:含不规则起伏地表、不规则地下波阻抗界面、以及不规则速度异常体的复杂地学模型,本文采用三角网格单元模型参数化下的分区多步改进型最短路径算法,实现了多震相地震射线的追踪计算,结合共轭梯度法求解带约束的阻尼最小二乘反演问题,实现了多震相走时联合同时反演成像的方法技术.当界面起伏较大时出现散射,从而造成散射点所在区域射线密度过密,导致该区域内速度和界面的过度更新.为了克服上述问题,我们在同时反演中引入了射线密度的概念,从而有效地解决了上述过度更新问题.数值模拟实验表明:采用三角网格单元进行模型参数化,可保证在复杂模型中的正演计算具有较高的计算精度;同时反演中可以准确地刻画不规则异常体和不规则反射界面.因此,本文提出的走时成像方法技术具有较广的实用价值.     

基于碳酸盐岩孔隙结构预测孔隙度方法研究

许多研究都已经证实在碳酸盐岩储层中孔隙结构对声波速度影响很大,因此在孔隙度反演时必须考虑孔隙结构的影响.本文通过对Gassmann方程的合理简化并引入Eshelby-Walsh干燥岩石椭球包体近似公式,推导出包含岩石孔隙结构参数、饱和岩石压缩系数与岩石基质压缩系数三个参数的计算孔隙度的新公式,该式岩石基质压缩系数是通过Russell流体因子和Gassmann-Boit-Geer tsma方程计算式建立目标函数反演获得的,然后通过测井交汇图技术把岩石孔隙结构参数与岩石基质压缩系数优选转换成纵横波速度与密度关系式,进而导出具体地区考虑碳酸盐岩孔隙结构孔隙度具体计算公式,测井与地震资料应用表明,基于碳酸盐岩孔隙结构的孔隙度预测方法的精度高于常规方法.     

变密度声波方程多参数全波形反演策略

多参数全波形反演中各参数之间的相互耦合增加了反演的非线性程度.通过分析各参数之间的相互影响,提出合理的多参数反演策略是解决该问题的有效途径.本文从变密度声波方程出发,首先研究了密度在速度反演中的重要作用,然后分析了速度对密度反演的影响程度,进而提出了一种有利于速度、密度分步联合反演的策略.第一步,利用给定的初始模型对速度、密度进行同时反演,得到比较可靠的速度反演结果;第二步,利用第一步反演得到的速度和给定的初始密度作为初始模型,继续进行双参数同时反演,这样可以同时得到比较可靠的速度、密度反演结果.为了进一步提高反演精度,将第二步反演得到的速度、密度作为初始模型,再进行下一轮双参数联合反演.二维理论模型实验结果充分说明了本文提出的这种反演策略的有效性.     

叠前多级优化联合偏移速度建模

推导了基于角度域共成像点道集的叠前深度层析速度建模公式,提出了一种叠前多级优化联合偏移速度建模方法.通过基于共散射点(CSP)道集的叠前时间偏移速度分析获取初始速度,利用基于角度域共成像点道集(ADCIGs)的叠前深度层析速度反演进行速度更新建模.实现步骤可以概括为:首先,将叠前地震数据映射为CSP道集,利用CSP道集的叠加速度谱进行速度分析得到均方根速度场;其次,通过Dix公式将均方根速度场转换为层速度场,以此进行层析初始速度建模,基于ADCIGs实现叠前深度层析速度反演,最终得到高精度的叠前偏移速度场.断层模型和实际资料试算结果验证了该方法的正确性和有效性.     

一种重力异常概率成像的扩展计算

根据重力数据反演结果的数据类型不同,可将重力反演概括为两类:一类是应用线性或者非线性算法,直接计算成像空间的密度分布;第二类是计算得到一种所谓等效密度,用以勾画重力异常场源分布,称为概率成像方法.相对于第一类方法,第二种方法计算更为简单,反演过程也更为稳定.但在一些应用中,需要获取地下介质的实际密度值,进而通过岩性层析等来确定岩性分布,此时,等效密度反演方法表现出了其局限性.本文从概率密度方法出发,应用一种迭代计算,可完成将概率密度值到实际密度值的转化,同时,增加了反演结果的分辨率.本文应用两个理论模型证明了该方法的有效性.     

