Least-squares reverse time migration in visco-acoustic media based on symplectic stereo-modeling method

The authors proposed a symplectic stereo-modeling method(SSM)in the Birkhoffian dynam-ics and apply it to the visco-acoustic least-squares reverse time migration(LSRTM).The SSM adopts ste-reo-modeling operator in space and symplectic Runge-Kutta scheme in time,resulting in great ability in suppressing numerical dispersion and long-time computing.These advantages are further confirmed by numerical dispersion analysis,long-time computation test and computational efficiency comparison.After these theoretical analyses and experiments,acoustic and visco-acoustic LSRTM are tested and compared between SSM method and the conventional symplectic method(CSM)using the fault and marmousi models.Meanwhile,dynamic source encoding and exponential decay moving average gradients method are adopted to reduce the computation cost and improve the convergence rate.The imaging results show that LSRTM based on visco-acoustic wave equations effectively takes into account the influence of viscosity can therefore compensate for the amplitude attenuation.Besides,SSM method not only has high numerical accuracy and computational efficiency,but also performs effectively in LSRTM.

An improved reverse time migration for subsurface imaging over complex geological structures:A numerical study

In seismic exploration,it is a critical task to image and interpret different seismic signatures over complex geology due to strong lateral velocity contrast,steep reflectors,overburden strata and dipping flanks.To understand the behavior of these seismic signatures,nowadays Reverse Time Migration(RTM)technique is used extensively by the oil&gas industries.During the extrapolation phase of RTM,the source wavefield needs to be saved,which needs high storage memory and large computing time.These two are the main obstacles of RTM for production use.In order to overcome these disadvantages,in this study,a second-generation improved RTM technique is proposed.In this improved form,a shift operator is introduced at the time of imaging condition of RTM algorithm which is performed automatically both in space and time domain.This effort is made to produce a better-quality image by minimizing the computational time as well as numerical artefacts.The proposed method is applied over various benchmark models and validated by implementing over one field data set from the Jaisalmer Basin,India.From the analysis,it is observed that the method consumes a minimum of 45%less storage space and reduce the execution time by 20%,as compared to conventional RTM.The proposed RTM is found to work efficiently in comparison to the conventional RTM both in terms of imaging quality and minimization of numerical artefacts for all the benchmark models as well as field data.

Multiparameter least-squares reverse time migration for acoustic–elastic coupling media based on ocean bottom cable data

In marine seismic exploration,ocean bottom cable technology can record multicomponent seismic data for multiparameter inversion and imaging.This study proposes an elastic multiparameter lease-squares reverse time migration based on the ocean bottom cable technology.Herein,the wavefield continuation operators are mixed equations:the acoustic wave equations are used to calculate seismic wave propagation in the seawater medium,whereas in the solid media below the seabed,the wavefields are obtained by P-and S-wave separated vector elastic wave equations.At the seabed interface,acoustic–elastic coupling control equations are used to combine the two types of equations.P-and S-wave separated elastic migration operators,demigration operators,and gradient equations are derived to realize the elastic least-squares reverse time migration based on the P-and S-wave mode separation.The model tests verify that the proposed method can obtain high-quality images in both the P-and S-velocity components.In comparison with the traditional elastic least-squares reverse time migration method,the proposed method can readily suppress imaging crosstalk noise from multiparameter coupling.

Multisource least-squares reverse-time migration with structure-oriented filtering

The technology of simultaneous-source acquisition of seismic data excited by several sources can significantly improve the data collection efficiency. However, direct imaging of simultaneous-source data or blended data may introduce crosstalk noise and affect the imaging quality. To address this problem, we introduce a structure-oriented filtering operator as preconditioner into the multisource least-squares reverse-time migration （LSRTM）. The structure-oriented filtering operator is a nonstationary filter along structural trends that suppresses crosstalk noise while maintaining structural information. The proposed method uses the conjugate-gradient method to minimize the mismatch between predicted and observed data, while effectively attenuating the interference noise caused by exciting several sources simultaneously. Numerical experiments using synthetic data suggest that the proposed method can suppress the crosstalk noise and produce highly accurate images.

