Metalliferous Brine Exploration and Reservoir Intelligent Identification in Qaidam Basin, Northwestern China

Metalliferous brine represents a globally significant strategic mineral resource. The western Qaidam Basin in Qinghai, China, harbours immense potential for deep metalliferous brine deposits, yet exploration remains limited due to technical challenges such as the difficulty in identifying deep brine-bearing reservoirs and inaccuracies in delineating their spatial distribution. This paper focuses on the core technological methodology of integrated well and seismic data for deep metalliferous brine detection and intelligent reservoir identification. It comprehensively utilises geological, seismic, and logging data from oil and gas exploration in the western Qaidam Basin to conduct research on multi-source geophysical data fusion and intelligent interpretation. A systematic analysis of brine layer response characteristics in logging (e.g., low resistivity, low natural gamma) and seismic data was conducted. For the first time, seismic forward modelling clearly defined the identification resolution limits of onshore seismic data for halite-bearing sand bodies at primary frequencies of 25–50 Hz: Effective identification requires sandbody interlayers ≥1 metre and single sandbody thickness ≥7–8 metres. Overlapping sandbodies with elevation differences <6 metres are prone to misinterpretation as single layers, while low-velocity interlayers may cause strong reflections to drown out brine-bearing layer signals. This provides crucial theoretical support for practical data interpretation. Building upon this, an innovative approach combining well-logging and seismic data inversion with intelligent recognition based on a deep neural network (UNet++) was proposed. By integrating the high resolution of logging with the lateral continuity advantage of seismic data, automated and high-precision identification of brine layers was achieved. The research successfully established a brine-bearing layer prediction model, enabling quantitative forecasting of the spatial distribution of metalliferous brine layers in the western Qaidam area. This provides scientific justification for subsequent drilling deployment in target zones. It significantly enhances the exploration efficiency and intelligence level for deep metalliferous brine, holding substantial scientific significance and practical value for advancing mineral resource reserves and production.