"Miscibility Variations in Compositionally Grading Petroleum Reservoirs" by Lars Høier

The study demonstrates that the three thermal diffusion models are only internally consistent for thermal diffusion ratio in the case of lean gases. Miscibility conditions in gas condensates are given particular attention.

This work demonstrates how the inclusion of thermal models in the calculation of vertical compositional variations may have a large impact on the minimum miscibility pressure MMP(h) results.

Contents
Aknowledgement
Summary
1 Introduction
1.1 Objective
1.2 Organisation
2 Vertical Compositional Gradients
2.1 Introduction
2.2 Main Governing Equations and Solution Techniques
2.2.1 General Derivation
2.2.2 Isothermal Calculations
2.2.3 Passive Thermal Diffusion
2.2.4 Including Thermal Diffusion
2.3 Application of Isothermal Equations
2.3.1 Topical Compositional Variation with Depth
2.3.2 Variation in Properties with Depth
2.3.3 A New Algorithm for Determination of Gas-Oil Contact
2.3.4 Effects of Sampling Errors on Compositional Gradients
2.3.5 Hydrocarbons-in-Place Calculations
2.4 Implementation of Thermal Diffusion in Compositional Gradient Calculations
2.4.1 Background on Thermal Diffusion
2.4.2 Thermal Diffusion in Binary and Multicomponent Mixtures
2.4.3 Influence on Compositional Gradient Calculations
2.5 Conclusions and Recommendations
2.6 Nomenclature
2.7 References
3 Developed Miscible Gas Injection
3.1 Introduction
3.2 Calculating Minimum Miscibility Conditions
3.2.1 Definitions and Background
3.2.2 Key physical Parameters, Experiments and EOS Parameters
3.2.3 Evaluation of MMP/MME Calculation Algorithms
3.2.4 Quantification of Uncertainty in Slimtubc Simulations
3.2.5 Comparison between MMP Predictions with Different Methods
3.3 Effects of Pressure and Injection Gas Composition on Miscibility
3.3.1 Pressure Effect on Developed Miscibility
3.3.2 Effects of Injection Gas Composition on MMP
3.4 Minimum Miscibility Conditions in Compositionally Grading Reservoirs
3.4.1 Method and Assumptions
3.4.2 MMP with Depth in SVO Reservoir with Gas Cap
3.4.3 MMP with Depth in NCO Reservoir with Gas Cap
3.4.4 MMP with Depth in VOA Reservoir with Undersaturated GOC
3.4.5 MME Variations for Different Reservoir Systems
3.5 Miscibility in Gas Condensate Reservoirs
3.5.1 MMP with Depth in Gas Condensate Reservoirs
3.5.2 Grid Effect in Gas Condensate MMP Determination
3.5.3 Miscibility in Depleted Gas Condensate Reservoirs
3.5.4 Consequences for Gas Cycling Processes
3.6 Temperature Effect on Miscibility
3.6.1 Temperature Effect on MMP with Injection Gas Enrichment
3.6.2 Effect of "Passive" Thermal Diffusion on MMP with Depth
3.6.2 Including Thermal Diffusion in MMP with Depth Calculations
3.7 Discussion and Analyses
3.7.1 Horizontal Gas Injection in Compositionally Graded System
3.7.2 Rate Dependence in Vertical Gas Injection
3.7.3 Vertical Gas Injection in System with Undersaturated GOC
3.7.4 MMP Variation in Depleted Oil Systems with Initial Compositional Gradient
3.7.3 Recombination Gas-Oil Ratio Effect on MMP
3.8 Conclusions and Recommendations
3.9 Nomenclature
3.10 References
Appendix A: Complete EOS Fluid Characterization
Appendix B: Compositional Predictions with Proposed GOC Algorithm
Appendix C: MMP Determination for Slimtube Simulations
Appendix D: Grid Effect in the Zick Multicell Algorithm

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