Deepwater oil and gas development projects are extremely challenging. Specific factors contributing to deepwater subsurface characterization challenges include: limited well count, large variation in gross rock volume (GRV) estimates of low relief structures produced by even minor depth uncertainty, and complex overburdens (e.g., complex allochthonous salt). In response to these challenges, we conducted a multi-organization depth uncertainty analysis over the St. Malo subsalt, Lower Tertiary development in deepwater Gulf of Mexico. The project applied WesternGeco’s Quantitative Uncertainty Analysis (QUA) method. QUA is a linearized Bayesian velocity model (and subsequent depth) uncertainty analysis process sampling a set of anisotropic tomographic models. Bayesian methods require a prior model, which is a quantitative representation of our current subsurface understanding. Those familiar with Bayesian methods (e.g., from geostatistical reservoir characterization) know the importance and impact of properly specifying this prior model. To specify this prior we integrated information from various subsurface disciplines (geophysics, geology, drilling). The depth uncertainty estimates that were obtained are being used in building the next generation static model for St. Malo.