Numerical Interpretation of Single Well Chemical Tracer Tests for ASP Injection

Abstract

A series of single well injection tests has been conducted to estimate the efficiency of Alkaline Surfactant Polymer (ASP) flooding. These injection tests comprised a Single Well Chemical Tracer (SWCT) test that was done after water injection to establish a baseline remaining oil saturation and a second SWCT test conducted after ASP injection to measure the Remaining Oil Saturation (ROS) after ASP. Analytical methods are generally used to interpret SWCT tests and to determine the remaining oil saturation. These techniques work best when the response is close to an ideal, single peak. However, the responses from the SWCT tests in our single well tests sequences are complex, showing multiple peaks. This is indicative of complicating factors such as cross-flow between layers. To understand the complex response we used numerical simulation techniques to interpret the SWCT tests. The numerical model includes the physics of ASP, such as interfacial tension reduction, water viscosity modification, and the related reduction in ROS as wells as an accurate model for tracer dispersion. The model allows full control of physical dispersion and does not require the use of numerical diffusion to mimic the effect of physical dispersion. The numerical simulation sequence involves the full single well injection test history including SWCT tests before and after the ASP injection. The key challenge in matching the tests results with the numerical simulations was to model the complex response, which was different for each well tested. Elaborate numerical simulations, different from the conventional interpretation method, were used to successfully match all tests. This paper presents the simulation work, an explanation of the parameters varied to obtain agreement between numerically predicted and actual SWCT responses and the numerical simulation tools used to match the SWCT tests.

MUSCL scheme for Single Well Chemical Tracer Test simulation, design and interpretation

“…Actually, all these effects combined with the numerical resolution specificities may have a significant impact on the S orw uncertainty range, which is the main output of a SWCTT. Interpretation of such a SWCTT may become even trickier when the near wellbore region is made of different layers that hydrodynamically communicate as shown in [28]. That complexity justifies to dispose of: -A precise numerical scheme, as the one proposed in this work.…”

Semi-Analytical Solution of Chemical Flooding in Heterogeneous Non-Communicating Layers with a Focus on Low Salinity Water Flooding

“…Based on the literature, there is a clear need to have analytical tools to predict fluid behavior. For example, we need to predict fluid flow behavior in EOR processes (Lake et al 2014; and to predict solute transport (De Zwart et al 2011;Shen et al 2016). This work can be used as a bench mark to extend work that has been done for 1D chemical flooding so that it is applicable in 2D non-communicating models, e.g., multi-component gas flooding (Johns et al 1994), surfactant flooding (Walsh and Lake 1989), polymer flooding (Borazjani et al 2016; AlSofi and Blunt 2013), low salinity and engineered water flooding (Jerauld et al 2008;Al-Ibadi et al 2019b), combined low salinity with polymer injection (Khorsandi et al 2017), thermal flooding (Pope 1980) and other similar applications.…”

Numerical Interpretation of Single Well Chemical Tracer (SWCT) Tests to Determine Residual Oil Saturation in Snorre Reservoir

“…Based on the experience of other researches (Deans et al, 2007, Jerauld et al, 2010, de Zwart et al, 2011, DeZabala et al, 2011, in the present test, three-layer model is used in order to match the modelled tracer profiles to field data. Then, the fraction of total fluid injected and produced from each layer is set to match the modelled and measured EtAc profiles, and then, the S or for each layer is determined to match the modelled and measured EtOH profiles.…”