Steeply dipping structural target-oriented viscoacoustic least-squares reverse time migration and its application

Steeply dipping structural imaging is a significant challenge because surface geophones cannot obtain seismic primary reflection wave information from steeply dipping structures.Prismatic waves with a significant amount of steeply dipping information can be used to improve the imaging eff ect on steeply dipping structures.Subsurface attenuation leads to amplitude loss and phase distortion of seismic waves,and ignoring this attenuation during imaging can cause blurring of migration amplitudes.In this study,we proposed a steeply dipping structural target-oriented viscoacoustic least-squares reverse time migration(LSRTM)method with prismatic and primary waves as an objective function based on the viscous wave equation,while deriving Q-compensated wavefield propagation and joint operators of prismatic and primary waves and the Q-compensated demigration operator.Numerical examples on synthetic and field data verified the advantages of the proposed viscoacoustic LSRTM method of joint primary and prismatic waves over conventional viscoacoustic LSRTM and non-compensated LSRTM when using attenuating observed data.

Least-squares reverse time migration method using the factorization of the Hessian matrix

Least-squares reverse time migration(LSRTM)can eliminate imaging artifacts in an iterative way based on the concept of inversion,and it can restore imaging amplitude step by step.LSRTM can provide a high-resolution migration section and can be applied to irregular and poor-quality seismic data and achieve good results.Steeply dipping refl ectors and complex faults are imaged by using wavefi eld extrapolation based on a two-way wave equation.However,the high computational cost limits the method’s application in practice.A fast approach to realize LSRTM in the imaging domain is provided in this paper to reduce the computational cost signifi cantly and enhance its computational effi ciency.The method uses the Kronecker decomposition algorithm to estimate the Hessian matrix.A low-rank matrix can be used to calculate the Kronecker factor,which involves the calculation of Green’s function at the source and receiver point.The approach also avoids the direct construction of the whole Hessian matrix.Factorization-based LSRTM calculates the production of low-rank matrices instead of repeatedly calculating migration and demigration.Unlike traditional LSRTM,factorization-based LSRTM can reduce calculation costs considerably while maintaining comparable imaging quality.While having the same imaging eff ect,factorization-based LSRTM consumes half the running time of conventional LSRTM.In this regard,the application of factorization-based LSRTM has a promising advantage in reducing the computational cost.Ambient noise caused by this method can be removed by applying a commonly used fi ltering method without signifi cantly degrading the imaging quality.

Conjugate gradient and cross-correlation based least-square reverse time migration and its application

Although conventional reverse time migration can be perfectly applied to structural imaging it lacks the capability of enabling detailed delineation of a lithological reservoir due to irregular illumination. To obtain reliable reflectivity of the subsurface it is necessary to solve the imaging problem using inversion. The least-square reverse time migration （LSRTM） （also known as linearized refleetivity inversion） aims to obtain relatively high-resolution amplitude preserving imaging by including the inverse of the Hessian matrix. In practice, the conjugate gradient algorithm is proven to be an efficient iterative method for enabling use of LSRTM. The velocity gradient can be derived from a cross-correlation between observed data and simulated data, making LSRTM independent of wavelet signature and thus more robust in practice. Tests on synthetic and marine data show that LSRTM has good potential for use in reservoir description and four-dimensional （4D） seismic images compared to traditional RTM and Fourier finite difference （FFD） migration. This paper investigates the first order approximation of LSRTM, which is also known as the linear Born approximation. However, for more complex geological structures a higher order approximation should be considered to improve imaging quality.

Stable attenuation-compensated reverse time migration and its application to land seismic data

Intrinsic attenuation of the earth causes energy loss and phase distortion in seismic wave propagation.To obtain high-resolution imaging results,these negative effects must be considered during reverse time migration(RTM).We can easily implement attenuation-compensated RTM using the constant Q viscoacoustic wave equation with decoupled amplitude attenuation and phase dispersion terms.However,the nonphysical amplitude-compensation process will inevitably amplify the high-frequency noise in the wavefield in an exponential form,causing the numerical simulation to become unstable.This is due to the fact that the amplitude of the compensation grows exponentially with frequency.In order to achieve stable attenuation-compensated RTM,we modify the analytic expression of the attenuation compensation extrapolation operator and make it only compensate for amplitude loss within the effective frequency band.Based on this modified analytic formula,we then derive an explicit time-space domain attenuation compensation extrapolation operator.Finally,the implementation procedure of stable attenuation-compensated RTM is presented.In addition to being simple to implement,the newly proposed attenuation-compensated extrapolation operator is superior to the conventional low-pass filter in suppressing random noise,which will further improve the imaging resolution.We use two synthetic and one land seismic datasets to verify the stability and effectiveness of the proposed attenuationcompensated RTM in improving imaging resolution in viscous media.

