Hybrid Seismic-Electrical Data Acquisition Station Based on Cloud Technology and Green IoT

Traditional geophysical prospecting instruments cannot fulfill the requirements of deep energy prospecting. The instruments that measure single physical quantities, such as seismic and electrical instruments, have certain limitations. Moreover, the time period required for traditional instruments to collect, acquire, and process data is too long. To address these issues, a hybrid seismic-electrical data acquisition system based on cloud technology and green IoT was proposed and developed. A seismic analog acquisition circuit and an electrical analog acquisition circuit were designed, and the control module was designed and debugged. The system is equipped with a wireless module connected to a wireless-to-4G/5G module, which uploads the data collected by the hybrid seismic-electrical data acquisition station to the cloud platform. The background master control center completes the rapid processing of geophysical data using the robust storage and computing capabilities of the cloud. Meanwhile, it sends control commands to the cloud to control the acquisition system. This system has completed simultaneous prospecting of multiple physical quantities and achieved rapid monitoring through cloud technology. Finally, the system was used to perform fracture monitoring and a comparison of two mines in Daqing City, Heilongjiang Province. The monitoring results were satisfactory. Thus, the presented system can play a role in seismic-electrical prospecting, and can be applied to actual engineering endeavors quickly and reliably.

[1]  Miaowen Wen,et al.  MBID: Micro-Blockchain-Based Geographical Dynamic Intrusion Detection for V2X , 2019, IEEE Communications Magazine.

[2]  L. R. Sykes,et al.  Evolving Towards a Critical Point: A Review of Accelerating Seismic Moment/Energy Release Prior to Large and Great Earthquakes , 1999 .

[3]  M. Markovaara‐Koivisto,et al.  Discovered and undiscovered mineral resources: Evolving accounts and future prospects of minerals in Finland , 2018 .

[4]  Qisheng Zhang,et al.  Mine Fracturing Monitoring Analysis Based on High-Precision Distributed Wireless Microseismic Acquisition Station , 2019, IEEE Access.

[5]  Estella A. Atekwana,et al.  Imaging Precambrian Lithospheric Structure in Zambia using Electromagnetic Methods , 2018 .

[6]  Mario Schmidt Scarcity and Environmental Impact of Mineral Resources—An Old and Never-Ending Discussion , 2018, Resources.

[7]  Paolo Gardoni,et al.  Using opportunities in big data analytics to more accurately predict societal consequences of natural disasters , 2019, Civil Engineering and Environmental Systems.

[8]  E. Cian,et al.  Global Energy Consumption in a Warming Climate , 2019 .

[9]  A. Pasha,et al.  Oil consumption and economic growth: Evidence from Pakistan , 2018 .

[10]  Jun Wu,et al.  Making Knowledge Tradable in Edge-AI Enabled IoT: A Consortium Blockchain-Based Efficient and Incentive Approach , 2019, IEEE Transactions on Industrial Informatics.

[11]  Mianxiong Dong,et al.  FCSS: Fog-Computing-based Content-Aware Filtering for Security Services in Information-Centric Social Networks , 2019, IEEE Transactions on Emerging Topics in Computing.

[12]  David J Wales,et al.  Exploring Energy Landscapes. , 2018, Annual review of physical chemistry.

[13]  H. N. Gharti,et al.  Modeling Three‐Dimensional Wave Propagation in Anelastic Models With Surface Topography by the Optimal Strong Stability Preserving Runge‐Kutta Method , 2019, Journal of Geophysical Research: Solid Earth.

[14]  Qiang Zhang,et al.  Climate policy: Steps to China's carbon peak , 2015, Nature.

[15]  Joseph Sarkis,et al.  How to globalize the circular economy , 2019, Nature.

[16]  Jeffrey D. Shulman,et al.  The Effects of Autoscaling in Cloud Computing , 2018, Manag. Sci..

[17]  Ubaidullah Alias Kashif,et al.  Architectural Design of Trusted Platform for IaaS Cloud Computing , 2018, Int. J. Cloud Appl. Comput..

[18]  Hongmei Duan,et al.  Development of high-precision distributed wireless microseismic acquisition stations , 2018, Geoscientific Instrumentation, Methods and Data Systems.

[19]  M. Simons,et al.  Estimates of aseismic slip associated with small earthquakes near San Juan Bautista, CA , 2016 .

[20]  Witold Pedrycz,et al.  Security Data Collection and Data Analytics in the Internet: A Survey , 2019, IEEE Communications Surveys & Tutorials.

[21]  Ü. Dikmen,et al.  Two-dimensional joint inversion of Magnetotelluric and local earthquake data: Discussion on the contribution to the solution of deep subsurface structures , 2018 .

[22]  M. Dentith,et al.  Application of Deep–Penetrating Geophysical Methods to Mineral Exploration: Examples From Western Australia , 2018 .

[23]  Klemen Kenda,et al.  Streaming Data Fusion for the Internet of Things , 2019, Sensors.

[24]  Jianhua Li,et al.  Big Data Analysis-Based Secure Cluster Management for Optimized Control Plane in Software-Defined Networks , 2018, IEEE Transactions on Network and Service Management.

[25]  Enrico Serpelloni,et al.  Vertical GPS ground motion rates in the Euro‐Mediterranean region: New evidence of velocity gradients at different spatial scales along the Nubia‐Eurasia plate boundary , 2013 .

[26]  R. Finkelman,et al.  Coal geology in China: an overview , 2018, Coal Geology of China.

[27]  Shu-Ching Chen,et al.  Multimedia Big Data Analytics , 2018, ACM Comput. Surv..

[28]  Arun Kumar Sangaiah,et al.  EdgeLaaS: Edge Learning as a Service for Knowledge-Centric Connected Healthcare , 2019, IEEE Network.

[29]  3D joint inversion of gravity-gradient and borehole gravity data , 2017 .

[30]  Zhang Qisheng,et al.  Development of a new seismic-data acquisition station based on system-on-a-programmable-chip technology , 2013 .

[31]  J. Jacka The Anthropology of Mining: The Social and Environmental Impacts of Resource Extraction in the Mineral Age , 2018, Annual Review of Anthropology.

[32]  Adrian A. S. Barfod,et al.  Hydrostratigraphic modeling using multiple-point statistics and airborne transient electromagnetic methods , 2017, Hydrology and Earth System Sciences.

[33]  Kegang Li,et al.  A High Security Distance Education Platform Infrastructure Based on Private Cloud , 2018, Int. J. Emerg. Technol. Learn..

[34]  G. Mudd,et al.  Unresolved Complexity in Assessments of Mineral Resource Depletion and Availability , 2018, Natural Resources Research.