Lean Gas Condensate Research Articles

Accurate, cost-effective strategy for lean gas condensate sampling, characterization, and phase equilibria study

Accurate recognition of the fluid phase behaviour is the most important and first step for the preservation and hydrocarbon reservoir management. Among the various hydrocarbon fluids, the lean gas condensate fluids show complex and unique behaviour. Due to the nature of these fluids, errors in the laboratory constant volume depletion (CVD) experimental data are inevitable. In this study, the significance of using CVD data in the EoS tuning process is debated using six samples of lean gas condensate. According to the negative composition in the CVD data material balance of all samples, just data of the constant composition expansion (CCE) experiment, saturation pressure, and liquid density in the stock tank are used for tuning the equation of state (EoS) as fundamental experimental data. The results of this study demonstrate that without using any CVD experimental data in the EoS tuning process, this data can be generated accurately using tuned EoS with fundamental data. Therefore, there is no need to do CVD experiments for lean gas condensate fluids characterization, which leads to reduces not only the error in the simulation process but also the laboratory costs. Furthermore, the tuning strategy in this study demonstrates that molecular weight of plus fraction and the volume shift parameter of the heaviest pseudo-component are the effective parameters to adjust the EoS. The objective function has reduced from 0.7360 to 0.1538 (79.10% improvement) just by using these two parameters. A constrained tuning strategy was proposed to keep the critical properties and acentric factor expected trends versus carbon number. The results show uniform and swing trends in the case of constrained and unconstrained tuning strategies, respectively. Therefore, using a constrained tuning strategy is essential to obtain a fluid with an authentic thermodynamic background after the tuning process. The proposed analysis method of CVD experimental data suggests that gas compressibility factor and gas composition as the main sources of error, while the experimental parameters of retrograde liquid and cumulative gas production have ignorable errors.

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

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. NOTE: This paper is published as part of the 2021 SPE Reservoir Simulation Conference Special Issue.

Numerical Well Test Analysis of Condensate Dropout Effects in Dual-Permeability Model of Naturally Fractured Gas Condensate Reservoirs: Case Studies in the South of Iran

Naturally fractured reservoirs (NFR) represent an important percentage of worldwide hydrocarbon reserves and production. The performance of naturally fractured gas condensate reservoirs would be more complicated regarding both rock and fluid effects. In contrast to the dual-porosity model, dual-porosity/dual-permeability (dual-permeability) model is considered as a modified model, in which flow to the wellbore occurs through both matrix and fracture systems. Fluid flow in gas condensate reservoirs usually demonstrates intricate flow behavior when the flowing bottom-hole pressure falls below the dew point. Accordingly, different regions with different characteristics are formed within the reservoir. These regions can be recognized by pressure transient analysis. Consequently, distinguishing between reservoir effects and fluid effects is challenging in these specific reservoirs and needs numerical simulation. The main objective of this paper is to examine the effect of condensate banking on the pressure behavior of lean and rich gas condensate NFRs through a simulation approach. Subsequently, evaluation of early-time characteristics of the pressure transient data is provided through a single well compositional simulation model. Then, drawdown, buildup, and multirate tests are conducted to establish the condition in which the flowing bottom-hole pressure drops below the dew point causing retrograde condensation. The simulation results are confirmed through well test analysis in both Iranian naturally fractured rich and lean gas condensate fields. Interpretations of simulation analysis revealed that the richer gas is more prone to condensation. When the pressure drops below the dew point, the pressure derivative curves in the rich gas system encounter a more shift to the right, and the trough becomes more pronounced as compared to the lean one.

