Stratigraphic modeling plays a critical role in characterizing subsurface conditions, while it faces significant uncertainty due to geological heterogeneity and sparse borehole data. Emerging multiple types of stratigraphic data provide a fresh perspective to overcome issues associated with exploiting the intricate stratigraphic relationships from sparse measurements. Presently, most interpolation methods rely solely on stratum types derived from boreholes as a single input, which struggles to efficiently utilize multi-type stratigraphic data, such as dip angle and stratigraphic image. This study addresses the problems by proposing a novel Weighted Ellipse Nearest Neighbors (WENN) approach to efficiently interpolate the stratigraphic model in 2D and 3D with uncertainty quantification. The proposed model could flexibly couple multi-type stratigraphic data without incurring additional costs to deliberately obtain specific mandatory data types. Specifically, when fed with solely stratum types, WENN can be applied in both 2D and 3D contexts with easier application, higher efficiency, and higher accuracy than existing models. The inclusion of dip angles could enhance the accuracy and engineering interpretation of 2D stratigraphic models. With a paralleled stratigraphic image available, WENN can interpolate the gaps using both stratum type, dip angles and stratigraphic image, facilitating the development of a 3D stratigraphic model. WENN offers engineers an alternative approach to handling multiple data types and is adaptable to diverse geotechnical scenarios with varying data availability.