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ijcpe-1068
Interpretation of Mud Losses in Carbonates Based on Cuttings Description, Well-Logging, Seismic and Coherency Data
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    Hartha Formation is an overburdened horizon in the X-oilfield which generates a lot of Non-Productive Time (NPT) associated with drilling mud losses. This study has been conducted to investigate the loss events in this formation as well as to provide geological interpretations based on datasets from nine wells in this field of interest. The interpretation was based on different analyses including wireline logs, cuttings descriptions, image logs, and analog data. Seismic and coherency data were also used to formulate the geological interpretations and calibrate that with the loss events of the Hartha Fm.

   The results revealed that the upper part of the Hartha Fm. was identified as an interval capable of creating potential mud losses, resulting in high NPT. This is due to its diagenetic features such as succrosic dolomites and vuggy zones that could act as thief zones. Seismic potential was used for the prediction of the geological related non-productive drilling time in the Hartha interval. The seismic data quality in this interval was good, with geological observations already made. Detailed interpretation and analysis of the Hartha interval were performed and integrated with the existing seismic interpretation, rock properties, and NPT database to calibrate wells with the loss events to the seismic observations.

 

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Investigating the quality of open street map roads data inside Baghdad city
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
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Publication Date
Thu Feb 01 2018
Journal Name
Applied Mathematical Modelling
Identification of a multi-dimensional space-dependent heat source from boundary data
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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

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Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Natural Gas Science And Engineering
Recovery of mono-ethylene glycol by distillation and the impact of dissolved salts evaluated through simulation of field data
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Publication Date
Thu May 31 2018
On the Use of 6th-Order Tunable Complementary Metal-Oxide-Semiconductor Varactor based Filter in Ultra-Wideband Low Noise Amplifier
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Background:

The plethora of the emerged radio frequency applications makes the frequency spectrum crowded by many applications and hence the ability to detect specific application’s frequency without distortion is a difficult task to achieve.

Objective:

The goal is to achieve a method to mitigate the highest interferer power in the frequency spectrum in order to eliminate the distortion.

Method:

This paper presents the application of the proposed tunable 6th-order notch filter on Ultra-Wideband (UWB) Complementary Metal-Oxide-Semiconductor (CMOS) Low Noise

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Publication Date
Sun Nov 07 2021
Journal Name
Review Of International Geographical Education Online
Assessment of Information Security Risk Management System based on ISO/IEC27005 in the Independent High Electoral Commission: A Case Study
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The current research aims to study the extent to which the Independent High Electoral Commission applies to information security risk management by the international standard (ISO / IEC27005) in terms of policies, administrative and technical procedures, and techniques used in managing information security risks, based on the opinions of experts in the sector who occupy positions (General Manager The directorate, department heads and their agents, project managers, heads of divisions, and those authorized to access systems and software). The importance of the research comes by giving a clear picture of the field of information security risk management in the organization in question because of its significant role in identifying risks and s

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Solution of the electromechanical machining problem using the collocation method based on Bernstein polynomials
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Publication Date
Mon Oct 01 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Effluent quality assessment of Al-Diwaniyah sewage treatment plant based on wastewater quality index
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Treated effluent wastewater is considered an alternative water resource which can provide an important contribution for using it in different purposes, so, the wastewater quality is very important for knowing its suitability for different uses before discharging it into fresh water ecosystems. The wastewater quality index (WWQI) may be considered as a useful and effective tool to assess wastewater quality by indicating one value representing the overall characteristic of the wastewater. It could be used to indicate the suitability of wastewater for different uses in water quality management and decision making. The present study was conducted to evaluate the Al-Diwaniyah sewage treatment plant (STP) effluent quality based on wastewa

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Publication Date
Wed Jan 01 2014
Journal Name
International Journal Of Computer Applications
Mobile Position Estimation based on Three Angles of Arrival using an Interpolative Neural Network
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In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

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