The interpretation of geochemical data of a regional survey of the Wadi ash Shu'bah quadrangle resulted in the selection of areas for follow-up studies. The results of the detailed geochemical studies of these areas, combined with field observation, resulted in the identification of areas of moderate and high mineral resource potential. The most important areas are (1) the Jibal Ba'gham area for tin and tungsten resources associated with the post-Hadn Jufayfah syenogranite; (2) the Murran gossan belt, Aqab gossan area, and Rawdah gossan area for massive-sulfide mineralization associated with Hulayfah-group greenstones; (3) the Rawdat al Ba'ayith area and Jibal Abid area for precious- and base-metal mineralization associated with pre-Hadn intermediate-composition plutons; and (4) the Wadi al Qahad area for skarn and precious- and base-metal mineralization associated with pre-Hadn granodiorite.

The Wadi ash Shu'bah quadrangle (sheet 26E) lies in the north-central part of the late Proterozoic Arabian Shield. Plots showing distributions of single elements and factor scores of the regional geochemical data of wadi concentrates were used to identify areas for follow-up work. Detailed follow-up studies consisted of collection of rocks, wadi concentrates, and wadi sediments. The most useful pathfinder elements for precious- and base-metal mineralization are Pb and Cu for tin and Sn, La, Y, Nb, and Be for tungsten mineralization. R-mode factor analyses of the regional wadi-concentrate data resulted in one factor interpreted as reflecting post-Hadn evolved alkalic-granite lithology and, therefore, tin and tungsten mineralization.

A major problem in the interpretation of the regional data resulted from the incomplete removal of magnetite before analyses. The magnetite can cause anomalous values for Ni, Fe, V, Cu, and Co because of it's ability to incorporate these elements into it's structure during magmatic crystallization. It is essential that samples be prepared and analyzed in a consistent manner so that the resulting data may be as reliable as possible.