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ZENODO
Article . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
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PROCESSING GRAVITY-MAGNETIC DATA FOR FIELD SEPARATION

Authors: İsgаndаrov E.; Majidov A.; Mustafazadeh Z.;

PROCESSING GRAVITY-MAGNETIC DATA FOR FIELD SEPARATION

Abstract

Abstract This article focuses on the basic processing of gravity-magnetic data to separate fields into regional and local components. A key stage in the processing and interpretation of gravimetric and magnetic data is the potential field transformation phase, which involves identifying local and regional anomalies from the total observed field. Local potential field anomalies reflect structural heterogeneities in the density and magnetic properties of rocks, while regional anomalies are associated with the deep structure of the Earth's crust. To perform the transformation of gravimetric and magnetic fields, the department developed an algorithm and the Force-Fortran program IZOTR, which enables digital data transformation using various transformation methods. This article describes the algorithm and block-diagram of the IZOTR program, as well as some of the results of processing actual and simulated gravity-magnetic fields using this program in a modern interface.

Keywords

gravity field, magnetic field, algoritm, transformation, local and regional anomalies, averaging method

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average