Prediction of interface of geological formations using generalized additive model

Xiaohui Qi, Zhiyong Yang*, Jian Chu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Geological information such as geological interfaces is important for the design of underground excavation and supporting measures. This in turn requires a method to predict accurately the locations of geological interfaces for the gap areas between boreholes. This study presents a generalized additive model (GAM) to predict the location of the geological interfaces. The performance of the GAM method is evaluated using both simulated data and borehole data for the determination of rockhead in two different geological formations in Singapore. The results show that the GAM method can provide a reasonable confidence interval (CI) of the mean trend and the prediction interval (PI) in the sense that the 95% CI covers about 95% of the actual mean curve while the 95% PI covers around 95% of testing data. Furthermore, the geological complexity can be well reflected as the prediction uncertainty in the geologically complex area is larger than that in the geologically regular area. More importantly, the users can impose prior information or personal judgment regarding the shape of the geological profile on the model. This is an important feature to enable further improvement in the accuracy of the prediction. Highlights A generalized additive model is used to predict the location of the geological interfaces The performance of the GAM method is evaluated using both simulated data and actual borehole data from Singapore The results show that the GAM method can provide a reasonable confidence interval of the mean trend and the prediction interval of a prediction Geological complexity can be well reflected in the sense that the prediction uncertainty in the geologically complex area is relatively large Expert judgment or knowledge on the geological profile can be applied to the model, which improves the prediction accuracy.

Original languageEnglish
Pages (from-to)127-139
Number of pages13
JournalGeorisk
Volume16
Issue number1
DOIs
Publication statusPublished - 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 Informa UK Limited, trading as Taylor & Francis Group.

ASJC Scopus Subject Areas

  • Civil and Structural Engineering
  • Building and Construction
  • Safety, Risk, Reliability and Quality
  • Geotechnical Engineering and Engineering Geology
  • Geology

Keywords

  • cubic spline
  • generalized additive model
  • geological interface
  • Spatial prediction

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