Fluid and rock heterogeneity assessment of gas condensate reservoirs by wavelet transform of pressure-transient responses

The response of gas condensate reservoirs is directly influenced by heterogeneity. In such reservoirs, condensate is created around wellbore areas, when the reservoir pressure falls below the dew point pressure. Consequently, the distribution of this condensate bank makes fluid flow in the reservoir even more complicated by changing rock-fluid properties (e.g., relative permeability). This alteration can be assumed as a new heterogeneity, called fluid heterogeneity. The separation of fluid heterogeneity from rock heterogeneity is a challenging task. The main idea of this study is to investigate the transient pressure responses of a gas condensate reservoir to separate rock and fluid heterogeneities. Different homogeneous and heterogeneous reservoir models of a reservoir were constructed by the geostatistical approach. A commercial reservoir simulator was used to simulate the behavior of different drawdown and buildup scenarios. The fluid is a lean gas condensate selected from one of the Middle East formations. The wavelet transform (WT) approach was implemented to characterize the behavior of condensate banks for both homogeneous and heterogeneous models. Analyzing the wavelet approximate and detail coefficients of the pressure-transient responses enabled us to distinguish the rock and fluid heterogeneities. The results showed that the wavelet detail coefficient could be a good indicator of reservoir heterogeneity. Moreover, the WT could be successfully used to distinguish different regions of a condensate bank inside the reservoir under study. The implemented approach showed promising results in analyzing the pressure-transient responses of gas condensate reservoirs.

The Tolmount Field, Block 42/28d, UK North Sea

Abstract The Tolmount Field is a lean gas condensate accumulation located in Block 42/28d of the UK Southern North Sea. The field was discovered in 2011 by well 42/28d-12, which encountered good-quality gas-bearing reservoir sandstones of the Permian Leman Sandstone Formation. The discovery was appraised in 2013 by wells 42/28d-13 and 42/28d-13Z, which logged the gas–water contact on the eastern flank of the field. The Tolmount structure is a four-way, dip-closed, faulted anticline, orientated NW to SE. The reservoir comprises mixed aeolian dune and fluvial sheetflood facies deposited within an arid continental basin. Dune sands display the best reservoir properties with porosities around 22% and permeabilities exceeding 100 mD. Only minor diagenetic alteration has occurred, primarily in the form of grain-coating illite. Superior reservoir quality is observed at Tolmount compared to adjacent areas, due to the preservation of dune facies, a hypothesized early gas emplacement and a relatively benign burial history. Current mapped gas initially-in-place estimates for the field are between 450 bcf and 800 bcf, with an estimated recovery factor between 70 and 90%. An initial four-well development is planned, with first gas expected in 2020.

MONITORING GAS DISTRIBUTION AND ORIGIN IN THE CULZEAN FIELD, UK CENTRAL NORTH SEA, USING DATA FROM A CONTINUOUS ISOTOPE LOGGING TOOL AND ISOTUBE AND TEST SAMPLES

The high pressure – high temperature Culzean field, UK Central North Sea, contains lean gas condensate in the Triassic Joanne sandstones and the Middle Jurassic Pentland sandstones. A comprehensive gas analysis programme was installed as an integrated part of field development in order to monitor gas composition, distribution and origin in the reservoirs and overburden pre‐ production start‐up. Isotube OUT and isotube IN gas samples were collected. The isotube IN data show that some gas is recycled, including alkenes representing contamination from the degradation of mud additives; but concentrations are minor, and do not seem to affect the isotope values derived from the C2 and C3 isotube OUT gases significantly. 13C‐enriched methane derived from drill‐bit metamorphism is recorded in the isotube IN gas, but likewise in low concentrations. Gas data were also acquired from a Continuous Isotope Logging Tool (CILT) which measures real‐time gas concentrations and isotope values of C1–C3 each foot through the entire drilled section. The CILT thus provides a continuous trend of methane isotope values versus depth, and this trend is useful in identifying changes in gas composition. However, concerns related to CILT include: (i) C1–C3 stable carbon isotope detection limits for isotube OUT gas analyses are considerable lower than for CILT; due to the lower isotube gas concentrations required for measurement of C3 isotopes, isotubes are able to map a shallower vertical thermogenic gas migration front in the overburden. (ii) Discrepancies between isotube OUT and CILT isotope values may be significant and cannot be assigned to analytical uncertainty; by contrast, test gas and isotube OUT isotope values are comparable. Hence, CILT isotope values from specific depths cannot stand in isolation but must be complemented by isotube OUT isotope measurements.Gas in the Pentland reservoir is the most coaly in composition due to self‐sourcing from the Pentland coals. The coals are the primary source rock for the gas encountered in the entire reservoir interval at Culzean, but the underlying Joanne sandstones contain contributions from highly mature marine shales in the Kimmeridge Clay Formation and/or Heather Formation. The Lower Cretaceous seal on top of the Pentland reservoir is relatively tight but some minor migration/leakage of thermogenic gas into the overburden is recorded by the detection of C3 isotopes. Thermogenic gas also occurs in high porosity intervals in the Upper Cretaceous succession but this gas is interpreted to have migrated laterally in porous carrier beds and did not enter these intervals at the well locations.

