We have applied multiscale deformable-layer tomography (DLT) to build a laterally varying velocity model, using a single-offset vertical seismic profile (VSP) data set acquired for a salt proximity survey in southern Texas. The purpose of the VSP survey is to delineate the 2D salt flank using the P-wave reflections. Previous study has identified an anhydrate layer as the cap rock of the salt dome. The large impedance contrasts of this anhydrite layer generate strong downgoing P (sediment)-S (anhydrite)-P (salt) waves recorded by downhole geophones. Incidentally, the P-S-P-waves have traveltimes similar to those of the P-wave salt flank reflections, thus contaminating the imaging of the salt flank. Identifying shear-mode contamination requires an accurate velocity model of anhydrite. However, the extremely poor coverage of the single-offset VSP greatly challenges tomographic techniques to determine the lateral velocity variation. We tackle this problem using multiscale DLT, which characterizes the velocity field by a set of deformable layers. We constrain the layer velocities using the check-shot data and invert for the geometric variation. The inverted model indicates that the anhydrite layer has a “thick-thin-thick” lateral variation with offset, and the S-wave in the anhydrite layer helps in imaging the P-S-P-waves along the well track. The estimated anhydrite layer geometry is validated by the kinematic accuracies of P-waves in the data domain and P-S-P-waves in the image domain. Some in-salt dipping structures are determined by multiscale DLT as well. This field data example indicates that multiscale DLT is feasible for estimating velocities using VSP data of the single-offset situation. An accurate velocity model is the key for modeling and adaptive subtraction of the shear-mode contamination related to the salt geometry.

Fractured basements are not only potential reservoirs for hydrocarbon resources, but they also provide significant storage space for carbon dioxide (CO2) sequestration and radioactive waste disposal. However, fractured basements are challenging for seismic imaging methods due to the complexities in their fault and fracture networks, strong heterogeneity, highly variable structural dip, and strong impedance contrasts between the basement rocks and the surrounding sediments. We present a field case in which a walkaway vertical seismic profiling (VSP) survey was conducted at a fractured basement play located in the Bohai Bay Basin, China, to improve the resolution compared with a preexisting surface seismic profile. Using the advanced random-space-shift (RSS) reverse time migration (RTM), we obtain a high-resolution image with a clear delineation of the highly faulted dipping basement. From numerical and field examples, we find that the application of the RSS-RTM improves the final image by mitigating unavoidable errors in the migration velocity model, which would otherwise result in an unfocused image using the conventional RTM approach. In addition, we determine the importance of proper wavefield separation using 3C recordings, which is the key to ensuring the quality of the final image. With an optimized VSP imaging workflow, we provide an enhanced image for the fractured basement to support the geologic interpretations and development decisions.

Seismic migrations are generally formulated as the adjoint operators of linear forward modeling and often lead to images with degraded resolution, unbalanced illumination and migration artifacts, especially in surveys with geologic complexity and irregular acquisition geometry. Least-squares migration (LSM) is able to mitigate these problems and produce better resolved images that are suitable for subsequent AVO/AVA inversion. However, no matter what domain LSM is implemented in, the computational cost is still several times or even one order of magnitude more than that of traditional migration. In this paper, we present an efficient image-domain least-square Kirchhoff depth migration (LSKDM), in which the Hessian matrix is approximated by a grid of point-spread-functions (PSFs). Traditional PSF computing algorithm requires a non-negligible cost caused by a successive operation of modeling and migration, and has to satisfy a sampling restriction to avoid interference between nearby PSFs. We present in this paper that, by using the ray-based Green’s functions and the linear traveltime approximation, the PSFs can be constructed explicitly at a significantly reduced computational cost and is able to adapt flexible spatial sampling that is fine enough to detect small-scale illumination variation. With the constructed PSFs, we formulate an image-domain LSKDM to iteratively solve for the optimal reflectivities. Numerical tests on synthetic and field data examples demonstrate that the proposed LSKDM is highly efficient and is capable of producing images with enhanced spatial resolution and amplitude fidelity when compared with the Kirchhoff depth migration (KDM) image.

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.

The pre-/sub-salt fractured networks provide key clues to understanding the tectonic history and the subsurface reservoir evolution. Yet, they are among the most complicated targets for geophysical investigations. We develop a structure-oriented mapping technique to delineate the high-resolution dipping layers across the borehole region using the zero-offset vertical-seismic-profiling (ZVSP) survey, which is conventionally used to provide one-dimensional (1-D) wave propagation information. The key information for the single-shot VSP mapping, which is the structural dip across the borehole, is unreliable from the poor sub-salt surface seismic image. Alternatively, we obtain the structural dips via reflection layer tomography. Taking advantage of the accurate interval velocities and the high-fidelity identifications from the reflection events, we manage to invert for the geometry of the main reflectors identified across the wellbore. Based on such information, we propose an effective processing strategy and achieve a high-resolution image of the dipping structures around the borehole region from the ZVSP. The current result compares reasonably well with the corresponding surface seismic profile but supplies higher-resolution details of the dipping structures and fault networks below the thick evaporite caprock where the surface seismic image degrades sharply. The enhanced subsurface image encourages better structural evaluation, geologic interpretation, and future 2-D/3-D VSP survey design.

In complex near-surface geologic settings, first-arrival traveltime tomography suffers from strong data noise and uneven raypath coverage. To reduce the inversion non-uniqueness, model smoothing is necessary but often without incorporating structural constraints based on seismic images. The reasons include lack of shallow reflections, strong noise, and gradient velocity field with strong lateral variation. We propose to estimate the near-surface structural trend from the velocity solution of deformable-layer tomography (DLT), that inverts for velocity contours directly. Then the structural dips derived from the DLT solution are taken as the structural regularization in the subsequent traveltime tomographic inversion. Tests for the 2011 SAGEEP workshop model illustrate that this DLT-guided structural regularization steers the tomographic inversion toward more accurate near-surface models. The application of the DLT-guided structural regularization to a field data reveals the near-surface geology of a beach area in Qingdao, China. The DLT solution could complement seismic images or other structural information in regularizing tomographic inversion.