2019
DOI: 10.1109/access.2019.2937915
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3D Localization for Internet of Underground Things in Oil and Gas Reservoirs

Abstract: Magnetic Induction (MI) is an efficient wireless communication method to deploy operational internet of underground things (IOUT) for oil and gas reservoirs. The IOUT consists of underground things which are capable of sensing the underground environment and communicating with the surface. The MI-based IOUT enable many applications, such as monitoring of the oil rigs, optimized fracturing, and optimized extraction. Most of these applications are dependent on the location of the underground things and therefore… Show more

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Cited by 18 publications
(11 citation statements)
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References 38 publications
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“…Similarly, a semi-definite programming-based localization technique was developed in [132] for MI-based underground sensor networks. Nevertheless, the achievable accuracy for MI-based underground networks was investigated in [136]. All of these works are focused on MI-based communications where the work on EM, acoustic, and VLC do not exist.…”
Section: Robust and Accurate Localization Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Similarly, a semi-definite programming-based localization technique was developed in [132] for MI-based underground sensor networks. Nevertheless, the achievable accuracy for MI-based underground networks was investigated in [136]. All of these works are focused on MI-based communications where the work on EM, acoustic, and VLC do not exist.…”
Section: Robust and Accurate Localization Methodsmentioning
confidence: 99%
“…Multi-hop networking/Hardware design [117] 300 -900 MHz Improvement of the transmission range by using relays Deployment strategies [118] 10 kHz Use of meta-material shell for the transceiver design to improve the received power [139], vehicular ad-hoc networks [140], source localization [141], radar tracking [142], cognitive radio networks [143]- [145], and underwater wireless networks [146]- [148]. Therefore, in [136], we derived the expression of the CRLB for the MIbased IoUT localization. The derived bound in [136] takes into account the channel and network parameters of MI-based IoUT.…”
Section: Refmentioning
confidence: 99%
“…In [77,261], authors studies how mineral and rocks in underground environment effect the accuracy of localization. The accuracy is also investigated in [85,86,257] for MI-based WUC. It is important to note that localization work exist only for the MI-based and there is no work done in EM-, acoustic-, and VLC-based WUC.…”
Section: Efficient Localization Methodsmentioning
confidence: 99%
“…CRLB has been used for many wireless networks, e.g., IoT [251], source localization, cognitive radio networks [252][253][254], radar tracking [255], and vehicular ad-hoc networks [256]. Authors in [257] derives CRLB for MI-based WUC localization for Oil & Gas scenario, and considering network and channel parameters. A summary of EM-based WUC is presented in Table 7.…”
Section: Channel Modelingmentioning
confidence: 99%
“…However, localization is necessary to determine the position of the underground nodes. Nasir Saeed et al resolved this problem using isometric scaling [282] and CRBL (Cramer Rao Lower Bound) in the closed-form to perform 3D localization as opposed to the existing two-dimensional solutions. Lastly, seismic exploration is another one of the uses of IoUT [58].…”
Section: Underground Communicationsmentioning
confidence: 99%