The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Predicting vertical stress was indeed useful for controlling geomechanical issues since it allowed for the computation of pore pressure for the formation and the classification of fault regimes. This study provides an in-depth observation of vertical stress prediction utilizing numerous approaches using the Techlog 2015 software. Gardner's method results in incorrect vertical stress values with a problem that this method doesn't start from the surface and instead relies only on sound log data. Whereas the Amoco, Wendt non-acoustic, Traugott, average technique simply needed density log as input and used a straight line as the observed density, this was incorrect for vertical computing stress. The results of these methods

Crude oil is one of the most important sources of energy in the world. To extract its multiple components, we need oil refineries. Refineries consist of multiple parts, including heat exchangers, furnaces, and others. It is known that one of the initial operations in the refineries is the process of gradually raising the temperature of crude oil to 370 degrees centigrade or higher. Hence, in this investigation the focus is on the furnaces and the corrosion in their tubes. The investigation was accomplished by reading the thickness of the tubes for the period from 2008 to 2020 with a test in every two year, had passed from their introduction into the work. Where the thickness of more than one point was measured on each tube in the sa

The study's primary purpose is to explore an appropriate way of monitoring and assessing water depths using the satellite remote sensing technique of the Al Habbaniyah Lake in Iraq. This research studied the experience-conditions (thresholds) of different bands for multi-temporal satellite image data with different satellite image sensors (Landsat 5-TM, and EO1-ALI) for the same region, to recognize regions of water depths. The threshold values are taken that to separate the Al Habbaniyah Lake to the required depths (shallow, deep, and very deep), as a supervised method. A three-dimension feature space plot had used to represent these regions. The relationship of the mean values of the three separated water regions with all TM and A

Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate

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 sh

This work represents study the rock facies and flow unit classification for the Mishrif carbonate reservoir in Buzurgan oil Field, which located n the south eastern Iraq, using wire line logs, core samples and petrophysical data (log porosity and core permeability). Hydraulic flow units were identified using flow zone indicator approach and assessed within each rock type to reach better understanding of the controlling role of pore types and geometry in reservoir quality variations. Additionally, distribution of sedimentary facies and Rock Fabric Number along with porosity and permeability was analyzed in three wells (BU-1, BU-2, and BU-3). The interactive Petrophysics - IP software is used to assess the rock fabric number, flow zon

   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, and

   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, a