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.

A stabilized least-squares imaging condition with structure constraints

Conventional shot-gather migration uses a cross-correlation imaging condition proposed by Clarebout （1971）, which cannot preserve imaging amplitudes. The deconvolution imaging condition can improve the imaging amplitude and compensate for illumination. However, the deconvolution imaging condition introduces instability issues. The least-squares imaging condition first computes the sum of the cross-correlation of the forward and backward wavefields over all frequencies and sources, and then divides the result by the total energy of the forward wavefield. Therefore, the least-squares imaging condition is more stable than the classic imaging condition. However, the least-squares imaging condition cannot provide accurate results in areas where the illumination is very poor and unbalanced. To stabilize the least-squares imaging condition and balance the imaging amplitude, we propose a novel imaging condition with structure constraints that is based on the least-squares imaging condition. Our novel imaging condition uses a plane wave construction that constrains the imaging result to be smooth along geological structure boundaries in the inversion frame. The proposed imaging condition improves the stability of the imaging condition and balances the imaging amplitude. The proposed condition is applied to two examples, the horizontal layered model and the Sigsbee 2A model. These tests show that, in comparison to the damped least-squares imaging condition, the stabilized least-squares imaging condition with structure constraints improves illumination stability and balance, makes events more consecutive, adjusts the amplitude of the depth layers where the illumination is poor and unbalanced, suppresses imaging artifacts, and is conducive to amplitude preserving imaging of deep layers.

Elastic-energy imaging condition based on energy-flow vector

Elastic reverse-time migration can effectively deal with multicomponent seismic data in which the imaging condition based on energy norm can extract the scalar-imaging result from multicomponent data.However,the energy cross-correlation imaging condition characterized by particle velocity and stress suffers from the problem of overdependence on the background elastic parameters.Therefore,we characterize the elastic-wave energy using the energy-flow vector,which is equal to the energy density,without background elastic parameters.According to the source and receiver wave fields,we propose an imaging energyflow vector and an elastic-wave energy imaging condition.Under the assumption of a planewave solution,the backscattering suppression is verified.The numerical simulations show that the elastic-energy imaging condition can obtain the energy image without backscattering.Compared with the cross-correlation imaging conditions in a vector-based wave field,the proposed imaging condition can eliminate the dependence on the background elastic parameters and effectively process seabed multicomponent data,which are conducive to further providing an interpretation of marine geological structures.

3D prestack reverse time migration of ground penetrating radar data based on the normalized correlation imaging condition

The reverse time migration(RTM)of ground penetrating radar(GPR)is usually implemented in its two-dimensional(2D)form,due to huge computational cost.However,2D RTM algorithm is difficult to focus the scattering signal and produce a high precision subsurface image when the object is buried in a complicated subsurface environment.To better handle the multi-off set GPR data,we propose a three-dimensional(3D)prestack RTM algorithm.The high-order fi nite diff erence time domian(FDTD)method,with the accuracy of eighth-order in space and second-order in time,is applied to simulate the forward and backward extrapolation electromagnetic fi elds.In addition,we use the normalized correlation imaging condition to obtain pre-stack RTM result and the Laplace fi lter to suppress the low frequency noise generated during the correlation process.The numerical test of 3D simulated GPR data demonstrated that 3D RTM image shows excellent coincidence with the true model.Compared with 2D RTM image,the 3D RTM image can more clearly and accurately refl ect the 3D spatial distribution of the target,and the resolution of the imaging results is far better.Furthermore,the application of observed GPR data further validates the eff ectiveness of the proposed 3D GPR RTM algorithm,and its fi nal image can more reliably guide the subsequent interpretation.

Preserved amplitude migration based on the one way wave equation in the angle domain

Traditional pre-stack depth migration can only provide subsurface structural information. However, simple structure information is insufficient for petroleum exploration which also needs amplitude information proportional to reflection coefficients. In recent years, pre-stack depth migration algorithms which preserve amplitudes and based on the one- way wave equation have been developed. Using the method in the shot domain requires a deconvolution imaging condition which produces some instability in areas with complicated structure and dramatic lateral variation in velocity. Depth migration with preserved amplitude based on the angle domain can overcome the instability of the one-way wave migration imaging condition with preserved amplitude. It can also offer provide velocity analysis in the angle domain of common imaging point gathers. In this paper, based on the foundation of the one-way wave continuation operator with preserved amplitude, we realized the preserved amplitude prestack depth migration in the angle domain. Models and real data validate the accuracy of the method.

