Summary
While there are a number of mechanistic foam models available in the literature, it still is not clear how such models can be used to guide actual field development planning in enhanced oil recovery (EOR) applications. This study aims to develop the framework to determine the optimum injection condition during foam EOR processes by using a mechanistic foam model. The end product of this study is presented in a graphical manner, based on the sweep-efficiency contours (from reservoir simulations) and the reduction in gas mobility (from mechanistic modeling of foams with bubble population balance).
The main outcome of this study can be summarized as follows: First, compared to gas/water injection with no foams, injection of foams can improve cumulative oil recovery and sweep efficiency significantly. Such a tendency is observed consistently in a range of total injection rates tested (low, intermediate, and high total injection rates Qt). Second, the sweep efficiency is more sensitive to the injection foam quality fg for dry foams, compared to wet foams. This proves how important bubble-population-balance modeling is to predict gas mobility reduction as a function of Qt and fg. Third, the graphical approach demonstrates how to determine the optimum injection condition and how such an optimum condition changes at different field operating conditions and limitations (i.e., communication through shale layers, limited carbon dioxide (CO2) supply, cost advantage of CO2 compared to surfactant chemicals, etc.). For example, the scenario with noncommunicating shale layers predicts the maximum sweep of 49% at fg = 55% at high Qt, while the scenarios with communicating shale layers (with 0.1-md permeability) predicts the maximum sweep of only 40% at fg = 70% at the same Qt. The use of this graphical method for economic and business decisions is also shown, as an example, to prove the versatility and robustness of this new technique.
Liquid-assisted gas-lift process (LAGL), a variation of conventional gas lift, is a relatively new technique to improve the productivity of existing wells suffering from liquid loading. Its versatility is especially attractive because modern wells tend to be deeper, often with long horizontal sections, as shown by the examples from offshore and unconventional resources developments. By conducting transient computer simulations in various scenarios (i.e., a wide range of injection conditions for shallow and deep wells), this study aims to gain the fundamental knowledges associated with LAGL and learn how to apply them optimally in the field applications - unloading liquids in the producing wells and, at the same time, reducing the maximum injection pressure (Pinj-max) required.
After determining model parameters from the simulation fit to experimental data and extending the simulations into a wide range of conditions, this study shows the following major findings. First, adding water in the injection stream during LAGL process does not always guarantee a reduction in Pinj-max. Instead, the results support that there is a certain range of injection-condition window (in terms of gas and liquid flowrates (Qg and Qw)) within which the process can effectively reduce the maximum injection pressure (Pinj-max). Second, the presence of such a window associated with a multi-valued problem is caused by the complex multiphase flow behavior, which coincides with the change in flow regimes (i.e., transitioning from mist/annular flow to slug flow). Third, applying the injection condition within the window in field-scale trials may not be necessarily straight forward because the pressure and liquid holdup responses sometimes show oscillatory behaviors (whether cyclic or chaotic) during the process. These oscillatory behaviors occur more easily in deeper wells in which the system allows more time for the injected gas and liquid mixture to get segregated during the downward flow in the annulus. The use of pressure and liquid holdup contours, as implemented in this study, is believed to be a useful means of planning for the LAGL treatments in the field.
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