Abstract
Wireless communication in subsurface wells and reservoir has been a major challenge in ensuring robust data transmission, and reliable communication between the sensors. Challenges from the multiple reflection as well as other external factors, makes subsurface communication a unique challenge for modern communication algorithms. While multiple-Input, multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) communication has been extensively implemented in wireless communication for signal processing, unique challenges arise in subsurface reservoirs caused by unknown formation properties and fluid movements.
We present a new smart MIMO-OFDM algorithm for wireless communication in subsurface reservoirs. The new algorithm integrates both MIMO and OFDM into a deep learning framework. It optimizes the communication quality as well as reliability of the communication between the various subsurface wireless devices. The joint integration and smart adjustment leverages the power of both algorithms simultaneously, and allows significantly improved communication robustness between the wireless devices.
We tested the smart MIMO-OFDM on a synthetic carbonate reservoir formation with multiple wireless sensors and wireless appliances. Fracture Robots (FracBots, about 5 mm in size) technology will be used to sense key reservoir parameters (e.g., temperature, pressure, pH and other chemical parameters). The technology is comprised of a wireless microsensor network for mapping and monitoring fracture channels in conventional and unconventional reservoirs. The system establishes wireless network connectivity via magnetic induction (MI)-based communication, since it exhibits highly reliable and constant channel conditions with sufficiently communication range inside an oil reservoir environment. The results exhibited strong performance of the wireless communication, hence providing reliable and robust subsurface wireless communication.
The novel framework presents a vital component in enhancing subsurface wireless communication and achieve robust data transfer. The results outline the opportunity for wireless communication to become a critical component for subsurface communication.
