Computer-assisted stochastic multi-well correlation: Depositional surface interpolation versus theoretical depositional profile
Paul Baville and Marcus Apel and Silvan Hoth and Dirk Knaust and Christophe Antoine and Cédric Carpentier and Guillaume Caumon. ( 2022 )
in: 21st Annual Conference of the IAMG, International Association for Mathematical Geosciences
Abstract
Assisted well correlation aims at complementing sedimentological expertise with computational rigor to increase automation, improve reproducibility and assess uncertainties during stratigraphic correlation. In this work, a computer-assisted method is proposed to automatically generate possible well correlations based on facies interpretation, dipmeter data and prior knowledge about depositional environments. Facies interpretation and dipmeter data may be used to interpolate three-dimensional surfaces using the three-dimensional Bézier cubic curves between pairs of well markers and triangular Bézier cubic patches between triplets of well markers. These curves and surfaces are compared to a theoretical depositional profile generated from depositional environment knowledge by computing the area between the curves and the profile, or the volume between the patches and the profile. The main principle of correlation used in this method assumes that these areas and volumes may be linked to the likelihood of each possible correlation: the higher the area or the volume, the lower the correlation likelihood. Well correlations are computed using correlation costs between all possible marker combinations aggregated by the Dynamic Time Warping Algorithm. The proposed method produces consistent stratigraphic well correlation with respect to the data set. However, this approach is highly sensitive to the well order of correlation because of the Dynamic Time Warping Algorithm.
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BibTeX Reference
@inproceedings{baville:hal-03909438, abstract = {Assisted well correlation aims at complementing sedimentological expertise with computational rigor to increase automation, improve reproducibility and assess uncertainties during stratigraphic correlation. In this work, a computer-assisted method is proposed to automatically generate possible well correlations based on facies interpretation, dipmeter data and prior knowledge about depositional environments. Facies interpretation and dipmeter data may be used to interpolate three-dimensional surfaces using the three-dimensional Bézier cubic curves between pairs of well markers and triangular Bézier cubic patches between triplets of well markers. These curves and surfaces are compared to a theoretical depositional profile generated from depositional environment knowledge by computing the area between the curves and the profile, or the volume between the patches and the profile. The main principle of correlation used in this method assumes that these areas and volumes may be linked to the likelihood of each possible correlation: the higher the area or the volume, the lower the correlation likelihood. Well correlations are computed using correlation costs between all possible marker combinations aggregated by the Dynamic Time Warping Algorithm. The proposed method produces consistent stratigraphic well correlation with respect to the data set. However, this approach is highly sensitive to the well order of correlation because of the Dynamic Time Warping Algorithm.}, address = {Nancy, France}, author = {Baville, Paul and Apel, Marcus and Hoth, Silvan and Knaust, Dirk and Antoine, Christophe and Carpentier, C{\'e}dric and Caumon, Guillaume}, booktitle = {{21st Annual Conference of the IAMG}}, hal_id = {hal-03909438}, hal_version = {v1}, month = {August}, organization = {{International Association for Mathematical Geosciences}}, title = {{Computer-assisted stochastic multi-well correlation: Depositional surface interpolation versus theoretical depositional profile}}, url = {https://hal.science/hal-03909438}, year = {2022} }