Marchenko imaging can effectively suppress migration artifacts associated with internal multiples while preserving amplitude fidelity. However, most existing Marchenko imaging studies are conducted under the assumption of isotropic media. Neglecting the anisotropic characteristics of real media can lead to inaccurate phase estimation of the initial focusing function, thereby reducing the accuracy of the reconstructed Green’s functions and the final imaging results. To address this issue, this paper proposes a Marchenko imaging method tailored for tilted transversely isotropic (TTI) media. First, the initial focusing function from a subsurface imaging point to the surface is estimated using the pseudo-acoustic first-order velocity-stress equations in TTI media. The preprocessed shot records, together with the estimated initial focusing function, are then used as input to reconstruct Green’s functions by solving Marchenko equation. Next, the reconstructed up- and down-going Green’s functions are incorporated into an energy-compensated cross-correlation imaging condition to generate the imaging results. This procedure is repeated to achieve Green’s function reconstruction and imaging for all imaging points within the subsurface target region. Synthetic model experiments demonstrate that the proposed method enables accurate reconstruction of Green’s function in TTI media and produces clear imaging results with a high signal-to-noise ratio.

When seismic waves propagate through the highly heterogeneous shallow layers, multiple orders of scattering waves will be developed along the wave paths, leading to a very complex wave pattern on the reflection data received by the geophones on the surface. The scattered noise exhibits a non-uniform pattern on the shot gathers from the near to far offset over recording time. The frequency content of the scattered waves typically span over the entire frequency band, greatly compromising the quality of seismic data. In desert regions, the serious heterogeneity of near surface sand layers contributes great much to the severity of the scattering noise, posing substantial challenges to the processing and imaging of seismic data. In this paper, Marchenko's method is employed to reconstruct the seismic source and detector positions underneath the heterogeneous geological formations, effectively mitigating the impact of scattered noise to the final image. Numerical experiments demonstrate successful seismic wave redatuming beneath the scattering layers, leading to scattering noise suppressed shot data on the redatum surface. The noise suppressed data hence result in a much cleaner final migration image.

Target-oriented least squares reverse time migration (TO-LSRTM) is a method designed for imaging below the complex overburden. It achieves this by bypassing the overburden and focusing wavefields over the region of interest. The critical aspect of this process lies in obtaining Marchenko double-focusing redatumed data. However, traditional Marchenko redatuming methods neglect the impact of anisotropy, leading to distortions in the travel times and amplitudes of redatumed data, thus affecting imaging accuracy. To overcome this problem, we develop a target-oriented vertical transverse isotropic least-squares reverse time migration (TO-VTI-LSRTM) method. This method uses the direct wave from the subsurface virtual source point obtained by the first-order VTI pseudo-acoustic equation as the initial condition to solve the Marchenko equation, so as to correct the velocity anisotropy in the process of redatuming, and the redatumed data is used as the virtual observed data for inversing the reflection coefficients of the subsurface local region. Numerical experiments validate the capabilities and advantages of the proposed method. Imaging results demonstrate that this approach effectively eliminates imaging artifacts caused by anisotropy and overburden internal multiple reflections, resulting in high-quality imaging results.

Marchenko imaging has the particular ability to generate the subsurface image free of spurious artifacts related to internal multiples. However, conventional Marchenko imaging (C-MI) is performed based on the assumption that the sources and receivers of the recorded seismic data are placed on a flat surface, which is restrictive and hard to satisfy in mountainous areas with rugged topography. The elevation-static correction (or time shift) is a usual solution to ensure this assumption holds. But it only works well if the surface consistency is satisfied. To alleviate the limitations of C-MI in processing seismic data acquired from mountainous areas with rugged topography, we present a technique for conducting Marchenko imaging from a floating datum. The proposed Topography-Marchenko imaging (T-MI) is achieved by estimating an initial down-going focusing function between a floating datum and a focal point in the subsurface. In this work, we use seismic data corrected to a floating datum rather than a final datum as input to the iterative Marchenko scheme to retrieve Green’s functions. The retrieved Marchenko Green’s functions are further used to generate the subsurface image. The T-MI method can effectively avoid imaging distortions caused by the elevation-static correction. The proposed T-MI method is validated through applications to a synthetic model with rugged topography and a land dataset acquired from a mountainous area in Northwest Sichuan, China.

The Marchenko method has received significant attention in geophysics due to its specific ability to retrieve the accurate Green's functions directly from data without a subsurface focal point to have an actual physical receiver located at it. However, its application capacity in anisotropic medium remains unexplored. Given the increasing complexity of exploration tasks, it has become imperative to investigate its feasibility of deploying the Marchenko method in anisotropic media. This study aims to assess the applicability of the Marchenko method in retrieving Green's functions in anisotropic medium with a synthetic dataset simulated over a tilted transversely isotropic (TTI) model. The Green's functions are retrieved based on the assumptions that the data are acquired from either an isotropic or TTI medium model. A comparison analysis reveals that the first arrivals obtained based on the TTI medium assumption provides more accurate travel times and amplitudes, resulting in a more accurate reconstruction of the Green's function. The study demonstrates that Marchenko method can be effectively applied in anisotropic medium.

