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.
A band rationing method is applied to calculate the salinity index (SI) and Normalized Multi-Band Drought Index (NMDI) as pre-processing to take Agriculture decision in these areas is presented. To separate the land from other features that exist in the scene, the classical classification method (Maximum likelihood classification) is used by classified the study area to multi classes (Healthy vegetation (HV), Grasslands (GL), Water (W), Urban (U), Bare Soil (BS)). A Landsat 8 satellite image of an area in the south of Iraq are used, where the land cover is classified according to indicator ranges for each (SI) and (NMDI).
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
... Show MoreThe shale volume is one of the most important properties that can be computed depending on gamma ray log. The shale volume of Mishrif Formation (carbonate formation from middle Cenomanian- early Turonian) was studied for the regional area of the middle and southern parts of Iraq. The gamma ray log data from seventeen wells ( Kf-3,Kf-4, Ad-1,Ad -2,Dh-1, Bu-47, Ns-2, Ns-4, Am-1,Am-2,Hf-2,Hf-115,Mj-3,Mj-15, Su-7,Wq-15 and Lu-7) distributed in the study area were used to compute the shale volume of Mishrif Formation. From the available data of the considered wells, a regional isopach map of Mishrif Formation was obtained. The isopach map indicates that the maximum thickness of Mishrif Formation is located at the eastern part of t
... Show MoreAn Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to
... Show MoreThis study deals with the interpretation of structural 3D seismic reflection of the Kumait oil field in southern Iraq within the administrative boundaries of the Maysan Governorate. Synthetic seismograms are prepared by using available data of the Kt-1 oil field by using Petrel software to define and pick the reflector on the seismic section of the Zubair Formation, Which represents the Cretaceous Age. The study shows that the Kumait structure is an anticline fold. It is thought to be a structure trap caused by the collision of the Arabian and Iranian plates and trending in the same direction as driving factors in the area, which are from the northwest to the southeast, and the overall trend of strata is north and northeast. Sei
... Show MoreThe reservoir characterization of Lower Qamchuqa (Shu'aiba) Formation (Aptian) is studied at the well BH-86 of Bai- Hassan Oilfield in Kirkuk area, Northern Iraq. The lithological study (of 91 thin sections) revealed that the formation consists of shaly limestone, a thin bed of marl within the limestone, and dolomitic limestone. Four petrographic microfacies were noticed Lime mudstone microfacies, Dolomudstone microfacies, Lime wackestone microfacies, subdivided into benthonic foraminifera lime wackestone submicrofacies and bioclasts lime wackestone submicrofacies, and the last microfacies is the Lime packstone microfacies, which is subdivided into pelloidal lime packstone submicrofacies and Orbitolina lime packstone microfaci
... Show MoreThe evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
... Show MoreWastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost
... Show MoreAn interpretive (structural and stratigraphic) study of the two,-dimensional seismic, data of East Nasiriya area (30 km to the south east of Nasiriya oil field within Thi-Qar province, southeastern Iraq) was carried out using Petrel 2017 program. The study area has an importance due to its location between many oil fields, but still without exploration of oil wells. Twenty five seismic lines were used, date back to different types of seismic surveys conducted in the region at different time periods. Also, the seismic velocity surveys of the nearest wells to oil fields, such as Nasiriya-1 and Subba-8, in addition to their sonic and density logs were used. A synthetic seismogram with a good matching with the seismic section was achie
... Show MoreThe Hartha Formation is a major carbonate succession deposited during the Late Campanian period. The current study depends on four selected wells (EB 1, 2, 4 and 30) within the East Baghdad oil field to study electrofacies and petrophysical properties related to the reservoir characterization.
The Hartha Formation is divided into three electro-facies units using GR and SP logs in Petrel software. The upper unit of the Hartha Formation is composed mainly of limestone. The middle unit is composing of thick layers of shale. The lower unit is composed mainly of limestone with few shale layers. The three units are divided into three types of rocks in relation to the total porosity: 1. High-moderate active porosity rocks (type I)
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