A new two-and-a-half dimensional (2.5D) regularized inversion scheme has been developed for the interpretation of residual gravity data by a dipping thin-sheet model. This scheme solves for the characteristic inverse parameters (depth to top z, dip angle θ , extension in depth L, strike length 2 Y, and amplitude coefficient A) of a model in the space of logarithms of these parameters (log(z), log(θ ), log(L), log(Y), and log(|A|)). The developed method has been successfully verified on synthetic examples without noise. The method is found stable and can estimate the inverse parameters of the buried target with acceptable accuracy when applied to data contaminated with various noise levels. However, some of the inverse parameters encountered some inaccuracy when the method was applied to synthetic data distorted by significant neighboring gravity effects/interferences. The validity of this method for practical applications has been successfully illustrated on two field examples with diverse geologic settings from mineral exploration. The estimated inverse parameters of the real data investigated are found to generally conform well with those yielded from drilling. The method is shown to be highly applicable for mineral prospecting and reconnaissance studies. It is capable of extracting the various characteristic inverse parameters that are of geologic and economic significance, and is of particular value in cases where the residual gravity data set is due to an isolated thinsheet type buried target. The sensitivity analysis carried out on the Jacobian matrices of the field examples investigated here has shown that the parameter that can be determined with the superior accuracy is θ (as confirmed from drilling information). The parameters z, L, Y, and A can be estimated with acceptable accuracy, especially the parameters z and A. This inverse problem is non-unique. The non-uniqueness analysis and the tabulated inverse results presented here have shown that the parameters most affected by the non-uniqueness are L and Y. It has also been shown that the new scheme developed here is advantageous in terms of computational efficiency, stability and convergence than the existing gravity data inversion schemes that solve for the characteristic inverse parameters of a sheet/dike.