VSP Imaging Using Free-Surface Multiples With Wavefield Decomposition: Synthetic and Field Data Examples

Vertical seismic profiling (VSP) is an effective technique to provide high-resolution seismic images of the reservoir area. However, the quality of the images is limited by the poor illumination of primary reflection wave. In conventional VSP imaging, only the upgoing primaries are used. Adding free-surface–related multiples into the imaging process can significantly improve the coverage of the illuminated area. Conventional migration methods using multiples need the complex process of multiple prediction. Data-to-data migration (DDM) is an effective imaging technique for multiples in which the recorded data is migrated directly. To improve the imaging quality of DDM in VSP imaging, we propose separating the wavefield into downgoing and upgoing components using Hilbert transform when reverse-time migration (RTM) is implemented in DDM, and the inverse-scattering imaging condition is further applied to the decomposed wavefields. The proposed method eliminates low-frequency noises and false images generated from the conventional cross-correlation imaging condition, and further enhance the illumination in the VSP imaging. Synthetic examples and application to a walkaway field data demonstrate that it can attenuate the noise and improve the imaging resolution effectively. By using DDM with inverse scattering imaging condition and wavefield decomposition based on Hilbert transform, VSP imaging using free-surface–related multiples becomes a practical complement for conventional VSP imaging.

Crosscorrelation migration of microseismic source locations with hybrid imaging condition

Locating microseismic sources is critical to monitor the hydraulic fractures that occur during fluid extraction/injection in unconventional oil or gas exploration. Waveform-based seismic location methods can reliably and automatically image weak microseismic source locations without phase picking. Among them, the cross-correlation migration (CCM) method can avoid excitation time scanning by generating virtual gathers. We propose a CCM location method based on the hybrid imaging condition (HIC). There are four main steps in the implementation of this method: 1) selection of receivers with good azimuthal coverage; 2) generation of virtual gathers by correlating the reference receiver with the rest of the receivers; 3) summation of back-projections in the virtual gathers; and 4) multiplication of all summations. The CCM-HIC method was tested on synthetic and field datasets, and the results were compared with those obtained by conventional summation imaging condition (SIC) and multiplication imaging condition (MIC). The comparison results demonstrate that the CCM-HIC is sufficiently robust to obtain better stability and higher spatial resolution image of source location, despite the presence of strong noise.

The Pseudo-Laplace Filter for Vector-Based Elastic Reverse Time Migration

The scalar images (PP and PS) can be effectively obtained in vector-based elastic reverse time migration by applying dot product–based scalar imaging conditions to the separated vector wavefields. However, the PP image suffers from polarity reversal issues when opening angles are greater than 90∘ and backscattering artifacts when opening angles are close to 180∘. To address these issues, we propose the pseudo-Laplace filter for the dot product–based scalar imaging condition. Based on the analysis of the Laplace filter in the scalar image of vector-based wavefields, the second-order parallel-oriented partial derivatives of Cartesian components cross-correlation results are selected to construct the pseudo-Laplace filter. In contrast, second-order normal-oriented partial derivatives of the Cartesian component’s cross-correlation results are omitted. The theoretical analysis with the plane wave assumption shows that the proposed pseudo-Laplace filter can solve the problems of backscattering artifacts and polarity reversal in PP images by the scalar imaging condition. Due to additional polarity correction and backscattering attenuation, numerical examples show excellent performance in PP images with a pseudo-Laplace filter. Furthermore, the application of the pseudo-Laplace filter requires trivial additional computation or storage.