Proper orthogonal decomposition based seismic source wavefield reconstruction for finite element reverse time migration

The large storage requirement is a critical issue in cross-correlation imaging-condition based reverse time migration(RTM),because it requires the operation of the source and receiver wavefields at the same time.The boundary value method(BVM),based on the finite difference method(FDM),can be used to reconstruct the source wavefield in the reverse time propagation in the same way as the receiver wavefield,which can reduce the storage burden of the RTM data.Considering that the FDM cannot well handle models with discontinuous material properties and rough interfaces,we develop a source wavefield reconstruction strategy based on the finite element method(FEM),using proper orthogonal decomposition(POD)to enhance computational efficiency.In this method,we divide the whole time period into several segments,and construct the POD basis functions to get a reduced order model(ROM)for the source wavefield reconstruction in each segment.We show the corresponding quantitative analysis of the storage requirement of the POD-FEM.Numerical tests on the homogeneous model show the effectiveness of the proposed method,while the layered model and part of the Marmousi model tests indicate that the POD-FEM can keep an excellent balance between computational efficiency and memory usage compared with the full-stored method(FSM)and the BVM,and can be effectively applied in imaging.

Viscoacoustic prestack reverse time migration based onthe optimal time-space domain high-order finite-difference method

Prestack reverse time migration （RTM） is an accurate imaging method ofsubsurface media. The viscoacoustic prestack RTM is of practical significance because itconsiders the viscosity of the subsurface media. One of the steps of RTM is solving thewave equation and extrapolating the wave field forward and backward; therefore, solvingaccurately and efficiently the wave equation affects the imaging results and the efficiencyof RTM. In this study, we use the optimal time-space domain dispersion high-order finite-difference （FD） method to solve the viscoacoustic wave equation. Dispersion analysis andnumerical simulations show that the optimal time-space domain FD method is more accurateand suppresses the numerical dispersion. We use hybrid absorbing boundary conditions tohandle the boundary reflection. We also use source-normalized cross-correlation imagingconditions for migration and apply Laplace filtering to remove the low-frequency noise.Numerical modeling suggests that the viscoacoustic wave equation RTM has higher imagingresolution than the acoustic wave equation RTM when the viscosity of the subsurface isconsidered. In addition, for the wave field extrapolation, we use the adaptive variable-lengthFD operator to calculate the spatial derivatives and improve the computational efficiencywithout compromising the accuracy of the numerical solution.

Amplitude preserved VSP reverse time migration for angle-domain CIGs extraction

An improved method of generating angle-domain common-image gathers（ADCIGs） by VSP reverse time migration（RTM） is introduced in this paper.The formula which is used to compute the receiver wavefield for VSP RTM is modified by adding an amplitude correction term in order to conveniently output amplitude-preserved ADCIGs.Compared with the surface seismic data,VSP data contains much richer wavefields.However,the direct and downgoing waves can bring about serious imaging artifacts in ADCIGs,especially the direct wave.The feasibility and validity of this method is demonstrated by both numerical and real VSP data from western China.Thus,the ADCIGs from this method can provide reliable basic data for VSP migration velocity analysis,VSP AVO/AVA analysis,and inversion.

Regularized least-squares migration of simultaneous-source seismic data with adaptive singular spectrum analysis

Simultaneous-source acquisition has been recog- nized as an economic and efficient acquisition method, but the direct imaging of the simultaneous-source data produces migration artifacts because of the interference of adjacent sources. To overcome this problem, we propose the regularized least-squares reverse time migration method （RLSRTM） using the singular spectrum analysis technique that imposes sparseness constraints on the inverted model. Additionally, the difference spectrum theory of singular values is presented so that RLSRTM can be implemented adaptively to eliminate the migration artifacts. With numerical tests on a fiat layer model and a Marmousi model, we validate the superior imaging quality, efficiency and convergence of RLSRTM compared with LSRTM when dealing with simultaneoussource data, incomplete data and noisy data.

