An Equation of State Compositional Model

1980 ◽  
Vol 20 (05) ◽  
pp. 363-376 ◽  
Author(s):  
Keith H. Coats
Keyword(s):  
Equation Of State ◽  
Critical Point ◽  
Oil And Gas ◽  
Numerical Models ◽  
Volatile Oil ◽  
Gas Condensate ◽  
Numerical Dispersion ◽  
Stable Convergence ◽  
Compositional Model ◽  
Miscible Flooding

Abstract This paper describes an implicit, three-dimensional formulation for simulating compositional-type reservoir problems. The model treats three-phase flow in Cartesian (x-y-z) or cylindrical (r-theta-z) geometries. Applicability ranges from depletion or cycling of volatile oil and gas condensate to miscible flooding operations involving either outright or multicontact-miscibility.The formulation uses an equation of state for phase equilibrium and property calculations. The equation of state provides consistency and smoothness as gas- and oil-phase compositions and properties converge near a critical point. This avoids computational problems near a critical point associated with use of different correlations for K values as opposed to phase densities. Computational testing with example multicontact-miscibility (MCM) problems indicates stable convergence of this formulation as phase properties converge at a critical point. Results for these MCM problems show significant numerical dispersion, primarily affecting the calculated velocity of the miscible-front advance. Our continuing effort is directed toward reduction of this numerical disperson and comparison of model results with laboratory experiments for both MCM and outright-miscibility cases.We feel that the implicit nature of the model enhances efficiency as well as reliability for most compositional-type problems. However, while we report detailed problem results and associated computing times, we lack similar reported times to compare the overall efficiency of an implicit compositional formulation with that of a semi-implicit formulation. Introduction Many papers have treated increasingly sophisticated or efficient methods for numerical modeling of black-oil reservoir performance. That type of reservoir allows an assumption that reservoir gas and oil have different but fixed compositions, with the solubility of gas in oil being dependent on pressure alone.A smaller number of papers have presented numerical models for simulating isothermal "compositional" reservoirs, where oil and gas equilibrium compositions vary considerably with spatial position and time. With some simplification, the reservoir problems requiring compositional treatment can be divided into two types. The first type is depletion and/or cycling of volatile oil and gas condensate reservoirs. The second type is miscible flooding with MCM generated in situ.A distinction between these types is that the first usually involves phase compositions removed from the critical point, while the second type generally requires calculation of phase compositions and properties converging at the critical point. A compositional model should be capable of treating the additional problem of outright miscibility where the original oil and injected fluid are miscible on first contact.A difficulty in modeling the MCM process is achievement of consistent, stable convergence of gas-and oil-phase compositions, densities, and viscosities as the critical point is approached. A number of studies have reported models that use different correlations for equilibrium K-values as opposed to phase densities. Use of an equation of state offers the advantage of a single, consistent source of calculated K-values, phase densities, and their densities near a critical point. SPEJ P. 363＾

Determination of Bubble-Point and Dew-Point Pressure Without a Visual Cell

2014 ◽  
Author(s):  
R.. Hosein ◽  
R.. Mayrhoo ◽  
W. D. McCain
Keyword(s):  
Oil And Gas ◽  
Saturation Pressure ◽  
Volatile Oil ◽  
Phase Region ◽  
Gas Condensate ◽  
Dew Point ◽  
Bubble Point ◽  
Point Pressure ◽  
Dew Point Pressure

Abstract Bubble-point and dew-point pressures of oil and gas condensate reservoir fluids are used for planning the production profile of these reservoirs. Usually the best method for determination of these saturation pressures is by visual observation when a Constant Mass Expansion (CME) test is performed on a sample in a high pressure cell fitted with a glass window. In this test the cell pressure is reduced in steps and the pressure at which the first sign of gas bubbles is observed is recorded as bubble-point pressure for the oil samples and the first sign of liquid droplets is recorded as the dew-point pressure for the gas condensate samples. The experimental determination of saturation pressure especially for volatile oil and gas condensate require many small pressure reduction steps which make the observation method tedious, time consuming and expensive. In this study we have extended the Y-function which is often used to smooth out CME data for black oils below the bubble-point to determine saturation pressure of reservoir fluids. We started from the initial measured pressure and volume and by plotting log of the extended Y function which we call the YEXT function, with the corresponding pressure, two straight lines were obtained; one in the single phase region and the other in the two phase region. The point at which these two lines intersect is the saturation pressure. The differences between the saturation pressures determined by our proposed YEXT function method and the observation method was less than ± 4.0 % for the gas condensate, black oil and volatile oil samples studied. This extension of the Y function to determine dew-point and bubble-point pressures was not found elsewhere in the open literature. With this graphical method the determination of saturation pressures is less tedious and time consuming and expensive windowed cells are not required.

