Abstract

The case study here presented supports the on-going EOR development project of a low net-to-gross fluvial system producing viscous oil form a thick sedimentary column in San Jorge Gulf Basin, Argentina. The selected strategy consists in combining dynamic modeling, analytic tools and field measurements to assess field potential and to model uncertainty through different yet plausible deterministic scenarios.

The selected area is Los Perales field in Southern Argentina, with 2880 wells producing from more than 1000 m thick column of thin fluvial sandstone bodies and tuffaceous shale floodplain intercalations. This is a mature field extensively drilled, although single sand extension is likely to be below well spacing. Sands are captured by well logs but have no seismic representation, making connectivity prediction in between wells critical for any IOR or EOR project. For this reason, sand lateral connectivity is estimated by statistical tools, and then several plausible 3D connectivity scenarios are used to model geological uncertainty. Simple analytical tools support simulation results on the identification of key dynamic factors affecting polymer flood incremental volumes. Nevertheless, different modeling approaches are here combined to build deterministic scenarios such as fine scale 2D section models and different resolution 3D sector models for different purposes.

We estimate that, given the adverse mobility ratio, when 45% water saturation is reached in the reservoir water sweep efficiency becomes so dramatically low that almost no oil is pushed and water cut raises over 95% as historical production data shows during the 25-year water-flood history in the field. The resulting low recovery factor presents a huge opportunity for polymer flood not only in the already swept areas and heterogeneous regions but also in some unproduced layers with water forecast on swabbing tests. A zone-ranking based on a vertical proportion curve for reservoir and non-reservoir intervals allows us to narrow the development to lower risk confined regions. Further investigation and detail modelling in these regions permit us to assess uncertainty and estimate incremental volumes as up to 3 times those recovered by water-flooding. Production logging confirmed the relevance of targeted intervals in well production, hence supporting polymer business case.

This methodology is used to forecast, rank and select the best areas for polymer flood. This integrated approach combines geology, petrophysics and engineering using several laboratory tests, multiple deterministic scenarios and statistical tools to analyze polymer flood opportunities in a large field producing from a low net-to-gross thick sedimentary column.

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