Optimization of Chemical Flooding in a Mixed-Wet Dolomite Reservoir

Abstract

Many pilot tests and several commercial field projects have been performed over the past few decades and have shown that surfactant/polymer and alkaline/surfactant/polymer floods can recovery high percentages of residual oil saturation. However, these chemical processes are sensitive to parameters such as chemical slug size and concentrations, salinity, reservoir heterogeniety and surfactant adsorption among other key parameters. In this study, a sensitivity analysis of these key parameters was performed to optimize a chemical flood design for a mixed-wet dolomite reservoir in the Permian Basin. The simulations were performed using the reservoir simulator UTCHEM, a multiphase, multicomponent chemical flooding simulator. The base case design was developed using a reservoir model provided by the operator, injection and production rate constraints from actual field conditions, brine and oil properties from the field, and chemical properties provided by the EOR laboratory at the University of Texas. An optimum design was selected based on net present value calculated from discounted cash flow analysis. The results of this study showed that chemical flooding this mixed-wet dolomite reservoir is likely to be profitable over at range of crude oil prices based upon the laboratory performance of the surfactant/polymer flood and the optimum process design determined in this study. Introduction A very large amount of remaining oil in the U.S. resides in carbonate reservoirs. Many of these carbonate reservoirs have very low primary and waterflood recovery efficiencies, so much residual and bypassed oil remains as a target for enhanced oil recovery. Enhanced oil recovery methods known as surfactant-polymer (SP) flooding[1–7] and alkaline-surfactant-polymer (ASP) flooding[8–14] have been shown to be effective in recovering remaining oil in many successful pilot tests and some relatively small commercial field projects. Most SP and ASP floods have been done in sandstone reservoirs. However, an SP pilot done in a carbonate reservoir showed promising results.[15] Many past SP and ASP simulation studies have been performed to understand the sensitivity and complexity of chemical flooding.[9,14,17–20] These simulation studies have shown chemical flooding to be sensitive to several design and chemical parameters such as slug sizes, chemical concentrations, and chemical retention due to adsorption and other mechanisms. Wu[18] and Wu et al.[20] did an optimization study of a SP flood for a typical onshore water-wet sandstone reservoir focusing on the optimum design when crude oil was about $20 per Bbl. Wu's optimum SP design consisted of a large slug of low concentration surfactant and polymer followed by little if any polymer and water drives. This design was based upon the assumption the surfactant was active at very low concentrations and had very low adsorption and low crude oil prices. The success of a SP flood depends upon the ability to propagate the surfactant and polymer, overcome chemical adsorption, and improve the sweep efficiency. In this work, an optimization study was performed to meet these three goals and maximize the oil recovery and profitability of a SP flood in a mixed-wet dolomite reservoir. The optimization study included a sensitivity analysis, which included the aforementioned parameters, and an uncertainty analysis, which was extended to other parameters such as kv/kh, capillary desaturation curves (CDC), and permeability. The optimization and sensitivity simulations reported in this paper were performed using UTCHEM, a chemical flooding simulator developed and validated for chemical processes such as SP and ASP. The results of the simulations were analyzed using discounted cash flow to determine the economic feasibility of the optimized SP flood design for a particular carbonate reservoir in the Permian basin.

Alkaline/Surfactant/Polymer (ASP) Flooding

“…In 1978, a 1-D numerical simulator was developed by Pope and Nelson [21] to describe surfactant enhanced oil recovery and it has been extended to other chemical processes and to 3-D as UT-CHEM [22][23][24]. Furthermore, ECLIPSE, which is a commercial reservoir simulator, was developed by Schlumberger.…”

Upscaling Polymer Flooding to Model Sub-gridblock Geological Heterogeneity and Compensate for Numerical Dispersion

“…More recent field applications used 0.5 PV as a starting slug size and then adjust it based on performance and economic considerations. Anderson et al (2006) suggested that slugs greater than 0.5 PV have little effect and indicated the need for buffers to avoid slug disintegration. For this exercise, 0.4 PV is compared with continuous injection of polymer.…”

“…Gharbi (2001) suggested 2800 ppm was an optimum polymer concentration in an Alkaline-Surfactant-Polymer flood design. Anderson et al (2006) used values between 1000 and 2000 ppm in a surfactant-polymer flood. These two papers used oil price as the main selection criterion.…”

Polymer flooding design and optimization under economic uncertainty

“…For these reasons, previous work has been limited to lab-scale optimization and field-scale sensitivity studies (Zerpa et al, 2005). For instance, in Anderson et al (2006) a sensitivity study was undertaken to optimize a surfactant-polymer (SP) flood. To overcome computational costs, both Zerpa et al (2005) and Horowitz et al (2010) presented and tested surrogate-based optimization.…”