动态监测骨质疏松性微结构退化的超声全波反演方法

研究了基于全波反演(FWI)的骨骼超声层析成像方法,用于动态监测骨质疏松性微结构退化的进程。采用雌性小鼠注射药物建立骨质疏松症模型,在第0,2,4,6周通过Micro-CT扫描活体小鼠,重建获得小鼠股骨骨骼结构。以第0周骨骼结构为基准输入模型,通过不同的超声收发模式(透射、反射及透射-反射双模式),仿真分析了FWI监测不同骨质疏松进程的骨微结构退化的效果。结果表明,初始模型为均匀介质(纯水)时,FWI反演失效,不能准确重建骨骼结构。初始模型中考虑了基准骨骼结构(第0周)时,FWI能准确反演骨骼组织声速(均方根误差(RMSE)<17 m/s,平均相对误差(MRE)<7.2%),精确重建骨骼结构(结构相关系数(CC)>0.85),因此可以准确监测不同骨质疏松进程(第2,4,6周)的骨微结构退化情况。对比不同超声收发模式,透射-反射双模式FWI监测骨微结构退化的性能优于单一透射或反射FWI监测方法。考虑了基准骨骼模型的FWI可用于动态监测骨微结构退化,对评估骨质疏松进展具有一定意义。

跨孔雷达全波形反演成像方法的研究

跨孔雷达全波形反演是一种使用全波形信息反演两钻孔之间地下信息的层析成像技术.常规的层析成像反演大部分采用射线追踪方法,其中基于初至时的射线追踪方法可以反演出速度剖面(介电常数剖面),基于最大振幅的层析成像可以反演出衰减剖面(电导率剖面).常规射线追踪方法有许多不足,究其原因是该方法仅使用了小部分的信号信息.为了进一步提高成像分辨率,本文全面推导了全波形跨孔雷达层析成像反演方法,该方法利用雷达波全幅度相位信息能够反演出地下高分辨率的介电常数和电导率图像.本文通过基于局域网的分布式并行算法,有效地解决了巨量数据正演计算问题.文中首先建立了基于单轴各向异性介质完全匹配层的时间域有限差分二维正演算法,进而通过应用包括时间维度在内的全波场信息与残场逆向传播的全波场信息乘积来计算梯度方向,通过求取以步长为自变量的目标函数的极值确定步长公式,并提出以第一次介电常数反演作为同步反演的初始模型,能够有效提高收敛速度.本文对多组模型进行成像实验,取得了较好的反演效果.

各向异性弹性参数的广义非线性反演方法

在非线性最优化理论的基础上结合地球物理反演问题,提出各向异性弹性参数的广义非线性反演方法。结合各向异性弹性参数反演,推导出反演所需的梯度向量,梯度向量中Jacobi矩阵各个元素的求取是利用与正演完全相同的方法,并构造了一个公式,从单位阵开始来修改函数的海色矩阵的逆矩阵,这样,不用求海色矩阵及其逆阵就能求函数的极小值,减少了计算量,给出了实际的反演结果。地质模型的反演结果证明,该方法是可行的,且反演精度高,具有较好的发展前景。

国际大油公司深水油气勘探实践及启示——以圭亚那斯塔布鲁克区块为例

近年来,国际大油公司持续在深水领域取得勘探突破。其中埃克森美孚公司领导的勘探联合体在圭亚那的斯塔布鲁克区块获得31个深水油气田发现,使圭亚那成为南美地区石油行业的重要国家之一,同时也带动了周边海域的勘探热潮。圭亚那盆地横跨圭亚那和苏里南海域,埃克森美孚公司在圭亚那盆地的油气勘探主要经历了3个阶段,分别是1957—1982年超前布局圭亚那盆地苏里南海域;1999—2015年再进圭亚那盆地并长期坚守圭亚那海域;2015年至今地质认识和地震技术助推获得一系列勘探发现。国际大油公司,尤其是埃克森美孚公司领导的勘探联合体在圭亚那的勘探实践表明,开展区域地质综合研究并结合新资料坚定勘探信心,通过引进合作伙伴共担风险、共享收益,是风险勘探的典型做法,可为中国油公司实现从“走出去”迈向“走上去”开展海外油气勘探业务提供借鉴和参考。

