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Increasing confidence in full field modelling and water flood planning for a giant reservoir under primary depletion through Material Balance modelling
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Abstract<p>One of the principle inputs to project economics and all business decisions is a realistic production forecast and a practical and achievable development plan (i.e. waterflood). Particularly this becomes challenging in supergiant oil fields with medium to low lateral connectivity. The main objectives of the Production Forecast and feasibility study for water injection are:</p><p>1- Provide an overview of the total expected production profile, expected wells potential/spare capacity, water breakthrough timing and water cut development over time</p><p>2- Highlight the requirements to maintain performance, suggest the optimum development pattern</p><p>3- Increasing confidence in business decisions to develop the reservoir in question</p><p>The main tool used for these purposes is a sophisticated reservoir simulation software, namely CMG©, since it can predict reservoir behavior, honor physical constraints and capture the heterogeneity within the reservoir to accurately predict performance. However, the starting point for this kind of complicated studies needs to start from the basics, in order to understand the big picture and be able to plan properly for the scope to be delivered, hence, utilizing analytical tools like MBAL becomes quite necessary, if not crucial, to the success of full field modelling and choosing an optimum water flood pattern and design.</p><p>This paper covers the methodology for building the reservoir component utilizing a Material Balance model, of which the results will be used as an input to reservoir simulation to evaluate and accurately predict reservoir performance, which directly feeds into planning for water flooding projects and selection of an optimum flood pattern.</p><p>A Tank model was built at first to assess and understand the driving forces (energies) of the reservoir in question, utilizing pressure and production data from legacy wells, the prepared model is also supported by geological and petro physical studies to give representative results. Acquired Static Bottom Hole Pressures (SBHPs) in wells were used as anchor points for the tank pressure and to test the validity of the history match. Multiple analytical methods to QC the results and STOIIP volume were conducted, e.g. the Havlena-Odeh method.</p><p>This methodology has been tested successfully in the stated super giant oil field, in which the reservoir in question is a carbonate rock formation. An example of this is covered in the paper. It was concluded that utilizing a history matched and coherent MBAL model before conducting a detailed reservoir simulation study can save a lot of time and effort by providing guidance to the path which needs to be followed, and sheds light on the critical elements to be looked after. This has also helped to uncover the driving mechanisms and energies in the reservoir, hence allowing the engineer to plan for the necessary voidage replacement and water injection rates to sustain the reservoir pressure and pattern development. Another technical advantage of the described method is the higher sustainability of the model.</p><p>The suggested method, in combination with geological and petro physical information available, can be applied to majority of the reservoirs. This combination is paramount to ensure optimum time and planning that is followed for each reservoir development study that involves water flooding.</p>
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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Radon concentrations assessment in tap water for different areas in Baghdad city using Rad7
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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Mathematical Model for BOD in Waste Water Discharges from Al Dora Refinery in Baghdad
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This research consists of two parts, the first part concern with analyzing the collected data of BOD and COD values in discharge waste water from Al-Dora refinery during 2010 to find the relationship between these two variables The results indicates that there is a high correlation between BOD and COD when using a natural logarithm model (0.86 ln(COD)) with correlation coefficient of 0.98. This relationship is useful in predicting the BOD value using the COD value. The second part includes analyzing collected data from the same site in order to find a relationsip between BOD and other parameters COD, Phenol(phe), Temperature(T), Oil, Sulphat(SO4),pH and Total dissolved solids( TDS) discharged from the refinery. The results indicated that th

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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
Prediction Unconfined Compressive Strength for Different Lithology Using Various Wireline Type and Core Data for Southern Iraqi Field
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Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reservoir permeability prediction based artificial intelligence techniques
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   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

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Publication Date
Tue Dec 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Electrofacies Characterization of an Iraqi Carbonate Reservoir
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Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.

The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC

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Publication Date
Sun Sep 27 2020
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Health Promotion Program for the Prevention of Epidemics at Primary Health Care Centers in Baghdad City: Comparative Study
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Objective(s): To evaluate and compare between Health Promotion Program for the Prevention of Epidemics at Primary Health Care Centers in Baghdad City.

Methodology: A descriptive study, using the evaluation and comparative approaches, is conducted to evaluate health promotion program for the prevention of epidemics at primary health care centers in baghdad city from October 15th  2019 through March 1st 2020. A purposive, non-probability, sample of (42) health promotion unit officers were recruited from the same number of primary health care centers which were divided into (14) main, (14) sub and (14) family medicine primary health care centers i

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Surface Roughness and Material Removal Rate in Electrochemical Machining Using Taguchi Method
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Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
NUMERICAL INVESTIGATION OF STATIC AND DYNAMIC STRESSES IN SPUR GEAR MADE OF COMPOSITE MATERIAL
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In this current work, Purpose; to clearly the fundamental idea for constructing a design and
investigation of spur gear made of composite material its comes from the combination of (high
speeds, low noise, oil-les running, light weight, high strength, and more load capability)
encountered in modern engineering applications of the gear drives, when the usual metallic gear
cannot too overwhelming these combinations.
An analyzing of stresses and deformation under static and dynamic loading for spur gear tooth
by finite element method with isoparametric eight-nodded in total of 200 brick element with 340
nods in three degree of freedom per node was selected for this analysis. This is responsible for the
catastropic fa

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Publication Date
Sun Jul 01 2012
Journal Name
Ieee Transactions On Geoscience And Remote Sensing
Echo Amplitude Normalization of Full-Waveform Airborne Laser Scanning Data Based on Robust Incidence Angle Estimation
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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction in One of Iraqi Carbonate Reservoir Using Statistical, Hydraulic Flow Units, and ANN Methods
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   Permeability is an essential parameter in reservoir characterization because it is determined hydrocarbon flow patterns and volume, for this reason, the need for accurate and inexpensive methods for predicting permeability is important. Predictive models of permeability become more attractive as a result.

   A Mishrif reservoir in Iraq's southeast has been chosen, and the study is based on data from four wells that penetrate the Mishrif formation. This study discusses some methods for predicting permeability. The conventional method of developing a link between permeability and porosity is one of the strategies. The second technique uses flow units and a flow zone indicator (FZI) to predict the permeability of a rock mass u

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