GRAVITY Analysis & Interpretation GG 450 Feb 5, 2008

Don’t fall into the worst modeling trap! : "IF IT FITS THE DATA, IT MUST BE RIGHT." (NOT SO!) You can say: IF IT DOESN’T FIT IT’S WRONG (OR AT LEAST INCOMPLETE). Another trap with models: "If the model doesn’t fit the data, keep adding variables." (NOT SO!) THE NUMBER OF VARIABLES SHOULD BE CONSIDERABLY LESS THAN THE DEGREES OF FREEDOM OF YOUR DATA. Decide what parameters you will allow to vary, and find the best model you can. Don’t try to fit every data point - just get the "most reasonable" fit.

Gravity Analysis The gravity signal, corrected to FAA, contains information from ALL mass in the earth - but only that relatively close to you will yield a significant anomaly. - How can you tell whether a signal is generated near or far away? We adjust our gravity survey to emphasize anomalies generated in the depth range we are concerned with. Remove "regionals" before working on shallower sources. Consider the following profile:

mgals This profile contains at least three possible anomalous sources. The SMOOTHED SLOPE of the anomaly is likely the result of a deep structure. Our profile is not long enough to resolve this anomaly, so we can remove it by taking out a slope for the whole profile:

mgals We can do this in a modeling program by entering a deep sloping layer that we can later ignore.

The anomaly still contains a bowl-shaped component that likely is the result of either a broader or deeper anomalous body. Since we can see much of this anomaly (about one wavelength) we can attempt to model it.

The depth of this anomalous interface can be adjusted along with the density contrast across the boundary to provide reasonable geology - such as a valley buried with sediment. Once that is done, the remaining anomaly likely comes from smaller shallower sources: Before adding the "bowl" to the model After adding the "bowl" to the model

We are now in a situation where we can model the SHORTEST wavelength (shallowest) anomalies without interference from the longer wavelength, possibly deeper, anomalies. Is it worth using precise methods, such as statistically accurate curve fitting, to model our observed anomaly? Probably not - since our models are necessarily non- unique and arbitrary, why worry about precision? It might tempt you to believe that your model is correct, not just plausible.

With GMSys: remove trend

Remove Long Wavelength

Model Residuals

What types of data can constrain gravity models?