Least-squares reverse time migration (LSRTM) is a migration method for retrieving subsurface reflectivity using linear inversion theory. Compared to traditional imaging methods, LSRTM offers higher resolution and amplitude preservation. However, the computational cost of LSRTM in the data-domain is high and inevitably leads to the creation of imaging artifacts due to internal multiples. In this study, we propose a target-oriented data-domain LSRTM based on the first-order velocity-stress equation and the Marchenko equation. By two steps of source redatuming and receiver redatuming, this method extrapolates the wavefield from the acquisition surface to beneath the complex overburden, eliminating the impact of multiple scattering within the overburden and achieving target-oriented imaging. Numerical result shows that this method effectively mitigates imaging artifacts caused by internal multiples within the overburden, thus enhancing imaging quality.

The least-squares reverse time migration (LSRTM) can obtain high resolution and true amplitude imaging results. However, LSRTM for full model domain data requires simulation throughout the entire model space, resulting in significant computational costs. In addition, the Born approximation, which is based on single scattering theory, can cause imaging artifacts by treating multiple reflections from the overburden as primary reflections. To address these issues, the Marchenko redatuming method can be used to separate the influence of the overburden. However, due to factors such as acquisition aperture, phase and amplitude errors can occur in far offset Marchenko redatumed data. Therefore, a prestack correlative LSRTM method based on Marchenko redatumed data is proposed for target-oriented imaging, which includes two key points. First, the method aims to reconstruct the data recorded from the surface onto the target datum using the Marchenko redatuming theory to obtain the response without the influence of overburden. Second, by constructing the prestack normalized zero-lag cross-correlation error function, the optimal reflection coefficient model is found for each shot's record, and the final imaging result is generated by stacking the optimal reflection coefficient model of all redatumed data, thereby alleviating the problem of the incoherent stacking at far offset in redatumed data, which reduces the imaging quality. Numerical examples demonstrate that the proposed method has higher computational efficiency and can provide imaging results with fewer artifacts.

Geological modeling is an important method to characterize subsurface structures and describe subsurface oil and gas reservoirs and their connectivity. In the case of stratified reservoirs such as clastic rocks, the existing geological modeling techniques have been able to meet the needs of exploration and development. The marine carbonate rocks in the Tarim Basin are characterized by deep geological age and complex geological structure. The traditional modeling method assumes that the geological variables have good regional continuity, while for carbonate Karst reservoirs, because of the strike-slip fault system effect, the spatial distribution of the cavity reservoirs is complex and non-homogeneous. Due to the cavity nature of carbonate reservoirs, the conventional geo-modeling is difficult to be used in carbonate reservoir modeling. The objective of this work is to build a geo-model by using a Bayesian approach based on a cavity benchmark model and compare with the properties from the model and evaluate its accuracy. Although cavities are usually easy to identify by finding the strong amplitude of the 'beam string' reflections. Using the seismic impedance inversion data to characterization, the cavities, the boundary and petrophysical property of the cavities can be better described compared to the seismic amplitude attribute such as RMS amplitude. Using gradient structure tensor and tensor vote processing, the fractured zone and faults are recognized. By merging the cavities, faults and fractured zone, we obtained a structure facies volume as the controlling of the Bayesian geo-modeling. The porosity model is built using the facies controlled well-seismic joint Bayesian geo-modeling method. Furthermore, compared with the benchmark porosity model and the result of traditional sequential Gaussian simulation method, we discuss the accuracy and advantages of Bayesian method that includes facies control and strong seismic constraints.

