This paper proposes an enhanced Polar code construction method to mitigate the significant performance degradation observed in strong Rician fading channels, such as the problem of low data transmission rate of downhole parameters to mud logging. The proposed approach integrates average mutual information equivalence (AMIE) with a sequence rearrangement (SR) strategy by Gaussian Approximation (SR-AMIE-GA). First, an equivalent noise variance is derived by solving the mutual information equivalence equation between the Rician channel and the binary-input additive white Gaussian noise (BI-AWGN) channel, enabling accurate reliability estimation of bit subchannels. Second, a sequence rearrangement technique is introduced based on the Hamming weights of the generator matrix rows: information bits in the lowest-weight regions are reduced, while selected frozen bits are reassigned to highly reliable subchannels, thereby optimizing the distance spectrum and enhancing the error correction capability of frozen bits. Simulation results under successive cancellation list (SCL) decoding with code length 256 and code rate 0.5 demonstrate that the proposed algorithm achieves gains of 0.28 dB and 0.25 dB at bit error ratio (BER) = 10−3.5 and block error rate (BLER) = 10−3, respectively, compared to the Reed-Muller Polar base on frozen bits (FRM-Polar) code, significantly improving error correction performance in critical downhole Rician channels. This work provides robust communication support for industrial automation applications, including intelligent drilling robots and unmanned inspection systems, and facilitates the implementation of cyber-physical systems (CPS) in challenging environments.