Assessment of Empirical Pressure–Volume–Temperature Correlations in Gas Condensate Reservoir Fluids: Case Studies

Measurement and modeling of fluid properties and phase behavior of gas condensate reservoir fluids are challenging tasks. Many researchers proposed various empirical correlations based on either simple measurable field or laboratory data (e.g., gas-to-condensate ratio (GCR), compositions, and plus fraction characteristics) to estimate other PVT (pressure–volume–temperature) properties. In this study, several empirical correlations for estimating gas condensate fluid properties have been selected to be evaluated against available field data gathered from Iranian gas condensate fields. Experimental data from 30 lean gas condensate samples taken from nine gas condensate fields in the south of Iran were collected to examine the reliability of the empirical correlations. A wide range of field data were used for the evaluation: reservoir temperatures of 343.7–385.9 K, gas molecular weights of 17.40–21.13 g/mol, dew point pressures of 21.37–35.64 MPa, gas compressibility factors of 0.84–1.06 at dew point pressure, maximum retrograde condensates of (MRC) 0.09–2.91%, and GCRs of 5964–110,012.6 m3/m3. The estimated empirical correlations were compared to the measured field data, and the accuracy of the correlations was evaluated via error analysis. The parameters included in the assessment of empirical correlations were C7+ mole%, gas molecular weight, MRC, GCR, dew point pressure, and gas compressibility factor at dew point pressure. The results indicate that correlations of parameters with dew point pressure and with MRC have minimum and maximum errors, respectively. In cases where the GCR is high, correlations with C7+ mole% were not suitable for assessment. Also, estimation of gas compressibility factors at dew point pressure based on empirical correlations is not recommended.

An improved method for calculating critical temperatures and critical pressures in natural gas mixtures with up to nC11 hydrocarbons

This study suggests an improvement to the empirical model proposed by Peng (1986, Can. J. Chem. Eng. 64, 827–830) to calculate critical temperatures and critical pressures in natural gas mixtures. It aims to extend its application to natural gas mixtures containing hydrocarbons compounds up to undecane (nC11). This work focuses on establishing new matrices of coefficients Aij by obtaining new binary interactions between heavy compounds and the rest of compounds present in natural gas mixtures. The analysis considered more than 300 natural gas mixtures. Different comparisons were made between calculated critical properties, and referenced critical properties. Mean absolute errors <1.00% for the critical temperatures, and <2.70% for critical pressures were obtained. These low average deviations demonstrate the accuracy of this study, and could be considered as an easy-to-use engineering tool for estimating critical properties in natural gas mixtures, applicable to lean gas, rich gas, gas condensate, and Natural Gas Liquids (NGL).

Canning Basin - Petroleum Systems Analysis

New high resolution geochemical information was acquired for fluids from recent Canning Basin wells and interpreted in context with previous work on fluid typing and correlation by Geoscience Australia (GA). Ungani field oils are interpreted to be derived from the same/very similar clastic source rock, comprising bacterial and marine algal matter deposited under anoxic to sub-oxic conditions, and generated within the peak oil window for a high quality marine source rock. Observed low GOR’s are the consequence of both source rock type and gas removal. Liquids from the Yulleroo field are derived from a similar source to the Ungani oils, with the addition of dry gas from a higher maturity and/or more gas prone source, and generated and expelled at slightly higher maturity. The current lean gas condensate phase is the result of the addition of dry gas combined with minimal water washing. In nearly all aspects the Ungani and Yulleroo liquids resemble the L4 family previously attributed by GA to a probable Carboniferous age source. Gas-condensate from the Valhalla North-1 field was derived from a more mature source rock deposited in an oxic environment and containing more gas prone (terrigenous) organic matter. Map based modelling incorporated eleven 1D models in the Ungani-Yulleroo and Valhalla-Asgard region, and a map based burial history and maturity model. The source rock model was derived from the liquid geochemistry results rather than the poor quality source rock potential data gathered to date. Burial history modelling and maturity modelling at the top of the Lower Laurel Carbonate shows maturity for gas expulsion in the main trough and oil to light oil expulsion on the flanks of the basin. Maximum burial in the basin took place immediately prior to the Fitzroy Uplift, resulting in the main phase of oil generation and expulsion taking place around 200Ma.