PreviousNext No AccessSEG Integration of Geophysics, Geology, and Engineering Workshop, Chengdu, China, 26–28 June 2023Characterization for the carbonate-karst reservoir based on target-oriented full-waveform inversionAuthors: Kai LiXuri HuangYezheng HuJing TangWen XiaoKai LiSouthwest Petroleum UniversitySearch for more papers by this author, Xuri HuangSouthwest Petroleum UniversitySearch for more papers by this author, Yezheng HuSouthwest Petroleum UniversitySearch for more papers by this author, Jing TangSouthwest Petroleum UniversitySearch for more papers by this author, and Wen XiaoInstitute of Tarim Oilfield CompanySearch for more papers by this authorhttps://doi.org/10.1190/igge2023-07.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InReddit Abstract Carbonate karst reservoirs have been a challenge in the hydrocarbon exploration and production industry. The anomalously high-amplitude bright spot on seismic migration sections, which is also called the string of beads response or strong beadlike-reflection (SBR), is the common feature of the oil-bearing or gas-bearing reservoirs in Ordovician carbonate. Although the SBRs have their unique characteristics, it is difficult to discriminate the range of karst reservoirs in detail from seismic migration sections due to the interference between multiple diffractions from the boundaries of caves. Here we present a target-oriented full-waveform inversion method to differentiate karst cavities from the surrounding areas. With the proposed method, the surface recorded shot data are first redatummed using the Marchenko method to a depth level immediately above the target area with very limited knowledge of the overburden medium. Then, the shot profile data for the local model of the target area is computed and used with the redatummed shot records to construct the inversion misfit function. The full-waveform inversion in frequency domain is used to obtain the velocity in the target area. The synthetic data test demonstrates that the obtained model can well describe the karst reservoir morphology. Keywords: full-waveform inversion, carbonate, inversionPermalink: https://doi.org/10.1190/igge2023-07.1FiguresReferencesRelatedDetails SEG Integration of Geophysics, Geology, and Engineering Workshop, Chengdu, China, 26–28 June 2023ISSN (online):2159-6832Copyright: 2023 Pages: 142 publication data© 2023 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 22 Aug 2023 CITATION INFORMATION Kai Li, Xuri Huang, Yezheng Hu, Jing Tang, and Wen Xiao, (2023), "Characterization for the carbonate-karst reservoir based on target-oriented full-waveform inversion," SEG Global Meeting Abstracts : 24-27. https://doi.org/10.1190/igge2023-07.1 Plain-Language Summary Keywordsfull-waveform inversioncarbonateinversionPDF DownloadLoading ...

在油气勘探解释工作中,井震标定是一个关键步骤,在VSP资料没有覆盖的区域,通常需要人工将测井合成记录与井旁道地震信号联系起来,这个过程可能非常耗时,而且在某些情况下是不准确的.而动态时间规整(DTW)是一种衡量两个时间序列之间相似度的方法,该方法可以减少人工拉伸或压缩的误差,实现井震资料的自动匹配,利用动态时间规整方法得到的各点漂移时间进行时深关系和地震层速度反演.但无约束情况下的井震标定并不准确,本文提出了在地质层约束下动态时间规整进行标定,更新时深关系并根据时深曲线趋势延伸到钻前,从而得到更新后的速度信息和钻前的速度信息.将该方法进行理论测试,更新后的速度信息能够满足在误差范围以内,为后续的三维速度场空间插值建模提供准确的速度信息.

The Marchenko method can retrieve Green’s functions between virtual sources in the subsurface and receivers at the surface from single-sided reflection data. This process, called Marchenko redatuming, allows the estimation of the full-wavefield information in the inhomogeneous subsurface. The retrieved Green’s functions form the input for creating the subsurface image free of artifacts caused by internal multiples. However, when using the cross-correlation imaging condition in Marchenko imaging, the shallower regions of the obtained image suffer from reduced resolution due to unwanted interference, which occurs in the cross-correlation gathers at far offsets. With a simple model, we find that the image resolution obtained using the cross-correlation Marchenko imaging (CCMI) method is influenced by both image position and the integral range of the cross-correlation function. To improve the image resolution of the CCMI method, we propose an optimal aperture-bounded cross-correlation Marchenko imaging (OA-CCMI) method. The optimal aperture is defined as an intercept at which the time difference between the first arrivals of up- and down-going Green’s functions equals one wavelet period. The integration of the cross-correlation function is then performed over the determined optimal range that varies with the image position rather than a fixed aperture. As a result, we exclude the unwanted destructive interference from the cross-correlation gather, resulting in a high-resolution image. The effectiveness of the proposed method has been validated with its applications to synthetic and field data tests.

Traffic noise is an important type of passive seismic data because it usually includes strong dispersive surface wave components and can be easily accessed. It can be used to extract virtual surface waves via seismic interferometry algorithms for the purpose of imaging subsurface shear wave velocity distribution. In this paper, we propose a scheme to improve the retrieval of surface waves from traffic noise recorded using linear arrays along traffic roads. By deconvolving the decomposed traffic noise wavefield, robust surface wave traces can be computed from a short noise record. First the far‐field component of the traffic noise recording is extracted and separated into unidirectionally propagating components. Then deconvolution interferometry is applied to these separated far‐field wavefield to extract surface wave Green's function. With this scheme, crosstalk noise and near‐field artifacts are excluded from the computation, and surface wave traces with high signal‐to‐noise ratio (SNR) are achieved using short traffic noise traces. In a synthetic test virtual surface waves estimated with the proposed method show significantly higher SNR than those computed with the conventional interferometry workflows, and matches well with simulated active source traces. A field data example with traffic noise recorded in a distributed acoustic sensing experiment also shows that surface waves estimated using the proposed methodology demonstrate higher SNR than those computed with the conventional interferometry schemes and that the virtual surface waves generated using 4 s of traffic noise demonstrate signal quality comparable to the surface waves recorded in this experiment with an active source.

