Abstract
The article considers the first successful example of the UGS operation process modeling based on a saturation parameter derived from well logging data in a multivariant space-time form. Well logging data is a valuable source of information on the actual gas distribution in the UGS reservoirs and on its dynamics during gas injection and production. In traditional hydrodynamic modeling, accounting for the existing dataset of a well logging control is problematic; traditional geometric interpolation algorithms either do not allow obtaining equally probable realizations of the modeled distribution, or require a priori setting of the trend model, which is normally impossible for solving this problem. Previously, no model could fully consider all available well logging control data.
The initial modeling data is a sparse array of heterogeneous space-time structure with a priori unknown value distribution. The only currently known method that is able to obtain an equally probable set of realizations based on data with both arbitrary position and property distribution is the Amazonas method, which is based on a local prediction of properties based on robust statistics in a randomly located search window. Nowadays, the experience of the successful application of this method for multi-variant modeling of the reservoir property allocation has been accumulated. In this article, the possibility of its application to solve the issue of modeling the UGS gas dynamics was studied for the first time.
The result of this research is a multivariant dynamic model of the UGS gas deposit, fully reproducing the entire array of well logging control data for several gas injection/production cycles. Although this type of model does not have the forecast power of a full – fledged simulation model, it helps solving problems going beyond the scope of the traditional hydrodynamic modeling. It can be used to identify areas of maximum uncertainty, which are prospective for setting up work on additional object exploration (including drilling new monitoring wells), to define discrepancies between the gas volumes carried as assets and the actual volumes of gas, to study gas dynamics and to perform multi – variant calculation of gas volumes in the reservoir in cases where, for one reason or another, it is impossible to build a traditional hydrodynamic model.
