Abstract

Relative permeability data are very important for reservoir engineering, because these parameters highly influence waterflooding efficiency, oil/liquid production forecast and therefore economics of an asset.

Core experiments for determination of relative permeability curves are point-wise and do not completely reconstruct formation conditions. Application of core relative permeabilities on field scale may lead to inadequate modeling of real flow conditions and result in actual production not complying with forecast during commercial exploitation.

Current structure of Russian Federation oil resources is such that most of the promising oil and gas regions are at full autonomy conditions, with lack of year-round road connection and infrastructure for production transfer. Thus, new techniques are required for acquisition of parameters important for reservoir engineering (including in-situ relative permeabilities), which are well-suited to production limits during pilot field study program.

A promising approach to in-situ determination of flow parameters is well testing. A well test technique for determining oil and water relative permeabilities developed at OGRI RAS is based on generation of multidirectional two-phase flows and provides data for determination of an extended set of formation characteristics. Interpretation includes special algorithms and software with application of numerical methods for direct problem solution and optimal control methods for inverse problem solution.

Well test for determination of in-situ relative permeabilities described in the paper has been performed at an oilfield in Western Siberia at conditions of arctic climate and full autonomy.

Results of the well test led to:

  • correction of relative permeability data earlier obtained from core analysis,

  • establishing higher water mobility in full range of water saturations and probably no increased threshold of water mobility (critical saturation);

  • adjustment of oil and liquid production plan for full field development project, which resulted in more reasonable estimation of asset investment attractiveness and optimal decision on recovery strategy.

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