Microfacies Evaluation of Mauddud Formation in Ratawi Field, South Iraq


This paper includes studying the microfacies evalution of Mauddud Formaion in four wells(Rt-2, Rt-5, Rt17 and Rt-19). Seventy-seven(77) sampels were collected of above mentioned wells. Based on fossil content of the samples under study, four main microfacies were identified: packstone , wakestone , grainstone and lime mudstone microfacies ,which deposited in shallow open marine and restricted marine environments. Petrographic examination of thin section indicated that diagenesis vary in intensity from one site to another, such as dissolution, cementation, compaction, dolomitization and micritization, which led to the improvement and deterioration of porosity. The dominant pore types are vuggy, interparticle and intercrystal.The lithology, mineralogy and the matrix were determined by using crossplot method, which showed that the predominant lithology of the formation is limestone with the presence of dolomite in very few percentages and the mineralogy is calcite. Based on the relationship between porosity and permeability the resevoir performance of the microfacies classified into four types: bad, fair, good and very good. Based on petrophysical properties and core description of well study Mauddud Formation was divided into four rock units A,B,C and D , in terms of reservoir, units A and C are considered good ,while B and D are bad.


The process of combining the significant information from a series of images into a single image called image sharpening or image fusing, where the resultant fused image will be had more spatial and spectral information than any of the input images. in this research two images for the same place in different spatial resolution have been used the first one was panchromatic and the second image was multispectral with spatial resolution 0.5m and 2 m respectively. these image were captured by world view-2 sensor. This research present four pan sharpening methods like, HSV, Brovey, color normalize, Gram shmidt and PCA these methods were used to combine the adopted images to get multispectral image with high spatial resolution. many criteria such as MSE, RMSE, PSNR, CC, ERGAS and RASE have been used to evaluate the quality of the result images.