Due to associated uncertainties,modelling the spatial distribution of depth to bedrock(DTB) is an important and challenging concern in many geo-engineering applications.The association between DTB,the safety and econo...Due to associated uncertainties,modelling the spatial distribution of depth to bedrock(DTB) is an important and challenging concern in many geo-engineering applications.The association between DTB,the safety and economy of design structures implies that generating more precise predictive models can be of vital interest.In the present study,the challenge of applying an optimally predictive threedimensional(3D) spatial DTB model for an area in Stockholm,Sweden was addressed using an automated intelligent computing design procedure.The process was developed and programmed in both C++and Python to track their performance in specified tasks and also to cover a wide variety of diffe rent internal characteristics and libraries.In comparison to the ordinary Kriging(OK) geostatistical tool,the superiority of the developed automated intelligence system was demonstrated through the analysis of confusion matrices and the ranked accuracies of different statistical errors.The re sults showed that in the absence of measured data,the intelligence models as a flexible and efficient alternative approach can account for associated uncertainties,thus creating more accurate spatial 3D models and providing an appropriate prediction at any point in the subsurface of the study area.展开更多
The Troy Bedrock Valley (TBV) and its tributary valleys are the principal pre-glacial drainage in southern Wisconsin and northern Illinois, USA. This study focused on the headwaters of a tributary that occurs in McHen...The Troy Bedrock Valley (TBV) and its tributary valleys are the principal pre-glacial drainage in southern Wisconsin and northern Illinois, USA. This study focused on the headwaters of a tributary that occurs in McHenry County, IL. Drilling, geophysical surveys, and the analysis of existing geologic and water well data were used to determine the lithologic and geometric characteristics of the sediments that fill the paleovalley. A 3D geologic model of these sediments was then developed in Petrel. More than 65 m of Quaternary sediments filled the paleovalley. The model domain covers approximately 30 km<sup>2</sup>. The valley drains to the west and meanders, which is distinct from the straight course of the overlying modern Kishwaukee River. The sediments that filled the valley were subdivided into five units. These units include Illinois-age Glasford Formation coarse-grained proglacial outwash and alluvial deposits (GS2, GS1) and fine-grained lacustrine and diamicton deposits (G2 and G1). The Wisconsin-age Henry Formation sand and gravel cap the valley fill, and Cahokia alluvium buries everything.展开更多
基金funded through the support of the Swedish Transport Administration through Better Interactions in Geotechnics(BIG)the Rock engineering Research Foundation(BeFo)Tyrens AB。
文摘Due to associated uncertainties,modelling the spatial distribution of depth to bedrock(DTB) is an important and challenging concern in many geo-engineering applications.The association between DTB,the safety and economy of design structures implies that generating more precise predictive models can be of vital interest.In the present study,the challenge of applying an optimally predictive threedimensional(3D) spatial DTB model for an area in Stockholm,Sweden was addressed using an automated intelligent computing design procedure.The process was developed and programmed in both C++and Python to track their performance in specified tasks and also to cover a wide variety of diffe rent internal characteristics and libraries.In comparison to the ordinary Kriging(OK) geostatistical tool,the superiority of the developed automated intelligence system was demonstrated through the analysis of confusion matrices and the ranked accuracies of different statistical errors.The re sults showed that in the absence of measured data,the intelligence models as a flexible and efficient alternative approach can account for associated uncertainties,thus creating more accurate spatial 3D models and providing an appropriate prediction at any point in the subsurface of the study area.
文摘The Troy Bedrock Valley (TBV) and its tributary valleys are the principal pre-glacial drainage in southern Wisconsin and northern Illinois, USA. This study focused on the headwaters of a tributary that occurs in McHenry County, IL. Drilling, geophysical surveys, and the analysis of existing geologic and water well data were used to determine the lithologic and geometric characteristics of the sediments that fill the paleovalley. A 3D geologic model of these sediments was then developed in Petrel. More than 65 m of Quaternary sediments filled the paleovalley. The model domain covers approximately 30 km<sup>2</sup>. The valley drains to the west and meanders, which is distinct from the straight course of the overlying modern Kishwaukee River. The sediments that filled the valley were subdivided into five units. These units include Illinois-age Glasford Formation coarse-grained proglacial outwash and alluvial deposits (GS2, GS1) and fine-grained lacustrine and diamicton deposits (G2 and G1). The Wisconsin-age Henry Formation sand and gravel cap the valley fill, and Cahokia alluvium buries everything.
