Gravity Data Reduction and Interpretation Using a Digital Computer, a Case History

Cite
David B. Morris, Robert A. Sultzbach, 1967. "Gravity Data Reduction and Interpretation Using a Digital Computer, a Case History", Mining Geophysics Volume II, Theory, Don A. Hansen, Walter E. Heinrichs, Jr., Ralph C. Holmer, Robert E. MacDougall, George R. Rogers, John S. Sumner, Stanley H. Ward
Download citation file:
×  Share

Tools
Abstract
A largescale gravity survey program produces a continuing flow of data which must be computed, interpretedstored for future reference. Computer methods developed to facilitate the processing of these data are discussed.
A gravity datareduction program performs processing and computation of gravimeter and elevation field notes. The computation of instrument drift, scale correction factor, observed gravity, theoretical gravity, station elevationBouguer gravity at several densities is accomplished by the program. BL station observed gravity values required for the computations are maintained on a magnetic disk file which is automatically updated with the newly computed stations. The results are printed in a standard format and preserved for future reference in a punchedcard history file.
A specialized gravity profile interpretation program computes the depth to bedrock for two dimensional alluvial valleys from the Bouguer gravity profile. The alluvial cross section is approximated by a series of vertical rectangular strips. Depth to bedrock is computed by an iterative procedure. As an optional feature, the regional correction is automatically determined as a function of the Bouguer profile by the iterative procedure. The interpreted section is plotted along with the Bouguer gravity profile with an online plotter.
The computer methods are competitive costwise with manual methodsthey provide the additional advantages of speed, accuracyversatility.
The first steps toward automated processing of gravity data at Kennecott were taken in conjunction with regional gravity work. In 1958 a gravity data history file was established on punched cards. Each gravity station
Figures & Tables
Contents
Mining Geophysics Volume II, Theory
The relative merits of any geophysical method in a given situation can be predicted by careful study of the expected messagetonoise1 ratio. For example, let us draw or deduce from the subsequent text, the anomaly formulas due to a spherical inhomogeneity in the subsurface and the symbols in each formula are explained in the text. The gravity, magnetic, resistivity, and inducedpolarization surveys all are volume dependent, whereas the electromagnetic method is dependent only upon the area of the inhomogeneity, normal to the inducing field. Thus, a thin disk can give nearly the same electromagnetic anomaly as a sphere of the same radius.
If we can make a reasonable estimate of the physical property contrast anticipated to exist between ore and host, we can then predict the anomaly magnitude expected from the sphere, when buried at any given depth, via the geometric factor. Note that from this viewpoint, given the maximum or saturation value of unity for the physical property factor, the magnetic and resistivity methods theoretically give the same percent anomaly due to a sphere. The physical property function M–iN for the electromagnetic method has a maximum value of one half for a sphere while the change with frequency of the electrical resistivity contrast.
Thus, except for a factor of two, the magnetic, resistivity, electromagnetic, and inducedpolarization methods should give the same maximum anomaly. Note that the geometry of the anomalous fields for each of these methods is an induced dipole with a resultant falloff of peak anomaly proportional to the inverse cube of the depth to the center of the sphere below the measuring plane. In contrast, the gravity method exhibits an inverse second power falloff due to an induced monopole. The density contrast between ore and host sometimes exhibits a maximum value of two. Thus f r om a maximum message viewpoint, one would be inclined to rate the methods in the order given above. However, we need to counter this bias by considering expected values of the physical property factor and the noise for any given geologic situation.
Let us look, then, at iron ore, massive sulfides, and disseminated sulfides, items treated i n Volume I. We should expect the following physical property ranges: A very wide range of properties is evident and hence the prediction of an anomaly magnitude looks hopeless.