A quantitative spatial analysis of mineral deposit distributions in relation to their proximity to a variety of structural elements is used to define parameters that can influence metal endowment, deposit location and the resource potential of a region. Using orogenic gold deposits as an example, geostatistical techniques are applied in a geographic-information-systems-based regional-scale analysis in the high-data-density Yilgarn Craton of Western Australia. Metal endowment (gold production and gold 'rank' per square kilometer) is measured in incremental buffer regions created in relation to vector lines, such as faults. The greatest metal tonnages are related to intersections of major faults with regional anticlines and to fault jogs, particularly those of dilatant geometry. Using fault length in parameter search, there is a strong association between crustal-scale shear zones/faults and deposits. Nonetheless, it is the small-scale faults that are marginal or peripheral to the larger-scale features that are more prospective. Gravity gradients (depicted as multiscale edges or gravity 'worms') show a clear association to faults that host gold deposits. Long wavelength/long strikelength edges, interpreted as dominantly fault-related, have greater metal endowment and provide a first-order area selection filter for exploration, particularly in areas of poor exposure. Statistical analysis of fault, fold and gravity gradient patterns mainly affirms empirical exploration criteria for orogenic gold deposits, such as associations with crustal-scale faults, anticlinal hinge zones, dilational jogs, elevated fault roughness, strong rheological contrasts and medium metamorphic grade rocks. The presence and concurrence of these parameters determine the metallogenic endowment of a given fault system and segments within the system. By quantifying such parameters, the search area for exploration can be significantly reduced by an order of magnitude, while increasing the chance of discovery.