Method for assessing well interference at under-gas cap zone using CRM material balance model

Abstract

Optimization of injection operation conditions is a primary task when designing the development of mature oil fields. To select optimal injectivities, solutions to the optimization problem based on a CRM (capacitance resistance model) analytical model are used. CRM models based on analytical solutions of the material balance equations of weakly compressible fluids due to their speed can be used as an alternative to flow simulation models in solving a number of problems to support oil field development. The main task of CRM models is to determine the well interference factor, i.e. the share of fluid produced due to a particular injection well. These factors can be used to analyze waterflooding and develop solutions for waterflood optimization. At the same time, in some cases reservoir fluids may have high gas content, which is a classical limitation of a CRM model and leads to underestimation of the interference factors when estimating the injection performance. In this paper, the authors propose an approach to solve the problems of distortion of such factors, and for the first time in CRM application practice a model has been adapted for use in the conditions of high GORs and has a potential for being applied for under-gas cap zones. This is achieved by including in the equations the physical properties of gas and their behavior under reservoir conditions. The complication of algorithms did not significantly affect the model run time, but allowed to match the model both separately and jointly for liquid and gas phases. Thus, the improved classical CRM model has significantly expanded the scope of application of operational waterflood analysis tools for assessing the current situation. No less complicated and urgent is the problem of forecasting the production of gas liberated in the conditions of the previously mentioned under-gas-cap zones, because it implies the need to estimate the future reservoir pressure. The authors intend to devote the next paper to finding a solution to this issue, taking into account the proposed new method of reservoir pressure estimation using a CRM model.