Uncertainty in Chemical Flooding: A new data optimization algorithm for modelling of surfactant flood

O. Akinyele, K. D. Stephen

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

1 Citation (Scopus)


A data optimization algorithm has been created to solve the inversion modelling by fractional-flow theory for chemical enhanced oil recovery processes. The routine is scalable, flexible, and easy to deploy in other programming and numerical computing environments for uncertainty analysis especially when upscaling methods is not available. Fractional-flow theory provides valuable insights for 1-D calculations, and reservoir model validation. We used the MATLAB programming environment to develop an adaptable framework, deployed the code to manipulate the plotting of functions, and data needed to calibrate and derive relative permeability functions for upscaling. The code is published in open format and is accessible online for research purposes. The approach integrates three computational processes to attain the effective properties, total mobility, oil bank saturation, mass balance, and flow velocity. We used predicted and regularization terms to define the multi-objective function, then minimized using an active-region quasi-newton optimization algorithm. The graphical user interface is embedded with an adjustable response cost function manifold used to ensure the solution converges to the observed flow parameters. The method was applied to design relative permeability curves for miscible and immiscible surfactant displacement systems, which may be encountered in experimental or simulation studies.

Original languageEnglish
Title of host publication2nd EAGE Digitalization Conference and Exhibition
PublisherEAGE Publishing BV
Number of pages5
ISBN (Electronic)9789462824133
Publication statusPublished - Mar 2022
Event2nd EAGE Digitalization Conference and Exhibition 2022 - Vienna, Austria
Duration: 23 Mar 202225 Mar 2022


Conference2nd EAGE Digitalization Conference and Exhibition 2022

ASJC Scopus subject areas

  • Computer Science Applications
  • Software


Dive into the research topics of 'Uncertainty in Chemical Flooding: A new data optimization algorithm for modelling of surfactant flood'. Together they form a unique fingerprint.

Cite this