Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1065
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dc.contributor.authorShareefa Mulla Alien_US
dc.date.accessioned2020-01-08T09:44:47Z-
dc.date.available2020-01-08T09:44:47Z-
dc.date.issued2019en_US
dc.identifier.urihttp://hdl.handle.net/123456789/1065-
dc.description.abstractThis thesis describes the development of an expert system that automates the design of carbonate reservoir matrix acidizing. There are many rules and constraints that govern the design of this process. Automating these rules speeds up the decision process, and helps novice engineers to make better design, and eliminates the need to have experts around in every design job. The system provides specific acidizing treatment recipes to either remove the damage or enhance the permeability around the wellbore, and ultimately improve the well productivity. The carbonate matrix acidizing treatment starts by giving wellbore cleanout recommendations, followed by pre-flush, main acid, diversion, and post-flush recommendations The developed system in this study includes the treatment selection of the pre-flush stage, the main acid stage, diversion stage, and the post-flush stage. Also, it includes the additives that are recommended to be used in the treatment. The compatibility between the recommended acids with the additives, and the rock mineralogical composition and the crude composition, has been considered to ensure full effectiveness of the carbonate acidizing treatment Application of the developed expert system to carbonate acidizing treatment design has been illustrated using several documented case histories. The acidizing guidelines used in the system replicate the standard field procedures and practices for carbonate reservoir acidizing. Implementation of these guidelines contributes in improving the success rate of the acidizing treatment and avoiding the financial losses associated with design failuresen_US
dc.language.isoenen_US
dc.publisher Kuwait university - college of graduate studiesen_US
dc.subjectCarbonate, Acid, Stimulation, Automation, Expert, Systemen_US
dc.titleAn Automated System for Design of Matrix Acidizing in Carbonate Formationsen_US
dc.title.alternativeنظام آلي لتصميم تحميض المصفوفة في تكوينات الكربوناتen_US
dc.contributor.supervisorProf. Ali A. Garrouchen_US
dc.contributor.universityID214127525en_US
dc.description.conclusionsAn automated carbonate matrix acidizing expert system has been developed in this study to run as an application using Java Applet. The approach implemented in the carbonate matrix acidizing expert system is developed based on an acidizing procedure that consists of several stages which includes specific guidelines formed as decision trees. These stages are the pre-flush stage, main acid stage, diversion stage, and post-flush stage. Also, it includes the additives that are recommended to be used in the treatment and mixed with either the pre-flush, or the main acid stage. The recommended treatment focuses on a number of specific conditions including high reservoir temperature, presence of H2S and, the significance of iron content, low temperature dolomite formations, and the presence of asphaltene, scale and wax deposits The expert system that was built in this study accounts for the mineralogical compatibility of the rock with the injected acids and additives. Also, it accounts for the compatibility of the injected acid with the in-situ crude oil, the reservoir temperature, and the damage type that exist. The development of the reasoning logic of the automated carbonate matrix acidizing expert system has been accomplished, along with the implementation of the expert system which replicates the standard field procedures and the practices followed by the field experts for carbonate reservoir acidizing. The development of the expert system was achieved through coding the reasoning logic represented in the decision trees. Exsys® Corvid software has been used in implementing and developing the carbonate matrix acidizing expert system. It is an expert system development tool that can be used to automate decision-making processes by defining variables, creating IF-THEN rules, developing Logic Blocks and Command Blocksen_US
dc.relation.program2090  Petroleum Engineering and Geosciencesen_US
dc.contributor.cosupervisorProf. Haitham M.S. Lababidien_US
dc.date.semesterFallen_US
dc.description.examinationYen_US
dc.description.gpa3.79en_US
dc.description.credits33en_US
dc.description.degreeDegree in: Petroleum Engineeringen_US
Appears in Programs:0650 Petroleum Engineering
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