Well logs data are the most widely used data to evaluate subsurface rocks, their petrophysical properties include porosity, permeability and fluid saturation. They are essential for the hydrocarbon reserves estimations and perforation zones determination for production purposes and fields development. Well logging operations of the targeted reservoirs could not be done in NO-10 Well, Noor Oilfield, Southern Iraq due to some problems related to the well condition. The gamma-ray and sonic logs were the only recorded logs, while neutron, density and deep resistivity logs are missed. The missing neutron, density and deep resistivity logs of the Early Cretaceous Nahr Umr Sandstone and the Late Cretaceous Mishrif formations of the well NO-10 were produced and compared together using the Artificial Neural Network ANN in Petrel software. The results show that the total correlation of the ANN Nahr Umr model for the neutron, density and deep resistivity logs are 0.81, 0.49 and 0.51 respectively. Interestingly, the ANN Mishrif Formation model recorded 0.88, 0.92 and 0.81 for neutron, density and resistivity logs respectively. The results show excellent relationships between the original and the predicted logs in the Mishrif model, unlike the Nahr Umr model expect in ANN of the neutron log. It was expected that the total relationships are low in Nahr Umr due to the lithology variation that includes interbedded consolidated and unconsolidated sandstone interbedded with the shale. It is also observed that the gamma log shows low values and the caliper logs is smoothed in the Mishrif. In contrast, the Nahr Umr sandstone logs show that many washouts have occurred. Therefore, logs' responses highly possible to be affected in the Nahr Umr Formation which leads to a decreasing in the coefficient of determinations.

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Petrophysical properties including volume of shale, porosity and water saturation are significance parameters for petroleum companies in evaluating the reservoirs and determining the hydrocarbon zones. These can be achieved through conventional petrophysical calculations from the well logs data such as gamma ray, sonic, neutron, density and deep resistivity. The well logging operations of the targeted limestone Mishrif reservoirs in Ns-X Well, Nasiriya Oilfield, south of Iraq could not be done due to some problems related to the well condition. The gamma ray log was the only recorded log through the cased borehole. Therefore, evaluating the reservoirs and estimating the perforation zones has not performed and the drilled well was abandoned. This paper presents a solution to estimate the missing open-hole logs of Mishrif Formation including sonic, neutron, density and deep resistivity using supervised Artificial Neural Network (ANN) in Petrel software (2016.2). Furthermore, the original gamma-ray log along with the predicted logs data from ANN models were processed, and the petrophysical properties including volume of shale, effective porosity and water saturation were calculated to determine the hydrocarbon zones. The ANN Mishrif Formation models recorded coefficient of determination (R2) of 0.65, 0.77, 0.82, and 0.04 between the predicted and the tested logs data with total correlations of 0.67, 0.91, 0.84 and 0.57 for sonic, neutron, density, and resistivity logs respectively. The best possible hydrocarbon-bearing zone ranges from the depth of about 1980-2030 m in the mB1unit. The ANN provides a good accuracy and data matching in clean and non-heterogeneous formations compared to those with higher heterogeneity that contain more than one type of lithology. The Ns-X Well can, therefore, be linked to the development plans of the Nasiriya Field instead of neglect it.

Core description, well logs data, petrographic analysis and scanning electron microscope technique were conducted to unravel factors controlling the preservation of high porosity up to 25% in deeply-buried sandstones > 4 km of the Lower Cretaceous Nahr Umr reservoir, southern Iraq. The Nahr Umr Formation composed of sandstone interbedded with shale, minor siltstones and streaks of limestone. The sandstones are arenites and range from fine to coarse, and poor to moderate sorted. Parallel lamination, planer cross-bedded and lenticular bedding are common sedimentary structures found in the formation, suggesting that the Nahr Umr deposited in fluvial-deltaic to the shallow-marine environment. Cementation by syntaxial quartz overgrowth was retarded by the presence of illite coats, which was formed by the illitization of the infiltrated smectite that formed during the deposition around the quartz grains. Microquartz coats in the form of quartz crystals probably further prevented the quartz overgrowths. Thus, the porosity of Nahr Umr preserved by the illite coats and microquartz crystals, whereas, the process of K-feldspar dissolution has created secondary porosity. The stylolite formation and the quartz-calcite replacement are the main sources of silica for the precipitation of quartz overgrowth.