At the present, sensors are everywhere across different sectors of the oil and gas industry. Seismic acquisition in upstream, pipeline monitoring in midstream, and asset tracking in downstream are examples of applications in which we need more and more sensors to satisfy a pressing need for accuracy. Sensor data in many cases should be quickly aggregated and coordinated, sometimes from harsh environments where crew intervention and maintenance must be minimized for safety and cost reasons. This mandates data collection/transmission strategies that are power efficient and demand minimal maintenance to operate autonomously. To address this issue, a unified wireless sensing framework is required that consists of the following three components: low-power, long-range wireless sensors with inherent compatibility with the “Internet of Things” (IoT); advanced scalable wireless networking protocols; and data storage/analytics on the cloud for analysis and decision making. These three components combined create a flexible, plug-and-play, scalable network that provides worldwide accessibility to the data and is cost efficient because you pay as you grow for storage and computation. Aiming at materializing such a ubiquitous wireless sensing paradigm, we have studied the feasibility of using a new family of IoT-based wireless technologies: so-called low-power wide-area networks (LPWANs). We have conducted a proof-of-concept field test in which we have employed LoRa, a predominant member of the LPWAN family, for real-time seismic quality control/monitoring. Our field test results corroborate that cheap (less than US$10) subscription-free LoRa wireless modules can be embedded into our seismic recording systems allowing us to transmit more than 6 MB of data per node per day, while the data can be transmitted over distances of a few kilometers with less than a milliwatt of average power consumption. The transmitted data can be monitored in real time on the cloud for further analysis and decision making.