Guidelines for Choosing Compositional and Black-Oil Models for Volatile Oil and Gas-Condensate Reservoirs

Abstract

This paper provides specific guidelines for choosing the PVT model, black-oil or equation of state (EOS), for full-field reservoir simulation of volatile/near-critical oil and gas condensate fluid systems produced by depletion and/or gas injection. In the paper we have used a "generic" reservoir from the North Sea containing a fluid system with compositional grading from a medium-rich gas condensate upstructure, through an undersaturated critical mixture at the gas-oil contact, to a volatile oil downstructure. A component pseudoization procedure is described which involves a stepwise automated regression from the original 22-component EOS. We found that a six-component pseudoized EOS model described the reservoir fluid system with good accuracy and, for the most part, this EOS model was used in the study. Methods are proposed for generating consistent black-oil PVT tables for this complex fluid system. The methods are based on consistent initialization and accurate in-place surface gas and surface oil volumes when compared with initialization with an EOS model. We also discuss the trade-off between accurate initialization and accurate depletion performance (oil and gas recoveries). Each "reservoir" is simulated using black-oil and compositional models for various depletion and gas injection cases. The simulated performance for the two PVT models is compared for fluid systems ranging from a medium rich gas condensate to a critical fluid, to slightly volatile oils. The initial reservoir fluid composition is either constant with depth or exhibits a vertical compositional gradient. Scenarios both with saturated and undersaturated GOC are considered. The reservoir performance for the two PVT models is also compared for different permeability distributions. Reservoir simulation results show that the black-oil model can be used for all depletion cases if the black-oil PVT data are generated properly. In most gas injection cases, the black-oil model is not recommended—with only a few exceptions. We also show that black-oil simulations using solution oil/gas ratio equal to zero (rs=0) does not always define a conservative ("P10") sensitivity for gas injection processes. If gravity segregation is strong, the incremental loss of oil recovery due to "zero vaporization" is more than offset by exaggerated density differences caused by erroneous gas densities. Introduction Reservoir simulation is a versatile tool for reservoir engineering. Usually CPU-time is the limiting factor when the simulation model is made. The objective of this paper is to provide guidelines for choosing black-oil or compositional reservoir simulators. The paper also recommends procedures for generation of black-oil PVT tables and for initialization of black-oil and pseudoized EOS simulation models. Furthermore, a stepwise component pseudoization procedure in order to minimize the number of component when a compositional simulator is required. Simulated production performance both for injection and depletion from black-oil and compositional are compared for a variety of reservoir fluids ranging a medium rich gas condensate to a critical fluid, to slightly volatile. Both reservoirs with constant composition and compositional grading reservoir with depth have been simulated. Selection of Reservoir Fluid System A fluid sample was selected from a North Sea field. The reservoir is slightly undersaturated with an initial reservoir pressure of 490 bara at the "reference" depth of 4640 m MSL. The selected reference sample contains 8.6 mol-% C7+, it has a two-stage GOR of 1100 Sm3/Sm3 and a dewpoint of 452 bara at 163°C. Table 1 gives the reference fluid composition (Fig. 1). 22-Component SRK EOS Model The Pedersen et al. SRK1 EOS characterization method was used to generate the "base" EOS model. Decanes-plus was split into 9 fractions using the EOS simulation program PVTsim.

Compartmentalization or gravity segregation? Understanding and predicting characteristics of near-critical petroleum fluids

“…A multi-stage flash calculation, as described using a Peng-Robinson EOS (Tsai & Chen 1998), is more appropriate. Fevang et al (2000) propose a systematic approach to choosing the correct fluid model for PVT modelling of critical fluids.…”

Gas Condensate Damage in Hydraulically Fractured Wells

“…Fevang et al 18 studied a variety of fluids ranging from medium rich gas condensate to near critical fluids using black-oil and compositional models. They simulated production for both injection and natural depletion production schemes and compared the results obtained with both models.…”

“…Fevang et al 18 recommended the use of compositional simulation models for gas injection studies and limited the use of black-oil model only for reservoir fluids with minimal vaporization, and lean gas condensate reservoirs undergoing cycling injection above the dewpoint pressure.…”

Estimating oil–gas ratio for volatile oil and gas condensate reservoirs: artificial neural network, support vector machines and functional network approach

“…Walsh and Towler (1994) also introduced another method to compute the MBO properties from the CVD experiment data of gas condensate. Fevang et al (2000), showed strategies to assist engineers in choosing either MBO or compositional approaches. In 2006, Fattah et al presented Alimadadi et al (2011), predicted the PVT properties using ANN model.…”