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Relative permeabilities are very important for reservoir engineering, because these parameters highly influence waterflooding efficiency, oil/liquid production forecast and therefore economics of an asset. Evaluation of multiphase flow parameters from core data suffers from small REV and pointwise level of averaging. It distorts the actual flow conditions at the reservoir level, and their history matching from production data requires long history of waterflooding. The technological complexity of new oil reservoirs development rises the problem of determining the displacement effeciency (Edisp) and relative permeability functions (RP) in the downhole conditions for reliable evaluation of investment attractiveness of the asset and creating sound development of the project. This paper summarizes the experience and interpretation of two-phase well testing using OGRI RAS technology. Integrated well testing to determine Edisp and RP (for oil-water system) is based on the creation of two-phase (oil and water) multidirectional flows and repeatable recordings of pulsed neutron logging (PNL) to monitor changes in water saturation near wellbore. For reliable geophysical interpretation it is necessary to monitor changes in the water phase salinity in contact with formation water, injectied water and technological solutions. Integrated interpretation of such testing procedure is based on the numerical solution of direct and inverse problems in the two-dimensional, two-phase (oil-water), two (oil + water) or three (oil + water + salt) component statement. The experience of conducting and interpreting such tests for oil fields at the exploration stage and pilot projects in conditions of autonomy and arctic climate is delivered in the paper. Accumulated experience allowed us to justify the optimal design of the testing process, well preparation and the well testing procedure itself. Special schemes of downhole and wellhead equipment setup are devised for solving all the research problems without lifting operations. Original technical solutions for well completion and continuous pumping of water-based agent in arctic climate, with large permafrost interval and very low formation injectivity were also developed. Complex technique of joint geophysical and flow measurements interpretation in the course of well testing is substantiated. The effective numerical algorithms and software for solving inverse problems to identify oil and water RP at reservoir conditions in two-dimensional, two-phase (oil-water), two (oil + water) or three (oil + water + salt) component model were also proposed and validated. Significant effect of technological fluids penetration into the formation during well completion and tripping on reservoir water salinity in the near wellbore area is revealed, Simplified method of accounting for and controlling salinity changes during interaction between reservoir, injected and residual technological water phases is proposed. For the object tested, effective estimates of displacement efficiency and RP curves are obtained. These parameters substantially correct core data and provide more reliable prediction of water flooding system efficiency and assessment of the investment attractiveness of the asset.

Переход к 3D компьютерному моделированию остро поставил вопрос насыщения модели точной первичной информацией о коллекторских свойствах пласта.

Relative permeabilities (RP) play an important role in reservoir engineering. RP functions together with the permeability anisotropy coefficient predetermine waterflooding efficiency and oil/water ratio in production forecast. Traditionally multiphase flow parameters are estimated from core analysis data. But such measurements suffer from small representative elementary volume (REV) and limited characterization of reservoir properties. Therefore using core data in 3D reservoir modelling could lead to distorted description of actual flow conditions. Despite those functions (RP) could be history matched with assimilated production data, such a procedure would require long history of waterflooding. So the authors’ idea is to apply integrated well test study to estimate the displacement efficiency and/or relative permeability functions at downhole conditions. Well testing is traditionally applied in reservoir engineering for single-phase reservoir parameters estimation. Our approach is extended to multi-phase flow and is based on data collection at well bottomholes and subsequent data assimilation in flow model. In this paper we summarize both features of mathematical problem statement and identifiability of multiphase parameters through inverse problem solution, but also discuss 10+ -year experience in interpretation of two-phase well testing using our technologies. To estimate multiphase parameters, we have to jointly consider complex data of well logging and dynamic data of well testing. Both data sets are used in the inverse problem quality criteria, where the least squares method has been applied. Forward problem corresponds to a 3D multiphase fluid flow model in porous media. The latter consists of continuity equation with multiphase Darcy equation instead of moment balances. For data assimilation modern methods of optimal control theory were successfully applied. For all synthetic test cases real reservoir parameters were accurately recovered through the use of forward simulation data. In order to estimate reservoir heterogeneity, we applied a single-phase model to get the ratio of vertical to horizontal permeability. Data of well self-interference testing were used for vertical permeability estimation. Depending on the depth of reservoir pressure perturbation, reservoir properties could be properly inferred from observations. Two other options of 3D interference testing using vertical and horizontal wells are also presented. In other words, all the problems considered are identifiable, and the level of their correctness is completely predetermined by the amount and quality of observed data. And transition to digital (intelligent) oil-and-gas production and closed-loop reservoir management [1] provides a possibility to remove discussed restrictions and all inverse problems considered should be accounted as fully identifiable.

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