Reservoir rock typing integrates geological, petrophysical, seismic, and reservoir data to identify zones with similar storage and flow capacities. Therefore, three different methods to determine the type of reservoir rocks in the Mushrif Formation of the Amara oil field. The first method represents cluster analysis, a statistical method that classifies data points based on effective porosity, clay volume, and sonic transient time from well logs or core samples. The second method is the electrical rock type, which classifies reservoir rocks based on electrical resistivity. The permeability of rock types varies due to differences in pore geometry, mineral composition, and fluid saturation. Resistivity data are usually obtained from w

     Reservoir characterization requires reliable knowledge of certain fundamental properties of the reservoir. These properties can be defined or at least inferred by log measurements, including porosity, resistivity, volume of shale, lithology, water saturation, and permeability of oil or gas. The current research is an estimate of the reservoir characteristics of Mishrif Formation in Amara Oil Field, particularly well AM-1, in south eastern Iraq. Mishrif Formation (Cenomanin-Early Touronin) is considered as the prime reservoir in Amara Oil Field. The Formation is divided into three reservoir units (MA, MB, MC). The unit MB is divided into two secondary units (MB1, MB2) while the unit MC is also divided into two sec

Petrophysical properties of Mishrif Formation at Amara oil field is determined
from interpretation of open log data of (Am-1, 2 ,3 ,4 ,5 ,6 ,7 ,8 ,9 ,10 ,11 ,12
and13) wells. These properties include the total, the effected and the secondary
porosity, as well as the moveable and the residual oil saturation in the invaded and
uninvaded zones. According to petrophysical properties it is possible to divided
Mishrif Formation which has thickness of a proximately 400 m, into seven main
reservoir units (MA, MB11, MB12, MB13, MB21, MC1, MC2) . MA is divided into
four secondary reservoir units , MB11 is divided into five secondary reservoir units ,
MB12 is divided into two secondary reservoir units , MB13 is divided into

The reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of rese

Mishrif Formation is the main reservoir in Amara Oil Field. It is divided into three units (MA, TZ1, and MB12). Geological model is important to build reservoir model that was built by Petrel -2009. FZI method was used to determine relationship between porosity and permeability for core data and permeability values for the uncored interval for Mishrif formation. A reservoir simulation model was adopted in this study using Eclipse 100. In this model, production history matching executed by production data for (AM1, AM4) wells since 2001 to 2015. Four different prediction cases have been suggested in the future performance of Mishrif reservoir for ten years extending from June 2015 to June 2025. The comparison has been mad

      The seismic method depends on the nature of the reflected waves from the interfaces between layers, which in turn depends on the density and velocity of the layer, and this is called acoustic impedance. The seismic sections of the East Abu-Amoud field that is located in Missan Province, south-eastern Iraq, were studied and interpreted for updating the structural picture of the major Mishrif Formation for the reservoir in the Abu-amoud field. The Mishrif Formation is rich in petroleum in this area, with an area covering about 820 km². The seismic interpretation of this study was carried out utilizing the software of Petrel-2017. The horizon was calibrated and defined on t

Gas Chromatography GC, Gas Chromatography–Mass spectrometry GC/MS techniques used for analysis of the crude oils that taken from (10) producing wells in Nasiriyah oil field including (NS-1, NS-3, NS-4, NS-5, NS-6, NS-7, NS-8, NS-9, NS-10, and NS-12) from Mishrif reservoir . This reservoir is one of the important reservoirs in Al-Nasiriyah oil field, and it will be the main subject in the current study in order to provide information of crude oil analysis in this area, also to provide information on its characterizations. Mishrif Formation is one of the principle carbonate reservoir in central and southern Iraq. It is part of the wasia group and widespread throughout the Arabian gulf, It is deposited during Cenomanian-Early Turonian cyc

      The seismic method depends on the nature of the reflected waves from the interfaces between layers, which in turn depends on the density and velocity of the layer, and this is called acoustic impedance. The seismic sections of the East Abu-Amoud field that is located in Missan Province, south-eastern Iraq, were studied and interpreted for updating the structural picture of the major Mishrif Formation for the reservoir in the field. The Mishrif Formation is rich in petroleum in this area, with an area covering about 820 km². The horizon was calibrated and defined on the seismic section with well logs data (well tops, check shot, sonic logs, and density logs) in the interp

The present study includes the evaluation of petrophysical properties and lithological examination in two wells of Asmari Formation in Abu Ghirab oil field (AG-32 and AG-36), Missan governorate, southeastern Iraq. The petrophysical assessment was performed utilizing well logs information to characterize Asmari Formation. The well logs available, such as sonic, density, neutron, gamma ray, SP, and resistivity logs, were converted into computerized data using Neuralog programming. Using Interactive petrophysics software, the environmental corrections and reservoir parameters such as porosity, water saturation, hydrocarbon saturation, volume of bulk water, etc. were analyzed and interpreted. Lithological, mineralogical, and matrix recogniti