Intelligent or smart completion wells vary from conventional wells. They have downhole flow control devices like Inflow Control Devices (ICD) and Interval Control Valves (ICV) to enhance reservoir management and control, optimizing hydrocarbon output and recovery. However, to explain their adoption and increase their economic return, a high level of justification is necessary. Smart horizontal wells also necessitate optimizing the number of valves, nozzles, and compartment length. A three-dimensional geological model of the As reservoir in AG oil field was used to see the influence of these factors on cumulative oil production and NPV. After creating the dynamic model for the As reservoir using the program Petrel (2017.4), we

well log analysis is used to determine the rock properties like porosity, water saturation, and shale volume. Archie parameters in Archie equation, which sometimes considered constants greatly affect the determination of water saturation, also these parameters may be used to indicate whether the rocks are fractured or not so they should be determined. This research involves well logging analysis for Zubair formation in Luhais field which involves the determination of Archie parameters instead of using them as constant.

The log interpretation proved that the formation is hydrocarbon reservoir, as it could be concluded from Rwa (high values) and water saturation values (low values), the lithology of Zubair from cro

     Four subsurface sections and electrical, porosity logs, and gamma-ray logs of the Khasib Formation (age Late Turonian-Lower Coniacian) were studied to identify reservoir characteristics and to evaluate the reservoir properties of the Khasib reservoir units in the East Baghdad oilfield. The lithology of the formation is limestone throughout the whole sequence in all studied wells EB-83, EB-87, EB-92, and EB94. It is bounded conformably from the top by Tanuma Formation and has a conformable lower contact with Kifl Formation. The lower and upper boundaries of the formation were determined using well log analysis, and the formation was divided into three main rock units (Kh1, Kh2, and Kh3), depending on the porosity logs. The porosi

Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.

The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC

Mishrif Formation regards one of the most important reservoirs in Iraq. Well logging represents one of the most important tool in the formation evaluation. According to the Petrophysical properties that have been gotten from well logging, Mishrif Formation in terms of reservoirs units, consist of several reservoirs units. Major reservoirs units divided into three reservoir units,MA,MB&MC. Each of these major units divided into minor reservoirs units (MB11,MB12,MC2&MC3).MB major reservoir units represent the best reservoir unit. These reservoirs units separated by cap rocks(mainly tight limestone)(CR1,CR2,CR3,CR4,CR5,CR6,and CR7).CPI were demonstrated for all wells.Hydrocarbon saturation vs.

In this study, a qualitative seismic velocity interpretation is made up through using 2D-seismic reflection data on Luhais oil field in southern of Iraq which is situated at about 105 Km to the east from the Basra city. Luhais oil field was chosen to study the type and nature of the distribution of the seismic velocities of Nahr Umr and Zubair Formations in order to show its explorational importance, where these formations contain abundant quantities of hydrocarbons. Picking of the tops of Nahr Umr and Zubair was carried out from the synthetic seismogram which is calculated from sonic-logs and check shot of well Lu-2. Velocity model was obtained via using an implementation of Petrel program version, 2013 and was corrected according to to

The main objective of this study is to develop a rate of penetration (ROP) model for Khasib formation in Ahdab oil field and determine the drilling parameters controlling the prediction of ROP values by using artificial neural network (ANN).

     An Interactive Petrophysical software was used to convert the raw dataset of transit time (LAS Readings) from parts of meter-to-meter reading with depth. The IBM SPSS statistics software version 22 was used to create an interconnection between the drilling variables and the rate of penetration, detection of outliers of input parameters, and regression modeling. While a JMP Version 11 software from SAS Institute Inc. was used for artificial neural modeling.

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Exploitation of mature oil fields around the world has forced researchers to develop new ways to optimize reservoir performance from such reservoirs. To achieve that, drilling horizontal wells is an effective method. The effectiveness of this kind of wells is to increase oil withdrawal. The objective of this study is to optimize the location, design, and completion of a new horizontal well as an oil producer to improve oil recovery in a real field located in Iraq. “A” is an oil and gas condensate field located in the Northeast of Iraq. From field production history, it is realized the difficulty to control gas and water production in this kind of complex carbonate reservoir with vertical producer wells. In this study, a horizont

The estimation of the initial oil in place is a crucial topic in the period of exploration, appraisal, and development of the reservoir. In the current work, two conventional methods were used to determine the Initial Oil in Place. These two methods are a volumetric method and a reservoir simulation method. Moreover, each method requires a type of data whereet al the volumetric method depends on geological, core, well log and petrophysical properties data while the reservoir simulation method also needs capillary pressure versus water saturation, fluid production and static pressure data for all active wells at the Mishrif reservoir. The petrophysical properties for the studied reservoir is calculated using neural network technique

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