Curtis H. Whitson

Characterizing hydrocarbon plus fractions

Methods are developed for characterizing the molar distribution (mole fraction/molecular weight relation) and physical properties of petroleum fractions such as heptanes-plus (C/sub 7/ +). These methods should enhance equation-of-state (EOS) predictions when experimental data are lacking. The three-parameter gamma probability function is used to characterize the molar distribution, as well as to fit experimental weight and molar distributions and to generate synthetic distributions of heptanes-plus fractions. Equations are provided for calculating physical properties such as critical pressure and temperature of single carbon-number (SCN) groups. A simple three-parameter equation is also presented for calculating the Watson characterization factor from molecular weight and specific gravity. Finally, a regrouping scheme is developed to reduce extended analyses to only a few multiple-carbon-number (MCN) groups. Two sets of mixing rules are considered, giving essentially the same results when used with the proposed regrouping procedure.

Modeling Gas-Condensate Well Deliverability

This paper gives an accurate method for modeling the deliverability of gas condensate wells. Well deliverability is calculated using a modified form of the Evinger-Muskat 1 pseudopressure (originally proposed for solution gas drive oil wells). The producing GOR is needed to calculate pseudopressure, together with PVT properties (black-oil or compositional), and gas-oil relative permeabilities. The proposed method is successfully tested for radial, vertically fractured, and horizontal wells. Using the proposed deliverability model, we show that fine-grid single-well simulations can be reproduced almost exactly with a simple rate equation using pseudopressure. The key is knowing the producing GOR accurately. The effect of near-wellbore damage, vertical fracture, or flow improvement due to horizontal well trajectory is readily incorporated into the rate equation as a constant skin term. The effect of gas-oil relative permeability is studied. We show that well deliverability impairment due to near-wellbore condensate blockage is only dependent on the relative permeabilities within the range defined by 1 0.3) only affect deliverability for richer gas condensates (with maximum liquid dropout of 10% or greater). A key observation and conclusion from this study is that critical oil saturation has no direct effect on well deliverability. We also show that IFT-dependence of relative permeability has little or no effect on gas condensate well performance (e.g. length of plateau production). The most important application of this study is to provide a simple method for calculating bottomhole flowing pressure (BHFP) in coarse-grid models. We show that the proposed pseudopressure method is readily calculated for each well grid cell based only on grid cell pressure and producing GOR. Local grid refinement near wells is not necessary, and relatively large well grid cells can be used while still providing an accurate description of well deliverability. Based on our analysis of the three basic flow regions of a gas condensate well, and the large effect of near-wellbore condensate blockage on well deliverability, we propose an experimental procedure for measuring relative permeabilities (specifically for modeling well deliverability).

Evaluating Constant-Volume Depletion Data

This paper presents methods for evaluating constant volume depletion (CVD) data obtained from experimental analyses of gas condensates and volatile oils. Theoretical and practical developments are supported by experimental data from a North Sea gas-condensate fluid. The three major contributions of the work are: presentation of material-balance equations to calculate fluid properties from measured CVD data; a simple method for calculating black-oil formation volume factors and solution GORs using material-balance results and a separator flash program; and investigation of the Peng-Robinson (PR) equation of state (EOS) as a tool for matching measured PVT data and studying vapor/liquid phase behavior during CVD.

Compositional Grading - Theory and Practice

AbstractThis paper quantifies the potential variation in compositionand PVT properties with depth due to gravity, chemical, andthermal forces. A wide range of reservoir fluid systems havebeen studied using all of the known published models forthermal diffusion in the non-isothermal mass transportproblem.Previous studies dealing with the combined effect ofgravity and vertical thermal gradients on compositionalgrading have either been (1) of a theoretical nature, withoutexamples from reservoir fluid systems, or (2) proposing oneparticular thermal diffusion model, usually for a specificreservoir, without comparing the results with other thermaldiffusion models.We give a short review of gravity/non-isothermal modelspublished to date. In particular, we show quantitativedifferences in the various models for a wide range of reservoirfluids systems. Solution algorithms and numerical stabilityproblems are discussed for the non-isothermal models whichrequire numerical discretization, unlike the exact analyticalsolution of the isothermal gradient problem.A discussion is given of the problems related to fluidinitialization in reservoir models of complex fluid systems.This involves the synthesis of measured sample data andtheoretical models. Specific recommendations are given forinterpolation and extrapolation of vertical compositionalgradients. The importance of dewpoint on the estimation of agas-oil contact is emphasized, particularly for newly-discovered reservoirs where only a gas sample is available andthe reservoir is near saturated.Finally, we present two field case histories – one where theisothermal gravity/chemical equilibrium model describesmeasured compositional gradients in a reservoir gradingcontinuously from a rich gas condensate to a volatile oil; andanother example where the isothermal model is grosslyinconsistent with measured data and convection or thermaldiffusion has apparently resulted in a more-or-less constantcomposition over a vertical column of some 5000 ft.IntroductionComposition variation with depth can result for severalreasons:1. Gravity segregates the heaviest components towards thebottom and lighter components like methane towards thetop

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

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 22component 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 blackoil model is not recommended  with only a few exceptions. We also show that black-oil simulations using solution oil/gas ratio equal to zero (r s=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.

Fluid Characterisation for Gas Injection Study using Equilibrium Contact Mixing

Abstract This paper describes the development of an equation of state (EOS) for a gas injection simulation study of a compositionally-grading near-critical oil reservoir. As the number of initial oil sample was limited and no gas-cap gas compositional data was available, the equilibrium contact mixing (ECM) test was used to (a) help tune the EOS to near-critical phase equilibrium existing at the near-critical gas-oil contact, and (b) to estimate the initial gas-cap PVT properties. Available standard depletion type PVT data, multi-contact swelling test data, slim tube test data and ECM data were used in the development of the full-fluid “detailed” EOS using 16 components. Characterisation of the C 7+ fraction together with regression of EOS parameters was carried out to tune the fluid model to match all available measured PVT data. Isothermal compositional gradient calculations were performed for all available samples and then a sample was selected to best represent the most important measured properties such as saturation pressure, saturated density and the compositional gradients in the reservoir. Equilibrium contact mixing data provide key gas-cap gas properties and vapour/liquid phase equilibria data for developing the EOS, also important for studying near-miscible gas injection processes.