Harm Dijk

Detailed Modeling of the Alkali Surfactant Polymer (ASP) Process by Coupling a Multi-purpose Reservoir Simulator to the Chemistry Package PHREEQC

Accurate modeling of an Alkali Surfactant Polymer (ASP) flood requires detailed representation of the geochemistry and, if natural acids are present, the saponification process. Geochemistry and saponification affect the propagation of the injected chemicals and the amount of generated natural soaps. These in turn determine the chemical phase behavior and hence the effectiveness of the ASP process. In this paper it is shown that by coupling the Shell in-house simulator MoReS with PHREEQC a robust and flexible tool has been developed to model ASP floods. PHREEQC is used as the chemical reaction engine, which determines the equilibrium state of the chemical processes modeled. MoReS models the impact of the chemicals on the flow properties, solves the flow equations and transports the chemicals. The validity of the approach is confirmed by benchmarking the results with the ASP module of the UTCHEM simulator (UT Austin). Moreover, ASP core floods have been matched with the new tool. The advantages of using PHREEQC as the chemical engine are its rich database of chemical species and its flexibility to change the chemical processes to be modeled. Therefore, the coupling procedure presented in this paper can also be extended to other chemical-EOR methods.

Selecting the “Right” ASP Model by History Matching Core Flood Experiments

SUMMARY 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 mixing 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 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 core flood simulation results demonstrating the advantages and disadvantages of presented approaches. Finally we give recommendations and guidelines on how and when the proposed models could be used.

SSelecting the "Right" ASP Model by History Matching Coreflood Experiments

SUMMARY 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 mixing 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 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 core flood simulation results demonstrating the advantages and disadvantages of presented approaches. Finally we give recommendations and guidelines on how and when the proposed models could be used.

Uncertainty Management in a Giant Fractured Carbonate Field, Oman, Using Experimental Design

The purpose of this chapter is to provide a workflow for modeling uncertainty. It focuses upon a mature (brown) field redevelopment in a giant fractured carbonate field in Oman. We used experimental design to constrain the range and impact of individual parameters on production forecasts using historical field performance data. The approach allowed for an assessment of the interaction and impact of the uncertainty for a large number of subsurface parameters with a manageable number of model runs. A priori assumptions of the uncertainty range of each parameter were first modeled and then challenged during initial screening runs. Subsequently, historical data were used to constrain the uncertainty range of those parameters that were sensitive to past production performance. The uncertainty range of all other parameters was carried forward into the production forecast, and their impact on various development options was tested. The results of this work were input into a data gathering and pilot production plan to further delimit uncertainty ranges and to help select and optimize development options.

Modeling of Alkali Surfactant Polymer Process by Coupling a Multi-purpose Simulator to the Chemistry Package PHREEQC

Accurate modeling of an Alkali Surfactant Polymer (ASP) flood requires detailed representation of the geochemistry and, if natural acids are present, the saponification process. Geochemistry and saponification affect the propagation of the injected chemic