Domain Adaptive Ship Detection in Optical Remote Sensing Images

With the successful application of the convolutional neural network (CNN), significant progress has been made by CNN-based ship detection methods. However, they often face considerable difficulties when applied to a new domain where the imaging condition changes significantly. Although training with the two domains together can solve this problem to some extent, the large domain shift will lead to sub-optimal feature representations, and thus weaken the generalization ability on both domains. In this paper, a domain adaptive ship detection method is proposed to better detect ships between different domains. Specifically, the proposed method minimizes the domain discrepancies via both image-level adaption and instance-level adaption. In image-level adaption, we use multiple receptive field integration and channel domain attention to enhance the feature’s resistance to scale and environmental changes, respectively. Moreover, a novel boundary regression module is proposed in instance-level adaption to correct the localization deviation of the ship proposals caused by the domain shift. Compared with conventional regression approaches, the proposed boundary regression module is able to make more accurate predictions via the effective extreme point features. The two adaption components are implemented by learning the corresponding domain classifiers respectively in an adversarial training way, thereby obtaining a robust model suitable for both of the two domains. Experiments on both supervised and unsupervised domain adaption scenarios are conducted to verify the effectiveness of the proposed method.

ADDRESSING THE CROSSTALK ISSUE IN IMAGING USING SEISMIC MULTIPLE WAVEFIELDS

Surface-related multiple wavefields constitute redundant information in conventional migration and can often be difficult to attenuate. However, when used for migration, multiple wavefields can improve subsurface illumination. Unfortunately, the process of imaging using multiples involves the management of crosstalk, which largely restricts its application. Crosstalk causes phantom images formed by spurious correlation of unrelated events in a migration process. These events can be unrelated orders of multiples in the source and receiver wavefields; they can also be one event associated with a reflector in the source wavefield and another event generated by a different reflector in the receiver wavefield. In this paper, we first examine crosstalk by explicitly investigating its generation mechanisms in a migration process and classifying it into different categories based on causality. Following this analysis, crosstalk can be predicted in a migration process and subtracted in the image domain; however, this method is usually difficult to apply due to the complexity of wavefield separation and adaptive subtraction. Furthermore, we present different algorithms to attenuate the crosstalk, including a deconvolution imaging condition, a least-squares migration (LSM) method, and an advanced algorithm combining LSM with a deconvolution imaging condition. We illustrate these different strategies on synthetic examples. A deconvolution imaging condition can attenuate some crosstalk, but it is less effective at suppressing strong coherent crosstalk events. However, the LSM method can fundamentally address the crosstalk issue, and this approach is further optimized when combined with a deconvolution imaging condition.

Polarity-reversal correction for vector-based elastic reverse time migration

Polarity reversal is a well-known problem in elastic reverse time migration, and it is closely related to the imaging conditions. The dot product of source and receiver wavefields is a stable and efficient way to construct scalar imaging conditions for decomposed elastic vector wavefields. However, for PP images, the dot product introduces an angle-dependent factor that will change the polarity of image amplitudes at large opening angles, and it is also contaminated by low-wavenumber artifacts when sharp contrasts exist in the velocity model. Those two problems can be suppressed by muting the reflections with large opening angles at the expense of losing useful information. We have developed an elastic inverse-scattering imaging condition that can retain the initial polarity of the image amplitude and significantly reduce the low-wavenumber noise. For PS images, much attention is paid to the polarity-reversal problem at the normal incidence, and the dot-product-based imaging condition successfully avoids this kind of polarity reversal. There is another polarity-reversal problem arising from the sign change of the PS reflection coefficient at the Brewster angle. However, this sign change is often neglected in the construction of a stacked PS image, which will lead to reversed or distorted phases after stacking. We suggested using the S-wave impedance kernel used in elastic full-waveform inversion but only in the PS mode as an alternative to the dot-product imaging condition to alleviate this kind of polarity-reversal problem. In addition to dot-product-based imaging conditions, we analytically compare divergence- and curl-based imaging conditions and the elastic energy norm-based imaging condition with the presented imaging conditions to identify their advantages and weaknesses. Two numerical examples on a two-layer model and the SEAM 2D model are used to illustrate the effectiveness and advantages of the presented imaging conditions in suppressing low-wavenumber noise and correcting the polarity-reversal problem.