The Erlian basin is one of the most important basins in northern China to host sandstone-type uranium deposits (SUDs), in which Bayanwula, Saihangaobi, and Hadatu are under development, to name a few. Issues such as the metallogenic mechanism and mineralization of these deposits need to be addressed throughout the mining process. Over the past several decades, 2D and 3D seismic reflection surveys have been carried out to study these typical SUDs. The seismic technique has become the most effective geophysical tool of uranium (U) exploration, and it is used to develop our understanding of the stratigraphic configuration, faults, and sandstone contents of target layers in uranium environments. In addition, seismic interpretation could yield useful suggestions regarding the subsequent drilling program in the work area. There are two seismically predictable patterns of SUDs, named “Big depression + fault” and “Large-angle unconformity + fault”, which have been established following detailed seismic research in this basin. The characteristics of these faults are as follows: (1) the “‘U’-shaped formation” is conducive to the inflow of O-U-bearing groundwater into the target sandstone; (2) the “Big depression of reductive formation” provides plenty of organic matter (containing reducing media and U pre-enrichment) to promote redox reaction mineralization; (3) “Large-angle unconformity” is favorable to the migration of reducing substances, consequently leading to an enhancement in redox U mineralization; (4) “faults with long-term activity” become rising channels for reducing the presence of fluids and gases at depth; and (5) “sandstone and its scrambled seismic facies”. The results also offer indirect evidence of a connection between hydrothermal fluids and U mineralization; a hypothesis of “hydrothermal effusion” mineralization is proposed accordingly. In conclusion, seismically produced images of geological structures and sandstone distribution could yield important information for U prospecting and mine planning; it is worth considering seismic technologies in the future exploration of SUDs.

In surface active seismic exploration, the near-surface imaging based on reflection signals provides valuable information for mineral exploration and deeper resources. However, the strong noises at near surface and stretching effects at nonzero offsets with conventional seismic data processing method severely damage the seismic reflection signals with low fold at near surface. The innovative method for the enhancement of seismic signals is the seismic interferometry method. However, due to the one-sided illumination, the seismic interferometry is still not suitable for the retrieval of reflection signals in most practical situations. In this article, we present the correlation-based interferometry (CI) method to enhance the reflection signals for near-surface imaging using the first cross correlation to construct virtual reflection signals and the second cross correlation to achieve the interferometric normal move-out (INMO) correction of the seismic reflection events with no stretching, which keeps the high resolution of near-surface reflection signals. Meanwhile, because of constructive interference stack, the CI method can significantly improve the signal-to-noise ratio (SNR) of reflection signals. The synthetic and field seismic data examples illustrate that the data-driven CI method performs better than the conventional stack (CS) method based on the velocity model for the near-surface reflection imaging.

In conventional land seismic exploration, shallow seismic reflections with low fold are usually contaminated by noise and most conventional acquisition geometries struggle to produce sufficient near-offset fold to process shallow seismic reflections based on the velocity model. Deep seismic reflections tend to occur as weak events due to seismic wave absorption and attenuation. To enhance the shallow and deep seismic reflections, we have developed a data-driven reflection imaging method based on seismic interferometry of cross-coherence type, which first retrieves coherent reflections by cross-coherence of full wavefields with zero-offset reflections and then achieves imaging results with high quality by summing all of the crosscorrelations of full wavefields with coherent reflections in a common-midpoint gather. The novel purely data-driven method does not require any velocity information and can flatten noisy interfering reflection events with no waveform distortions. The focusing effects, which represent the stack of all the seismic reflection events, increase the fold of weak seismic reflections and further significantly improve the signal-to-noise ratio of imaging results. In comparison with data-driven reflection imaging methods based on seismic interferometry of crosscorrelation type, our results illustrate that the data-driven reflection imaging method based on seismic interferometry of cross-coherence type can automatically compress the band-limited source signature and make full use of background noise to broaden the bandwidth of reflection signals for achieving imaging results with a higher resolution.

Normal moveout (NMO) correction is an important step in seismic data processing. Conventional NMO methods, however, suffer from serious stretching distortions, especially at the shallow layer and far-offset traces. These distortions are not conducive to subsequent data processing at all. Reflection seismic interferometry, the cores of which are cross-correlation and stacking, is the latest technology to achieve noise suppression and signal enhancement. Compared with cross-correlation, higher-order cumulants (HOC) has better performance of time delay estimation and signal enhancement. To fully exploit its advantages, we propose reflection seismic interferometry based on HOC instead of cross-correlation to solve NMO stretching in this letter. Our proposed method is first tested on synthetic example and then applied to field data from eastern China. The corresponding results demonstrate that the proposed data-driven method, without the need of velocity information, not only solves the far-offset traces’ stretching distortions of NMO correction, but also has a better noise suppression effect compared with other two existing methods. These advancements are important to improve the resolution of seismic data and increase the amplitude fidelity.

Reverse time migration (RTM) can provide high-quality seismic images and is one of the most advanced migration methods. Imaging condition method is a crucial component in RTM. Different imaging conditions show different abilities to obtain image amplitude, physical validity, and resolution. The cross-correlation imaging condition can achieve high imaging accuracy for complex structures. Nevertheless, this approach necessitates the storage of almost the entire source wavefields, which demands a substantial amount of storage space and consequently reduces the computational efficiency of reverse time migration. In contrast, the excitation amplitude imaging condition, which relies solely on wavefield information at the imaging time, eliminates the necessity for extensive storage, thereby enhancing the computational efficiency of reverse time migration. However, conventional methods determine the imaging time by identifying the maximum amplitude of the source wavefield at each grid point. In scenarios involving large offsets or strong reflection interfaces, this approach can lead to inaccuracies in determining the imaging time. In this paper, we utilize an advanced adaptive finite-difference operator method to solve the eikonal equation for determining imaging time. This approach markedly enhances the accuracy of first-arrival traveltimes calculations at near offsets, which is especially critical for seismic imaging. Numerical examples from simple model, the Marmousi model, and field seismic data demonstrate the effectiveness of our proposed method.