3D Stochastic Stratigraphic Well Correlation of Carbonate Ramp Systems

Florent Lallier and Sophie Viseur and Jean Borgomano and Guillaume Caumon. ( 2009 )
in: 2009 International Petroleum Technology Conference

Abstract

In the static and dynamic workflow of carbonate reservoirs, stratigraphic correlation of well data is one of the first and most influent steps. Indeed, facies distribution and petrophysical properties mainly control flow simulation and are often computed thanks to geostatistical methods, on grids based on stratigraphic correlation and structural data interpreted from seismic data (Borgomano [2008]). In reservoir uncertainty modeling approaches, a unique grid is built, and uncertainties about layering geometry, facies distribution and petrophysical properties are handled using multiple geostatistical simulations (Charles et al, 2001). This article aims at assessing uncertainties due to stratigraphic correlations by also generating several set of possible stratigraphic well correlations. Several grids may then be built from these results and used for facies and property modeling. The method presented here generates automatically and stochastically sequence stratigraphic correlations of carbonate ramp systems by hierarchically integrating multiple pieces of 3D information as: (1) interpreted well data, (2) correlation lines extracted from seismic, and (3) information obtained on analogs. To perform the correlation, we propose a multi-dimensional and stochastic extension of the Dynamic Time Warping Algorithm.

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BibTeX Reference

@INPROCEEDINGS{lallierIPTC,
    author = { Lallier, Florent and Viseur, Sophie and Borgomano, Jean and Caumon, Guillaume },
     title = { 3D Stochastic Stratigraphic Well Correlation of Carbonate Ramp Systems },
     month = { "dec" },
 booktitle = { 2009 International Petroleum Technology Conference },
      year = { 2009 },
       doi = { 10.2523/IPTC-14046-ABSTRACT },
  abstract = { In the static and dynamic workflow of carbonate reservoirs, stratigraphic correlation of well data is one of the first and most influent steps. Indeed, facies distribution and petrophysical properties mainly control flow simulation and are often computed thanks to geostatistical methods, on grids based on stratigraphic correlation and structural data interpreted from seismic data (Borgomano [2008]). In reservoir uncertainty modeling approaches, a unique grid is built, and uncertainties about layering geometry, facies distribution and petrophysical properties are handled using multiple geostatistical simulations (Charles et al, 2001). This article aims at assessing uncertainties due to stratigraphic correlations by also generating several set of possible stratigraphic well correlations. Several grids may then be built from these results and used for facies and property modeling. The method presented here generates automatically and stochastically sequence stratigraphic correlations of carbonate ramp systems by hierarchically integrating multiple pieces of 3D information as: (1) interpreted well data, (2) correlation lines extracted from seismic, and (3) information obtained on analogs. To perform the correlation, we propose a multi-dimensional and stochastic extension of the Dynamic Time Warping Algorithm. }
}