Migration scheme for imaging offset VSP data within local phase space

The imaging of offset VSP data in local phase space can improve the image of the subsurface structure near the well.In this paper,we present a migration scheme for imaging VSP data in a local phase space,which uses the Gabor-Daubechies tight framebased extrapolator（G-D extrapolator） and its high-frequency asymptotic expansion to extrapolate wavefields and also delineates an improved correlation imaging condition in the local angle domain.The results for migrating synthetic and real VSP data demonstrate that the application of the high-frequency G-D extrapolator asymptotic expansion can effectively decrease computational complexity.The local angle domain correlation imaging condition can be used to weaken migration artifacts without increasing computation.

Optimizing the wavefield storage strategy in reflection-acoustic logging reverse-time migration

In this paper,wavefield storage optimization strategies are discussed with respect to reverse-time migration(RTM)imaging in reflection-acoustic logging,considering the problem of massive wavefield data storage in RTM itself.In doing so,two optimization methods are proposed and implemented to avoid wavefield storage.Firstly,the RTM based on the excitation-amplitude imaging condition uses the excitation time to judge the imaging time,and accordingly,we only need to store a small part of wavefield,such as the wavefield data of dozens of time points,the instances prove that they can even be imaged by only two time points.The traditional RTM usually needs to store the wavefield data of thousands of time points,compared with which the data storage can be reduced by tens or even thousands of times.Secondly,the RTM based on the random boundary uses the idea that the wavefield scatters rather than reflects in a random medium to reconstruct the wavefield source and thereby directly avoid storing the forward wavefield data.Numerical examples show that compared with other migration algorithms and the traditional RTM,both methods can effectively reduce wavefield data storage as well as improve data-processing efficiency while ensuring imaging accuracy,thereby providing the means for high-efficiency and highprecision imaging of fractures and caves by boreholes.

An effective denoising strategy for wave equation migration based on propagation angles

We present an effective denoising strategy for two-way wave equation migration. Three dominant artifact types are analyzed and eliminated by an optimized imaging condition. We discuss a previously unsolved beam-like artifact, which is probably caused by the cross-correlation of downward transmitting and upward scattering waves from both the source and receiver side of a single seismic shot. This artifact has relatively strong cross- correlation but carries no useful information from reflectors. The beam-like artifact widely exists in pre-stack imaging and has approximately the same amplitude as useful seismic signals. In most cases, coherent artifacts in the image are caused by directionally propagating energy. Based on propagation angles obtained by wavefield gradients, we identify the artifact energy and subtract its contribution in the imaging condition. By this process most artifacts can be accurately eliminated, including direct wave artifacts, scattering artifacts, and beam- like artifacts. This method is independent of the wavefield propagator and is easy to adapt to almost all current wave equation migration methods if needed. As this method deals with the physical artifact origins, little damage is caused to the seismic signal. Extra k-domain filtering can additionally enhance the stacking result image quality. This method succeeds in the super-wide-angle one-way migration and we can expect its success in other two-way wave equation migrations and especially in reverse time migration.

Application of GPR reverse time migration in tunnel lining cavity imaging

Correctly locating the tunnel lining cavity is extremely important tunnel quality inspection.High-accuracy imaging results are hard to obtain because conventional one-way wave migration is greatly aff ected by lateral velocity change and inclination limitation and because the diff racted wave cannot be accurately returned to the real spatial position of the lining cavity.This paper presents a tunnel lining cavity imaging method based on the groundpenetrating radar(GPR)reverse-time migration(RTM)algorithm.The principle of GPR RTM is described in detail using the electromagnetic wave equation.The finite-difference timedomain method is employed to calculate the backward extrapolation electromagnetic fi elds,and the zero-time imaging condition based on the exploding-reflector concept is used to obtain the RTM results.On this basis,the GPR RTM program is compiled and applied to the simulated and observed GPR data of a typical tunnel lining cavity GPR model and a physical lining cavity model.Comparison of RTM and Kirchhoff migration results reveals that the RTM can better converge the diff racted waves of steel bar and cavity to their true position and have higher resolution and better suppress the eff ect of multiple interference and clutter scattering waves.In addition,comparison of RTM results of diff erent degrees of noise shows that RTM has strong anti-interference ability and can be used for the accurate interpretation of radar profi le in a strong interference environment.

