This study deals with establishing the depositional environment of the Fatha Formation through facies analysis. It also deals with dividing the formation into units based on the rhythmic nature. Data from selected shallow wells near Hit area and deep wells at East Baghdad Oil field are used. Five major lithofacies are recognized in this study, namely, greenish grey marl, limestone, gypsum (and/or anhydrite), halite and reddish brown mudstone (with occasional sandstone).The limestone lithofacies is divided into three microfacies: Gastropods bioclastic wackestone microfacies, Gastropods peloidal bioclastic packstone, and Foraminiferal packstone microfacies.The lithofacies of the Fatha are nested in a rhythmic pattern or what is known as shallowing-upwards cycle. Each rhythm begins with shallow marine subtidal environment followed by hypersaline lagoonal environment then supersaline lakes and Salinas, and may finally terminate with continental deposits. Each regressive rhythm is followed by a transgressive phase. According the repitions of the lithofacies, the Fatha Formation can be divided stratigraphically into three units namely Unit 1, Unit 2 and Unit 3 (in ascending order). Different kinds of nesting of lithofacies are recognized in each unit. Only Unit 2 shows complete rhythms.
Facies, Depositional Environment and Cyclicity of the Fatha Formation in East Baghdad Oil Field, Iraq.
facies
cyclicity
Fatha Formation
rhythms and units
evaporite
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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