The empirical relationships between a large group of geologic and mineralogical characteristics and the economic merit or status of the 725 gold deposits, ranging from prospects to major producers, in the Timmins-Kirkland Lake area of Ontario have been examined using statistical correlations and multiple linear regression techniques. The economic status of each deposit was ranked on a logarithmic scale of its known or estimated content of gold.Deposits of high economic status are more likely to contain a suite of gold-associated minerals (e.g., scheelite, tourmaline, arsenopyrite, tellurides, sphalerite, and molybdenite) and are more likely to be spatially associated with deposits of any economic status containing these minerals. Lithologies which show a positive correlation with economic status include small, high-level "porphyry" intrusions and lamprophyre dikes. Chemical sedimentary rocks (mainly oxide iron-formation) and coarse granitoid rocks show a negative correlation with economic status. Variables which enter multiple linear regression equations are generally those which correlate strongly with economic status and show significant variation from expected distributions. For the entire area comprising the 725 deposits, a set of geologic and mineralogical variables explains 28 percent of the variation in economic status, whereas for the southeast quarter of the area comprising 254 deposits and for the northwest quarter of the area comprising 148 deposits, 49 and 41 percent, respectively, of the variation in economic status are explained by a modified set of variables. The regression equations allow the economic status of a deposit to be calculated from the geologic and mineralogical data to within 1.1 to 1.6 economic status units (orders of magnitude of contained gold) of its true value, 68 percent of the time.Maps of orthogonalized and contoured measured economic status, calculated economic status, and maps showing the location of deposits with minerals which correlate strongly with economic status all highlight the major mining camps, and indicate additional areas of exploration interest. However, the contouring procedure can give misleading results in areas of low deposit density where these occur adjacent to areas of high deposit density.Quantitative expressions of the relationships between economic and geologic and mineralogical characteristics of deposits can be potentially useful in rating areas and prospects for mineral exploration. This touches on a common problem in exploration: placing a dollar value on prospect A relative to prospect B, given the known geologic and mineralogical differences between them.

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