Applied Novel Quality Check Method for PVT Data with High Impurities Using Various Samples from Malaysian Fields

2021 ◽  
Author(s):  
Luky Hendraningrat ◽  
Intan Khalida Salleh
Keyword(s):  
Molecular Weight ◽  
Equation Of State ◽  
Gas Phase ◽  
Oil And Gas ◽  
Comprehensive Evaluation ◽  
Gas Condensate ◽  
Fluid Composition ◽  
Essential Information ◽  
Pvt Data ◽  
Wide Range

Abstract PVT analysis of reservoir fluid samples provides essential information for determining hydrocarbon in place, depletion strategy, and hydrocarbon flowability. Hence, quality checking (QC) is necessary to ensure the best representative sample for further analysis. Recently, a novel tool based on Equation of State (EOS) was introduced to tackle the limitation of the Hoffmann method for surface samples with high impurities and heavier components. This paper presents comprehensively evaluating a novel EOS-based method using various PVT data from Malaysian fields. Numerous PVT separator samples from 30 fields with various reservoir fluids (Black Oil, Volatile, and Gas Condensate) were carried out and evaluated. The impurities contain a wide range of up to 60%. The 2-phase P-T (pressure and temperature) diagram of each oil and gas phase before recombination was calculated using PVT software based on Equation of State (EOS). The 2-phase P-T diagram was created and observed the intersection point as calculated equilibrium at separator conditions. Once it is observed and compared with written separator condition in the laboratory report and observed its deviation. Eventually, the result will be compared with the Hoffmann method. The Hoffmann method is well-known as a traditional QC method that was initially developed using gas condensate PVT data to identify possible errors in measured separator samples. If the sample has high impurities and/or heavier components, the Hoffmann method will only show a straight line to the lighter components and those impurities and heavier components will be an outlier that engineers will misinterpret that it has errors and cannot be used for further analysis such PVT characterization. The QC using EOS-based were conducted using actual fields data. It shows potential as novel QC tools but observed only less than 10% of data with complete information that can meet intersection points located precisely similar with reported in the laboratory. There is some investigation and evaluation of the EOS-based QC method. First, most of the molecular weight of the heavier fluid composition of gas and oil phase was not reported or used assumptions especially when its mole fraction is not zero. Second, properties of heavier components of the oil phase (molecular weight and specific gravity) were not measured and assumed similar as wellstream. Third, pressure and temperature data are inconsistent between the oil and gas phase at the separator condition. This study can provide improvement in laboratory measurement quality and help engineers to have a better understanding of PVT Report, essential data requirements, and assumptions used in the laboratory. Nevertheless, the Hoffmann method can be used as an inexpensive QC tool because it can be generated in a spreadsheet without a PVT software license. Both combination techniques can provide a comprehensive evaluation for separator samples with high impurities before identifying representative fluid for further analysis.

Features of the geological structure of an oil and gas condensate field in Tomsk region

2021 ◽  
pp. 48-60
Author(s):  
S. F. Mulyavin ◽  
A. V. Byakov ◽  
R. A. Neschadimov
Keyword(s):  
Oil And Gas ◽  
Phase State ◽  
Volatile Oil ◽  
Geological Structure ◽  
Gas Condensate ◽  
Gas Content ◽  
Oil Viscosity ◽  
Coastal Marine ◽  
Tomsk Region ◽  
Continental Origin

The X oil and gas condensate field is located in Parabel district of Tomsk region; the field is large in terms of recoverable reserves. Oil and gas content is confined to Jurassic sediments of Tyumen suite and Vasyugan suite. The reservoirs of the Vasyugan suite are marine and coastal-marine sediments, characterized by alternating sandstones, mudstones, siltstones, clays and exhibit complex internal aging. The productive deposits of the Tyumen suite are of continental origin and are distinguished by significant lithological variability. One oil deposit (J11 stratum), one gas and oil deposit (J12 stratum) and three gas condensate deposits (J13-4, J3, J4-5 strata) were identified in the productive formations. The article analyzes the features of the geological structure and conditions of sedimentation of productive strata. In terms of its phase state and physicochemical proper-ties, the fluid of the J11 deposit is a "volatile oil", phase state of which is close to the near-critical. Reservoirs of productive formations are of terrigenous type, porous, low-permeability, while the oil productivity of the formations is high due to the ultra-low oil viscosity.

