Quantitative seismic attribute analysis using artificial neural networks and seismic stratigraphic interpretation of lower to middle Miocene sedimentsoffshore New Jersey

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 seism...

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Main Author: Karakaya, Sarp
Format: Text
Language:unknown
Published: No Publisher Supplied 2012
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Online Access:https://dx.doi.org/10.7282/t3kd1wpm
https://rucore.libraries.rutgers.edu/rutgers-lib/39123/
id ftdatacite:10.7282/t3kd1wpm
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spelling ftdatacite:10.7282/t3kd1wpm 2023-05-15T13:50:23+02:00 Quantitative seismic attribute analysis using artificial neural networks and seismic stratigraphic interpretation of lower to middle Miocene sedimentsoffshore New Jersey Karakaya, Sarp 2012 https://dx.doi.org/10.7282/t3kd1wpm https://rucore.libraries.rutgers.edu/rutgers-lib/39123/ unknown No Publisher Supplied Text article-journal ScholarlyArticle 2012 ftdatacite https://doi.org/10.7282/t3kd1wpm 2021-11-05T12:55:41Z 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. Text Antarc* Antarctic Ice Sheet DataCite Metadata Store (German National Library of Science and Technology) Antarctic East Antarctic Ice Sheet
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
description 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.
format Text
author Karakaya, Sarp
spellingShingle Karakaya, Sarp
Quantitative seismic attribute analysis using artificial neural networks and seismic stratigraphic interpretation of lower to middle Miocene sedimentsoffshore New Jersey
author_facet Karakaya, Sarp
author_sort Karakaya, Sarp
title Quantitative seismic attribute analysis using artificial neural networks and seismic stratigraphic interpretation of lower to middle Miocene sedimentsoffshore New Jersey
title_short Quantitative seismic attribute analysis using artificial neural networks and seismic stratigraphic interpretation of lower to middle Miocene sedimentsoffshore New Jersey
title_full Quantitative seismic attribute analysis using artificial neural networks and seismic stratigraphic interpretation of lower to middle Miocene sedimentsoffshore New Jersey
title_fullStr Quantitative seismic attribute analysis using artificial neural networks and seismic stratigraphic interpretation of lower to middle Miocene sedimentsoffshore New Jersey
title_full_unstemmed Quantitative seismic attribute analysis using artificial neural networks and seismic stratigraphic interpretation of lower to middle Miocene sedimentsoffshore New Jersey
title_sort quantitative seismic attribute analysis using artificial neural networks and seismic stratigraphic interpretation of lower to middle miocene sedimentsoffshore new jersey
publisher No Publisher Supplied
publishDate 2012
url https://dx.doi.org/10.7282/t3kd1wpm
https://rucore.libraries.rutgers.edu/rutgers-lib/39123/
geographic Antarctic
East Antarctic Ice Sheet
geographic_facet Antarctic
East Antarctic Ice Sheet
genre Antarc*
Antarctic
Ice Sheet
genre_facet Antarc*
Antarctic
Ice Sheet
op_doi https://doi.org/10.7282/t3kd1wpm
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