In order to design and analyze Alkaline Surfactant Polymer (ASP) pilots and to generate reliable ASP field forecasts a robust scalable modeling workflow for the ASP process is required. A starting point of such a workflow is to carry out ASP coreflood tests and history match those using numerical models. This allows validation of the models and generates a set of chemical flood parameters that can be used for field-scale simulation forecasts.
It is well established that lowering of interfacial tension due to maximum of in-situ generated soap with injected surfactant and improved mobility control due to the polymer play a crucial role in the ASP process. Therefore, all models for the ASP process take into account these mechanisms in one way or the other. However, ASP models can differ in the detail in which (geo-) chemical reactions and the phase behavior are addressed. Inclusion of the more details into the numerical model could result in better understanding and more accurate prediction, but it comes at a price, viz., it requires more measured input data and increases computational time. Thus, depending on the accuracy requirements, available experimental data and time the modeling of ASP flood can be performed using different simulation approaches.
This paper describes several modeling approaches for ASP. We start with a brief description of these methods and their input requirements. Then we compare the ASP coreflood simulation results demonstrating the advantages and disadvantages of presented approaches. We also demonstrate that both ASP models can be applied at the field level by simulating an ASP flood in a sector model. Finally we give some recommendations and guidelines on how and when the proposed models should be used.