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The new 5G-powered system improves data quality and reduces latency in geophysical exploration while enhancing wireless acquisition methods.
Seismic acquisition technology for oil and gas exploration has reached the full-node real-time acquisition phase after its substantial evolution from cabled to wireless and offline to real-time. Practical applications are limited by communication protocol bandwidth, coverage, and stability. As a result, most nodes continue to encounter difficulties in handling real-time transmission of massive seismic datasets, experience high latency, and command centers are unable to monitor equipment status and acquisition quality in real time. These limitations have prevented wireless systems from fully replacing the cabled acquisition pattern. To address these challenges, the SINOPEC Geophysical Research Institute developed a proprietary fifth-generation (5G) Smart Point® seismic acquisition system. By integrating 5G mobile communication technology with geophysical exploration needs, the system builds a collaborative ‘End–Edge–Cloud’ intelligent architecture. It performs advanced ‘real-time acquisition and quality control’ during field operations and effectively resolves a series of key technical issues, such as low-latency transmission, millisecond-level synchronization, and intelligent real-time quality control (RTQC). This addresses the long-standing limitations of insufficient equipment and quality control under the current construction model. It establishes a complete RTQC technical system and supporting software framework, realizing fully wireless data acquisition and on-site real-time quality monitoring. In 3D practices conducted in various typical areas, such as the complex mountainous regions of Southern China, the system has demonstrated its comprehensive capabilities for large-scale applications in complicated onshore areas, significantly improving acquisition efficiency and data quality, and promoting the transformation of seismic exploration from ‘experience-driven’ to ‘data-intelligent.’
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Wang et al. (2025) studied this question.
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