Weighted spectral correlation angle target detection method for land‑based hyperspectral imaging

In land-based spectral imaging,the spectra of ground objects are inevitably afected by the imaging conditions(weather conditions,atmospheric conditions,light conditions,zenith and azimuth angle conditions)and spatial distribution of targets,leading to uncertainties featured by“same object diferent spectrum”.That is,the spectrum of a ground object may change within a certain range under diferent imaging conditions.Traditional target detection(TD)methods are mainly based on similarity measurements and do not fully account for the spectral uncertainties.These detection methods are prone to false detections or missed detections.Therefore,reducing the impact of spectral uncertainties on TD is an important research topic in hyperspectral imaging.In this paper,we frst review traditional TD methods and compare their principles and characteristics.It is found that the spectral correlation angle(SCA)method has good adaptability in land-based imaging.The shortcoming of the SCA method that it cannot refect the local spectrum characteristics,is also analyzed.As the efect of spectral uncertainties cannot be completely overcome by the SCA method,a new similarity measurement method,the weighted spectral correlation angle(WSCA)method,is proposed.It can reduce the infuence of spectral uncertainties on TD by increasing the weight of particular bands.Finally,we use two sets of experiments to analyze the efect of the WSCA method on TD.Its performance in overcoming spectral uncertainties caused by variations in imaging conditions or uneven spatial distributions of targets is tested.The results show that the WSCA method can efectively reduce the infuence of spectral uncertainties and obtain a good detection result.

Least-squares reverse-time migration for reflectivity imaging

A least-squares reverse-time migration scheme is presented for reflectivity imaging. Based on an accurate reflection modeling formula, this scheme produces amplitude-preserved stacked reflectivity images with zero phase. Spatial preconditioning, weighting and the Barzilai-Borwein method are applied to speed up the convergence of the least-squares inversion. In addition, this scheme compensates the effect of ghost waves to broaden the bandwidth of the reflectivity images. Furthermore, roughness penalty constraint is used to regularize the inversion, which in turn stabilizes inversion and removes high-wavenumber artifacts and mitigates spatial aliasing. The examples of synthetic and field datasets demonstrate the scheme can generate zerophase reflectivity images with broader bandwidth, higher resolution, fewer artifacts and more reliable amplitudes than conventional reverse-time migration.

Reflection full waveform inversion

Because of the combination of optimization algorithms and full wave equations, full-waveform inversion(FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data.Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI.

High fidelity virtual try-on network via semantic adaptation and distributed componentization

Image-based virtual try-on systems have significant commercial value in online garment shopping.However,prior methods fail to appropriately handle details,so are defective in maintaining the original appearance of organizational items including arms,the neck,and in-shop garments.We propose a novel high fidelity virtual try-on network to generate realistic results.Specifically,a distributed pipeline is used for simultaneous generation of organizational items.First,the in-shop garment is warped using thin plate splines(TPS)to give a coarse shape reference,and then a corresponding target semantic map is generated,which can adaptively respond to the distribution of different items triggered by different garments.Second,organizational items are componentized separately using our novel semantic map-based image adjustment network(SMIAN)to avoid interference between body parts.Finally,all components are integrated to generatethe overall result by SMIAN.A priori dual-modalinformation is incorporated in the tail layers of SMIAN to improve the convergence rate of the network.Experiments demonstrate that the proposed method can retain better details of condition information than current methods.Our method achieves convincing quantitative and qualitative results on existing benchmark datasets.

Sub-molecular features of single proteins in solution resolved with scanning tunneling microscopy

Scanning tunneling microscopy (STM) can be used to image individual biological molecules, such as proteins, in vacuum or air. This requires sample dehydration and thus may not reflect the native state of the molecule. Extensive efforts have been made to image single proteins in solution using STM; however, the images have revealed only round or oval shapes with no sub-molecular details. Here, we present the sub-molecular features of streptavidin proteins under physiological conditions using a homebuilt low-leakage-current and highstability liquid phase STM. The N-lobe, C-lobe, and C-terminal tail of the epidermal growth factor receptor kinase domains were also resolved in solution. Our results demonstrate that the structure, morphology, and dynamics of a protein molecule can be examined under physiological conditions by the STM. [Figure not available: see fulltext.] © 2016, Tsinghua University Press and Springer-Verlag Berlin Heidelberg.