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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Petroleum University of Technology</PublisherName>
				<JournalTitle>Iranian Journal of Oil and Gas Science and Technology</JournalTitle>
				<Issn>2345-2412</Issn>
				<Volume>4</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>05</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Comparison of Simulated Annealing, Genetic, and Tabu Search Algorithms for Fracture Network Modeling</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>50</FirstPage>
			<LastPage>67</LastPage>
			<ELocationID EIdType="pii">9592</ELocationID>
			
<ELocationID EIdType="doi">10.22050/ijogst.2015.9592</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Saeed</FirstName>
					<LastName>Mahmoodpour</LastName>
<Affiliation>Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohsen</FirstName>
					<LastName>Masihi</LastName>
<Affiliation>Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-2937-0668</Identifier>

</Author>
<Author>
					<FirstName>Sajjad</FirstName>
					<LastName>Gholinejhad</LastName>
<Affiliation>Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2014</Year>
					<Month>02</Month>
					<Day>23</Day>
				</PubDate>
			</History>
		<Abstract>The mathematical modeling of fracture networks is critical for the exploration and development of natural resources. Fractures can help the production of petroleum, water, and geothermal energy. They also greatly influence the drainage and production of methane gas from coal beds. Orientation and spatial distribution of fractures in rocks are important factors in controlling fluid flow. The objective function recently developed by Masihi et al. 2007 was used herein to generate fracture models that incorporate field observations. To extend this method, simulated annealing, genetic, and tabu search algorithms were employed in the modeling of fracture networks. The effectiveness of each algorithm was compared and the applicability of the methodology was assessed through a case study. It is concluded that the fracture model generated by simulated annealing is better compared to those generated by genetic and tabu search algorithms.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Spatial Configuration of Fractures</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Simulated Annealing</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Genetic algorithm</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Tabu Search Algorithm</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Fracture Network</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://ijogst.put.ac.ir/article_9592_b538f279cb2ca36268b23f557a831508.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
