Impact of Alkaline-Surfactant-Polymer Flooding Model on Upscaled Recovery Predictions: Medium and Heavy Oils

Abstract

Alkali-surfactant-polymer (ASP) flooding is a commercially viable enhanced oil recovery method. The complexity of chemical interactions, multi-phase flow, emulsification, capillary number changes and upscaling issues, especially in highly heterogeneous reservoir, make field designs difficult to extrapolate from coreflood measurements. In this work, two representaions of low interfacial tension conditions in chemical flooding were evaluated to determine the impact of model formulation on scaling-up from lab data to field situations. The first one is a mechanistic model based on interpolation of relative permeability curves parametrized with respect to the local capillary number. The second model requires tracking a thermodynamically stable phase known to exist at water-oil ultralow interfacial tension, namely a microemulsion. To perform this analysis, two sets of chemical coreflooding results were history matched and then the tuned models were utilized for field-scale predictions. For ASP flooding, a sensitivity analysis was implemented to show the importance of microemulsion phase on ASP upscaled (field scale) forecast. In this study, coreflooding experiments were performed using three different crude oils, case I: heavy oil with high acid number, case II: medium oil with high acid number and finally, case III: light oil with very low acid number. Predictions between the two modeling approaches are shown to diverge from each other upon upscaling of core-scale history matched models. This discrepancy is mostly attributed to the need to track a microemulsion phase behavior as well as its properties. Effects are more pronounced for heavier oil with high acid number. The results of this analysis should be useful to constrain field projections of any field design of surfactant-assisted EOR projects. Additionally, this study provides guidelines to understand existing uncertainties in current chemical flooding simulation regarding our ability to accurately predict the results of such a chemical flood design.

How much would silica nanoparticles enhance the performance of low-salinity water flooding?

“…With the aid of a photolithography technique, first the underlying pattern of the porous medium was etched on a silicon wafer to achieve a homogenous pattern with coordination number of 4, which means every pore body is connected to 4 neighboring pores on average. This standard pattern has typically been employed in previous work (Wu et al 2016a, b;Wang et al 2014;Kazempour et al 2014). It was polished to obtain a smooth pattern by removing any unwanted residues.…”

Chemical Flooding in Heavy-Oil Reservoirs: From Technical Investigation to Optimization Using Response Surface Methodology

“…Theoretically, the use of alkali aims to generate an in-situ surfactant/soap by reacting with the natural acids in oil in order to reduce the IFT between O-W, which makes the removal of crude oil easier thereafter [32,33]. Furthermore, the penetration of the alkaline solution into the crude oil causes the formation of a W/O emulsion, thereby reducing the mobility of the displacing fluids and diverting the injected fluids into the unswept region, resulting in an improvement in the sweep efficiency [34].…”

Numerical simulation of enhanced oil recovery studies for aqueous gemini surfactant‐polymer‐nanoparticle systems

“…The current industry is involved in the application of realistic chemical flood simulators like STARS by Computer Modelling Group (CMG), UTCHEM by the University of Texas at Austin (UT Austin), REVEAL by Petroleum Experts (Petex), and ECLIPSE by Schlumberger (SLB). The physics associated with fluid properties' evaluation differ in each type of reservoir simulator 17‐19 . UTCHEM is a compositional simulator capable of simulating different types of EOR processes owing to the provision of four different phases (gas, aqueous, oil, microemulsion) and incorporation of advanced numerical concepts 20 .…”

“…However, this tool is not well known among professionals and engineers in production areas and the existence of a fourth phase, that is, microemulsion may cause problems in field studies 17,20,21 . As per UTCHEM and REVEAL, the presence of a microemulsion phase is a key parameter to model displacement efficiency, in spite of the fact that microemulsion properties are not generally measured in pilot tests and field operations 18‐21 . Both ECLIPSE and STARS do not consider microemulsion phase as contributor to flooding simulation and represent oil displacement behavior via analyses of relative permeability curves for experimental results 17,22,23 .…”

“…Pandey et al employed CMG‐STARS for coreflood modeling experiments and investigated flow parameters that could be subsequently used in pilot field tests 26 . Kazempour and others investigated the validity of multi‐phase component EOR systems in detail, and identified the dynamic behavior of fluid components existing within core‐flood model 18 . Tunnish et al successfully matched experimental flooding results using CMG to effectively tune relative permeability curves and predict the chemical fluid's ability to produce in‐situ crude oil 27 .…”