A hierarchical stochastic modeling approach for representing point bar geometries and petrophysical property variations

Ismael Dawuda, Sanjay Srinivasan

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


The flow of fluids in point bars is affected by the existence of heterogeneities like shale drapes that are found on the surfaces of inclined heterolithic stratifications. In fact, these shale drapes can act as fluid flow baffles; therefore, developing a framework for modeling point bars and their associated heterogeneities is vital. In this study, a stochastic process-based modeling approach is presented for capturing the main point bar heterogeneities: accretion surfaces (i.e., the aerial heterogeneity) and inclined heterolithic stratifications (i.e., the vertical heterogeneity). The former was modeled using a sine-generation function and the latter, with a sigmoidal function after which they were combined into a 3D point bar model. To ensure proper modeling of petrophysical properties, we developed a more representative gridding scheme which generates curvilinear grids representative of the point bar geometry. This grid was then transformed into a rectilinear grid to allow for geostatistical simulation after which all petrophysical properties were mapped back into the original curvilinear grid. An essential element of this modeling approach is the stochastic representation of shale drapes at the interface between successive accretion surfaces. The workflow was tested using a real field dataset for the Cranfield field, Mississippi. The constructed model was then subjected to a flow simulation study mimicking a CO2 storage scenario. Various sensitivities were simulated to evaluate the effect of heterogeneities on CO2 flow within the point-bar. Results demonstrate the importance of representing point-bar related heterogeneity and the spatial distribution of shale drapes on CO2 plume migration and storage.

Original languageEnglish (US)
Article number105127
JournalComputers and Geosciences
StatePublished - Jul 2022

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computers in Earth Sciences


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