Multi-scale seismic full waveform inversion in the frequency-domain with a multi-grid method

Although full waveform inversion in the frequency domain can overcome the local minima problem in the time direction, such problem still exists in the space direction because of the media subsurface complexity. Based on the optimal steep descent methods, we present an algorithm which combines the preconditioned bi-conjugated gradient stable method and the multi-grid method to compute the wave propagation and the gradient space. The multiple scale prosperity of the waveform inversion and the multi-grid method can overcome the inverse problems local minima defect and accelerate convergence. The local inhomogeneous three-hole model simulated results and the Marmousi model certify the algorithm effectiveness.

Two-dimensional frequency-domain acoustic fullwaveform inversion with rugged topography

We studied finite-element-method-based two-dimensional frequency-domain acoustic FWI under rugged topography conditions. The exponential attenuation boundary condition suitable for rugged topography is proposed to solve the cutoff botmdary problem as well as to consider the requirement of using the same subdivision grid in joint multifrequency inversion. The proposed method introduces the attenuation factor, and by adjusting it, acoustic waves are sufficiently attenuated in the attenuation layer to minimize the cutoff boundary effect. Based on the law of exponential attenuation, expressions for computing the attenuation factor and the thickness of attenuation layers are derived for different frequencies. In multifrequency-domain FWI, the conjugate gradient method is used to solve equations in the Gauss-Newton algorithm and thus minimize the computation cost in calculating the Hessian matrix. In addition, the effect of initial model selection and frequency combination on FWI is analyzed. Examples using numerical simulations and FWI calculations are used to verify the efficiency of the proposed method.

Elastic envelope inversion using multicomponent seismic data with filtered-out low frequencies

The absence of low-frequency information in seismic data is one of the most difficult problems in elastic full waveform inversion. Without low-frequency data, it is difficult to recover the long-wavelength components of subsurface models and the inversion converges to local minima. To solve this problem, the elastic envelope inversion method is introduced. Based on the elastic envelope operator that is capable of retrieving low- frequency signals hidden in multicomponent data, the proposed method uses the envelope of multicomponent seismic signals to construct a misfit function and then recover the long- wavelength components of the subsurface model. Numerical tests verify that the elastic envelope method reduces the inversion nonlinearity and provides better starting models for the subsequent conventional elastic full waveform inversion and elastic depth migration, even when low frequencies are missing in multicomponent data and the starting model is far from the true model. Numerical tests also suggest that the proposed method is more effective in reconstructing the long-wavelength components of the S-wave velocity model. The inversion of synthetic data based on the Marmousi-2 model shows that the resolution of conventional elastic full waveform inversion improves after using the starting model obtained using the elastic envelope method. Finally, the limitations of the elastic envelope inversion method are discussed.

一种用于准单站配置的步进频探地雷达建模方法

探地雷达是一种被广泛使用的无损检测技术。利用探地雷达对分层媒质进行全波反演时,构建精确的探地雷达正演模型具有十分重要的意义。该文提出一种可用于准单站配置的步进频探地雷达的建模方法。在该模型中,探地雷达系统及其与分层媒质间的相互作用被表示成线性方程,天线对雷达信号的影响被表示为只与频率有关的传输函数。为验证模型准确性,该文在实验室条件下搭建了准单站配置的步进频探地雷达系统,并对已知厚度的石膏板和木板的雷达测量信号进行全波反演。反演结果表明:石膏板和木板的厚度估计误差均不超过0.3mm,验证了所提出的正演模型具有高准确度。利用石膏板和木板搭建分层模型,该文进一步比较了准单站配置和单站配置步进频探地雷达系统对介电常数差异较小的分层媒质的反演性能。实验结果表明:准单站配置探地雷达能获得更精确的反演参数。通过对分界面反射信号的信噪比估计可知,准单站配置比单站配置探地雷达系统能获得高出约10dB的信噪比,因此具有更好的反演性能。

Improved hybrid iterative optimization method for seismic full waveform inversion

