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This work describes a method for estimating reservoir fluid composition for gas condensates and volatile oils from readily available field data. Required data are separator conditions; first stage separator gas specific gravity, non-hydrocarbon impurities content, and gas-liquid ratio; and stock tank API gravity. The well must be stabilized, and the flowing bottomhole pressure must be above the saturation pressure.A database comprising compositions for 23 wet gases, 33 gas condensates, and 19 volatile oils was taken from the literature. The data sets included compositions in mole fractions of methane through heptanes-plus and nonhydrocarbon impurities, along with molecular weight and specific gravity of the heptanes-plus fraction. The database was restricted to fluids with heptanes-plus content between 1 and 25 mole %, and with relatively low non-hydrocarbon impurities content (less than 4 mole % H 2 S, less than 6 mole % CO 2 , less than 11 mole % N 2 , and less than 18 mole % total nonhydrocarbons).The method predicts reservoir fluid composition through heptanes-plus along with molecular weight and specific gravity of the heptanes-plus fraction. The resulting reservoir fluid composition may be used with an untuned equation of state to obtain preliminary estimates of saturation pressure, maximum liquid dropout, and modified-black-oil (MBO) fluid property tables for simulation. The predicted composition may also be used as a cross check of laboratory-measured composition.The method has been tested on data sets for 16 gas condensates that were not part of the composition database. Predicted compositions were surprisingly accurate, with average absolute errors (AAE) for methane, 1.0 mole %; ethane, 1.2 mole %; propane, 0.7 mole %; butanes, 0.5 mole %; pentanes, 0.3 mole %; hexanes, 0.3 mole %, and heptanes-plus, 0.4 mole %. Predicted specific gravities and molecular weights of the heptanes-plus fraction had average absolute relative errors (AARE) of 1.3% and 9.7%, respectively. Saturation pressures calculated from the predicted gas-condensate compositions using an untuned equation of state had an average relative error (ARE) of -0.3% and an AARE of 6.9%, with a median relative error of -3.7% and a median absolute relative error of 4.5%.Because of the current commercial importance of liquids-rich gas plays, the method should find application for 1) obtaining preliminary estimates of composition before laboratory data are available, 2) estimating PVT properties such as saturation pressure, maximum liquid dropout, and MBO fluid property tables from field data when PVT measurements are not available, and 3) cross-checking laboratory-measured compositions. SPE 166414One recent correlation (Nassar et al 2013) has been proposed for calculating all four of the MBO volumetric properties, but does not include viscosities of the reservoir liquid and vapor phases. It is based on equation-of-state calculations, which honor the physical and thermodynamic constraints, but those constraints are not built into the correlations them...
This work describes a method for estimating reservoir fluid composition for gas condensates and volatile oils from readily available field data. Required data are separator conditions; first stage separator gas specific gravity, non-hydrocarbon impurities content, and gas-liquid ratio; and stock tank API gravity. The well must be stabilized, and the flowing bottomhole pressure must be above the saturation pressure.A database comprising compositions for 23 wet gases, 33 gas condensates, and 19 volatile oils was taken from the literature. The data sets included compositions in mole fractions of methane through heptanes-plus and nonhydrocarbon impurities, along with molecular weight and specific gravity of the heptanes-plus fraction. The database was restricted to fluids with heptanes-plus content between 1 and 25 mole %, and with relatively low non-hydrocarbon impurities content (less than 4 mole % H 2 S, less than 6 mole % CO 2 , less than 11 mole % N 2 , and less than 18 mole % total nonhydrocarbons).The method predicts reservoir fluid composition through heptanes-plus along with molecular weight and specific gravity of the heptanes-plus fraction. The resulting reservoir fluid composition may be used with an untuned equation of state to obtain preliminary estimates of saturation pressure, maximum liquid dropout, and modified-black-oil (MBO) fluid property tables for simulation. The predicted composition may also be used as a cross check of laboratory-measured composition.The method has been tested on data sets for 16 gas condensates that were not part of the composition database. Predicted compositions were surprisingly accurate, with average absolute errors (AAE) for methane, 1.0 mole %; ethane, 1.2 mole %; propane, 0.7 mole %; butanes, 0.5 mole %; pentanes, 0.3 mole %; hexanes, 0.3 mole %, and heptanes-plus, 0.4 mole %. Predicted specific gravities and molecular weights of the heptanes-plus fraction had average absolute relative errors (AARE) of 1.3% and 9.7%, respectively. Saturation pressures calculated from the predicted gas-condensate compositions using an untuned equation of state had an average relative error (ARE) of -0.3% and an AARE of 6.9%, with a median relative error of -3.7% and a median absolute relative error of 4.5%.Because of the current commercial importance of liquids-rich gas plays, the method should find application for 1) obtaining preliminary estimates of composition before laboratory data are available, 2) estimating PVT properties such as saturation pressure, maximum liquid dropout, and MBO fluid property tables from field data when PVT measurements are not available, and 3) cross-checking laboratory-measured compositions. SPE 166414One recent correlation (Nassar et al 2013) has been proposed for calculating all four of the MBO volumetric properties, but does not include viscosities of the reservoir liquid and vapor phases. It is based on equation-of-state calculations, which honor the physical and thermodynamic constraints, but those constraints are not built into the correlations them...
