{"title":"Optimization of Sp Flooding Design Using Simulation Calibrated with Lab Core Flooding","authors":"M. Ahmed, A. Sultan","doi":"10.2118/200228-ms","DOIUrl":null,"url":null,"abstract":"\n The development Chemical EOR technologies is increasing rapidly due to the massive need of hydrocarbons in the world and because most of the reservoirs have reached tertiary recovery phase. Carbonate reservoir have challenging conditions of high salinity and high temperature that affect the performance of SP flooding. In this paper, we are using a commertial simulator to optimize the design SP flooding in these harsh conditions, and use our previous core-flooding experiment to calibrate our simulation model.\n The porosity distribution for the model was determined by using the micro-CT imaging which gave the distribution along the core. The permeability was calculated based on the porosity-permeability relationship from the real core data. The real surfactant and polymer properties were measured in the lab in terms of rheology and IFT. History matching of the base case to the real core data was performed using particle swarm optimization machine. The matching parameters were the critical capillary number for de-trapping for both low and high IFT flooding, besides the relative permeability curvature parameter. Many scenarios were investigated after having a match with 2.3 AAE.\n The polymers used are a Thermo-Viscosifying Polymer (TVP) and an Acrylamido Tertiary Butyl Sulfonate (ATBS)/acrylamide (AM) copolymer. The surfactants are carboxybetaine based amphoteric surfactants SS-880 and SS-885. We did previous study to optimize the core-flooding design for SP flooding in the lab but we faced the problem of inconsistency. Because there are some factors that, we cannot control and keep them constant to compare results, like the core permeability and porosity and their distribution and mineralogy. The combination of surfactant and polymer in one slug gives more recovery than the injecting them individually. ATBS gave higher recovery than TVP. There is no difference in recovery due to changing the surfactants because their IFT is close to each other. The observation is that increasing the slug size will increase the recovery so we recommend using diminishing return economic analyses to determine the slug that gives the highest profit. Injecting SW-SP-SW is the best sequence among the other three sequences, taking the advantage of injecting longer slug of viscous fluid, as the increment due to IFT reduction is minor. The viscosity sensitivity study shows higher recovery with more viscous fluids so the limiting factor will be the economics and the pump capacity.\n Optimizing the SP flooding design for carbonate reservoirs using simulation with the help of lab experiments results for calibration will decrease the uncertainty. This technique is better because you can control the fixed and variable parameters to know exactly the effect of individual ones.","PeriodicalId":11113,"journal":{"name":"Day 1 Mon, March 21, 2022","volume":"3 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 1 Mon, March 21, 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/200228-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The development Chemical EOR technologies is increasing rapidly due to the massive need of hydrocarbons in the world and because most of the reservoirs have reached tertiary recovery phase. Carbonate reservoir have challenging conditions of high salinity and high temperature that affect the performance of SP flooding. In this paper, we are using a commertial simulator to optimize the design SP flooding in these harsh conditions, and use our previous core-flooding experiment to calibrate our simulation model.
The porosity distribution for the model was determined by using the micro-CT imaging which gave the distribution along the core. The permeability was calculated based on the porosity-permeability relationship from the real core data. The real surfactant and polymer properties were measured in the lab in terms of rheology and IFT. History matching of the base case to the real core data was performed using particle swarm optimization machine. The matching parameters were the critical capillary number for de-trapping for both low and high IFT flooding, besides the relative permeability curvature parameter. Many scenarios were investigated after having a match with 2.3 AAE.
The polymers used are a Thermo-Viscosifying Polymer (TVP) and an Acrylamido Tertiary Butyl Sulfonate (ATBS)/acrylamide (AM) copolymer. The surfactants are carboxybetaine based amphoteric surfactants SS-880 and SS-885. We did previous study to optimize the core-flooding design for SP flooding in the lab but we faced the problem of inconsistency. Because there are some factors that, we cannot control and keep them constant to compare results, like the core permeability and porosity and their distribution and mineralogy. The combination of surfactant and polymer in one slug gives more recovery than the injecting them individually. ATBS gave higher recovery than TVP. There is no difference in recovery due to changing the surfactants because their IFT is close to each other. The observation is that increasing the slug size will increase the recovery so we recommend using diminishing return economic analyses to determine the slug that gives the highest profit. Injecting SW-SP-SW is the best sequence among the other three sequences, taking the advantage of injecting longer slug of viscous fluid, as the increment due to IFT reduction is minor. The viscosity sensitivity study shows higher recovery with more viscous fluids so the limiting factor will be the economics and the pump capacity.
Optimizing the SP flooding design for carbonate reservoirs using simulation with the help of lab experiments results for calibration will decrease the uncertainty. This technique is better because you can control the fixed and variable parameters to know exactly the effect of individual ones.