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Fractal pattern recognition and recreation
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
2012 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

It speaks by itself that in order to find oil, one must know where to look for it. In this thesis I have investigated and created new tools to find salt in the bedrock, and to recreate images according to some parameters, (fractal dimension and lacunarity). The oil prospecting company Schlumberger gathers nowadays a huge amount of seismic information. It is very time consuming to interpret the seismic data by hand. My task is to find a good way to detect salt in the seismic images of the underworld, that can then be used to classify the seismic data. The theory indicates that the salt behaves as fractals, and by studying the fractal dimension and lacunarity we can make a prediction of where the salt can be located. I have also investigated three different recreation techniques, so that one can go from parameters values (fractal dimension and lacunarity) back to a possible recreation.

It speaks by itself that in order to find oil, one must know where to look for it. In this

thesis I have investigated and created new tools to find salt in the bedrock, and to

recreate images according to some parameters, (fractal dimension and lacunarity).

The oil prospecting company Schlumberger gathers nowadays a huge amount of

seismic information. It is very time consuming to interpret the seismic data by hand.

My task is to find a good way to detect salt in the seismic images of the underworld,

that can then be used to classify the seismic data. The theory indicates that the salt

behaves as fractals, and by studying the fractal dimension and lacunarity we can make

a prediction of where the salt can be located. I have also investigated three different

recreation techniques, so that one can go from parameters values (fractal dimension

and lacunarity) back to a possible recreation.

Place, publisher, year, edition, pages
2012. , 87 p.
Series
UPTEC F, ISSN 1401-5757 ; 12030
Keyword [en]
fractal, pattern recognition, lacunarity, fractal dimension
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:uu:diva-181224OAI: oai:DiVA.org:uu-181224DiVA: diva2:555390
Educational program
Master Programme in Engineering Physics
Uppsok
Technology
Supervisors
Examiners
Available from: 2012-10-01 Created: 2012-09-19 Last updated: 2018-01-12Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • Other locale
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Output format
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