An Autonomous Environmental Logging Microsystem (ELM) for Harsh Environments

Abstract

This paper describes the design, implementation, and evaluation of an environmental logging microsystem (ELM) for operation at elevated pressure and in corrosive environments, at temperatures up to 125°C. The ELM units are intended to be deployed in large quantities, allowed to collect data, and then retrieved, interrogated, and re-charged. Powered by a rechargeable battery embedded within the system, each ELM incorporates pressure and temperature sensors, control electronics, optical communication elements, and power management and battery recharging circuits. The pressure sensor is a customized capacitive transducer chip on a sapphire substrate; details are provided in a companion paper. The electronic components and battery used in ELM are selected on the basis of functionality and form factor; packaged components are selected for ease of assembly and for added protection against the environment. The pressure sensor, electronics and battery are assembled on a flexible circuit board, folded into a stack with dimensions 7.2 mm × 6.6 mm × 6.5 mm, and encapsulated in a steel tube filled with optically transparent silicone caulk. This encapsulation provides mechanical protection against shock and abrasion, as well as chemical protection against high salinity environments, while allowing the ambient pressure and temperature to be transferred to the sensing elements. Results are reported from high-temperature and high-pressure tests reaching 125°C and 7,250 psi in brine and other corrosive environments in laboratory conditions. Field tests that were conducted in a brine well to a maximum depth of 1,235 m are also described. The recorded data were post-processed to interpret the environmental pressure and temperature.

Autonomous Sensing Microsystem with H2S Compatible Package and Enhanced Buoyancy for Downhole Monitoring

“…Extended testing in laboratory conditions mimicking downhole environments suggest that the microsystem can provide measurements for up to 96 hours. overall system density was >2000 kg/m 3 (Openfield 2014;Choi et al 2017;Sui et al 2021), the microsystem described here achieved density lower than 1200 kg/m 3 , which was lower than the targeted upper limit of 1300 kg/m 3 . The microsystem utilized a packaging approach which provided protection against corrosive chemicals that may be encountered downhole, such as H 2 S, a feature not addressed in other work (Seren et al 2017;Buzi et al 2020;Sui et al 2021).…”

“…overall system density was >2000 kg/m 3 (Openfield 2014;Choi et al 2017;Sui et al 2021), the microsystem described here achieved density lower than 1200 kg/m 3 , which was lower than the targeted upper limit of 1300 kg/m 3 . The microsystem utilized a packaging approach which provided protection against corrosive chemicals that may be encountered downhole, such as H 2 S, a feature not addressed in other work (Seren et al 2017;Buzi et al 2020;Sui et al 2021). Additionally, this work utilized commercially standard wireless communication (BLE) and battery recharging (Qi) protocols, which can reduce development time and system cost.…”

“…Under the platform label of environmental logging microsystem (ELM), the University of Michigan has reported a series of investigations that combined custom sensors with rapidly prototyped commercial electronics, demonstrating operation to 50 MPa pressure and 125°C temperature. These early efforts (Sui et al 2021) did not incorporate inertial sensors. More importantly, they used an optical approach for battery recharging and bidirectional communication, requiring a transparent pathway into the package.…”

Application of ELM Algorithm Incorporating AE Principles in Wireless Communication Signal Detection

“…To improve the effectiveness and stability of the intelligent traffic management system, Cui et al proposed the fusion of gravitational algorithm and ELM to construct an improved ELM traffic flow prediction model, which was compared with other advanced models and found to have the highest prediction accuracy and sensitivity [10]. Sui et al combined ELM and packaging components such as pressure and temperature sensors to construct an environmental logging system to address the difficulty of performing measurement work in extreme environments such as high temperatures and high corrosiveness, and the method was found to be of practical use in empirical studies for normal field testing in extreme environments [11]. Since photovoltaic output is intermittently affected by weather conditions, Abdillah et al proposed a nuclear limit learning machine (K-ELM) method for solar irradiance prediction.…”

“…This step requires initialising the AE and connecting the weights. The encoding equation is shown in equation (11).…”