Multi-objective assisted inversion of chemical EOR corefloods for improving the predictive capacity of numerical models

Abstract Reservoir modeling is a powerful tool to thoroughly assess chemical EOR performances and to design the economically optimal injection sequence (chemicals concentration, slugs size). However, while building a model requires a large amount of data, laboratory experiments allow assessing a non-exhaustive number of parameters only. Some essential data besides remain costly or time-consuming to acquire. The calibration process is thus not straightforward and typically results in under-constrained models that may not provide meaningful results. To increase the model robustness, we propose to carry out a multiobjective assisted calibration, further tested on an additional differentiating experiment. The multi-objective aspect refers to the calibration of various production data acquired from a consistent series of recovery experiments. The methodology is applied to five surfactantpolymer displacements performed on sandstone cores, differing from the surfactant slug concentration, its size and the brine salinity. The experiments set is chosen to provide a wide range of tertiary recoveries, from 52% to 86% of residual oil in place. The oil recovery and the differential pressure are history matched with a limited number of adjustable parameters among which the surfactant adsorption, the wateroil interfacial tension and the extrapolation of Corey exponents along flooding history. The sensitivity to adjustable parameters is thoroughly explored by more than 1000 simulations to finally get a model that successfully reproduces the main features of the experiments. Calibration on a few experiments then gives more confidence in the model than when done on a single experiment. Its ability to reproduce the processes occurring in the core and to further predict the optimal chemical injection sequence is reinforced by the additional differentiating experiment which segregates different consistent models. This additional experiment specifically better constrains the surfactant adsorption.

[1]  T. Ertekin,et al.  The effect of the capillary number and its constituents on two-phase relative permeability curves , 1983 .

[2]  J. Hou,et al.  Supplement and optimization of classical capillary number experimental curve for enhanced oil recovery by combination flooding , 2014, Development and Application of Classical Capillary Number Curve Theory.

[3]  R. Farajzadeh,et al.  Detailed Modeling of the Alkali/Surfactant/Polymer (ASP) Process by Coupling a Multipurpose Reservoir Simulator to the Chemistry Package PHREEQC , 2012 .

[4]  An Experimental Study of the Influence of Interfacial Tension on Water–Oil Two-Phase Relative Permeability , 2010 .

[5]  M. Sagir,et al.  Kinetics and Equilibria of Synthesized Anionic Surfactant onto Berea Sandstone , 2014 .

[6]  M. D. McKay,et al.  A comparison of three methods for selecting values of input variables in the analysis of output from a computer code , 2000 .

[7]  Xiaoqi Wang,et al.  Laboratory and Simulation Study of Optimized Water Additives for Improved Heavy Oil Recovery , 2012 .

[8]  Surendra P. Gupta.  Dispersive Mixing Effects on the Sloss Field Micellar System , 1982 .

[9]  B. Braconnier,et al.  Efficient Scheme for Chemical Flooding Simulation , 2014 .

[10]  Véronique Gervais,et al.  Advanced Integrated Workflows for Incorporating Both Production and 4D Seismic-Related Data into Reservoir Models , 2012 .

[11]  F. Delbos,et al.  Adapted Nonlinear Optimization Method for Production Data and 4D Seismic Inversion , 2008 .

[12]  R. Junin,et al.  Equilibrium Adsorption Isotherms of Anionic, Nonionic Surfactants and Their Mixtures to Shale and Sandstone , 2009 .

[13]  Marinus J. Faber,et al.  Alkaline/Surfactant/Polymer Flood: From the Laboratory to the Field , 2011 .

[14]  Robert S. Schechter,et al.  The Measurement of Low Interfacial Tensionviathe Spinning Drop Technique , 1975 .

[15]  Chun Huh,et al.  Simulation To Support Interpretation of the Loudon Surfactant Pilot Tests , 1990 .

[16]  S. G. Mason,et al.  Measurement of interfacial tension from the shape of a rotating drop , 1967 .

[17]  R. C. Nelson.  The Salinity-Requirement Diagram - A Useful Tool in Chemical Flooding Research and Development , 1982 .

[18]  J. Labrid,et al.  A Numerical Study of Chemical Flooding Comparison With Experiments , 1983 .

[19]  T.-C. Jim Yeh,et al.  The effect of water content on solute transport in unsaturated porous media , 1999 .

[20]  Chun Huh,et al.  Interfacial tensions and solubilizing ability of a microemulsion phase that coexists with oil and brine , 1979 .

[21]  R. Hayes,et al.  Modelling dynamic adsorption of an anionic surfactant on Berea sandstone with radial flow , 1995 .

[22]  Qingjie Liu,et al.  Pore Scale Network Modeling of Relative permeability in Chemical flooding , 2003 .

