Development of a distributed hybrid seismic–electrical data acquisition system based on the Narrowband Internet of Things (NB-IoT) technology
The ambiguity of geophysical inversions, which is based on a single geophysical method, is a long-standing problem in geophysical exploration. Therefore, multi-method geophysical prospecting has become a popular topic. In multi-method geophysical prospecting, the joint inversion of seismic and electric data has been extensively researched for decades. However, the methods used for hybrid seismic–electric data acquisition that form the base for multi-method geophysical prospecting techniques have not yet been explored in detail. In this work, we developed a distributed, high-precision, hybrid seismic–electrical data acquisition system using advanced Narrowband Internet of Things (NB-IoT) technology. The system was equipped with a hybrid data acquisition board, a high-performance embedded motherboard based on field-programmable gate array, an advanced RISC machine, and host software. The data acquisition board used an ADS1278 24 bit analog-to-digital converter and FPGA-based digital filtering techniques to perform high-precision data acquisition. The equivalent input noise of the data acquisition board was only 0.5 µV with a sampling rate of 1000 samples per second and front-end gain of 40 dB. The multiple data acquisition stations of our system were synchronized using oven-controlled crystal oscillators and global positioning system technologies. Consequently, the clock frequency error of the system was less than 10−9 Hz at 1 Hz after calibration, and the synchronization accuracy of the data acquisition stations was ±200 ns. The use of sophisticated NB-IoT technologies allowed the long-distance wireless communication between the control center and the data acquisition stations. In validation experiments, it was found that our system was operationally stable and reliable, produced highly accurate data, and it was functionally flexible and convenient. Furthermore, using this system, it is also possible to monitor the real-time quality of data acquisition processes. We believe that the results obtained in this study will drive the advancement of prospective integrated seismic–electrical technologies and promote the use of IoT technologies in geophysical instrumentation.