Development of a New Correlation of Gas Compressibility Factor (Z-Factor) for High Pressure Gas Reservoirs

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Mohamed Mahmoud
Keyword(s):  
High Pressures ◽  
Compressibility Factor ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Gas Formation ◽  
New Correlation ◽  
Gas System ◽  
Data Points ◽  
New Formula ◽  
Gas Compressibility

Gas compressibility factor or Z-factor for natural gas system can be determined from Standing-Katz charts using the pseudocritical gas pressure and temperatures. These charts give accurate values for Z-factors. Reservoir simulation softwares need accurate correlations to estimate the values of Z-factor; one of the well-known correlations is Dranchuk and Abou-Kassem (DAK) Correlation. This correlation gives large errors at high gas reservoir pressures, this error could be more than 100%. The error in estimating Z-factor will lead to big error in estimating all the other gas properties such as gas formation volume factor, gas compressibility, and gas in place. In this paper a new accurate Z-factor correlation has been developed using regression for more than 300 data points of measured Z-factor using matlab in addition to other data points at low pressure and temperature from Standing-Katz charts and DAK correlation. Old correlations give good estimation of Z-factor at low gas reservoir pressures below 41.37 MPa (6000 psia), at high pressures the error started to appear. The developed correlation is a function of pseudoreduced pressure and temperature of the gas which makes it simpler than the existing complicated correlations. The new correlation can be used to determine the gas compressibility factor at any pressure range especially for high pressures the error was less than 3% compared to the measured data. The developed correlation is very simple to be used, it just needs the gas specific gravity that can be used to determine the pseudocritical properties of the gas and at last the Z-factor can be determined. A new formula of reduced gas compressibility was developed based on the developed Z-factor correlation which in turn can be used to determine the gas compressibility.

Comparison of Z-Factor Correlations Using a Large PVT Dataset with Emphasis on the GERG-2008 EOS

2021 ◽  
Author(s):  
Kristian Mogensen ◽  
Robert Merrill
Keyword(s):  
Compressibility Factor ◽  
Injection Pressure ◽  
Fluid Mixtures ◽  
Cubic Equation ◽  
Industry Standard ◽  
Gas Formation ◽  
Data Points ◽  
Factor Data ◽  
First Time ◽  
Gas Compressibility

Abstract The gas compressibility factor is an important property in reservoir simulation studies. It is directly linked to the gas formation volume factor and the gas density thereby impacting wellhead injection pressure, reservoir voidage, injectivity, as well as the tendency for gas gravity override to occur in the reservoir. ADNOC's PVT database contains experiments on almost 2,000 samples, of which more than 100 have been subject to advanced gas injection experiments. Z-factor data have been compiled from the liberated gas during DV experiments as well as from CCE experiments on reservoir gases, injection gases, and swollen fluid mixtures. Several of these mixtures are very rich in H2S, whereas pressure and temperature are in the range of 14.7-14,500 psia and 80-365 °F, respectively. We test several different methods for predicting the Z-factor, such as the industry-standard Hall-Yarborough method, in combination with various models for pseudo-critical pressure and temperature and including correction for non-hydrocarbon components. Other methods tested include the GERG-2008 model, considered to be state-of-the-art for predicting physical properties for well-described gas mixtures, as well as the well-known Peng-Robinson cubic equation of state. Based on close to 10,000 data points in our database, the GERG-2008 model typically predicts the Z-factor to be within 2% of the measured value, which is on par with the experimental uncertainty. However, for some rich gas condensate mixtures, the model gives larger errors because its parameters are only tuned to compositions with components up to C10. This is to our knowledge the first time that the GERG-2008 EOS has been compared to standard Z-factor correlations for such a large number of data points. If compositional information is available, we recommend using either the GERG-2008 model or the Hall-Yarborough model with pseudo-critical properties provided by Kay (1936). When compositions are not available, we find that the Standing correlation is more accurate than the Sutton model, also for sour mixtures.

Identification Method for Shallow Gas Layers in Cased Well

2014 ◽  
Vol 508 ◽  
pp. 146-149
Author(s):  
Xiao Min Tang ◽  
Xin Deng ◽  
Jian Fu ◽  
Lin Hou
Keyword(s):  
Gas Production ◽  
Production Testing ◽  
Neutron Lifetime ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Shallow Gas ◽  
Identification Methods ◽  
Identification Method ◽  
Gas Formation

In this paper, based on log response in gas formation, effective identification curves for shallow gas reservoirs are preferred from casedhole compensated neutron log, neutron lifetime log and openhole logs, and 4 parameters and 5 overlap curves are developed for identification of shallow gas reservoirs in cased wells. A gas reservoir in cased wells is interpreted with proposed identification methods. The gas production testing results shows that the proposed methods can determine shallow gas reservoirs in cased wells accurately.

A Comprehensive Review of Recent Advances in the Estimation of Natural Gas Compressibility Factor

2021 ◽  
Author(s):  
Oluwasegun Cornelious Omobolanle ◽  
Oluwatoyin Olakunle Akinsete
Keyword(s):  
Artificial Intelligence ◽  
Equation Of State ◽  
Compressibility Factor ◽  
Operating Conditions ◽  
Measurement Equation ◽  
Comprehensive Review ◽  
Holistic Understanding ◽  
Deviation Factor ◽  
Gas Compressibility ◽  
Limited Accuracy