Investigating the Behavior of Low Permeable Lean and Rich Gas Condensate Reservoirs

The producing behavior of low permeable gas condensate reservoirs is dramatically different from that of conventional reservoirs and requires a new paradigm to understand and interpret it. As the reservoir pressure initiates to decline and reaches to dew point pressure of the fluid then the condensate is formed and causes the restriction in the flow in the reservoir rock which results, decrease in the well productivity near the wellbore vicinity which is known as condensate blockage. Henceforward, it is better to understand the behavior of the low permeable lean and rich gas condensate reservoirs by several perspectives through the compositional simulator. Besides this study involves the following perspectives; the increase in the number of wells and by varying the flowrate of the gas in six different cases for low permeable lean and rich gas condensate reservoirs. It was concluded that low permeable lean and rich gas condensate reservoirs have similar gas recovery factors. Whereas the CRF plays inverse behavior for both reservoirs as CRF is maximum for lean gas condensate at single producing well but for rich gas condensate reservoir the CRF increases as the number of wells escalates. Additionally, in second effect the varying gas flowrates lean gas condensate reservoir has maximum CRF at lesser flowrate but it is opposite for the low permeable rich gas condensate reservoir, for single or two producing wells the flowrate effect plays but when the number of wells is increasing there is not any significant change in CRF

The use of numerical simulation to investigate the enhanced Eagle Ford shale gas condensate well recovery using cyclic CO2 injection method with nano-pore effect

The huge reserves of Eagle Ford shale gas condensate reservoirs have drawn great attention. The well productivity analysis indicates that the leading Eagle Ford is in reservoir decline stage. Condensate banking effect induces severer adverse effect on ultra-low permeability reservoirs and shale gas production than conventional reservoirs. The objective of this paper is to investigate the effect of CO2 huff-n-puff injection on mitigating condensate accumulation surrounding the induced fractures. The nano-pore confinement effect on condensate and gas production performance is considered. The nano-meter scale of shale condensate plays exhibit different phase behavior than conventional condensate reservoirs. The influence of nano-pore confinement on liquid phase behavior in shales is similar to adding CO2 in admixture with reservoir fluids, which acts to suppress the phase envelope. The interaction of CO2 injection with reservoir oil at molecular scale was discussed. Two scenarios including a lean gas condensate and rich gas condensate were compared in order to study the CO2 huff-n-puff performance with different reservoir fluids. The simulation results indicated that CO2 is more favorable in improving the rich condensate recovery. Removal of condensate accumulation in rich condensate Eagle Ford shale reservoirs by CO2 huff-n-puff injection results in substantial recovery increment in comparison with the pressure depletion scheme. This paper focuses on studying the influences of nano-pore walls on CO2 injection phase behavior in shale gas-condensate reservoirs.

Fines surface detachment and pore-throat entrapment due to colloidal flow of lean and rich gas condensates

This paper describes about the lean and rich gas condensate effects on fines migration in porous rocks. Fines detachment from rock surface and pore throat entrapment are frequent causes of formation damage and well productivity loss. In condensate reservoirs, there is a large volume of liquid formation during reservoir pressure depletion. This will result in liquid loading and production decline. In this work, we critically discuss the fines migration and the permeability decrease mechanism in the gas condensate reservoir. For this purpose, we numerically simulated a condensate reservoir, which is capable of undergoing a phase transition from gas to liquid as a function of pressure depletion, temperature, and time. We have implemented CFD modeling to simulate this retrograde condensation process. The major results revealed that there is a high amount of heat release during phase transition. This heat release and condensed liquid flow detached the fines from the rock surface and finally, get trapped in the pore-throat. Our models have been validated against the experiments and showed good agreement. Overall, this work may serve as a base to re-examine the gas condensate reservoir behavior with fines transport in porous rocks.

