A Numerical Simulation Tool – EORs

EORs is a special reservoir and prospect assessment software package. Using various applied techniques based on multi-criterion models, validated analytical approaches, existing industry expertise and expert knowledge in EOR applications, the ability of key Enhanced Oil Recovery (EOR) methods can be quickly evaluated. EORs assists reservoir engineers in the design and decision-making of reservoir production methods for EOR applications. It is particularly useful when quick evaluations are required and in situations with limited information on the reservoir and large uncertainties in the description of the reservoir , as is often the case at initial evaluation stages”

EORs Modules:-

  • Applicability Testing
  • Cyclic Waterflooding
  • Chemical flooding
  • Water Alternating Gas (WAG)

Applicability testing allows for a fast first-order screening (ranking) of the applicability of main EOR methods such as waterflooding, chemical, thermal and gas injection under specific conditions of the reservoir. Using a multi-criterion model, the applicability assessment is based on application ranges for critical reservoir parameters. The underlying expert system is based on existing industry expertise and EOR technology professional knowledge. The tool is user-friendly and available in standard or advanced dynamic mode, offering complete flexibility to modify the expert underlying system.

Estimation of the recovery factor is a tool for rapid evaluation of the suitability of the key EOR methods under certain conditions. It enables the probability of successful deployment of a given injection method to be determined. The calculated recovery factor can be used to rate the results. The module presents statistical data from international ventures.

Performance prediction is a specific “pre-simulation” method for quick quantitative predictions. It allows for a convenient assessment and comparison of the potential of recovery methods such as depletion, waterflooding, surfactant, polymer and surfactant/polymer flooding, miscible and immiscible gas (CO2, N2, HC) flooding, steam flooding and water-alternative gas (WAG) injection. Displacement results in 2D cross-section and approximate 3D geometry (5-spot pattern) are available for stratified reservoirs. Predictions are based on established analytical solutions, e.g. Buckley Leverett Method and approximation of the vertical balance (dominated by gravity). A wide range of reservoir parameters and measured results allow the user to perform a fast yet detailed reservoir analysis and sensitivity studies. A unique feature is its ability to handle a number of cases in just one ride. Therefore, a Monte Carlo system for estimating future production rates is incorporated.

Planning an EOR project needs careful attention to many problems including significant lead time for research, reviews, project design and above all, the economics of these high-cost EOR projects. An economic analysis is used for the application of the technically approved enhanced oil recovery methods. By conducting economic sensitivity analysis on key input variables such as oil prices, injection solvent rates, capital expenditure, operating expenditure, and oil recovery, the goal is to establish sensitivity analysis graphs for each variable in order to assess potential development planning for EOR projects. The ultimate goal of reservoir engineering management is economic optimization. Project economics are analyzed with projected growth, capital, operating expenses, and financial data. The results of the project could be extended to any EOR reservoir worldwide.

  • Cyclic waterflooding is a module for rapid assessment of the effect of cyclic injection on the efficiency of flooding of water in layered reservoirs. The pulsing injection effect is assessed by adding a correction to the Buckley Leverett model to take into account the transfer of fluid (cross-flow) between the layers in the reservoir. In the original Dykstra- Parsons model, this is ignored. The cross-flow includes physical gravity processes, neglecting the influence of capillary forces and the compressibility-related effects of pulsing conditions of injection.
  • Steam Flooding is a system based on the Jones model that allows for three key stages of the process of steam flooding: dam heat-up, oil recovery, and tail output. The system for steam flooding is based on the validated performance module. The device results were tested using a leading thermal reservoir simulator.
  • WAG system enables the calculation of improved oil recovery due to the immiscible 3-phase flow in the coated reservoir. The module uses the 3-phase model of Stone II and estimates residual oil saturation for the reservoir in general and for each individual layer based on user-specified two phases of relative permeability and schedule of WAG injection.

Software Features

  • New, easy-to-use GUI.
  • Flexible unit conversion method (e.g., SI, metric, field, laboratory).
  • Context-sensitive assistance.
  • Extensive graphical output.
  • Enhanced monitoring features for recording input and output for all modules.
  • Fast communication with other applications in windows.
  • To export findings to documents and presentations, copy/paste.
  • Configuration of the plot and preview of the print.
  • Export diagrams to most common formats.


  • Planning the plan for the use of dams and helping to determine how to use IOR methods.
  • Screening and simulation of first-order EOR.
  • Evaluation of quick reservoir and tolerance studies.
  • In cases with limited information or ambiguity in the definition of the dam, e.g. at the initial stage of assessment.
  • Often used before or during the use of numerical simulators to avoid high modeling/simulation costs.

Technical features

Applicability Screening Module:-

  • Multi-criterion model with interval approach and input distribution functions.
  • Expert framework for quick and convenient IOR applicability assessments.
  • Involves existing industry experience in IOR applications and expert knowledge.

Recovery Factor Estimation:-

  • Processing kernel based on a world-wide field case database.
  • Multi-dimensional models and algorithms for machine learning.

Performance Prediction Module:-

  • Displacement results in an estimated 2D cross-section and 3D (5-spot) geometry.
  • Based on evaluated analytical solutions, e.g.
  • Dykstra-Parsons (no cross-flow estimation),
  • Vertical equilibrium approximation (gravity dominated, max. cross-flow estimation).
  • Production decline curves analysis (based on exponential or hyperbolic decline).
  • Critical rates for gravity tonguing and viscous channeling.

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