Constant Volume Depletion Research Articles

Dynamical and rheological analysis of gas condensate reservoir characteristics and multiphase flow behavior of a well

This manuscript proposes dynamical and rheological analysis of gas condensate reservoir characteristics and multiphase flow behavior of a well located at the lower Indus basin gas condensate reservoir in Sindh, Pakistan. The main objective is to analyze the compositional variation impacts on the liquid dropout, flow behavior and well productivity. For the sake of data analysis, constant composition expansion and constant volume depletion capabilities have been tested via pressure, volume and temperature cell under measurement of dew point and liquid dropout flow. By invoking CMG: Win prop simulator on the basis of equation of state namely Peng Robenson and Soave Redlish Kwong equations, phase diagram and well stream physical parameters have been analyzed. Our result suggested crucial significance for the behavior of flow and well productivity that liquid generation changes with the physical properties of flowing stream namely vapor viscosity, compressibility factor and vapor density due to pressure depletion showing decreasing trend. Mole percent of lighter components C1 mole percent increases from 54.567 to 62.153. While mole percent of heavier components C18+ decreases from 3.453 to 1.513 with 45% liquid dropout. In brevity, maximum well productivity has been observed in composition-1 which is 5.005 MMscf/day at pressure of 3131 psig.

A MODEL FOR FORECASTING DEW POINT PRESSURE IN NIGER DELTA CONDENSATE RESERVOIRS USING CONSTANT VOLUME DEPLETION TESTS DATA

The dew point pressure plays a critical role in developing gas condensate reservoirs. It is a crucial factor used in fluid characterisation, performance estimation of gas reservoirs, and design of production systems. However, the composition of gas condensate fluid varies from one location to another, and thus, empirical correlations have been developed to determine the dew point pressure without conducting routine tests. As a result, correlations that are solely useful in the region where they were developed and analysed are developed. This work developed an empirical correlation using data from gas condensate wells in the Niger Delta using multiple linear regression. The model was developed using the Analytical Tools and techniques in Microsoft Excel. To develop the model, we utilised 63 data sets from the Constant Volume Depletion (CVD) experiment, which involved gas condensates from resources in the Niger Delta. The model comprises an empirical correlation that estimates the dew point pressure for gas condensate reservoirs. It uses compositional information of the fluid and reservoir temperature as input parameters. The correlation is derived through multiple regression analyses. Comparing the prediction accuracy of formulas based on the developed model and other conventional methods indicated that this model is more accurate than other statistical methods in predicting DPP within the Niger Delta region. This model can produce more accurate results than other estimation methods when working under limited field information and time constraints. The correlation developed in this process has a coefficient of determination of R2=0.869 and an Average Absolute Relative Error (AARE) of -2.0767%, along with a root mean square of 195279, indicating a high level of reliability in the proposed correlation.

Improved saturation-pressure relationship and multiphase pseudo-pressure calculations for retrograde gas reservoir production under boundary-dominated flow

For reservoirs containing fluids with complex flow characteristics, the calculation of multiphase pseudo-pressure plays a significant role in production data analysis (PDA) practices. In the case of retrograde gas reservoirs/gas condensate reservoirs under multiphase flow conditions, the lack of a reliable and complete saturation-pressure (So-p) relationship presents a significant challenge in obtaining the appropriate value of multiphase pseudo-pressure. Gas condensate reservoirs are one of the viable and lower-emission hydrocarbon sources for meeting the ever-increasing global energy demand. The economic value of producing gas condensates has inspired numerous research into employing innovative production techniques in developing gas condensate fields. Hence, this study proposes an improved saturation-pressure relationship alongside a Fractional Phase Mobility (FPM) criterion to mitigate potential errors in the multiphase pseudo-pressure calculation for gas condensate reservoirs under boundary-dominated flow. This work introduces an improved So-p relationship derived using a Rescaled Constant Volume Depletion (CVD) method for estimating multiphase pseudo-pressures. To demonstrate the effectiveness of the proposed approach, we provide direct comparisons with the Classical CVD method and numerical simulation results for multiple gas condensate cases subjected to constant and variable bottomhole pressure (BHP) schedules. In contrast to the classical approach, the Rescaled CVD method consistently delivers superior performance for multiphase pseudo-pressure estimations across all cases, thus supporting its potential as a robust and accurate approach for gas condensate reservoir modeling.

