To improve the imaging quality of wide-azimuth seismic data and enhance the uniformity of the attributes between adjacent bins, we developed a novel interpolation method in the offset-vector tiles (OVT) domain for wide-azimuth data. The orthogonal matching pursuit (OMP) interpolation method based on the Fourier transform is a frequency-domain processing technique based on discrete Fourier interpolation that achieves the goal of anti-aliasing by extracting the weight factor in the effective band from low-frequency data without aliasing. For data reconstruction, the OMP-based data interpolation technique in the OVT domain comprehensively uses the seismic data in five dimensions: the vertical and horizontal coordinates, time, offset and azimuth. Compared with conventional three-dimensional data interpolation, five-dimensional interpolation in the OVT domain is more accurate and achieves better results in practical applications.

Seismic petrophysics is an important link between seismic elastic properties and reservoir physical properties. Based on the petrological and microstructure characteristics of shale in the Qingshankou formation of Sanzhao sag in the north of Songliao Basin, this paper presents an anisotropy petrophysical model with complex pore structure suitable for organic shale constructed with the use of the Voigt-Reuss-Hill average model, an anisotropy self-consistent approximation+differential effective medium model, and the layering of clay and kerogen is simulated by using the Voigt-Reuss-Hill average and bond transform to achieve the simulation of shale anisotropy. Based on the proposed model, the effects of the organic volume fraction, porosity, and pore aspect ratio on rock elastic properties are discussed. The result shows that with the increase of matrix porosity, all elastic parameters show a decreasing trend; with the increase of the organic volume fraction, except shear modulus, other elastic parameters show an increasing trend. Through comparative analysis, the elastic parameters (Lamé impedance and Shear impedance) sensitive to the organic volume fraction and porosity are optimized; the seismic petrophysical cross-plot template with core calibration is constructed. The application shows that the predicted S-wave velocity based on the proposed model is in good agreement with the S-wave velocity derived from dipole source logging. Combined with the high-precision prestack elastic parameter inversion, the “sweet spot” characteristics can be well described, and the research could contribute to a better “sweet spot” description and provide a better support for shale exploration in Sanzhao sag.

The shale oil reservoir in the Lucaogou Formation in the Jimsar Sag, Junggar Basin has a complex lithology, complex pore structure, and strong heterogeneity. Conventional logging reservoir evaluation methods have difficulty accurately evaluating the lithology, physical properties, electrical properties, oil-bearing properties, source rock characteristics, brittleness, and horizontal in-situ stress. Starting from the logging response characteristics of complex lithologies, a multilevel, multi-logging parameter combination shale oil logging evaluation is proposed, and an evaluation model of the “seven properties” of shale oil reservoirs is established. This model is used to interpret the data in the study area and achieves good results, effectively solving the “three types of quality” evaluation problems of shale oil source rock quality, reservoir quality and engineering quality. Based on the comprehensive evaluation of the seven properties of logging, it is proposed that the lithology of the Lucaogou Formation shale oil determines the physical properties, brittleness, source rock properties, rock mechanical properties, contact relationships with the reservoir and physical property controls on the oil-bearing property; the “sweet spot” of shale oil in the Lucaogou Formation is clarified, providing effective support for the development of shale oil in the Jimsar Depression.

For seismic wave propagation in media with horizontal transverse isotropy (HTI), kinematic and dynamic attributes are anisotropic. P waves propagate slower in perpendicular to fracture azimuth than parallel to it, whereas reflection strength and frequency vary with azimuth. The azimuthal effects on reflection coefficients and seismic wave velocities in an HTI medium are quantitatively analyzed. The resulting theory-based and real-world azimuth gathers demonstrate the anisotropic nature of such media. The fitting of the ellipse is used to quantitatively predict the direction and strength of anisotropy in the study area, which is consistent with that obtained by the S-wave splitting prediction method. In wide-azimuth data processing, measures are taken to eliminate the influence of azimuthal anisotropy, and the coherent spectrum pickup method is used to accurately calculate the azimuthal velocity of underground HTI media and perform azimuthal anisotropy correction processing, which eliminates the time difference between fast and slow wave caused by azimuthal anisotropy. The achieved results provide support for subsequent high-resolution imaging.

The accurate identification of seismic faults, which serve as crucial fluid migration pathways in hydrocarbon reservoirs, is of paramount importance for reservoir characterization. Traditional interpretation is inefficient. It also struggles with complex geometries, failing to meet the current exploration demands. Deep learning boosts fault identification significantly but struggles with edge accuracy and noise robustness. To overcome these limitations, this research introduces SwiftSeis-AWNet, a novel lightweight and high-precision network. The network is based on an optimized MedNeXt architecture for better fault edge detection. To address the noise from simple feature fusion, a Semantics and Detail Infusion (SDI) module is integrated. Since the Hadamard product in SDI can cause information loss, we engineer an Attention-Weighted Semantics and Detail Infusion (AWSDI) module that uses dynamic multi-scale feature fusion to preserve details. Validation on field seismic datasets from the Netherlands F3 and New Zealand Kerry blocks shows that SwiftSeis-AWNet mitigates challenges like the loss of small-scale fault features and misidentification of fault intersection zones, enhancing the accuracy and geological reliability of automated fault identification.