基于卷积神经网络的地震偏移剖面中散射体的定位和成像

本文提出了一种基于深度学习卷积神经网络(CNN)的全波形反演方法,可对地震散射波场中的散射体进行成像和定位.本文的灵感来自如下猜想:在散射波场剖面上的每个点附近的局部波场与该点到各散射体之间的最小距离有关系,并且这个关系可以被CNN网络所识别.我们将该最小距离定义为散射距离场,并将散射距离场的类别(即大小等级)作为CNN网络的预期输出,而输入就是该点附近的局部波场.最后用上述CNN网络对散射波场进行逐点训练和识别.计算结果证实了我们的灵感猜想,即上述CNN网络能够在复杂散射波场中对散射体进行成像.只通过一个训练模型的学习,CNN网络即可反演多种散射模型的偏移剖面,最后得到"类别函数预测值"和"滤波剖面"两种成像结果,由此可以辨识出在复杂的偏移剖面中各散射体的位置.     

广义散射层析成像反演

本文详细地给出了基于非均匀介质的体散射广义散射层析成像反演的基本理论.广义散射层析成像反演可以描述为波场的反向传播和对成像场进行局部波数域滤波的过程.在数值算例中,利用背景速度沿深度方向均匀变化的v（z）介质中的简单的方块作为速度异常体的模型,通过对该模型产生的低频的Born数据和声波的正演数据的测试,在对采集系统进行有限频率带宽和空间孔径的校正来进行局部成像矩阵谱的恢复中,可以看出模型中各点的谱在恢复后的质量无论从覆盖的面积范围还是幅值的均一性上都有着明显的提高;在对速度模型的重建中,广义散射层析成像反演能够很好地恢复速度模型的低频分量,即便是方块速度异常体相对于背景速度的平均速度扰动是23%也能很好地重建模型中的速度,且对于不同的背景速度模型基本上都能很好地恢复Marmousi速度模型的低频分量.所以该方法将基于Born模型的层析成像反演适应范围进行了一定程度的扩展.     

广义散射层析成像反演

本文详细地给出了基于非均匀介质的体散射广义散射层析成像反演的基本理论.广义散射层析成像反演可以描述为波场的反向传播和对成像场进行局部波数域滤波的过程.在数值算例中,利用背景速度沿深度方向均匀变化的v(z)介质中的简单的方块作为速度异常体的模型,通过对该模型产生的低频的Born数据和声波的正演数据的测试,在对采集系统进行有限频率带宽和空间孔径的校正来进行局部成像矩阵谱的恢复中,可以看出模型中各点的谱在恢复后的质量无论从覆盖的面积范围还是幅值的均一性上都有着明显的提高;在对速度模型的重建中,广义散射层析成像反演能够很好地恢复速度模型的低频分量,即便是方块速度异常体相对于背景速度的平均速度扰动是23%也能很好地重建模型中的速度,且对于不同的背景速度模型基本上都能很好地恢复Marmousi速度模型的低频分量.所以该方法将基于Born模型的层析成像反演适应范围进行了一定程度的扩展.     

基于逆散射成像条件的最小二乘逆时偏移

最小二乘逆时偏移（LSRTM）相对于常规逆时偏移（RTM）具有分辨率更高、振幅更准确、噪音更少等优势,可以对复杂的地质构造进行有效的成像.这种迭代更新反演成像方法十分依赖目标函数的梯度质量和计算效率.当地质模型中存在强反射界面或者记录中存在折射波时,基于常规互相关成像条件（CCC）的最小二乘逆时偏移梯度会包含很强的低频噪音,从而使反演的收敛速度和成像质量降低.为此,本文在最小二乘逆时偏移的梯度中引进了逆散射成像条件来压制这种低频噪音,并以此提出基于逆散射成像条件（ISC）的最小二乘逆时偏移方法.数值模拟结果表明,两者计算耗时基本一致,但逆散射成像条件能高效压制梯度中的低频噪音,从而使反演过程中收敛加速,成像质量得到显著提高.     

密度和速度随机分布共网格模型的重力与地震联合反演

针对重力与地震联合反演存在的问题,结合已有的研究成果,本文研究实现了速度和密度随机分布共网格单元模型的建模技术,以适应密度和速度剧烈变化的复杂模型及联合反演的计算要求.重力正演利用了该网格的二度半体模型,并进一步改进了地震走时的二维射线追踪计算方法,以适用于速度随机分布的网格介质.结合改进的模拟退火算法,实现了这种共网格条件下的重力与地震资料的同步联合反演.模型试验证明了重力与地震联合反演可以准确确定复杂物性界面的密度和速度结构,适用于物性界面不完全一致和物性变化剧烈的复杂模型,并且联合反演结果要优于单独的重力反演.带先验信息约束下的实际资料的联合反演,进一步证明了该方法的适用性和效果,可提高反演精度并减少多解性.     

