Given gridded gravity anomaly values and certain limiting restrictions on the mass distribution, a three‐dimensional structural model can be calculated automatically from gravity anomaly data by successive approximations. The causative body is optionally assumed to be either flat‐topped, flat‐bottomed, or symmetrical about a horizontal plane. Density contrast and the position of a horizontal plane delimiting either the top, base, or midsection of the causative body must be specified. A first approximation of structure is obtained by means of the Bouguer slab relationship. The gravity field of this first model is calculated and at each grid point the ratio of observed to calculated gravity is used to modify the first structural model, thus leading to a second approximation of structure. The process is iterated until a satisfactory agreement between observed and calculated gravity is obtained.
The horizontal‐gradient method has been used since 1982 to locate density or magnetic boundaries from gravity data (Cordell, 1979) or pseudogravity data (Cordell and Grauch, 1985). The method is based on the principle that a near‐vertical, fault‐like boundary produces a gravity anomaly whose horizontal gradient is largest directly over the top edge of the boundary. Magnetic data can be transformed to pseudogravity data using Fourier techniques (e.g., Hildenbrand, 1983) so that they behave like gravity data; thus the horizontal gradient of pseudogravity also has maximum magnitude directly over the boundary. The method normally is applied to gridded data rather than to profiles. The horizontal‐gradient magnitude is contoured and lines are drawn or calculated (Blakely and Simpson, 1986) along the contour ridges. These lines presumably mark the top edges of magnetic or density boundaries. However, horizontal‐gradient magnitude maxima (gradient maxima) can be offset from a position directly over the boundary for several reasons. Offsets occur when boundaries are not near‐vertical, or when several boundaries are close together. This note predicts these offsets. Many other factors also cause offsets, but they are less straightforward and usually are only significant in local studies; we discuss these factors only briefly.
In the analysis of gravity data over thick sedimentary basins, density contrast can sometimes be approximated by a continuous function decreasing exponentially with depth. Typical values of the exponential decrement are in the order of 0.3 to [Formula: see text]. The gravity effect of an infinite (Bouguer) slab in this system tends to a finite limit as the slab becomes infinitely thick, leading to quantitative, and sometimes stringent, limitations on the resolving power of gravity analysis over deep structures. The exponential density term acts as an integrating factor in deriving the gravity effect of a prismatic building element, leading to a simple expression involving both the gravity field and its vertical derivative. A recursive computer algorithm giving the inverse solution automatically in terms of assigned density parameters is applied to a gravity profile over a graben structure at San Jacinto, California. The computed basin configuration is consistent with the seismically determined basement depth of 2.4 km and the estimated density layering of the graben fill.
The terracing operator works iteratively on gravity or magnetic data, using the sense of the measured field’s local curvature, to produce a field comprised of uniform domains separated by abrupt domain boundaries. The result is crudely proportional to a physical‐property function defined in one (profile case) or two (map case) horizontal dimensions. This result can be extended to a physical‐property model if its behavior in the third (vertical) dimension is defined, either arbitrarily or on the basis of the local geologic situation. The terracing algorithm is computationally fast and appropriate to use with very large digital data sets. Where gravity and magnetic data are both available, terracing provides an effective means by which the two data sets can be compared directly. Results of the terracing operation somewhat resemble those of conventional susceptibility (or density) mapping. In contrast with conventional susceptibility mapping, however, the terraced function is a true step function, which cannot be depicted by means of contour lines. Magnetic or gravity fields calculated from the physical‐property model do not, in general, produce an exact fit to the observed data. By intent, the terraced map is more closely analogous to a geologic map in that domains are separated by hard‐edged domain boundaries and minor within‐domain variation is neglected. The terracing operator was applied separately to aeromagnetic and gravity data from a 136 km × 123 km area in eastern Kansas. Results provide a reasonably good physical representation of both the gravity and the aeromagnetic data. Superposition of the results from the two data sets shows many areas of agreement that can be referenced to geologic features within the buried Precambrian crystalline basement. The emerging picture of basement geology is much better resolved than that obtained either from the scanty available drill data or from interpretation of the geophysical data by inspection.
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