Variable-grid reverse-time migration of different seismic survey data

With an increasing demand for high-resolution imaging of complex subsurface structures, thin layers and hidden reservoirs, borehole and cross-well seismic migration methods have become important. However, large differences are observed in the frequency bandwidth between the surface, borehole, and cross-well surveys. Thus, variable-grid- based algorithms have been adapted to reverse-time migration. Further, we introduce Lanczos filtering to ensure the stability of wavefield calculations as well as to decrease the artificial reflections that are caused due to the variable grid size. Finally, we observe that the application of this method to surface survey, borehole, and cross-well seismic data suggests improvements in the delineation of minor fractures and steeply dipping faults.

LEAST-SQUARES METHOD-BASED FEATURE FITTING AND EXTRACTION IN REVERSE ENGINEERING

The main purpose of reverse engineering is to convert discrete data pointsinto piecewise smooth, continuous surface models. Before carrying out model reconstruction it issignificant to extract geometric features because the quality of modeling greatly depends on therepresentation of features. Some fitting techniques of natural quadric surfaces with least-squaresmethod are described. And these techniques can be directly used to extract quadric surfaces featuresduring the process of segmentation for point cloud.

Huber inversion-based reverse-time migration with de-primary imaging condition and curvelet-domain sparse constraint

Least-squares reverse-time migration(LSRTM) formulates reverse-time migration(RTM) in the leastsquares inversion framework to obtain the optimal reflectivity image. It can generate images with more accurate amplitudes, higher resolution, and fewer artifacts than RTM. However, three problems still exist:(1) inversion can be dominated by strong events in the residual;(2) low-wavenumber artifacts in the gradient affect convergence speed and imaging results;(3) high-wavenumber noise is also amplified as iteration increases. To solve these three problems, we have improved LSRTM: firstly, we use Hubernorm as the objective function to emphasize the weak reflectors during the inversion;secondly, we adapt the de-primary imaging condition to remove the low-wavenumber artifacts above strong reflectors as well as the false high-wavenumber reflectors in the gradient;thirdly, we apply the L1-norm sparse constraint in the curvelet-domain as the regularization term to suppress the high-wavenumber migration noise. As the new inversion objective function contains the non-smooth L1-norm, we use a modified iterative soft thresholding(IST) method to update along the Polak-Ribie re conjugate-gradient direction by using a preconditioned non-linear conjugate-gradient(PNCG) method. The numerical examples,especially the Sigsbee2 A model, demonstrate that the Huber inversion-based RTM can generate highquality images by mitigating migration artifacts and improving the contribution of weak reflection events.

Passive multiple reverse time migration imaging based on wave decomposition and normalized imaging conditions

With the development of seismic exploration,passive-source seismic data has attracted increasing attention.Ambient noise passive seismic sources exists widely in nature and industrial production.Passive seismic data is important in logging while drilling(LWD),large-scale structural exploration,etc.In this paper,we proposed a passive multiple reverse time migration imaging(PMRTMI)method based on wavefield decomposition and normalized imaging conditions method.This method differs from seismic interferometry in that it can use raw passive seismic data directly in RTM imaging without reconstruction of virtual active gather,and we use the wavefield decomposition method to eliminate the low frequency noise in RTM.Further,the energy normalized imaging condition is used in full wavefield decomposition,which can not only enhance the image quality of both edge and deep information but also overcome the wrong energy problem caused by uneven distribution of passive sources;furthermore,this method exhibits high efficiency.Finally,numerical examples with the Marmousi model show the effectiveness of the method.

Reverse time migration based on normalized wavefield decomposition imaging condition

With the increasing complexity of prospecting objectives,reverse time migration( RTM) has attracted more and more attention due to its outstanding imaging quality. RTM is based on two-way wave equation,so it can avoid the limits of angle in traditional one-way wave equation migration,image reverse branch,prism waves and multi-reflected wave precisely and obtain accurate dynamic information. However,the huge demands for storage and computation as well as low frequency noises restrict its wide application. The normalized cross-correlation imaging conditions based on wave field decomposition are derived from traditional cross-correlation imaging condition,and it can eliminate the low-frequency noises effectively and improve the imaging resolution. The practical procedure includes separating source and receiver wave field into one-way components respectively,and conducting cross-correlation imaging condition to the post-separated wave field. In this way,the resolution and precision of the imaging result will be promoted greatly.

