Computer-assisted stochastic multi-well correlation: Sedimentary facies versus well distality

Paul Baville and Marcus Apel and Silvan Hoth and Dirk Knaust and Christophe Antoine and C├ędric Carpentier and Guillaume Caumon. ( 2022 )
in: Marine and Petroleum Geology, 135 (105371)

Abstract

Computer-assisted stratigraphic correlation can help to produce several scenarios reflecting interpretation uncertainties. In this work, we propose a method which translates sedimentary concepts into a correlation cost for each possible stratigaphic correlation. All these correlation costs are used to populate a cost matrix in order to apply the Dynamic Time Warping algorithm and to compute the n-best correlation sets having the n-least cumulative costs. The proposed cost function reflects prior knowledge about sediment transport direction, and it is tested on two wells penetrating a Middle Jurassic reservoir in the North Sea. Well markers are described by two parameters: (1) the sedimentary facies corresponding to a depositional environment, and (2) the relative distality of the well computed from its position along the sediment transport direction. The main principle of correlation used in this article assumes that a well marker (described by a facies and a distality) cannot be correlated with another well marker described by a depositionally deeper facies at a more proximal position, or a depositionally shallower facies at a more distal position. This approach produces consistent stratigraphic well correlations, and highlights the sensitivity of the solution to the facies zonation and to the relative well distality. Therefore, the proposed rule offers a way to coherently consider chronostratigraphic correlation and the associated uncertainties at the parasequence scale, i.e., at a smaller scale than generally considered in deterministic correlation.

Download / Links

BibTeX Reference

@article{baville:hal-03928044,
 abstract = {Computer-assisted stratigraphic correlation can help to produce several scenarios reflecting interpretation uncertainties. In this work, we propose a method which translates sedimentary concepts into a correlation cost for each possible stratigaphic correlation. All these correlation costs are used to populate a cost matrix in order to apply the Dynamic Time Warping algorithm and to compute the n-best correlation sets having the n-least cumulative costs. The proposed cost function reflects prior knowledge about sediment transport direction, and it is tested on two wells penetrating a Middle Jurassic reservoir in the North Sea. Well markers are described by two parameters: (1) the sedimentary facies corresponding to a depositional environment, and (2) the relative distality of the well computed from its position along the sediment transport direction. The main principle of correlation used in this article assumes that a well marker (described by a facies and a distality) cannot be correlated with another well marker described by a depositionally deeper facies at a more proximal position, or a depositionally shallower facies at a more distal position. This approach produces consistent stratigraphic well correlations, and highlights the sensitivity of the solution to the facies zonation and to the relative well distality. Therefore, the proposed rule offers a way to coherently consider chronostratigraphic correlation and the associated uncertainties at the parasequence scale, i.e., at a smaller scale than generally considered in deterministic correlation.},
 author = {Baville, Paul and Apel, Marcus and Hoth, Silvan and Knaust, Dirk and Antoine, Christophe and Carpentier, C{\'e}dric and Caumon, Guillaume},
 doi = {10.1016/j.marpetgeo.2021.105371},
 hal_id = {hal-03928044},
 hal_version = {v1},
 journal = {{Marine and Petroleum Geology}},
 keywords = {Stratigraphic correlation ; Uncertainty assessment ; Stochastic simulation ; Sediment routing ; Dynamic Time Warping algorithm},
 month = {January},
 pages = {105371},
 pdf = {https://hal.univ-lorraine.fr/hal-03928044/file/article%20-%20v9%20-%20Submission.pdf},
 publisher = {{Elsevier}},
 title = {{Computer-assisted stochastic multi-well correlation: Sedimentary facies versus well distality}},
 url = {https://hal.univ-lorraine.fr/hal-03928044},
 volume = {135},
 year = {2022}
}