Production data analysis of gas condensate reservoirs using two-phase viscosity and two-phase compressibility

Due to the occurrence of multi-phase flow in gas condensate reservoirs, production data of such reservoirs cannot be accurately analyzed using single-phase, dry gas models. In this work, we established a new semi-analytical method for rate-transient analysis of gas condensate reservoirs producing during boundary-dominated flow. In particular, the single-phase flow assumption in the development of the material-balance pseudotime function for dry gas reservoirs is alleviated by incorporating two-phase viscosity and two-phase compressibility into a modified two-phase pseudotime function. Introducing the definition of two-phase pseudotime achieves the goal of (approximately) linearizing the governing diffusivity equation. Using the principle of superposition applied to the constant rate solution, this methodology is extended for wells with dynamic changes in well operating conditions (i.e. rates and pressures).Original gas-in-place (OGIP) can also be quantified through a specialized plotting technique. To validate the developed method, synthetic production data using fine grid compositional simulations for both lean and rich gas condensate fluids are analyzed. In all cases, the proposed approach provides reasonable estimates of simulator input reservoir properties (e.g. OGIP). The presented technique is successfully applied to the analysis of field cases. This work provides a practical and simple engineering workflow for production data analysis of conventional gas condensate reservoirs with multi-phase flow during boundary-dominated flow.

Application of Artificial Neural Network–Particle Swarm Optimization Algorithm for Prediction of Gas Condensate Dew Point Pressure and Comparison With Gaussian Processes Regression–Particle Swarm Optimization Algorithm

For gas condensate reservoirs, as the reservoir pressure drops below the dew point pressure (DPP), a large amount of valuable condensate drops out and remains in the reservoir. Thus, prediction of accurate values for DPP is important and leads to successful development of gas condensate reservoirs. There are some experimental methods such as constant composition expansion (CCE) and constant volume depletion (CVD) for DPP measurement but difficulties in experimental measurement especially for lean retrograde gas condensate causes to develop of different empirical correlations and equations of state for DPP calculation. Equations of state and empirical correlations are developed for special and limited data sets and for unseen data sets they are not generalizable. To mitigate this problem, in this paper we developed new artificial neural network optimized by particle swarm optimization (ANN-PSO) for DPP prediction. Reservoir fluid composition, temperature and characteristics of the C7+ considered as input parameters to neural network and DPP as target parameter. Comparing results of the developed model in this research with Gaussian processes regression by particle swarm optimization (GPR-PSO), previous models and correlations shows that the predictive model is accurate and is generalizable to new unseen data sets.

Investigation into the effect of capillary number on productivity of a lean gas condensate reservoir

The main objective of this study is to provide a comprehensive investigation into the effect of Capillary number (NCa) on production from the lean gas condensate reservoirs and to show the importance of NCa in these types of reservoirs. In the current study a gas condensate reservoir has been simulated and validated using field and PVT data. The effect of NCa on the parameters such as producing gas flow rate, bottom-hole pressure, average reservoir pressure, the amount of condensate in the reservoir and the condensate saturation versus the distance from the production well has been investigated. It was found that NCa can increase the relative permeability of the gas followed by the reduction in condensate formation and pressure drop in the vicinity of wellbore. Furthermore, the results stated that NCa exists in about 10 ft away from the well and affects mainly the well productivity parameters such as bottom-hole pressure and gas flow rate. However, it does not affect the average reservoir pressure and condensate throughout the reservoir as much as the near wellbore parameters.