APPLICATION OF THE BLACK OIL PVT REPRESENTATION TO SIMULATION OF GAS CONDENSATE RESERVOIR PERFORMANCE

1987 ◽  
Vol 27 (1) ◽  
pp. 370
Author(s):  
W.H. Goldthorpe ◽  
J.K. Drohm
Keyword(s):  
Oil And Gas ◽  
Volatile Oil ◽  
Gas Condensate ◽  
Phase Behaviour ◽  
Dew Point ◽  
Pressure Drops ◽  
Gas Condensate Reservoirs ◽  
Reservoir Performance ◽  
Black Oil ◽  
Condensate Reservoir

Special attention must be paid to the generation of PVT parameters when applying conventional black oil reservoir simulators to the modelling of volatile oil and gas-condensate reservoirs. In such reservoirs phase behaviour is an important phenomenon and common approaches to approximating this, via the black oil PVT representation, introduce errors that may result in prediction of incorrect recoveries of surface gas and condensate. Further, determination of production tubing pressure drops for use in such simulators is also prone to errors. These affect the estimation of well potentials and reservoir abandonment pressures.Calculation of black oil PVT parameters by the method of Coats (1985) is shown to be preferred over conventional approaches, although the PVT parameters themselves lose direct physical meaning. It is essential that a properly tuned equation of state be available for use in conjunction with experimental data.Production forecasting based on simulation output requires further processing in order to translate the black oil surface phase fluxes into products such as sales gas, LPG and condensate. For gas-condensate reservoirs, such post-processing of results from the simulation of depletion or cycling above the dew point is valid. In principle it is invalid for cycling below the dew point but in practice it can still provide useful information.

scholarly journals Productions of volatile oil and gas-condensate from liquid rich shales

2018 ◽  
Vol 3 (1) ◽  
pp. 29-42 ◽  
Author(s):  
Palash Panja ◽  
Manas Pathak ◽  
Milind Deo
Keyword(s):  
Oil And Gas ◽  
Volatile Oil ◽  
Gas Condensate

scholarly journals The Adjustment of EOS of Gas-condensate Mixture under the Condition of Input Data Shortage

2020 ◽  
pp. 82-88
Author(s):  
О. V. Burachok ◽  
D. V. Pershyn ◽  
S. V. Matkivskyi ◽  
Ye. S. Bikman, Ye. S. Bikman ◽  
О. R. Kondrat
Keyword(s):  
Equation Of State ◽  
Input Data ◽  
Fractional Composition ◽  
Component Composition ◽  
Gas Condensate ◽  
Data Availability ◽  
Reservoir Modeling ◽  
Production Data ◽  
Compositional Model ◽  
Study Results

The article characterizes the key difficulties which emerge during the simulation of phase behaviors described using the model of “black oil” or fully functional compositional model with the help of the equation-of-state (EOS) in order to create valid continuously operating geological-technological 3D models of gas-condensate reservoirs. The input data for 3D filtration reservoir modeling, the development of which started in the 1960s, are the results of initial gas-condensate and thermodynamic studies. Hydrocarbon component composition of reservoir gas in the existing gas-condensate studies is given only to fraction C5+. Taking into account the peculiarities of initial thermodynamic research with the use of the differential condensation experiment and the absence of such type of experiment in the list of standard experiments in commercially-available PVT-simulators, there appeared a need to develop rational approaches and techniques for correct integration of existing geological-production data in PVT modeling. This article describes the methods for adjusting Peng-Robinson equation-of-state under the condition of input data shortage. Depending on initial data availability and quality, the authors have suggested two different methods. The first PVT-modeling method, which makes it possible to adjust the equation-of-state, is based on the data of component composition of gases and fractional composition of the stable condensate. In case the data of fractional composition of the stable condensate are not available, the authors suggest the second method that is the splitting of fraction C5+ following Whitson volumetric methodology. The suggested methods and two different approaches to EOS adjustment allow effective PVT-modeling using available geological and production data. Study results are presented as the graphical dependencies of comparison of potential hydrocarbons C5+content change in reservoir gas before and after configuring the equation-of-state, as well as the synthetic “liquid saturation” loss curve of the CVD experiment.

