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dc.contributor.advisorBasarir, Hakan
dc.contributor.advisorPan, Yutao
dc.contributor.advisorBerger, Sean Peter
dc.contributor.authorMinnaard, Cornelis (Koen) W.
dc.date.accessioned2022-10-18T17:19:31Z
dc.date.available2022-10-18T17:19:31Z
dc.date.issued2022
dc.identifierno.ntnu:inspera:116344653:65370244
dc.identifier.urihttps://hdl.handle.net/11250/3026779
dc.descriptionFull text not available
dc.description.abstract
dc.description.abstractMeasure While Drilling data is collected during production drilling in the Elkem Tana open pit mine. This data is currently underused in creating and updating the geological model of the ore body in the mine. Data collected during drilling of the bench can be used to predict the lithology in the bench, before the bench is produced. This report differentiates between three lithologies; namely Quartzite, which is the product; Schist, which is waste; and a transition layer in between containing both schist and quartzite, which is also waste. A 4D geological model was created of the bench in question, using 3D lidar scans from February to December 2021, by following the lithology boundaries over the time this bench is produced. This geological model was then correlated with the MWD data available for 446 boreholes present in this bench. The six available MWD parameters were analysed on its sensitivity in predicting lithology, with the goal to be able to differentiate between quartzite and schist from the MWD data. It was found that dampening pressure, feed pressure and percussion pressure accounted for the majority of variation in the data, and they are moderately (0,71) to strongly (0,88) correlated. A model can be created from this to detect the schist and quartzite to update the geological model. In general, the quartzite tends to be drilled at a slower rate, while using high percussion- high feed- and high dampening pressures. Schist shows the inverse with low percussion- low feed- and low dampening pressures, drilled at a higher rate.
dc.languageeng
dc.publisherNTNU
dc.title4D Geomodelling using Lidar scans and MWD data analysis
dc.typeMaster thesis


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