Local full-waveform inversion (FWI) methods use redatumed seismic responses of virtual receivers within the subsurface to build the local objective function based on the convolution-type representation theorem. The Marchenko method is widely used to obtain the redatumed data. The method only requires a smoothed velocity model with correct kinematic characteristics of seismic responses for redatuming of the single-sided reflection data. However, the standard Marchenko method is insensitive to lateral propagation of the wavefield. By injecting the standard Marchenko redatumed wavefield along the boundary of the target, the local wavefield propagation modeling produces errors, which affects the accuracy of the local FWI. In this paper, a method to obtain more accurate Green’s functions is proposed by incorporating vertical seismic profile data (VSP) into the calculation process of the Marchenko source-receiver redatuming. This method allows one to obtain the accurate laterally propagating waveform, resulting in a significant improvement of lateral resolution. The proposed method is applied to a benchmark model dataset and compared with the local FWI based on standard Marchenko redatuming.

The inadequate resolution of cavity karst reservoir characterization is a key factor affecting the hydrocarbon production efficiency of ultradeep marine carbonates. Full waveform inversion (FWI) using high-frequency seismic data can provide a higher resolution than conventional methods. However, computational efficiency limits its application. This letter proposed a target-oriented local FWI method for cavity karst reservoir characterization. Based on the wavefield injection and Marchenko redatuming methods, a local wavefield forward modeling operator is derived. It can obtain the local wavefield corresponding to the physical source at the surface. Based on this local wavefield reconstruction, an objective function of the local FWI is established. To enhance the reservoir boundaries in the inversion results, a stabilizing strategy that combines total variation (TV) and minimum support (MS) regularization is proposed. A synthetic data test demonstrates that the obtained model can well describe the cavity karst reservoir structures.

The Marchenko method can retrieve Green’s functions among virtual sources in the subsurface and receivers at the surface from single-sided reflection data. This process, called Marchenko redatuming, allows the estimation of the full-wavefield information in the inhomogeneous subsurface. The retrieved Green’s functions form the input for creating the subsurface image free of artifacts caused by internal multiples. However, when using the crosscorrelation imaging condition in Marchenko imaging, the shallower regions of the obtained image suffer from reduced resolution due to unwanted interference, which occurs in the crosscorrelation gathers at far offsets. With a simple model, we have found that the image resolution obtained using the crosscorrelation Marchenko imaging (CCMI) method is influenced by image position and the integral range of the crosscorrelation function. To overcome this problem, we develop an optimal aperture-bounded crosscorrelation imaging condition using only the constructive wavefields during integration. The optimal aperture is defined as an intercept at which the time difference between the first arrivals of up- and downgoing Green’s functions equals one wavelet period. The integration of the crosscorrelation function is then performed over the determined optimal range that varies with the image position rather than a fixed aperture. As a result, we exclude the unwanted destructive interference from the crosscorrelation gather, resulting in a high-resolution image. The effectiveness of our method has been validated with its applications to synthetic and field data tests.

Marchenko imaging is a novel technique to create subsurface images which are free of spurious artifacts related to internal multiples. The foundation of Marchenko imaging is applying a specific imaging condition to the retrieved Green’s functions. Crosscorrelation imaging condition is commonly used since holding advantages of straightforward implementations and stable performance, especially in field data applications. However, the image quality from crosscorrelation imaging condition is closely related to migration aperture, which specifies the spatial integration range involved in the crosscorrelation function. By investigating the impact of the migration aperture on crosscorrelation-based Marchenko imaging, we find that a large migration aperture will result in an image with low resolution and uneven energy distribution. To address this problem, we adopt an optimal aperture crosscorrelation Marchenko imaging (OAC-MI) method which imposes a constraint on spatial range of the integration. Synthetic tests demonstrate that the proposed approach improves the image resolution while keeps the energy distributed more evenly.

随着地震波成像技术的发展,利用全波形反演得到的结果比传统方法更加准确.频率域全波形反演利用全波场的振幅、频率等信息,用较少的频率就能还原出精度很高的速度模型.本次实验中正演采用的是有限单元法,反演利用的是高斯-牛顿共轭梯度法,研究了模型中含有异常体以及Marmousi模型下的二维声波频率域全波形反演的记过,以及存在的边界条件问题、反演算法效率问题和初始模型和频率组合的选取问题.

本文提出基于精确Zoeppritz方程的叠前三参数反演,推导了精确解的反射系数偏导,从而构建用于反演的雅可比矩阵;比较了精确Zoeppritz方程和Aki-Richards近似方程的反演精度和稳定性,建立了基于广义线性反演的叠前反演方法.