http://www.colloquiam.com/wd/index.php?action=history&feed=atom&title=Siemann%2A_et_al_2024aSiemann* et al 2024a - Revision history2026-05-11T11:37:12ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10http://www.colloquiam.com/wd/index.php?title=Siemann*_et_al_2024a&diff=301197&oldid=prevJSanchez: JSanchez moved page Draft Sanchez Pinedo 735961608 to Siemann* et al 2024a2024-06-06T13:49:07Z<p>JSanchez moved page <a href="/public/Draft_Sanchez_Pinedo_735961608" class="mw-redirect" title="Draft Sanchez Pinedo 735961608">Draft Sanchez Pinedo 735961608</a> to <a href="/public/Siemann*_et_al_2024a" title="Siemann* et al 2024a">Siemann* et al 2024a</a></p>
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</td></tr></table>JSanchezhttp://www.colloquiam.com/wd/index.php?title=Siemann*_et_al_2024a&diff=301196&oldid=prevJSanchez at 13:48, 6 June 20242024-06-06T13:48:12Z<p></p>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>The further development of offshore windfarm areas in various countries plays a key role in the transition of energy production towards renewable sources. As offshore windfarm areas tend to expand and the amount of ground truth data is limited, the estimation of geotechnical parameters at unknown locations integrating other site investigation data becomes a necessary tool. This is especially relevant for cost efficient area wide site characterization. Here, the proper integration and correlation of geotechnical and geophysical data is a key factor for reliable ground model building. This study investigates different prediction methods, while presenting a modelling framework which incorporates geological, geotechnical, and geophysical information to derive synthetic Cone Penetration Testing (CPT) profiles using offshore windfarm site investigation data from the German North Sea. We combine geological interpretation, CPT data and 2D ultra high-resolution seismic reflection data. The geophysical and geological information are used to guide geotechnical parameter prediction. Additionally, seismic horizons constrain the prediction as structural information. For evaluation, we test and compare several prediction techniques, with different level of complexity, from geostatistical methods to machine learning. Seismic attributes are used as auxiliary information to improve CPT parameter prediction. To validate the results, CPT parameters are predicted onto a representative 2D seismic line and a leave-one-out cross-validation (blindtest) is performed. Though all methods struggle to replicate local extremes, results indicate a reduction of prediction uncertainty when implementing seismic attributes.</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>The further development of offshore windfarm areas in various countries plays a key role in the transition of energy production towards renewable sources. As offshore windfarm areas tend to expand and the amount of ground truth data is limited, the estimation of geotechnical parameters at unknown locations integrating other site investigation data becomes a necessary tool. This is especially relevant for cost efficient area wide site characterization. Here, the proper integration and correlation of geotechnical and geophysical data is a key factor for reliable ground model building. This study investigates different prediction methods, while presenting a modelling framework which incorporates geological, geotechnical, and geophysical information to derive synthetic Cone Penetration Testing (CPT) profiles using offshore windfarm site investigation data from the German North Sea. We combine geological interpretation, CPT data and 2D ultra high-resolution seismic reflection data. The geophysical and geological information are used to guide geotechnical parameter prediction. Additionally, seismic horizons constrain the prediction as structural information. For evaluation, we test and compare several prediction techniques, with different level of complexity, from geostatistical methods to machine learning. Seismic attributes are used as auxiliary information to improve CPT parameter prediction. To validate the results, CPT parameters are predicted onto a representative 2D seismic line and a leave-one-out cross-validation (blindtest) is performed. Though all methods struggle to replicate local extremes, results indicate a reduction of prediction uncertainty when implementing seismic attributes.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">== Full Paper ==</ins></div></td></tr>
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</table>JSanchezhttp://www.colloquiam.com/wd/index.php?title=Siemann*_et_al_2024a&diff=301194&oldid=prevJSanchez at 13:48, 6 June 20242024-06-06T13:48:01Z<p></p>
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<td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 13:48, 6 June 2024</td>
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<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">                                </ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">==Abstract==</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">The further development of offshore windfarm areas in various countries plays a key role in the transition of energy production towards renewable sources. As offshore windfarm areas tend to expand and the amount of ground truth data is limited, the estimation of geotechnical parameters at unknown locations integrating other site investigation data becomes a necessary tool. This is especially relevant for cost efficient area wide site characterization. Here, the proper integration and correlation of geotechnical and geophysical data is a key factor for reliable ground model building. This study investigates different prediction methods, while presenting a modelling framework which incorporates geological, geotechnical, and geophysical information to derive synthetic Cone Penetration Testing (CPT) profiles using offshore windfarm site investigation data from the German North Sea. We combine geological interpretation, CPT data and 2D ultra high-resolution seismic reflection data. The geophysical and geological information are used to guide geotechnical parameter prediction. Additionally, seismic horizons constrain the prediction as structural information. For evaluation, we test and compare several prediction techniques, with different level of complexity, from geostatistical methods to machine learning. Seismic attributes are used as auxiliary information to improve CPT parameter prediction. To validate the results, CPT parameters are predicted onto a representative 2D seismic line and a leave-one-out cross-validation (blindtest) is performed. Though all methods struggle to replicate local extremes, results indicate a reduction of prediction uncertainty when implementing seismic attributes.</ins></div></td></tr>
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</table>JSanchezhttp://www.colloquiam.com/wd/index.php?title=Siemann*_et_al_2024a&diff=301193&oldid=prevJSanchez: Created blank page2024-06-06T13:47:50Z<p>Created blank page</p>
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