Production Modeling in the Eagle Ford Gas Condensate Window: Integrating New Relationships between Core Permeability, Pore Size, and Confined PVT Properties

2014 ◽  
Author(s):  
Alireza Sanaei ◽  
Ahmad Jamili ◽  
Jeffrey Callard ◽  
Ashish Mathur
Keyword(s):  
Pore Size ◽  
Gas Condensate ◽  
Pvt Properties ◽  
Eagle Ford ◽  
Core Permeability ◽  
Production Modeling

Fundamental PVT Calculations for Associated and Gas/Condensate Natural-Gas Systems

2007 ◽  
Vol 10 (03) ◽  
pp. 270-284 ◽  
Author(s):  
Robert P. Sutton
Keyword(s):  
Compressibility Factor ◽  
Pure Component ◽  
Gas Condensate ◽  
High Gravity ◽  
Pvt Properties ◽  
Reduced Pressure ◽  
Data Set ◽  
Associated Gas ◽  
Gas Condensates ◽  
Compressibility Factors

Summary Problems with existing procedures used to estimate gas pressure/volume/temperature (PVT) properties are identified. The situation is reviewed, and methods are proposed to alleviate these problems. Natural gases are derived from two basic sources: associated gas, which is liberated from oil, and gas condensates, where hydrocarbon liquid, if present, is vaporized in the gas phase. The two gases are fundamentally different in that a high-gravity associated gas is typically rich in ethane through pentane, while gas condensates are rich in heptanes-plus. Additionally, either type of gas may contain nonhydrocarbon impurities such as hydrogen sulfide, carbon dioxide, and nitrogen. Failure to distinguish properly between the two types of gases can result in calculation errors in excess of those allowable for technical work. Sutton (1985) investigated high-gravity gas/condensate gases and developed methods for estimating pseudocritical properties that resulted in more-accurate Z factors. The method is suitable for all light natural gases and the heavier gas/condensate gases. It should not be used for high-gravity hydrocarbon gases that do not contain a significant heptanes-plus component. The original Sutton database of gas/condensate PVT properties has been expanded to 2,264 gas compositions with more than 10,000 gas-compressibility-factor measurements. A database of associated-gas compositions containing more than 3,200 compositions has been created to evaluate suitable methods for estimating PVT properties for this category of gas. Pure-component data for methane (CH4), methane-propane, methane-n-butane, methane-n-decane, and methane-propane-n-decane have been compiled to determine the suitability of the derived methods. The Wichert (1970) database of sour-gas-compressibility factors has been supplemented with additional field and pure-component data to investigate suitable adjustments to pseudocritical properties that ensure accurate estimates of compressibility factors. Mathematical representations of compressibility-factor charts commonly used by the engineering community and methods used by the geophysics community are investigated. Generally, these representations/methods are robust and have been found suitable for ranges beyond those recommended originally. Natural-gas viscosity, typically estimated through correlation, has been found to be inadequate for high-gravity gas condensates, requiring revised procedures for accurate calculations. Introduction Since its publication, the Standing and Katz (1942) (SK) gas Z-factor chart has become a standard in the industry. Several very accurate methods have been developed to represent the chart digitally. The engineering community typically uses methods published by Hall and Yarborough (1973, 1974) (HY), Dranchuk et al. (1974) (DPR), and Dranchuk and Abou-Kassem (1975) (DAK). These methods all use some form of an equation of state that has been fitted specifically to selected digital Z-factor-chart data published by Poettmann and Carpenter (1952). The geophysics community typically uses a method developed by Batzle and Wang (1992) (BW). Recently, Londono et al. (2002) (LAB) refitted the chart with an expanded data set, resulting in a modified DAK method. They provided two equations: one fit to an expanded data set from the SK Z-factor chart and another that included pure-component data. A general gas Z-factor chart, such as the one developed by Standing and Katz (1942), is based on the principle of corresponding states (Katz et al. 1959). This principle states that two substances at the same conditions referenced to critical pressure and critical temperature will have similar properties. These conditions are referred to as reduced pressure and reduced temperature. Therefore, if two substances are compared at the same reduced conditions, the substances will have similar properties. In the context of this paper, the property of interest is the gas Z factor. Mathematically, the SK chart relates Z factor to reduced pressure and reduced temperature.

