A quantitative interpretation of gravity and magnetic anomalies in west of Tikrit city and surroundings, has been completed utilizing Grav2dc and Mag2dc (2D, 2.5D) forward techniques. The modeling has been carried out along four profiles, two NW-SE profiles along the distinct gravity residual anomalies and two NE-SW profiles along the magnetic residual anomalies. The most geologic plausible model that matches the data was picked. The model along the gravity profile (A-A') reveal faulting of the basement, whereas along the profiles B-B', C-C' and D-D' did not present faulting. The models comprise of two rock units, the first is the sedimentary cover and the second unit is the basement rock. According to the results of modeling, thickness of the sedimentary cover and basement depth values are in good agreement with the results of previous studies. The upper part of sedimentary cover exhibited different density and susceptibility contrasts. These contrasts may be interpreted in term of lithological lateral variation.
Quantitative Interpretation of Gravity and Magnetic Anomalies in West of Tikrit City and Surroundings, Iraq
Gravity
Magnetic
Residual anomaly
2D and 2.5D modeling
Iraq
Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Different Estimation Methods for System Reliability Multi-Components model: Exponentiated Weibull Distribution
Exponentiated Weibull Distribution (EWD)
Reliability of multi-component Stress – Strength models R(s
k)
Maximum likelihood estimator (MLE)
Moment estimator (MOM)
shrinkage method (Sh)
Least Squares Estimator (LS)
Rank Set Sampling (RSS). and mean squared error (MSE).
In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria
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