TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis work addresses the behavior and analysis procedures for injectivity tests on horizontal wells completed in an oilbearing reservoir. In general, pressure and pressure derivative behave quite similar to the single-phase solution calculated with oil properties, thus flow regimes can be identified by loglog plots. However, skin factor and effective well length estimates are severely affected if one neglects the effect caused by the contrast in fluid mobility. A simple approximate analytical solution for the wellbore pressure is derived in this work. The accuracy of this solution is verified by comparison of results obtained from a reservoir simulator using hybrid grids and local grid refinement. The analytical solution, supported by simulator results, indicates that the injected water going through a damaged zone has a strong and distinctive effect on both pressure and pressure derivative behavior at early times. It is also shown that, if relative permeability data are available, an equivalent single-phase data can be constructed from the measured wellbore pressures. These equivalent single-phase data can be analyzed by standard single-phase flow techniques for horizontal wells, providing reliable estimates for effective permeability, skin factor and effective wellbore length.

fax 01-972-952-9435. AbstractWe propose a novel well-test for in situ estimation of relative permeabilities under two-phase (oil-water) flow conditions. The test consists of three periods, (i) injection of water into an oil reservoir operating above bubble point pressure, (ii) a falloff test and (iii) a producing period. The producing period is critical as it yields production data that reflects changes in sandface mobility and thus is highly sensitive to the parameters used to model relative permeability curves, whereas, our results indicate that injection/falloff pressure data by themselves are not as reliable for defining relative permeability curves. We have developed optimization code based on the LevenbergMarquardt algorithm and coupled it with a commercial reservoir simulator to obtain a procedure for data analysis where the reservoir simulator is used as the forward model. By matching data by minimization of a weighted least squares objective function, we generate estimates of absolute permeability, relative permeabilities and the well skin factor. We show the method can be applied with either power law models or B-splines. We introduce a variable transformation that can be used to ensure that the estimated relative permeabilities are monotonic and concave up when B-splines are used.

∑ = − = Nobs i obs i sim i i d m d w m O 1 2 ) ( ) ( TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractOne of the challenges when making a history match study is to find an adequate parameterization for the reservoir model. The main assumptions of the geological characterization should be respect and the influence of parameters on the fluid flow simulation results should be taken into account. On the other hand, the number of parameters should be kept within reasonable bounds in order to make the process viable. In this work, three examples of novel ways to parameterize the history match problem will be shown. Two of them are real field cases and one is a synthetic case based on outcrop data. Common to all examples is the choice of parameters that are related to the geological model building process, such as the variogram in a geostatiscal modeling or correlations between petrophysical properties (permeability x porosity, for instance). In this context, the use of a versatile history matching tool was essential, allowing for a quantitative evaluation for the quality of the match and for managing a larger number of parameters, when comparing to the traditional trial and error procedure. These examples show how the combination of a suitable parameterization with a versatile assisted history matching tool can improve both the quality and the efficiency of the history matching process.

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