Multiscale Pressure/Volume/Temperature Simulation of Decreasing Condensate/Gas Ratio at Greater than Dewpoint Pressure in Shale Gas-Condensate Reservoirs

SPE Journal ◽  
2021 ◽  
pp. 1-13
Author(s):  
Sheng Luo ◽  
Fangxuan Chen ◽  
Dengen Zhou ◽  
Hadi Nasrabadi
Keyword(s):  
Pore Size ◽  
Shale Gas ◽  
Local Equilibrium ◽  
Gas Condensate ◽  
Abnormal Behavior ◽  
Fluid Distribution ◽  
Reservoir Pressure ◽  
Heavy Hydrocarbons ◽  
Gas Condensate Reservoirs ◽  
Gas Ratio

Summary In shale gas-condensate reservoirs, when the initial reservoir pressure is greater than the dewpoint pressure, the condensate/gas ratio (CGR) has been observed to decrease continuously as the pressure drops to less than the initial reservoir pressure. This abnormal behavior cannot be explained with conventional pressure/volume/temperature (PVT) models that ignore the presence of nanopores in shale rock. Herein, for the first time, we present a study that provides a physical explanation for the observed CGR trends by including the effect of nanopores on the fluid phase behavior and depletion of shale gas-condensate reservoirs. Our model uses multiscale PVT simulation by means of a pore-size-dependent equation of state (EOS). Two lean gas-condensate cases (shallow and deep reservoirs) are investigated. The simulation results show that hydrocarbons distribute heterogeneously with respect to pore size on the nanoscale. There are more intermediate to heavy hydrocarbons (C3–11+) but fewer light ends (C1–2) distributed in the nanopores than in the bulk region. At the end of depletion, because of confinement effects, large amounts of intermediate hydrocarbons are trapped in the nanopores, causing condensate recovery loss. Multiscale depletion simulations suggest that a decreasing CGR can occur at the beginning of production when the reservoir pressure is higher than the dewpoint pressure. Such behavior is caused by the nanopore depletion in the shale matrix, which is a process of selectively releasing light hydrocarbon components. We also present a novel approach to model the nonequilibrium fluid distribution between the fracture and nanopores using a simple local-equilibrium concept. Our results indicate that the nonequilibrium fluid distribution increases the CGR drop because of the compositional selectivity of the nanopore in favor of intermediate and heavy hydrocarbons.

Gas Injection EOR in Eagle Ford Shale Gas Condensate Reservoirs

2019 ◽  
Author(s):  
Reza Ganjdanesh ◽  
Wei Yu ◽  
Mauricio Xavier Fiallos ◽  
Erich Kerr ◽  
Kamy Sepehrnoori ◽  
...  
Keyword(s):  
Shale Gas ◽  
Gas Injection ◽  
Gas Condensate ◽  
Eagle Ford Shale ◽  
Eagle Ford ◽  
Gas Condensate Reservoirs

scholarly journals Evaluating the Challenges in Pressure – Volume – Temperature (PVT) Analysis of Gas Condensate Reservoirs

2020 ◽  
pp. 13-18
Author(s):  
Aniedi B. Usungedo ◽  
Julius U. Akpabio
Keyword(s):  
Gas Condensate ◽  
Production Performance ◽  
Prediction Algorithm ◽  
Pvt Properties ◽  
Volume Depletion ◽  
Volume Factor ◽  
Gas Condensate Reservoirs ◽  
Compositional Model ◽  
Compositional Modeling ◽  
Black Oil

Aims: The variations in production performances of the Black oil and compositional simulation models can be evaluated by simulating oil formation volume factor (Bo), gas formation volume factor (Bg), gas-oil ratio (Rs) and volatilized oil-gas ratio (Rv). The accuracy of these two models could be assessed. Methodology: To achieve this objective some basic parameters were keyed into matrix laboratory (MATLAB) using the symbolic mathematical toolbox to obtain accurate Pressure Volume Temperature (PVT) properties which were used in a production and systems analysis software to generate the production performance and hydrocarbon recovery estimation. Standard black oil PVT properties for a gas condensate reservoir was simulated by performing a series of flash calculations based on compositional modeling of the gas condensate fluid at the prescribed conditions through a constant volume depletion (CVD) path. These series of calculations will be carried out using the symbolic math toolbox. PVT property values obtained from both compositional modeling and black oil PVT prediction algorithm are incorporated to determine the production performance of each method for comparison. Results: The absolute open flow for the black oil PVT algorithm and the compositional model for the Rs value of 500 SCF/STB and Rs value of 720SCF/STB were 130,461 stb/d and 146,028 stb/d respectively showing a 10.66% incremental flow rate. Conclusion: In analyzing PVT properties for complex systems such as gas condensate reservoirs, the use of compositional modeling should be practiced. This will ensure accurate prediction of the reservoir fluid properties.

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