Pre-stack elastic reverse time migration in tunnels based on cylindrical coordinates

Seismic forward-prospecting in tunnels is an important step to ensure excavation safety. Nowadays, most advanced imaging techniques in seismic exploration involve calculating the solution of elastic wave equation in a certain coordinate system. However, considering the cylindrical geometry of common tunnel body, Cartesian coordinate system seemingly has limited applicability in tunnel seismic forwardprospecting. To accurately simulate the seismic signal received in tunnels, previous imaging method using decoupled non-conversion elastic wave equation is extended from Cartesian coordinates to cylindrical coordinates. The proposed method preserves the general finite-difference time-domain(FDTD)scheme in Cartesian coordinates, except for a novel wavefield calculation strategy addressing the singularity issue inherited at the cylindrical axis. Moreover, the procedure of cylindrical elastic reverse time migration(CERTM) in tunnels is introduced based on the decoupled non-conversion elastic wavefield. Its imaging effect is further validated via numerical experiments on typical tunnel models. As indicated in the synthetic examples, both the PP-and SS-images could clearly show the geological structure in front of the tunnel face without obvious crosstalk artifacts. Migration imaging using PP-waves can present satisfactory results with higher resolution information supplemented by the SS-images. The potential of applying the proposed method in real-world cases is demonstrated in a water diversion tunnel. In the end, we share our insights regarding the singularity treatment and further improvement of the proposed method.

Super-resolution least-squares prestack Kirchhoff depth migration using the L_0-norm

Least-squares migration （LSM） is applied to image subsurface structures and lithology by minimizing the objective function of the observed seismic and reverse-time migration residual data of various underground reflectivity models. LSM reduces the migration artifacts, enhances the spatial resolution of the migrated images, and yields a more accurate subsurface reflectivity distribution than that of standard migration. The introduction of regularization constraints effectively improves the stability of the least-squares offset. The commonly used regularization terms are based on the L2-norm, which smooths the migration results, e.g., by smearing the reflectivities, while providing stability. However, in exploration geophysics, reflection structures based on velocity and density are generally observed to be discontinuous in depth, illustrating sparse reflectance. To obtain a sparse migration profile, we propose the super-resolution least-squares Kirchhoff prestack depth migration by solving the L0-norm-constrained optimization problem. Additionally, we introduce a two-stage iterative soft and hard thresholding algorithm to retrieve the super-resolution reflectivity distribution. Further, the proposed algorithm is applied to complex synthetic data. Furthermore, the sensitivity of the proposed algorithm to noise and the dominant frequency of the source wavelet was evaluated. Finally, we conclude that the proposed method improves the spatial resolution and achieves impulse-like reflectivity distribution and can be applied to structural interpretations and complex subsurface imaging.

Attenuation-compensated reverse time migration of GPR data constrained by resistivity

The high-frequency electromagnetic waves of ground-penetrating radar(GPR)attenuate severely when propagated in an underground attenuating medium owing to the influence of resistivity,which remarkably decreases the resolution of reverse time migration(RTM).As an effective high-resolution imaging method,attenuation-compensated RTM(ACRTM)can eff ectively compensate for the energy loss caused by the attenuation related to media absorption under the influence of resistivity.Therefore,constructing an accurate resistivity-media model to compensate for the attenuation of electromagnetic wave energy is crucial for realizing the ACRTM imaging of GPR data.This study proposes a resistivity-constrained ACRTM imaging method for the imaging of GPR data by adding high-density resistivity detection along the GPR survey line and combining it with its resistivity inversion profile.The proposed method uses the inversion result of apparent resistivity data as the GPR RTM-resistivity model for imposing resistivity constraints.Moreover,the hybrid method involving image minimum entropy and RTM is used to estimate the medium velocity at the diff raction position,and combined with the distribution characteristics of the reflection in the GPR profile,a highly accurate velocity model is built to improve the imaging resolution of the ACRTM.The accuracy and eff ectiveness of the proposed method are verified using the ACRTM test of the GPR simulated data of a typical attenuating media model.On this basis,the GPR and apparent resistivity data were observed on a field survey line,and use the GPR resistivity-constrained ACRTM method to image the observed data.A comparison of the proposed method with the conventional ACRTM method shows that the proposed method has better imaging depth,stronger energy,and higher resolution,and the obtained results are more conducive for subsequent data analysis and interpretation.