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Quantitative seismic attribute analysis using artificial neural networks and seismic stratigraphic interpretation of lower to middle Miocene sediments offshore New Jersey
Descriptive
TitleInfo
Title
Quantitative seismic attribute analysis using artificial neural networks and seismic stratigraphic interpretation of lower to middle Miocene sediments
offshore New Jersey
offshore New Jersey
Name
(type = personal)
NamePart
(type = family)
Karakaya
NamePart
(type = given)
Sarp
NamePart
(type = date)
1984-
DisplayForm
SARP KARAKAYA
Role
RoleTerm
(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Mountain
NamePart
(type = given)
Gregory
DisplayForm
Gregory Mountain
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
chair
Name
(type = personal)
NamePart
(type = family)
Miller
NamePart
(type = given)
Kenneth G.
DisplayForm
Kenneth G. Miller
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Monteverde
NamePart
(type = given)
Donald
DisplayForm
Donald Monteverde
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = corporate)
NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
(type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm
(authority = RULIB)
school
TypeOfResource
Text
Genre
(authority = marcgt)
theses
OriginInfo
DateCreated
(qualifier = exact)
2012
DateOther
(qualifier = exact);
(type = degree)
2012-10
Place
PlaceTerm
(type = code)
xx
Language
LanguageTerm
(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
This study comprises two parts intended to improve understanding of the lower and middle Miocene depositional history of the New Jersey continental shelf. The first, lower Miocene-based part, aims to determine lateral variations in lithofacies between holes drilled by IODP Expedition 313 using seismic attributes and artificial neural networks. The second provides detailed seismic sequence stratigraphy of mid-Miocene successions. Neural networks are used in the first part to search for a relationship between seismic attributes and gamma log measurements of the lower Miocene section. Using this relationship, the networks generate 'pseudo gamma logs' that predict lateral changes in lithofacies based on accompanying changes in seismic attributes. A successful test of the technique is demonstrated using 3D seismic data and 6 closely-spaced gamma raylogs from the Denver Basin. A similar application to lower Miocene successions offshore NJ is unsuccessful, most likely due to an insufficient number of wells, complexity of lithofacies variations between wells up to 12 km apart, and/or an incorrect selection of attributes. In the second part, candidate sequence boundaries are identified in a grid of high- resolution, densely spaced profiles. In addition to a more detailed history than derived from prior studies, this part reveals previously unreported records of sediment erosion and possible global climate influence on the middle Miocene stratigraphic evolution offshore New Jersey. Eleven candidate sequence boundaries, three not documented by previous studies, are identified. System tract positions of each sequence are determined, while only one transgressive system tract and no lowstand fans are observed. Age estimates based on published studies show that the 11 mid Miocene sequences reported here span the interval between ~11.8-12.9 Ma, suggesting an average interval between each of 100 kyr. Clinoform rollovers prograded SE during the development of the oldest sequence of the study area beginning at a time that coincides with a major shift in !18O towards heavier values (represented by Mi4) and at about the time of the permanent East Antarctic ice sheet development. Grain size distribution of the prograding clinoforms is predicted by extrapolating IODP Expedition 313’s lithostratigraphic analysis of lower Miocene succession.
Subject
(authority = RUETD)
Topic
Geological Sciences
RelatedItem
(type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
Identifier
ETD_4193
PhysicalDescription
Form
(authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
xv, 190 p. : ill., maps
Note
(type = degree)
M.S.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Sarp Karakaya
Subject
(authority = ETD-LCSH)
Topic
Continental shelf--New Jersey
Subject
(authority = ETD-LCSH)
Topic
Geology, Stratigraphic--Miocene
Subject
(authority = ETD-LCSH)
Topic
Seismology--Research
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066840
RelatedItem
(type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
(type = local)
rucore19991600001
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3KD1WPM
Genre
(authority = ExL-Esploro)
ETD graduate
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Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
KARAKAYA
GivenName
SARP
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = start)
2012-08-15 15:08:15
AssociatedEntity
Name
SARP KARAKAYA
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
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111797760
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