Minimization risk technique for solving gravity inverse problems in weak assumptions about geological noise properties

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Minimization risk technique for solving gravity inverse problems in weak assumptions about geological noise properties

Journal Title: Геофизический журнал - Year 2016, Vol 38, Issue 5

Abstract

The concept of the hidden information on the gravity anomaly sources as joint fragment of the true and model disturbing objects was introduced. In the presence of uncertainty inherent in inverse problems, limit possibilities of algorithms for constructing the best estimates of the parameters source models is to maximize the secure amount of the extracted reliable information. Justified application to "ore" type gravity nonlinear inverse problems known to minimization risk concept in solving the choice problem under conditions of a priori information shortage. According to this concept as the best of the feasible solutions of the inverse problem is chosen at which the minimum of the expectation value error of interpretation results is achieved. It is assumed zero median noise in the observed gravity field, ie, the presence of positive and negative noise with equal probability, but it is not excluded that the absolute value of the interference of some one sign may prevail. Constructing a sufficiently representative set of feasible interpretation options of which will be chosen the best, performed by fitting algorithm in the finite element class models of geological bodies. An important advantage of the method, which is based on the idea of minimizing the risk is the possibility of an approximate estimate of the proximity of the proposed mathematical model to the true anomaly sources. Produced the results of computational experiments confirming the effectiveness of such assessments, as well as higher quality of the inverse problem solution using the proposed method in comparison with the traditional approach.

Authors and Affiliations

P. I. Balk, A. S. Dolgal

Keywords

gravitational exploration; interpretation; inverse problem; field source; noise; anomalous error; empirical risk minimization

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EP ID EP197318
DOI 10.24028/gzh.0203-3100.v38i5.2016.107825
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