Log-Derived Multi-variate Modeling and Subsurface Interpretation
Download this free whitepaper that showcases a case study on semi-automated, basin-scale geomodelling.
There is a clear need for automation to improve efficiency and reproducibility during the correlation and interpretation of well logs—both of which are labor-intensive tasks essential for building large-scale stratigraphic models in multi-variate analytics, geomodelling, and reservoir simulation workflows. Dynamic time warping and AI are promising techniques to automate these workflows.
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There is a clear need for automation to improve efficiency and reproducibility during the correlation and interpretation of well logs—both of which are labor-intensive tasks essential for building large-scale stratigraphic models in multi-variate analytics, geomodelling, and reservoir simulation workflows. Dynamic time warping and AI are promising techniques to automate these workflows.
Through a case study describing chronostratigraphic diagrams and log correlations generated with an automate stratigraphic correlation workflow, this whitepaper outlines how:
- The ChronoLog automated stratigraphic correlation pipeline was employed to develop a geologic model of the Midland Basin’s subsurface geology
- These techniques increased the accuracy and efficiency of constructing 3D stratigraphic and property models
- The resulting interpretation is being evaluated and is being used across various workflows
- The full 3D geologic volumes from this model are being used to populate geomodels for well planning, geosteering, detailed reservoir studies, and reservoir simulations
Download the full white paper here.