Saudi Arabian Oil Company

Truva Corporation

Abdallah Awadh Al-Shehri

Howard Khan Schmidt

Ian F Akyildiz

Shih-Chun Lin

Example computer-implemented methods, computer-readable media, and computer systems are described for providing communication protocol architecture or framework for magnetic induction (MI)-based communications in wireless underground sensor networks (WUSNs), for example, in underground oil reservoirs. In some aspects, environment information of an underground region that affects the transmission qualities of MI communications is evaluated. A protocol stack is identified. The protocol stack includes a number of layers for MI communications among a number of sensors in a WUSN in the underground region. A cross-layer framework and the distributed protocol are built to jointly optimize communication functionalities of the plurality of layers based on the evaluation.

Environment-aware cross-layer communication protocol in underground oil reservoirs

Example computer-implemented methods, computer-readable media, and computer systems are described for accurate localization of wireless sensor devices in underground oil reservoirs. In some aspects, every sensor measures respective received magnetic field strengths (RMFSs) on a plurality of respective magnetic induction (MI) links and transmits the measured respective RMFSs to at least one anchor devices. A set of distances is determined from the measured respective RMFSs. The set of distances is processed through an ordered sequence of algorithms, namely weighted maximum likelihood estimation (WMLE), semi-definite programming (SDP) relaxation, alternating direction augmented Lagrangian method (ADM), and conjugate gradient algorithm (CGA), to generate accurate localization of the wireless sensor devices in underground oil reservoirs.

Magnetic induction based localization for wireless sensor networks in underground oil reservoirs

Example computer-implemented methods, computer-readable media, and computer systems are described for accurate localization of wireless sensor devices in underground oil reservoirs. In some aspects, every sensor measures respective received magnetic field strengths (RMFSs) on a plurality of respective magnetic induction (MI) links and transmits the measured respective RMFSs to at least one anchor devices. A set of distances is determined from the measured respective RMFSs. The set of distances is processed through an ordered sequence of algorithms, namely weighted maximum likelihood estimation (WMLE), semi-definitec programming (SDP) relaxation, alternating direction augmented Lagrangian method (ADM), and conjugate gradient algorithm (CGA), to generate accurate localization of the wireless sensor devices in underground oil reservoirs.

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Abdallah Awadh Al-Shehri