Forecast of the net pay and Kh of the reservoir by logs, according to the results of XPT and MDT test

Goal. The article demonstrates the approaches for integrating the results of point and interval testing into petrophysical model in order to expand the understanding of the reservoir and to predict parameter Kh from well logging data.

Methods. At the first stage of the work, specific methods were identified for considering the data of the complex of tests by hydrodynamic logging and wireline formation test installations in the reservoir model by petrophysics. Moreover, in the conditions of low-permeability deposits, special attention is paid to the issue of obtaining the so-called dry mobility measurements during the HDD-OPK and their inclusion in the reservoir model.

At the second stage, the authors consider the integration of flow testing data and the results of hydrodynamic logging and wireline formation test and formation evaluation from well logging. To carry out such a task, it is necessary to verify and classify the results of flow testing by reliability, which became possible due to the developed criteria for assessing the quality of flow testing in this work. qualitative results of flow testing make it possible to operate with the value of Kh as a calibration when calculating Kh by well logging. Thanks to high-quality measurements of fluid mobility by the wireline formation test in the Achimov deposits, the permeability is transformed from absolute to effective individually for the type of fluid: gas, oil, water. After that, Kh prediction itself is carried out on the basis of well logging data, controlling the value of Kh (well logging) with Kh (flow testing). The uncertainty of the well logging reservoir model is removed by cross-plotting Kh (well logging-flow testing) in such a way that the correct reservoir model with the correct NET pay by logging forms the maximum match between the predicted Kh and the calibration one from the flow testing at the points of the calibration wells. This is facilitated by the low level of permeability of the Achimov deposits, which has little effect on the Kh value, in contrast to NET pay.

Results. 1. Methods have been obtained for considering the data of the complex of tests by the hydrodynamic logging — wireline formation test installations in the petrophysics's reservoir model. 2. A tool was obtained for calculating the predicted Kh from well logging data, consistent with the actual Kh data from well testing. 3. Universal criteria have been identified for assessing the quality of well test results. 4. A non-standard way of confirming/ refuting the petrophysics's reservoir model using cross-plotting Kh (well logging, formation evaluation — flow testing, fact) is proposed.

Conclusion. In the work, it was possible to build a unified scheme of actions for the implementation of both the first stage of work on integrating the results of the hydrodynamic logging — wireline formation tests into t petrophysics’s reservoir model, and the second stage according to the Kh forecast based on the well logging, calibrated to the actual well test results. This representation allows not only to improve the accuracy of the petrophysical forecast, but also to expand the coverage of the involved data from related areas of petroleum engineering.

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