Prediction of Liquid Loading in Gas Condensate and Volatile Oil Wells for Unconventional Reservoirs

2020 ◽  
Author(s):  
Reem Alsadoun ◽  
Mohammad Al Momen ◽  
Hongtao Luo
Keyword(s):  
Production Efficiency ◽  
Oil And Gas ◽  
Theoretical Calculations ◽  
Volatile Oil ◽  
Gas Condensate ◽  
Economic Losses ◽  
Well Performance ◽  
Liquid Loading ◽  
Critical Rate ◽  
Correlation Models

Abstract All producing wells experience reservoir pressure depletion which will ultimately cause production to cease. However, the accumulation of wellbore liquid known as liquid loading can reduce production at a faster rate bringing forward the end of well life. In theory, there are many works written on liquid loading in unconventional wells however, these assumptions are challenged when implemented in the field. The aim of this paper is to investigate the relationship between empirical and mechanistic methods used to determine liquid loading critical rates for volatile oil and gas condensate wells, improving liquid loading forecast workflow for future wells. The study was carried on a wide Pressure, Volume, and Temperature (PVT) window with varying compositions ranging from gas condensate to volatile oils. Wells with liquid loading exhibit sharp drops and fluctuations in production. Due to the wide variation in composition however, correlations used must be varied whilst accounting for both composition and horizontal configuration of the well. Using Nodal Analysis methods, Inflow Performance Relationships (IPR) and Vertical Lift Profile (VLP) curves were created from different correlation models fitted for multiple wells selected for this study to optimize well performance. By combining theoretical analysis and field practices for estimating liquid loading critical rate, the appropriate workflow was determined for the volatile oil and gas condensate wells. When comparing the critical rate for liquid loading calculated from theoretical methods against actual rates seen in the field, an inconsistency was observed between the two values for several wells. By establishing a relationship between field estimate and theoretical calculations, liquid loading was forecasted with greater certainty for varying PVT windows. When the liquid loading rate is determined earlier on, the production efficiency can be improved by deploying unloading measures, increasing the well’s producing life, and ultimately alleviating economic losses. By investigating, we were able to establish a suitable process to predict liquid loading critical rates for volatile oil and gas condensate wells. This workflow can be utilized by production engineers to arrange for liquid loading mitigation increasing well life and improving well economics.

scholarly journals Evaluation of black-oil PVT-model applicability for simulation of gas-condensate reservoirs

2020 ◽  
pp. 43-48
Author(s):  
O. V. Burachok ◽  
D. V. Pershyn ◽  
S. V. Matkivskyi ◽  
O. R. Kondrat
Keyword(s):  
Phase Transitions ◽  
Phase Equilibrium ◽  
Phase Behavior ◽  
Oil And Gas ◽  
Gas Condensate ◽  
Potential Yield ◽  
Model Application ◽  
Compositional Model ◽  
Black Oil ◽  
Black Oil Model

Creation of geological and simulation models is the necessary condition for decision making towards current development status, planning of well interventions, field development planning and forecasting. In case of isothermal process, for proper phase behavior and phase transitions two key approaches are used: a) simplified model of non-volatile oil, so called “black oil” model, in which each phase – oil, water and gas, are represented by respective component, and solution to fiow equations is based on finding the saturations and pressures in each numerical cell, and change of reservoir fiuid properties is defined in table form as a function of pressure; b) compositional model, in which based on equation of state, phase equilibrium is calculated for hydrocarbon and non-hydrocarbon components, and during fiow calculations, apart from saturations and pressures, oil and gas mixture is brought to phase equilibrium, and material balance is calculated for each component in gas and liquid phase. To account for components volatility, the classic black oil model was improved by adding to the formulation gas solubility and vaporized oil content. This allows its application for the majority of oil and gas reservoirs, which are far from critical point and in which the phase transitions are insignificant. Due to smaller number of variables, numerical solution is simpler and faster. But, considering the importance and relevance of increasing the production of Ukrainian gas and optimization of gas-condensate fields development, the issue of simplified black oil PVT-model application for phase behavior characterization of gas-condensate reservoirs produced under natural depletion depending on the liquid hydrocarbon’s potential yield. Comparative study results on evaluation of production performance of synthetic reservoir for different synthetically-generated reservoir fiuids with different С5+ potential yield is provided as plots and tables. Based on the results the limit of simplified black oil PVT-model application and the moment of transition to compositional model for more precise results could be defined.

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