In full waveform inversion （FWI）, Hessian information of the misfit function is of vital importance for accelerating the convergence of the inversion; however, it usually is not feasible to directly calculate the Hessian matrix and its inverse. Although the limited memory Broyden-Fletcher-Goldfarb-Shanno （L-BFGS） or Hessian-free inexact Newton （HFN） methods are able to use approximate Hessian information, the information they collect is limited. The two methods can be interlaced because they are able to provide Hessian information for each other; however, the performance of the hybrid iterative method is dependent on the effective switch between the two methods. We have designed a new scheme to realize the dynamic switch between the two methods based on the decrease ratio （DR） of the misfit function （objective function）, and we propose a modified hybrid iterative optimization method. In the new scheme, we compare the DR of the two methods for a given computational cost, and choose the method with a faster DR. Using these steps, the modified method always implements the most efficient method. The results of Marmousi and overthrust model testings indicate that the convergence with our modified method is significantly faster than that in the L-BFGS method with no loss of inversion quality. Moreover, our modified outperforms the enriched method by a little speedup of the convergence. It also exhibits better efficiency than the HFN method.

Frequency-domain auto-adapting full waveform inversion with blended source and frequency-group encoding

As a high quality seismic imaging method, full waveform inversion （FWI） can accurately reconstruct the physical parameter model for the subsurface medium. However, application of the FWI in seismic data processing is computationally expensive, especially for the three-dimension complex medium inversion. Introducing blended source technology into the frequency-domain FWI can greatly reduce the computational burden and improve the efficiency of the inversion. However, this method has two issues： first, crosstalk noise is caused by interference between the sources involved in the encoding, resulting in an inversion result with some artifacts; second, it is more sensitive to ambient noise compared to conventional FWI, therefore noisy data results in a poor inversion. This paper introduces a frequency-group encoding method to suppress crosstalk noise, and presents a frequency- domain auto-adapting FWI based on source-encoding technology. The conventional FWI method and source-encoding based FWI method are combined using an auto-adapting mechanism. This improvement can both guarantee the quality of the inversion result and maximize the inversion efficiency.

Prismatic and full-waveform joint inversion

Prismatic wave is that it has three of which is located at the reflection interface reflection paths and two reflection points, one and the other is located at the steep dip angle reflection layer, so that contains a lot of the high and steep reflection interface information that primary cannot reach. Prismatic wave field information can be separated by applying Born approximation to traditional reverse time migration profile, and then the prismatic wave is used to update velocity to improve the inversion efficiency for the salt dame flanks and some other high and steep structure. Under the guidance of this idea, a prismatic waveform inversion method is proposed （abbreviated as PWI）. PWI has a significant drawback that an iteration time of PWI is more than twice as that of FWI, meanwhile, the full wave field information cannot all be used, for this problem, we propose a joint inversion method to combine prismatic waveform inversion with full waveform inversion. In this method, FWI and PWI are applied alternately to invert the velocity. Model tests suggest that the joint inversion method is less dependence on the high and steep structure information in the initial model and improve high inversion efficiency and accuracy for the model with steep dip angle structure.

Sparse constrained encoding multi-source full waveform inversion method based on K-SVD dictionary learning

Full waveform inversion(FWI)is an extremely important velocity-model-building method.However,it involves a large amount of calculation,which hindsers its practical application.The multi-source technology can reduce the number of forward modeling shots during the inversion process,thereby improving the efficiency.However,it introduces crossnoise problems.In this paper,we propose a sparse constrained encoding multi-source FWI method based on K-SVD dictionary learning.The phase encoding technology is introduced to reduce crosstalk noise,whereas the K-SVD dictionary learning method is used to obtain the basis of the transformation according to the characteristics of the inversion results.The multiscale inversion method is adopted to further enhance the stability of FWI.Finally,the synthetic subsag model and the Marmousi model are set to test the effectiveness of the newly proposed method.Analysis of the results suggest the following:(1)The new method can effectively reduce the computational complexity of FWI while ensuring inversion accuracy and stability;(2)The proposed method can be combined with the time-domain multi-scale FWI strategy flexibly to further avoid the local minimum and to improve the stability of inversion,which is of significant importance for the inversion of the complex model.