A NONITERATIVE PROCEDURE FOR INVERTING PLANE-WAVE REFLECTION DATA AT SEVERAL ANGLES OF INCIDENCE USING THE RICCATI EQUATION*

Various exact methods of inverting the complete waveform of vertical seismic reflection data to produce acoustic impedance profiles have been suggested. These inverse methods generally remain valid for nonvertical, plane-wave data, provided total reflection does not occur. Thus, in principle, the “seismogram” at each ray parameter in a slant stack can be interpreted separately. Rather than invert each plane-wave seismogram separately, they can all be interpreted simultaneously and an “average” model thus obtained. Inversion for both the velocity and the density also becomes possible when two or more plane-wave seismograms are simultaneously inverted. The theory for a noniterative inversion method, based on the time-domain Riccati equation, is discussed. Numerical examples of inversions using this technique on synthetic data demonstrate its numerical stability and the advantage of simultaneous inversion of several seismograms to reduce the effect of noise in the data and increase the stability of the inversion process.     

Two-dimensional data-space joint inversion of magnetotelluric,gravity, magnetic and seismic data with cross-gradient constraints

In recent years, joint inversion has been widely used for integrated geological interpretation. We extended a data-space joint inversion algorithm of magnetotelluric, gravity and magnetic data to include first-arrival seismic travel-time and normalized cross-gradient constraints. We describe the main features of the algorithm and apply it to synthetic data generated for hypothetical models. For the synthetic data, we find that the joint inversion with multiple parameters is superior to the joint inversion with two or even three parameters, which can reduce the multisolution of inversion results more effectively. Furthermore, data-space joint inversion involves fewer memory requirements and better calculation speeds than traditional model-space joint inversion. The normalized cross-gradient constraints can better couple model parameters of different magnitudes compared with traditional unnormalized cross-gradient constraints, resulting in higher levels of structural similarity among resistivity, density, magnetic susceptibility and velocity models.     

Feasibility of waveform inversion of Rayleigh waves for shallow shear-wave velocity using a genetic algorithm

Conventional surface wave inversion for shallow shear (S)-wave velocity relies on the generation of dispersion curves of Rayleigh waves. This constrains the method to only laterally homogeneous (or very smooth laterally heterogeneous) earth models. Waveform inversion directly fits waveforms on seismograms, hence, does not have such a limitation. Waveforms of Rayleigh waves are highly related to S-wave velocities. By inverting the waveforms of Rayleigh waves on a near-surface seismogram, shallow S-wave velocities can be estimated for earth models with strong lateral heterogeneity. We employ genetic algorithm (GA) to perform waveform inversion of Rayleigh waves for S-wave velocities. The forward problem is solved by finite-difference modeling in the time domain. The model space is updated by generating offspring models using GA. Final solutions can be found through an iterative waveform-fitting scheme. Inversions based on synthetic records show that the S-wave velocities can be recovered successfully with errors no more than 10% for several typical near-surface earth models. For layered earth models, the proposed method can generate one-dimensional S-wave velocity profiles without the knowledge of initial models. For earth models containing lateral heterogeneity in which case conventional dispersion-curve-based inversion methods are challenging, it is feasible to produce high-resolution S-wave velocity sections by GA waveform inversion with appropriate priori information. The synthetic tests indicate that the GA waveform inversion of Rayleigh waves has the great potential for shallow S-wave velocity imaging with the existence of strong lateral heterogeneity.     

Full waveform inversion of gas hydrate reflectors in Northern South China Sea

Bottom Simulating Reflectors (BSRs) are considered to be the bottom of gas hydrate bearing sediments; hence, BSRs are used to identify gas hydrate and free gas. In order to obtain accurate velocity structure of BSRs, this paper presents a full waveform inversion strategy based on Genetic Algorithm. Synthetic seismograms are calculated using the slowness technique. Through numerical experiments made with noisy synthetic data, the inversion algorithm shows stable performance, and genetic operators are defined. This method was applied to field data from the northern South China Sea. Inversion results show that obvious velocity anomaly of BSRs can be detected, which indicates the existence of gas hydrate and free gas.     

