It is of great significance to quickly obtain the sedimentary characteristics of sandstone type uranium reservoir for guiding prospecting sandstone type uranium deposits. In order to solve this problem, a method based on the extraction and optimization of 3D seismic attributes is proposed. The target stratum of the uranium reservoir is accurately located by using the gamma and acoustic logging data together. The well seismic calibration for the uranium reservoir is carried out by making full use of the logging and seismic data. The high-density fine horizon tracking is implemented for the top, bottom, and obvious adjacent interfaces of the target stratum. Various seismic attributes along the target interface are extracted using stratigraphic slices. Analyzing the consistency between the results obtained by various seismic attributes and drilling data, the one that can best characterize the sedimentary characteristics of the target uranium reservoir is selected as the optimal seismic attribute. The sedimentary and its evolutionary characteristics of the target uranium reservoir are obtained by extracting the above optimal seismic attribute. A case study shows that we can obtain the 3D sedimentary characteristics of the target uranium reservoir fast and efficiently using the method based on the 3D seismic attribute. They can be used for providing important reference information for the exploration of sandstone type uranium deposits.

As a sedimentary mineral, most sandstone type uranium deposits are formed in petroliferous basins. Therefore, we can fully tap the residual economic value of historical logging and 3D seismic data measured for oil and gas to search for sandstone type uranium deposits. However, a large amount of acoustic logging data are missing in the target stratum of the uranium reservoir in that it is not the main stratum of oil and gas. A reconstructed method of acoustic logging data based on clustering analysis and with the low-frequency compensation of deterministic inversion is proposed to solve this problem. Secondly, we can use these logging data with seismic data to obtain the 3D inversion data volume representing the sand body of the uranium reservoir based on seismic lithological inversion. Then, we can also delimit the 3D spatial range of sandstone type uranium deposits in petroliferous basins based on the calibration of uranium anomaly and sub-body detection. Finally, a 3D field data example is given to test and analyze the effectiveness of the above research schemes.

Existing evaluations of sandstone-hosted uranium deposits commonly describe ore-controlling troughs and faults qualitatively, which limits the quantitative characterization of structural ore-controlling elements and the prediction of favorable mineralization areas. This study proposes a relative geological time (RGT)-constrained method for quantitatively computing intra-stratal trough attributes and a 3D seismic-based workflow for trough–fault coupled structural favorability prediction in sandstone-hosted uranium exploration and applies this framework to the Qianjiadian uranium mining area. An interpreted-horizon-constrained RGT volume was constructed to extract stratal two-way travel time (TWT) slices, and multi-scale trough attributes were calculated from local TWT relief differences. Fault attributes were constructed from laterally smoothed fault-scan results to improve fault-response continuity. Known mineralized wells were used to calibrate trough and fault responses and to construct trough ore-controlling index (TOI) and fault ore-controlling index (FOI) volumes. The calibrated TOI and FOI volumes were then integrated to generate a coupled favorability index (CFI) volume for structural favorability prediction. High CFI values occur mainly near major fault zones and in areas with moderate trough responses, indicating favorable trough–fault coupled structural conditions for uranium mineralization. Blind-well validation shows that 15 of 20 blind wells agree with the CFI prediction, yielding an overall accuracy of 75.0% and an AUC of 0.85. The proposed method converts qualitative trough and fault ore-control knowledge into computable, mineralization-calibrated, and blind-well-validated 3D structural favorability results, supporting favorable-area selection and drilling deployment in sandstone-hosted uranium exploration.