Ambiguity diagram for gradational density model to reduce uncertainty in the interpretation of gravity data
Abstract
Infinite models of geology at depth can be proposed in order to match their theoretical gravity anomaly. The problem so far does not offer a unique solution except in idealized cases. The uniqueness of solution or interpretation is not possible due to imperfection in the data and the basic ambiguity in case of potential fields which obey Laplace's equation. The first problem of imperfection in the data is the perennial one. The second difficulty, which is an inherent property, may also be reduced by placing restrictive but reasonable assumption on the admissible physical property, i.e. rigorous bounds on the density distribution. Similarly range of estimation of source parameters can be provided by construction of ambiguity diagram for gravity measurements, which provides an interval within which the unknown parameters are located with a given probability. Estimation of ambiguity of quantitative interpretation of gravity anomaly in the case of fault needs linearization but the gravity anomaly over a fault and gradational model contains logarithms, which can't be linearized. However it was shown that the anomaly curves are very similar to the curve of normal distribution function and therefore it was possible to replace the anomaly by the normal distribution function, which can be linearized to obtain the confidence limits of the parameters and to obtain range of ambiguity for a given fault or gradational model. In this paper ambiguity diagram for fault versus gradational model has been described in order to give a range of source parameters of a gradational density model. Synthetic examples for a fault and gradational density illustrate the use of ambiguity diagram and application is demonstrated through field gravity data.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2008
- Bibcode:
- 2008AGUFMIN51C1174D
- Keywords:
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- 1219 Gravity anomalies and Earth structure (0920;
- 7205;
- 7240);
- 3275 Uncertainty quantification (1873);
- 8010 Fractures and faults