<p>Depth weighting (DW) optimally improves inversion in potential methods without prior information. Meanwhile, the moment of inertia (MoI) method incorporates geological data, like dipping beds angles, as constraints for distinct advantages. In fact, the existing algorithm still stands separately. A mixed algorithm is required to incorporate both techniques into a unified algorithm called inertial axes constraint (IAC), which offers flexibility in its implementation to deal with or without prior geological information. The proposed IAC computational scheme is equipped with the compactness (Cm) regularization. The subsurface models obtained from the inversion based on DW and IAC are evaluated using qualitative and quantitative approximations. Furthermore, a fundamental uncertainty quantification of ambiguity of the subsurface model is conducted based on synthetic data modeling. As a result, the proposed IAC method yields satisfactory results in both synthetic and field datasets located in Lengguru Fold-and-Thrust Belt (LFTB), West Papua, Indonesia. A Pearson correlation coefficient (PCC) has been utilized to measure the result of the synthetical inverse modeling, and it was found that the PCC value based on the IAC method is 0.6, while the PCC value from the DW method is 0.1. It is concluded that incorporating prior geological information through the IAC method provides a better model solution compared to the DW method. The field datasets implementation reveals multiple dippings bed structures toward the east as the part of LFTB structures in the study area. Additionally, the intrusive body of Kwasitore granite is also delineated at its eastern part of the WSW-ENE gravity line profile. The IAC modeling results correspond well to the known LFTB geological settings and are more geologically reliable compared to the DW modeling result.</p>