Compositional Grading Theory and Practice

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SPE 63085 Compositional Grading Theory and Practice Lars Høier, Statoil Curtis H. Whitson, NTNU and Pera

Theory Simple 1D Gradient Models Isothermal Gravity/Chemical Equilibrium Defining General Characteristics Different Fluid Systems (SPE 28000) Quantifying Variations Non-Isothermal Models with Thermal Diffusion. Quantitative Comparisons Different Models Different Fluid Systems

Practice Using Samples Quantifying Uncertainties Develop a Consistent EOS Model Defining Trends Fluid Communication Initializing Reservoir Models Predicting a Gas-Oil Contact History Matching

Isothermal Gradient Model Balance of chemical and gravity potentials Given { H ref, p Rref, T ref, z iref } calculate z i (H) p R (H) p sat (H) IOIP(H) ~ z C7+ (H)

Isothermal Gradient Model 4500 4600 C 7+, mole fraction 0.00 0.05 0.10 0.15 0.20 0.25 0.30 C 7+ Reference Sample Reservoir Pressure Depth, m 4700 4800 4900 Saturation Pressure 5000 400 425 450 475 500 525 Pressure, bara

4500 IOIP(H) ~ z C7+ (H) C 7+, mol-% 0% 5% 10% 15% 20% 25% 30% Depth, m 4600 4700 4800 4900 Reference Sample STO Oil Added Using Gradient Calculation GOC 5000 400 425 450 475 500 525

Non-Isothermal Gradient Models Component Net Flux = Zero Chemical Energy Gravity Thermal Diffusion??? Given { H ref, p Rref, T ref, z iref } calculate z i (H) p R (H) p sat (H) T(H)

Non-Isothermal Gradients Thermal Diffusion Models Thermodynamic G T Haase Kempers Thermodynamic / Viscosity G T T Dougherty-Drickhamer (Belery-da Silva) Firoozabadi-Ghorayeb Passive G T Thermal Diffusion = 0, T 0

Ekofisk Example -9400 Depth, ft SSL -9700-10000 -10300-10600 Isothermal GCE Haase Kempers Belery, da Silva (25%) Firoozabadi-Ghorayeb -10900 15 20 25 30 C7+ Mole Percent

Cupiagua Reference Depth -11000 GOC Depth, ft SSL -12000-13000 -14000 Isothermal Model Field-Data Based Initialization -15000 4000 5000 6000 7000 Pressure, psia

Cupiagua -11000 Reference Depth GOC -12000 Depth, ft SSL -13000 Field-Data Based Initialization Isothermal Model -14000-15000 0.2 0.4 0.6 0.8 IOIP / HCPV, (Sm 3 / m 3 )

Cupiagua -11000 Reference Depth GOC -12000 Depth, ft SSL -13000 Field-Data Based Initialization Isothermal Model -14000-15000 10 15 20 25 30 35 C7+ Mole Percent

Theory Summary Isothermal model gives maximum gradient Convection tends to eliminate gradients Non-isothermal models generally give a gradient between these two extremes

Complicating Factors when traditional 1D models are inadequate Thermally-induced convection Stationary State not yet reached Dynamic aquifer depletes light components Asphaltene precipitation Varying PNA distribution of C 7+ components Biodegredation Regional methane concentration gradients Multiple source rocks

Practice Using Samples Quantifying Uncertainties Develop a Consistent EOS Model Defining Trends Fluid Communication Initializing Reservoir Models History Matching

Using Samples Plot C 7+ mol-% versus depth z C7+ ~ 1/B o = OGR/B gd i.e. IOIP=f(depth) Quantifying Uncertainty Use error bars for depth & composition C 7+ OGR / (C o + OGR) C o =(M/ρ) 7+ (p sc /RT sc )

3800 Åsgard, Smørbukk Field Geologic Layer A True Vertical Depth, mss 4000 4200 4400 4600 4800 Well B Well A DST 2 Well A DST 1 Well C Well D Well E 5000 0 5 10 15 20 25 30 35 C 7+ Mole Percent

Develop a Consistent EOS Use All Available Samples with Reliable Compositions Reliable PVT Data Fit Key PVT and Compositional Data Reservoir Densities Surface GORs, FVFs, STO Densities CVD Gas C 7+ Composition vs Pressure Reservoir Equilibrium Phase Compositions

Defining Trends Use All Samples Available Sample Exploration Wells Separator Samples Bottomhole Samples MDT Samples (water-based mud only) Oil Samples may be Corrected Gas Samples with Oil-Based Mud should not be used

Defining Trends Use All Samples Available Production Wells Early Data not yet affected by Significant Depletion Gas Breakthrough Fluid Displacement / Movement

Defining Trends Any sample's value in establishing a trend is automatically defined by inclusion of the samples error bars in depth and composition. Samples considered more insitu-representative are given more "weight" in trend analysis.

Fluid Communication Compute isothermal gradient for each and every sample Overlay all samples with their predicted gradients Don t expect complete consistency Do the gradient predictions have similar shape? Do the gradient predictions cover similar range in C 7+?

3800 Åsgard, Smørbukk Field Geologic Layer A True Vertical Depth, mss 4000 4200 4400 4600 4800 Well B Well A DST 2 Well A DST 1 Well D Well E Well C 5000 0 5 10 15 20 25 30 35 C 7+ Mole Percent

Orocual Field Venezuela 12,000 13,000 ORS-56 ORS-54 Structurally High Wells ORS-54 ORS-65 Mid-Perforation Depth, ft SS 14,000 15,000 ORC-25 ORS-66 16,000 0 5 10 15 20 25 C7+ Mole Percent

Initializing Reservoir Models Linear interpolation between select samples Guarantees Automatic History Matching Check for consistent of p sat vs depth Extrapolation Sensitivity 1 : isothermal gradient of outermost samples Sensitivity 2 : constant composition of outermost samples

3800 Åsgard, Smørbukk Field Geologic Layer A True Vertical Depth, mss 4000 4200 4400 4600 4800 Well B Well A DST 2 Well A DST 1 Well D Well E Well C 5000 0 5 10 15 20 25 30 35 C 7+ Mole Percent

3800 Åsgard, Smørbukk Field Geologic Layer A True Vertical Depth, mss 4000 4200 4400 4600 4800 Well B Well A DST 2 Well A DST 1 Well D Well E Well C 5000 0 5 10 15 20 25 30 35 C 7+ Mole Percent

Predicting a Gas-Oil Contact Dangerous but Necessary Use Isothermal Gradient Model Predicts minimum distance to GOC Most Uncertain Prediction using Gas Samples 10 50 m oil column per bar uncertainty in dewpoint! 2 10 ft oil column per psi uncertainty in dewpoint! Treat dewpoints (and bubblepoints) with special care