Methane Flooding in Lean Gas Condensate Reservoir

This article presents laboratory experiments to study the effectiveness of methane injection into core plugs of a real lean gas condensate reservoir in Iran, namely Jahroom, to revaporize the immobile condensate deposited as a result of the natural depletion process. The studies include two parts: (1) natural depletion process from initial reservoir pressure (5,240 psia) to the current reservoir pressure (2,780 psia); and (2) pressure maintenance at the current reservoir pressure by methane flooding. Results show that for the natural depletion process, the ultimate condensate recovery was 34%. However, ultimate recovery would be 82% after 2.5 pore volume methane injection.

Analysis and Comparison of Decline Models: A Field Case Study of a Naturally Fractured Gas Condensate Reservoir

Decline curve analysis is one of the most commonly used techniques to predict future production performance and estimate reserves from routinely available production data. This article presents obtained results from production data analysis of a naturally fractured lean gas condensate reservoir with homogenous reservoirs decline curve analysis methods. Different methods were used to estimate reservoir original gas in place and expected ultimate recovery. Results have shown that traditional Arp’s equations and Fetkovich type curve cannot estimate original gas in place and expected ultimate recovery reliably; but the values of the Blasingame type curve and Agarwal-Gardner type curve can estimate them with about 8% error.

Constructing a unique two-phase compressibility factor model for lean gas condensates

Generating a reliable experimental model for two-phase compressibility factor in lean gas condensate reservoirs has always been demanding, but it was neglected due to lack of required experimental data. This study presents the main results of constructing the first two-phase compressibility factor model that is completely valid for Iranian lean gas condensate reservoirs. Based on a wide range of experimental data bank for Iranian lean gas condensate reservoirs, a unique two-phase compressibility factor model was generated using design of experiments (DOE) method and neural network technique (ANN). Using DOE, a swift cubic response surface model was generated for two-phase compressibility factor as a function of some selected fluid parameters for lean gas condensate fluids. The proposed DOE and ANN models were finally validated using four new independent data series. The results showed that there is a good agreement between experimental data and the proposed models. In the end, a detailed comparison was made between the results of proposed models.

Experimental and Simulation Constructing of Phase Diagram and Quality Lines for a Lean Gas Condensate Reservoir Fluid

Constructing phase diagram and its subsequent quality lines for lean gas condensate reservoirs is always crucial and challenging topic in reservoir fluid studies. Due to small amounts of liquid drop-outs in lean gas condensates at reservoir conditions, full experimental tracking of phase diagram and its relevant quality lines is almost impossible for lean gas condensates. On the other hand, EOS models of reservoir fluid characterization softwares are always unable to estimate condensed liquid drop-outs at different pressures and temperatures precisely. This study aims to present a commingled experimental-simulation method which was designed to pinpoint and keep track full phase diagram with correspondent quality lines for a lean gas condensate fluid.

Determination of Dew Point Pressure With and Without a Visual Cell

The dew point pressure of a gas condensate fluid is used for planning the production profile of gas condensate reservoirs and for determining their economic success. Usually the best method of the determination of the dew point pressure loci 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 a liquid droplet is observed and is recorded as the dew point pressure. The gas volume of the saturated fluid at dew point pressure is used as a reference volume and the total hydrocarbon volume measured for each pressure depletion step is reported relative to this volume. For lean gas condensate systems the amount of heavy components that can condense during pressure reduction is less than 4 mol% (<50 bbls/MMscf). Such experimental determination of dew point pressure for these gases require many small pressure reduction steps which make the observation method tedious, time consuming, and expensive. In this study the authors demonstrate that a graphical method of determining dew point pressure, which does not require a windowed cell for visual observation is possible. The authors have extended the Y-function, which is often used to smooth out CME data for black oils to gas condensate systems. They started from the initial measured pressure and volume and by plotting log of the extended Y-function, which they call the YRRR-function, with the corresponding pressure so that two straight lines were obtained: one above and one below the dew point. The point at which these two lines intersect is the dew point pressure. The YRRR-function method was applied to determine the dew point pressure for both a lean and a rich gas condensate system. The difference between the dew point pressures determined by the authors’ proposed YRRR-function method and the observation method was less than ±2.0% for both gas systems. This extension of the Y-function to determine dew point pressure was not found elsewhere in the open literature.