Deposit-Density Models

A key function of many forms of quantitative mineral resource assessments is estimation of the number of undiscovered deposits. In any given region, there is some fixed but, in most cases, unknown number of undiscovered deposits of a given type—the number could be zero or a larger integer. Many quantitative resource assessments that are based on a common three-part form of assessment (Singer, 1993a) have used expert judgment to estimate the number of deposits. Estimates of this unknown number are presented in a probabilistic form to reflect the uncertainty associated with the estimate. Ideally, estimates of number of deposits should rely on analogies with similar well-explored geologic settings, just as grades and tonnages of well explored deposits serve as analogs of the qualities and sizes of undiscovered deposits. Estimates of the number of undiscovered deposits can be derived from counts of known deposits per unit area in explored control regions. Number of deposits per unit area of the control regions can be used in histograms to show variation of densities by deposit type. Some research has been conducted on densities of several deposit types so that these ratios can be more widely used as a guide for number-of-deposit estimates (Bliss, Orris, and Menzie, 1987; Bliss, Menzie, Orris, and Page, 1987; Bliss and Menzie, 1993; Bliss, 1992b; Root, Menzie, and Scott, 1992). Most of these studies provide point (i.e., single) estimates of the number of deposits per unit area. Singer et al. (2001) summarize the ideas behind these mineral deposit density models and provide individual estimates for twenty-seven combinations of deposit types and control locations. Many of the specially selected areas they describe provide standards to identify what should be considered high estimates of number of undiscovered deposits in most situations. Thus, many published mineral-deposit densities provide guides that suggest upper limits to estimates but are not necessarily useful in providing estimation guides for more likely situations.