Reduced-order model for CO2 enhanced oil recovery and storage using a gravity-enhanced process

Liwei Li, Saeid Khorsandi, Russell T. Johns, Robert Dilmore

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

CO2 flooding offers a means to recover significant amounts of oil while simultaneously sequestrating CO2. Estimates of the recovery by CO2 enhanced oil recovery (EOR) and storage are highly uncertain owing to reservoir heterogeneity and other reservoir design parameters. One way to optimize the design and characterize the uncertainty of such processes is to introduce a response surface model (RSM), which offers a simple-to-use and useful tool to forecast expected recoveries and storage potential for reservoirs with a broad range of reservoir and design parameters, with potential utility in development of high-level (i.e., regional and national scale) prospective resource assessments. Injectivity is important to economics of CO2 flood enhanced oil recovery, and horizontal wells can greatly increase the injectivity and, when coupled with horizontal production wells, the sweep efficiency, recovery, and storage efficiency in many horizontal and dipping reservoirs. This paper develops a reduced-order model (ROM) for continuous CO2 flooding in heterogeneous oil reservoirs when a horizontal injector and producer are used in a specific optimal pattern. The ROM aims to quickly estimate oil recovery and CO2 storage efficiency based on values of key dimensionless scaling groups. The key scaling groups for first contact miscible (FCM) two-phase (hydrocarbon and water) flow are derived, and their impact on performance metrics of oil recovery and CO2 storage potential are analyzed. First contact miscibility between the hydrocarbon phases is modelled based on the assumption that semi-gravity or gravity stable processes will offer sufficient time for CO2 to contact oil. In this research, a response surface analysis using both a Box-Behnken (BB) experimental design and Latin hypercube sampling (LHS) was also made to predict recovery and storage, and results of that analysis were used to validate the important scaling groups. Monte Carlo simulation with these response surfaces was then used to predict the P10, P50, and P90 expected recoveries and storage efficiencies. The results show that the processes of CO2 EOR and storage in heterogeneous oil reservoirs can be effectively scaled using 11 groups: effective aspect ratio, CO2- or water-oil mobility ratios, buoyancy ratio, normalized initial oil saturation, buoyancy number, residual hydrocarbon saturation, residual water saturation, Dykstra-Parsons coefficient, and correlation length coefficients in x- And z-directions. Furthermore, the results show that oil recovery and CO2 storage efficiencies of 82 to 91% can be obtained in this process for reservoirs with nonzero vertical permeability and no water influx. This is the first paperthat considers a gravity-enhanced process using all horizontal wells, where the process may not be completely gravity stable, to efficiently recovery incremental oil and store CO2. The approach represents a "next generation" CO2 EOR scenario to yield a large volume of CO2 stored per bulk volume of reservoir given unlimited CO2 injection capability, little water influx, and future economic benefits of sequestration and high enhanced oil recovery.

Original languageEnglish (US)
Title of host publicationSociety of Petroleum Engineers - SPE Annual Technical Conference and Exhibition, ATCE 2014
PublisherSociety of Petroleum Engineers (SPE)
Pages2245-2270
Number of pages26
ISBN (Electronic)9781634398879
DOIs
StatePublished - 2014
EventSPE Annual Technical Conference and Exhibition, ATCE 2014 - Amsterdam, Netherlands
Duration: Oct 27 2014Oct 29 2014

Publication series

NameProceedings - SPE Annual Technical Conference and Exhibition
Volume3

Other

OtherSPE Annual Technical Conference and Exhibition, ATCE 2014
Country/TerritoryNetherlands
CityAmsterdam
Period10/27/1410/29/14

All Science Journal Classification (ASJC) codes

  • Fuel Technology
  • Energy Engineering and Power Technology

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