The reliability of depth conversion in complex land areas is particularly challenging. Accuracy and precision are usually difficult to achieve simultaneously because of the limited amount and quality of seismic data and sparse control from well data. Ideally, depth-migration methods would be the right tools to produce such data for interpreters. However, despite recent significant breakthroughs in seismic imaging, the ability to provide precise depths is not always achievable with depth-imaging techniques. Therefore, depth conversion remains a crucial tool for converting a seismic image and its interpretation to geologic depth. We have developed an overview of the techniques used for depth conversion through a carefully selected set of geologically diverse field examples. We determine the challenges faced while applying each methodology and, more importantly, share our own experiences and pitfalls. We also evaluate the steps taken to overcome these limitations. All these studies highlight the pragmatic application of techniques and their common pitfalls to improve the workflows that can be implemented to solve other depth-conversion problems. Depth-conversion techniques can be classified depending on the approach used for velocity model building (VMB) (i.e., time-depth and instantaneous velocity functions, layer-cake models, or geostatistical velocity interpolations) and also depending on the ray-tracing procedure (i.e., vertical stretching or image ray). To verify the reliability of the VMB, we establish the following criteria for an acceptable velocity model: (1) honors hard data, (2) integrates all the available sources of velocity information, and (3) makes geologic sense. We reinforce the latter in complex areas where geologic control drives the chosen approach. For instance, in cases with strong velocity gradients (e.g., basement-involved structures), vertical depth conversion may not be able to solve all possible scenarios, resulting in an incomplete assessment of the structural uncertainty. To model such situations, we use a time-to-depth conversion based on the image-ray concept.