Gravity inversion, as a static potential field inversion, has inherent ambiguity with low vertical resolution. To reduce the nonuniqueness of the inversion, it is necessary to impose the a priori constraints derived by other geophysical inversions, drilling, or geologic modeling. Based on the a priori normalized gradients derived from seismic imaging or reference models, a structure-guided gravity inversion method with a few known point constraints is developed for mapping density with multiple layers. The cubic B-spline interpolation is used to parameterize the forward modeling calculation of the gravity response to smooth density fields. A recently adopted summative gradient is used to maximize the structural similarity between the a priori and inverted models. First, we have determined the methodology, followed by a synthetic fault model example to confirm its validity. Monte Carlo tests and uncertainty tests further examine the stability and practicality of the method. This method is easy to implement; consequently, it produces an interpretable density model with geologic consistency. Finally, we apply this method to the density modeling of the Chezhen Depression in the Bohai Bay Basin. Our work determines the distribution of deep Lower Paleozoic carbonate rocks and Archean buried hills with high-density characteristics. Our results are consistent with the existing formation mechanism of the “upper source-lower reservoir” type oil-gas targets.