Gravity interpretation of dipping faults using the variance analysis method
Creators
- 1. Geophysics Department, Faculty of Science, Cairo University, Giza (Egypt)
Description
A new algorithm is developed to estimate simultaneously the depth and the dip angle of a buried fault from the normalized gravity gradient data. This algorithm utilizes numerical first horizontal derivatives computed from the observed gravity anomaly, using filters of successive window lengths to estimate the depth and the dip angle of a buried dipping fault structure. For a fixed window length, the depth is estimated using a least-squares sense for each dip angle. The method is based on computing the variance of the depths determined from all horizontal gradient anomaly profiles using the least-squares method for each dip angle. The minimum variance is used as a criterion for determining the correct dip angle and depth of the buried structure. When the correct dip angle is used, the variance of the depths is always less than the variances computed using wrong dip angles. The technique can be applied not only to the true residuals, but also to the measured Bouguer gravity data. The method is applied to synthetic data with and without random errors and two field examples from Egypt and Scotland. In all cases examined, the estimated depths and other model parameters are found to be in good agreement with the actual values. (paper)
Availability note (English)
Available from http://dx.doi.org/10.1088/1742-2132/10/1/015003Additional details
Identifiers
Publishing Information
- Journal Title
- Journal of Geophysics and Engineering (Online)
- Journal Volume
- 10
- Journal Issue
- 1
- Journal Page Range
- [7 p.]
- ISSN
- 1742-2140
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 44126595
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
- Descriptors DEI
- ALGORITHMS; ECONOMICS; ERRORS; GRAVITATION; GRAVITATIONAL FIELDS; LEAST SQUARE FIT
- Descriptors DEC
- MATHEMATICAL LOGIC; MATHEMATICAL SOLUTIONS; MAXIMUM-LIKELIHOOD FIT; NUMERICAL SOLUTION