Look-ahead vertical seismic profiling inversion approach for density and compressional wave velocity in Bayesian framework

To reduce drilling uncertainties, zero-offset vertical seismic profiles can be inverted to quantify acoustic properties ahead of the bit. In this work, we propose an approach to invert vertical seismic profile corridor stacks in Bayesian framework for look-ahead prediction. The implemented approach helps to successfully predict density and compressional wave velocity using prior knowledge from drilled interval. Hence, this information can be used to monitor reservoir depth as well as quantifying high-pressure zones, which enables taking the correct decision during drilling. The inversion algorithm uses Gauss–Newton as an optimization tool, which requires the calculation of the sensitivity matrix of trace samples with respect to model parameters. Gauss–Newton has quadratic rate of convergence, which can speed up the inversion process. Moreover, geo-statistical analysis has been used to efficiently utilize prior information supplied to the inversion process. The algorithm has been tested on synthetic and field cases. For the field case, a zero-offset vertical seismic profile data taken from an offshore well were used as input to the inversion algorithm. Well logs acquired after drilling the prediction section was used to validate the inversion results. The results from the synthetic case applications were encouraging to accurately predict compressional wave velocity and density from just a constant prior model. The field case application shows the strength of our proposed approach in inverting vertical seismic profile data to obtain density and compressional wave velocity ahead of a bit with reasonable accuracy. Unlike the commonly used vertical seismic profile inversion approach for acoustic impedance using simple error to represent the prior covariance matrix, this work shows the importance of inverting for both density and compressional wave velocity using geo-statistical knowledge of density and compressional wave velocity from the drilled section to quantify the prior covariance matrix required during Bayesian inversion.     

Data acquisition and pre-processing required for simultaneous P-SV inversion

The goal of seismic reflection surveys is the derivation of petrophysical subsurface parameters from surface measurements. Today's well established technique in data acquisition, as well as processing terms, is based on the acoustic approximation to the real world's wave propagation. In recent years a lot of work has been done to extend the technique to the elastic approximation. There was especially an important trend towards elastic inversion techniques operating on plane-wave seismograms, called simultaneous P-SV inversion (or short P-SV inversion) within this paper. Being still under investigation, some important aspects of P-SV inversion concerning data acquisition as well as pre-processing, should be pointed out. To fit the assumptions of P-SV inversion schemes, at least a two-dimensional picture of the reflected wavefield with vertical and in-line horizontal receivers has to be recorded. Moreover, the theoretical work done suggests that in addition to a survey with a compressional wave source, a second survey should be done using sources radiating vertically polarized shear waves, is needed. Finally, proper slant stacking must be performed to get plane-wave seismograms. The P/S separated plane-wave seismograms are then well prepared for feeding into the inversion algorithms. P/S separated planewave seismograms are then well prepared for feeding into the inversion algorithm.s In this paper, a tutorial overview of the data acquisition and pre-processing in accordance with the P-SV inversion philosophy is given and illustrated using synthetic seismograms. A judgement on the feasibility of the P-SV inversion philosophy must be left to ongoing research.     

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.     

基于可视性分析与能量补偿的金属矿弹性波全波形反演

采用弹性波全波形反演方法精确重建深部金属矿多参数模型,建模过程采用基于地震照明的反演策略.首先给出基于照明理论的观测系统可视性定义,利用可视性分析构建新的目标函数,对反演目标可视性较高的炮检对接收到的地震记录在波场匹配时占有更高的权重,确保了参与反演计算中的地震数据的有效性;其次将给定观测系统对地下介质的弹性波场照明强度作为优化因子,根据地震波在波阻抗界面处的能量分配特点,自适应补偿波场能量分布和优化速度梯度,以提高弹性波全波形反演过程的稳定性和反演结果的精度.理论模型和金属矿模型反演试验结果表明,基于可视性分析和能量补偿的反演策略可以使弹性波全波形反演更快地收敛到目标函数的全局极小值,获得适用于金属矿高分辨率地震偏移成像的多参数模型.     

变阻尼约束层析成像及其在VSP资料中的应用(英文)

初至波走时层析成像已经取得了广泛的应用,然而,由于观测系统的限制,射线在模型中分布不均匀,导致层析结果的分辨能力不足。变阻尼约束方法应用不均匀的先验信息来匹配不均匀的数据分布,可以减小速度模型校正量与射线覆盖程度的相关性。本文将变阻尼约束方法应用于初至波旅行时层析成像中,并将平滑约束方法加入正则化方程组中来避免单独使用变阻尼约束带来的不稳定性,利用阿尔法滤波器对反演中间迭代结果进行平滑和去噪,采用LSQR算法求解线性方程组来提高收敛速度和压制误差传递。本文应用上述层析成像算法对VSP观测系统进行速度反演,分别应用于检测板速度模型数据和实际VSP资料速度反演中,结果表咀变阻尼约束层析成像可以改善射线不均匀覆盖带来的影响,从而提高速度反演结果的质量;VSP资料检波点附近的速度反演结果可靠性高。     

跨孔雷达全波形反演成像方法的研究

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