低频地震勘探与低频可控震源

低频地震勘探是近年来非常"热"的话题,本文探究了为什么低频地震勘探能够如此吸引众人的眼球,而低频可控震源为什么"千呼万唤"始出来?低频地震信号激发技术究竟面临哪些挑战?低频可控震源有哪些关键的技术参数?文中还结合KZ-28LF低频可控震源在国内开展的先导性试验,为业界展示其低频信号激发技术在解决油气问题方面的能力。

Wavefield reconstruction inversion with weaktotal-variation constraint based on first arrival traveltime tomography

The objective function of full waveform inversion is a strong nonlinear function,the inversion process is not unique,and it is easy to fall into local minimum.Firstly,in the process of wavefield reconstruction,the wave equation is introduced into the construction of objective function as a penalty term to broaden the search space of solution and reduce the risk of falling into local minimum.In addition,there is no need to calculate the adjoint wavefield in the inversion process,which can significantly improve the calculation efficiency;Secondly,considering that the total variation constraint can effectively reconstruct the discontinuous interface in the velocity model,this paper introduces the weak total variation constraint to avoid the excessive smooth estimation of the model under the strong total variation constraint.The disadvantage of this strategy is that it is highly dependent on the initial model.In view of this,this paper takes the long wavelength initial model obtained by first arrival traveltime tomography as a prior model constraint,and proposes a weak total variation constrained wavefield reconstruction inversion method based on first arrival traveltime tomography.Numerical experimental results show that the new method reduces the dependence on the initial model,the interface description is more accurate,the error is reduced,and the iterative convergence efficiency is significantly improved.

Studies on quasi-Newton methods in timedomain multiscale full waveform inversion

The time-domain multiscale full waveform inversion(FWI)mitigates the influence of the local minima problem in nonlinear inversion via sequential inversion using different frequency components of seismic data.The quasi-Newton methods avoid direct computation of the inverse Hessian matrix,which reduces the amount of computation and storage requirement.A combination of the two methods can improve inversion accuracy and efficiency.However,the quasi-Newton methods in time-domain multiscale FWI still cannot completely solve the problem where the inversion is trapped in local minima.We first analyze the reasons why the quasi-Newton Davidon–Fletcher–Powell and Broyden–Fletcher–Goldfarb–Shanno methods likely fall into the local minima using numerical experiments.During seismic-wave propagation,the amplitude decreases with the geometric diffusion,resulting in the concentration of the gradient of the velocity model in the shallow part,and the deep velocity cannot be corrected.Thus,the inversion falls into the local minima.To solve this problem,we introduce a virtual-source precondition to remove the influence of geometric diffusion.Thus,the model velocities in the deep and shallow parts can be simultaneously completely corrected,and the inversion can more stably converge to the global minimum.After the virtual-source precondition is implemented,the problem in which the quasi-Newton methods likely fall into the local minima is solved.However,problems remain,such as incorrect search direction after a certain number of iterations and failure of the objective function to further decrease.Therefore,we further modify the process of timedomain multiscale FWI based on virtual-source preconditioned quasi-Newton methods by resetting the inverse of the approximate Hessian matrix.Thus,the validity of the search direction of the quasi-Newton methods is guaranteed.Numerical tests show that the modified quasi-Newton methods can obtain more reasonable inversion results,and they converge faster and entail lesser computational resources than the gradient method.

Full waveform inversion with spectral conjugategradient method

Spectral conjugate gradient method is an algorithm obtained by combination of spectral gradient method and conjugate gradient method,which is characterized with global convergence and simplicity of spectral gradient method,and small storage of conjugate gradient method.Besides,the spectral conjugate gradient method was proved that the search direction at each iteration is a descent direction of objective function even without relying on any line search method.Spectral conjugate gradient method is applied to full waveform inversion for numerical tests on Marmousi model.The authors give a comparison on numerical results obtained by steepest descent method,conjugate gradient method and spectral conjugate gradient method,which shows that the spectral conjugate gradient method is superior to the other two methods.