A new semi-implicit formulation to solve the set of nonlinear difference equations that describe multiphase compositional flow in a reservoir is presented in this paper. Newton's method is applied on the nonlinear difference equations obtained after treating compositions in the flow terms explicitly, one iteration behind. The linearized system of equations generated from this treatment possess a peculiar matrix structure, that allows the reduction of the system, via matrix operations, to three equations in three unknowns per gridblock regardless of the number of components. The level of implicitness of the formulation presented in this paper is intermediate to IMPECS and Fully-Implicit methods and has a higher level of implicitness than a semi-implicit method previously proposed in the literature. It provides an attractive approach to solve problems where the rate of change of pressures, saturations and compositions in the reservoir are important, such that IMPECS method becomes impractical and the Fully-Implicit method becomes too expensive. Applications to the simulation of a well-test in a gas-condensate well and the natural depletion and gas-cycling of a volatile-oil reservoir are presented. Introduction Compositional simulation is an important tool to optimize recovery of reservoirs subject to changes in the composition of the hydrocarbon phases along the productive life of the reservoir. Gas-condensate and volatile-oil reservoirs are typical examples in which compositional simulation is mandatory. The first compositional simulators of general application were developed by Kazemi et al. in 1978 and by Fussell and Fussell in 1979. Thermodynamic equilibrium for the hydrocarbon phases was handled by Kazemi et al. through experimentally obtained equilibrium ratios, while Fussell and Fussell introduced the use of an equation of state. The approach used by these authors for solving the compositional reservoir flow equations is an extension of IMPES method, applied in black-oil simulation, which could be referred to as IMPECS, implicit pressure explicit compositions and saturations, method. IMPECS methods are attractive due to the relatively small computer work requirements, that make numerical simulation inexpensive; the low level of implicitness used to solve the flow difference equations makes such methods impractical in some applications. In 1980, Coats presented an implicit formulation, based on Newton iteration, to simulate compositional reservoir problems with an equation of state. The high numerical stability of the implicit method, with enhanced efficiency and reliability to handle most compositional problems, demands larger computer work requirements, that increase with the number of pseudocomponents being considered. In 1981, Nghiem et al. presented a variation of Kazemi et al.'s method that used an equation of state. They suggested the use of two-point upstream weighting for transmissibilities in the flow terms. Watts in 1983, based on the ideas of Acs et al., presented another approach, the sequential-implicit method, to solve the compositional flow difference equations. An attempt was made of combining the advantages of IMPECS while retaining some of the stability characteristics of the implicit method. Quandalle and Savary presented in 1989 a method, implicit in pressure and saturations and explicit in compositions, for the compositional problem. For multiphase flow, oil-gas-water, the gridblock equations are reduced to three equations in three primary unknowns, po, Sg and Sw. In doing this, the subset of thermodynamic equations is arbitrarily decoupled and then used, after solving for the primary unknowns, in a sequential fashion to solve for the oil and gas phase compositions; this is done as in IMPECS method by performing flash calculations on a cell-by-cell basis.
In this paper we present a general formulation to solve the non-linear difference equations that arise in compositional reservoir simulation. The general approach here presented is based on Newton's method and provides a systematic approach to generate several formulations to solve the compositional problem, each possesing a different degree of implicitness and stability characteristics. The Fully-Implicit method is at the higher end of the implicitness spectrum while the IMPECS method, implicit in pressure-explicit in composition and saturation, is at the lower end. We show that all methods may be obtained as particular cases of the fully-implicit method. Regarding the matrix problem, all methods have a similar matrix structure; the composition of the Jacobian matrix is however unique in each case, being in some instances amenable to reductions for optimal solution of the matrix problem. Based on this, a different approach to derive IMPECS type methods is proposed; in this case, the whole set of 2nc + 6 equations, that apply in each gridblock, is reduced to a single pressure equation through matrix reduction operations; this provides a more stable numerical scheme, compared to other published IMPECS methods, in which the subset of thermodynamic equilibrium equations is arbitrarily decoupled from the set of gridblock equations to perform such reduction. We discuss how the general formulation here presented can be used to formulate and construct an adaptive-implicit compositional simulator. We also present results on the numerical performance of FI, IMPSEC and IMPECS methods on some test problems.
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