  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 require
accurate localization techniques. The existing localization techniques for
MI-based underground sensing networks are two-dimensional and do not
characterize the achievable accuracy of the developed methods which are both
crucial and challenging tasks. Therefore, this paper presents the expression of
the Cramer Rao lower bound (CRLB) for three-dimensional MI-based IOUT
localization which takes into account the channel parameters of the underground
magnetic-induction. The derived CRLB provide the suggestions for an MI-based
underground localization system by associating the system parameters with the
error trend. Numerical results demonstrate that localization accuracy is
affected by different channel and networks parameters such as the number of
anchors, noise variance, frequency, and the number of underground things.