[23]  Kamy Sepehrnoori,et al.  Comparison of an Improved Compositional Micellar/Polymer Simulator With Laboratory Corefloods , 1987 .

[24]  D. W. Corbishley,et al.  Chemical Flood Simulation of Laboratory Corefloods for the Mangala Field: Generating Parameters for Field-Scale Simulation , 2008 .

[25]  R. L. Reed,et al.  SOME PHYSICOCHEMICAL ASPECTS OF MICROEMULSION FLOODING: A REVIEW , 1977 .

[26]  Kamy Sepehrnoori,et al.  Simulations of Chemical and Microbial Enhanced Oil Recovery Methods , 2002 .

[27]  Gary A. Pope,et al.  EFFECT OF CAPILLARY NUMBER ON THE RESIDUAL SATURATION OF A THREE-PHASE MICELLAR SOLUTION. , 1986 .

[28]  Lorenzo Anselmi,et al.  ASP System Design for an Offshore Application in La Salina Field, Lake Maracaibo , 2003 .

[29]  G. Pope,et al.  Identification and Evaluation of High-Performance EOR Surfactants , 2009 .

[30]  B. Jamaloei.  The Effect of Interfacial Tension on Two-phase Relative Permeability: A Review , 2015 .

[31]  Gary A. Pope,et al.  Mechanistic modeling of alkaline/surfactant/polymer floods , 2009 .

[32]  P. Moreau,et al.  Design of a Surfactant/Polymer Process in a Hard Brine Context: A Case Study Applied to Bramberge Reservoir , 2012 .

[33]  George J. Hirasaki,et al.  Evaluation of the Salinity Gradient Concept in Surfactant Flooding , 1983 .

[34]  I. Sobola,et al.  Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates , 2001 .

[35]  Didier Yu Ding,et al.  History Matching of Production and 4D Seismic Data: Application to the Girassol Field, Offshore Angola , 2012 .

[36]  J. Bruining,et al.  An empirical theory for gravitationally unstable flow in porous media , 2013, Computational Geosciences.

[37]  F. McCaffery,et al.  Low Interfacial Tension Displacement Studies , 1978 .

[38]  S. P. Neuman.  Universal scaling of hydraulic conductivities and dispersivities in geologic media , 1990 .

[39]  Christoph Hinz,et al.  Non‐Fickian transport in homogeneous unsaturated repacked sand , 2004 .

[40]  J. O. Amaefule,et al.  The Effect of Interfacial Tensions on Relative Oil/Water Permeabilities of Consolidated Porous Media , 1982 .

[41]  E. Koval,et al.  A Method for Predicting the Performance of Unstable Miscible Displacement in Heterogeneous Media , 1963 .

[42]  Véronique Gervais,et al.  Integrating Data of Different Types and Different Supports into Reservoir Models , 2012 .

[43]  M. Ahmadi,et al.  Experimental and Theoretical Study of a New Plant Derived Surfactant Adsorption on Quartz Surface: Kinetic and Isotherm Methods , 2015 .

[44]  C. Welty,et al.  A Critical Review of Data on Field-Scale Dispersion in Aquifers , 1992 .

[45]  Harry Surkalo,et al.  Alkaline-Surfactant-Polymer Flooding of the Cambridge Minnelusa Field , 2000 .

[46]  Bruce Carney,et al.  Simulations of Chemical Flooding-Comparison with Experimental Data , 1982 .

[47]  David S. Schechter,et al.  Relative permeabilities of a near critical binary fluid , 1992 .

[48]  Samir Touzani,et al.  Sensitivity Analysis and Optimization of Surfactant-Polymer Flooding under Uncertainties , 2014 .

[49]  J. Sheng.  Status of surfactant EOR technology , 2015 .

[50]  P. Moreau,et al.  A Combinatorial Approach for Identification of Performance EOR Surfactants , 2008 .

[51]  Jean-Louis Salager,et al.  Optimum Formulation of Surfactant/Water/Oil Systems for Minimum Interfacial Tension or Phase Behavior , 1979 .

[52]  J. Sheng.  Optimum phase type and optimum salinity profile in surfactant flooding , 2010 .

[53]  S. Paria,et al.  A review on experimental studies of surfactant adsorption at the hydrophilic solid-water interface. , 2004, Advances in colloid and interface science.

[54]  K. Ojha,et al.  Adsorption of surfactants on sand surface in enhanced oil recovery: Isotherms, kinetics and thermodynamic studies , 2013 .

[55]  R. G. Larson,et al.  Numerical Simulation Of Competing Chemical Flood Designs , 1978 .

[56]  Jim S. Liu,et al.  Numerical simulation of surfactant–polymer coreflooding experiments for carbonates , 2013 .

[57]  J. V. Wunnik,et al.  Modelling of ASP Flooding Using X-ray CT Core Flooding Experiments , 2015 .