Building a 3D geological model from field and subsurface data is a typical task in
geological studies involving natural resource evaluation and hazard assessment. In
this paper a 3D geological model for Asmari Reservoir in Fauqi oil field has been
built using petrel software. Asmari Reservoir belongs to (Oligocene- Lower
Miocene), it represents the second reservoir products after Mishrif Reservoir in Fauqi
field. Five wells namely FQ6, FQ7, FQ15, FQ20, FQ21 have been selected lying in
Missan governorate in order to build Structural and petrophysical (porosity and water
saturation) models represented by a 3D static geological model in three directions
.Structural model shows that Fauqi oil field represents un cylindrical anticlinal fold
which contains number of culminations at northern and southern parts separated by
depressions. After making zones for Asmari reservoir, which is divided into 4 zones
(Jeribe/ Euphrates and Kirkuk group which includes Upper Kirkuk, Buzurgan
member, Lower and Middle Kirkuk) , Layers are built for each zone of Asmari
reservoir depending on petrophysical properties. Petrophysical models (porosity and
water saturation) have been constructed for each zone of Asmari reservoir using
random function simulation algorithm. According to data analyses and the results
from modeling, the Upper Kirkuk zone which divided into five layers is a good
reservoir unit regarding its good petrophysical properties (high porosity and low water
saturation) with high presence of oil in economic quantities. Cross sections of porosity
model and water saturation model were built to illustrate the vertical and horizontal
distribution of petrophysical properties between wells of Fauqi oil field.
The object of the presented study was to monitor the changes that had happened
in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To
fulfill this goal, different satellite images had been used in different times, MSS
1973, TM 1990, ETM+ 2000 and MODIS 2010. K-Means which is unsupervised
classification and Neural Net which is supervised classification was used to classify
the satellite images 0Tand finally by use 0Tadaptive classification 0Twhich is0T3T 0T3Tapply
s0Tupervised classification on the unsupervised classification. ENVI soft where used
in this study.
Toxoplasmosis is a widespread infection of great importance, and that the disease does not show any clinical specific signs . this study was performed on 200 patients with schizophrenia were collected from :Al-Rashad Teaching Hospitals and 100 healthy individuals, considered as control group, the samples were collected during the period of December 2012 until the end of February, 2013. Antibodies against T. gondii parasite in the serum were detected by using latex agglutination test (LAT) and showed a percentage of positive antibodies in schizophrenic patients and healthy individuals (control) 143(71.5%) and 45( 45%) respectively.While using Enzyme Linked Immunosorbent Assay (ELISA) the positive blood sera in LAT test of the schizophreni
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Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time. In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D
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Image Fusion Using A Convolutional Neural Network
: Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision maker to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick–Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and Fourier mod
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To finalize any construction investment project, it would be necessary to identify the most significant problems and obstacles that lead to project reluctance and stalling. Unexpected events and conflicts may have disrupted these strategies and impacted project development. Due to the high initial investment costs of construction projects, crises can have an immediate impact, resulting in significant financial losses. The 2014 financial crisis was one of the most prominent crises that Iraq faced, which prompted the researcher to identify and evaluate those obstacles through this research and questionnaires using Pareto scientific theory to exclude factors that do not contribute to project lag. It was discovered that 28 o
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The litholog of Nahr Umr Formation was evaluated using the Acoustic Impedance (AI), Vp/Vs ratio cross plot colored by petrophysical properties (Vsh, PHIT, PHIE, and Sw) in Am-6-Am-10 wells. Bulk density is an important physical property that reflects matrix density and fluid density that exist in rocks pores. It is used as the main parameters to estimate physical characteristics (porosity, water saturation, shale volume, and others). AI was calculated using RHOB and VP logs. Shear velocity was calculated using Greenberg Castagna equations used for estimating the Vp/Vs ratio and the result Showed that the Nahr Umr Formation is composed of two main lithological units. The upper unit (depth 3540m -3672m) is composed of limestone (li
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