Abstract Accurate prediction of gas compressibility factor is essential for the evaluation of gas reserves, custody transfer and design of surface equipment. Gas compressibility factor (Z) also known as gas deviation factor can be evaluated by experimental measurement, equation of state and empirical correlation. However, these methods have been known to be expensive, complex and of limited accuracy owing to the varying operating conditions and the presence of non-hydrocarbon components in the gas stream. Recently, newer correlations with extensive application over wider range of operating conditions and crude mixtures have been developed. Also, artificial intelligence is now being deployed in the evaluation of gas compressibility factor. There is therefore a need for a holistic understanding of gas compressibility factor vis-a-vis the cause-effect relations of deviation. This paper presents a critical review of current understanding and recent efforts in the estimation of gas deviation factor.

scholarly journals Prediction of water breakthrough time in horizontal Wells in edge water condensate gas reservoirs

2020 ◽  
Vol 213 ◽  
pp. 02009
Author(s):  
Quan Hua Huang ◽  
Xing Yu Lin
Keyword(s):  
Horizontal Well ◽  
Negative Impact ◽  
Horizontal Wells ◽  
Breakthrough Time ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Water Breakthrough ◽  
Calculation Results ◽  
Seepage Model ◽  
Reasonable Prediction

Horizontal Wells are often used to develop condensate gas reservoirs. When there is edge water in the gas reservoir, it will have a negative impact on the production of natural gas. Therefore, reasonable prediction of its water breakthrough time is of great significance for the efficient development of condensate gas reservoirs.At present, the prediction model of water breakthrough time in horizontal Wells of condensate gas reservoir is not perfect, and there are mainly problems such as incomplete consideration of retrograde condensate pollution and inaccurate determination of horizontal well seepage model. Based on the ellipsoidal horizontal well seepage model, considering the advance of edge water to the bottom of the well and condensate oil to formation, the advance of edge water is divided into two processes. The time when the first water molecule reaches the bottom of the well when the edge water tongue enters is deduced, that is, the time of edge water breakthrough in condensate gas reservoir.The calculation results show that the relative error of water breakthrough time considering retrograde condensate pollution is less than that without consideration, with a higher accuracy. The example error is less than 2%, which can be effectively applied to the development of edge water gas reservoir.

Stress Sensitivity of Low Permeable and Water-Bearing Gas Reservoir without Gas Slippage Effect

2014 ◽  
Vol 962-965 ◽  
pp. 570-573
Author(s):  
Jian Yan ◽  
Xiao Bing Liang ◽  
Qian Wu ◽  
Qing Guo
Keyword(s):  
Water Saturation ◽  
Stress Sensitivity ◽  
Testing Methods ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Gas Well ◽  
Well Production ◽  
Gas Slippage ◽  
Slippage Effect ◽  
Function Relationship

Because of the gas slippage, the testing methods of stress sensitivity for gas reservoir should be different from that for oil reservoir. This text adopts the method that imposing back pressure on the outlet of testing core to weaken the gas slippage effect and tests the stress sensitivity of low permeability gas reservoirs, then analyzes the influence of permeability and water saturation on stress sensitivity. The results show that: low permeable and water-bearing gas reservoirs have strong stress sensitivity; the testing permeability has the power function relationship with net stress, compared to the exponential function, the fitting correlation coefficient is larger and more suited to the actual; the lower the permeability is and the higher water saturation is, the stronger the stress sensitivity is. The production of gas well is affected when considering the stress sensitivity, so the pressure dropping rate should be reasonable when low permeable gas reservoirs are developed. The results provide theoretical references for analyzing the well production and numerical simulation.

Economic Comparison of Alternatives for a Stranded Offshore Gas Reservoir

2021 ◽  
Vol 73 (08) ◽  
pp. 63-64
Author(s):  
Chris Carpenter
Keyword(s):  
Natural Gas ◽  
Economic Feasibility ◽  
Sensitivity Analyses ◽  
Pricing Models ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Pipe Length ◽  
Offshore Technology ◽  
University Of Oklahoma ◽  
Natural Gas Industry

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 30732, “Economic Feasibility Study of Several Usage Alternatives for a Stranded Offshore Gas Reservoir,” by Khoi Viet Trinh, SPE, and Rouzbeh G. Moghanloo, SPE, University of Oklahoma, prepared for the 2020 Offshore Technology Conference, originally scheduled to be held in Houston, 4–7 May. The paper has not been peer reviewed. Copyright 2020 Offshore Technology Conference. Reproduced by permission. This paper compares economics of a floating liquefied natural gas (FLNG) project with those of an onshore LNG plant and gas-to-wire (GTW) processes. Sensitivity analyses and tornado charts are used to evaluate the importance of various uncertain parameters associated with FLNG construction and operation. This study will be helpful for future considerations in using FLNG to convert offshore gas reservoirs previously considered stranded into economically viable resources. The results from this economic model can play a key role in the future of the natural gas industry and energy market in West Africa. Assumptions Before presenting different economic scenarios, the following assumptions must be established: * The pipeline will have the correct diameter, pressure rating, and metallurgy to transport produced gas. Only the pipe length will be considered a variable. * Operating expenses (OPEX) of both onshore LNG and FLNG will be the same. Realistically, however, OPEX of FLNG will be different from that of onshore LNG. * A subsidy from the Nigerian government has been obtained for the onshore LNG plant. * The electricity price is assumed to be $0.25/kWh. * An assumed upstream cost of $2/Mscf to cover onshore LNG gas pretreatment is assumed. * The onshore LNG plant and FLNG will have the same lifespan. However, in reality, availability of FLNG can be lower than that of onshore LNG. Pricing Models FNLG. Because of the relative recency of FNLG, few pricing models have been readily available. For the complete paper, Shell’s Prelude project is the basis for pricing of FLNG. Prelude costs averaged out to approximately $14 billion, which will be used as the cost of the facility for the FLNG scenario in the economic analysis.

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