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Data Driven Approach for Predicting Pore Pressure of Oil and Gas Wells, Case Study of Iraq Southern Oilfields
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Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables are vertical depth, bulk density, and acoustic compressional wave velocity, with the activation function of tangent sigmoid. The average percent error, absolute average percent error, mean square error, root mean square error, and correlation coefficient (R2) were applied for evaluation. The results revealed that the best artificial neural network structure was (3-8-1), with average percent error, absolute average percent error, mean square error, root mean square error, and correlation coefficient R2 of -0.52, 1.01, 3994, 63.2, and 0.995, respectively. A C++ computer program is provided with a calculation sample to simplify the implementation of the proposed artificial neural network. The dependency degree of pore pressure on each input parameter is investigated, revealing the highest impact of depth on pore pressure prediction. Furthermore, to check the validity of the artificial neural network against the different datasets, the artificial neural network performance was compared with 84 new data points and showed an advantage over the existing models. The very good performance of artificial neural network for different types of oil reservoirs and formations reveals an insignificant effect of lithology on the prediction of pore pressure.  

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Publication Date
Wed Sep 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Correlation of Penetration Rate with Drilling Parameters For an Iraqi Field Using Mud Logging Data
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This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.

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Publication Date
Tue Mar 03 2009
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of repetitive estimation methodsSelf-data
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In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation)  structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of  these procedures and compare them using generated data.

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Publication Date
Sun Dec 01 2013
Journal Name
2013 Sixth International Conference On Developments In Esystems Engineering
Ensure Security of Compressed Data Transmission
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Data compression offers an attractive approach to reducing communication costs using available bandwidth effectively. It makes sense to pursue research on developing algorithms that can most effectively use available network. It is also important to consider the security aspect of the data being transmitted is vulnerable to attacks. The basic aim of this work is to develop a module for combining the operation of compression and encryption on the same set of data to perform these two operations simultaneously. This is achieved through embedding encryption into compression algorithms since both cryptographic ciphers and entropy coders bear certain resemblance in the sense of secrecy. First in the secure compression module, the given text is p

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Publication Date
Tue Jul 01 2008
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
KEYS FOR IDENTIFICATION FOR GENERA AND SPECIES OF THRIPS (THYSANOPTERA : THRIPIDAE) FROM MIDDLE OF IRAQ
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Keys for 22 species representing ten genera Thripidae collection carried out during 1999-2001 in different localities in the middle of Iraq. Of them four species are described as new to science, Frankliniella megacephala sp. nov; Retithrips bagdadensis sp. nov; Chirothrips imperatus sp. nov; Taeniothrips tigridis sp. nov; Another thirteen species are recorded for the first time in Iraq; Thrips meridionalis (Pri.); Microcephalothrips abdominils (Crawford); Scolothrips pallidus (Beach); Scritothrips mangiferae Pri.; Frankliniella tritici Bagnall; Frankliniella schultzie Trybom; Frankliniella unicolor Morgan; Retithrips aegypticus Mar

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Publication Date
Sun Mar 15 2020
Journal Name
Journal Of The College Of Education For Women
The Use of English as Lingua Franca in the Classes of UKM: as A Case of Study
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           English has for long been one of the most widely used media of communication globally, especially in the Malaysian universities. It has been termed as a Lingua Franca because it is shared with other languages which are considered first languages by different speakers. For this reason, English as a Lingua Franca (ELF) has attracted a number of researchers to investigate its variety via other languages in various communities. The objective of this paper is therefore to establish the strategies which are employing by the international students at the National University of Malaysia/ UniversitiKebangsaan Malaysia (UKM) as an example of one of the Malaysian universities; when they e

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Publication Date
Thu Mar 18 2021
Journal Name
Energy & Fuels
Synergistic Effect of Nanoparticles and Polymers on the Rheological Properties of Injection Fluids: Implications for Enhanced Oil Recovery
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New nanotechnology-based approaches are increasingly being investigated for enhanced oil recovery (EOR), with a particular focus on heavy oil reservoirs. Typically, the addition of a polymer to an injection fluid advances the sweep efficiency and mobility ratio of the fluid and leads to a higher crude oil recovery rate. However, harsh reservoir conditions, including high formation salinity and temperature, can limit the performance of such polymer fluids. Recently, nanofluids, that is, dispersions of nanoparticles (NPs) in a base fluid, have been recommended as EOR fluids; however, such nanofluids are unstable, even under ambient conditions. In this work, a combination of ZrO2 NPs and the polyacrylamide (PAM) polymer (ZrO2 NPs–PAM) was us

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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Economics And Administrative Sciences
Determining the sources of growth of the cement industry in Iraq (analytical study for the period 1990-2014)
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The objective of this study is to determine the sources of growth of the cement industry in Iraq for the period 1990-2014 and to indicate the nature of the technological progress used in it. To achieve this objective we have built an econometric model, by adapting the production function constant elasticity for substitution, using multiple regression, and enforcement, SPSS program, and using the ordinary least squares method (OLS). The results showed that quantitative factors (labour and capital) are the main sources of growth the cement industry in Iraq, and the qualitative factors (technological progress) did not contribute effectively to achieve this growth. And that the production techniques adopted in the cement industry in

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
New Robust Estimation in Compound Exponential Weibull-Poisson Distribution for both contaminated and non-contaminated Data
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Abstract

The research Compared two methods for estimating fourparametersof the compound exponential Weibull - Poisson distribution which are the maximum likelihood method and the Downhill Simplex algorithm. Depending on two data cases, the first one assumed the original data (Non-polluting), while the second one assumeddata contamination. Simulation experimentswere conducted for different sample sizes and initial values of parameters and under different levels of contamination. Downhill Simplex algorithm was found to be the best method for in the estimation of the parameters, the probability function and the reliability function of the compound distribution in cases of natural and contaminateddata.

 

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Publication Date
Wed Jan 10 2024
Journal Name
Journal Of Optics
Pulsed laser deposition of Pd/WO3 nanoparticles on Si nanostructure for highly sensitive room-temperature gas sensors
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Publication Date
Sat Oct 01 2011
Journal Name
Iraqi Journal Of Physics
Some gas sensing properties of PbS thin films
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In this research PbS thin film have been prepared by chemical bath deposition technique (CBD).The PbS film with thickness of (1-1.5)μm was thermally treated at temperature of 100°C for 4 hours. Some Structural characteristics was studied by using X-ray diffraction (XRD)and optical microscope photograph some of chemical gas sensing measurements were carried out ,it shown that the sensitivity of (CO2) gas depend on the grain Size and deposition substrate. The grain size of PbS film deposited on on glass closed to 21.4 nm while 37.97nm for Si substrate. The result of current-voltage characterization shwon the sensitivity of prepared film deposited on Si better than film on glass.

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