Investigation on the Extent of Retrograde Condensation of Qianshao Gas Condensate Reservoir Using PVT Experiments and Compositional Reservoir Simulation

In the development of the Qianshao (QS) gas condensate reservoir, it is crucial to consider the phenomenon of retrograde condensation. Understanding the condensate saturation distribution with respect to time and space within the reservoir is essential for planning and implementing effective strategies for the future development of the QS gas condensate reservoir. In this paper, various PVT experiments (including reservoir oil recombination, flash separation, constant composition expansion, and constant volume depletion) were conducted to study the PVT properties and phase behavior of QS gas condensate fluid. Based on experimental data, our in-house PVT computation package was used to determine the appropriate EOS model parameters for the QS gas condensate. A four-step reservoir fluid characterization procedure and workflow for gas condensate reservoirs was developed. Furthermore, by analyzing the pressure-temperature phase envelope, the maximum possible condensate saturation in the QS well area was estimated to be around 3%. Numerical reservoir simulation models were developed using both the EOS model and actual reservoir engineering data. These simulation models were specifically designed to replicate the retrograde condensation process that occurs during production, taking into account both vertical and horizontal wells. By simulating the production process, these single-well reservoir simulation models enable us to quantitatively evaluate the condensate saturation and its distribution over space and time within a specific control area around a single well. Reservoir simulation results show that the condensate build-up around vertical and horizontal wells is quite different. For a vertical well, the maximum condensate oil saturation (30%) around the wellbore is located approximately 5 to 6 m from the well’s center. In contrast, the horizontal well model demonstrates a maximum condensate saturation of no more than 1.5%. This information is crucial for making informed decisions regarding the effective development and management of the QS gas condensate reservoir.

Analytical Method for Production Forecasting During Boundary-Dominated Flow in Unconventional Volatile Oil Reservoirs Using Single-Phase Analogy

Abstract This paper presents an analytical methodology for production forecasting of wells exhibiting boundary-dominated flow in unconventional volatile oil reservoirs. An analytical model using single-phase analogy is established to predict the production rate of a multi-fractured horizontal well under multiphase flow. Pseudo-variables are employed to linearize governing differential flow equations. Therefore, the analytical model for efficiently handling multiphase flow is essentially an advanced adaptation of existing single-phase models, in which we derive new multiphase fluid properties. To calculate the pseudo-variables accurately, we summarize accessible methods for the determination of saturation–pressure (S–P) relation and further provide an appropriate way to calculate multiphase pseudo-variables in unconventional volatile oil reservoirs based on simulation results. The simulation study indicates that the S–P relation given by constant volume depletion data for near-critical volatile oils leads to satisfactory results, and the S–P relation derived from the tank-type model is appropriate for ordinary volatile oils. The analytical solution and associated methods were validated through comparison with results from a compositional simulator; the excellent agreement during boundary-dominated flow demonstrated the accuracy of the analytical methodology. The analytical methodology can greatly reduce computation and is justified to make production forecasting in unconventional volatile oil reservoirs, this tractable methodology should be attractive to the industry.

Experimental Study on the Control Mechanism of Non-Equilibrium Retrograde Condensation in Buried Hill Fractured Condensate Gas Reservoirs

During the depletion development of condensate gas reservoirs, when the formation pressure drops below the dew point pressure, the condensate oil and natural gas systems are in the non-equilibrium state of foggy retrograde condensation. The rational use of the non-equilibrium phase characteristics of the foggy retrograde condensation phenomenon during the development process will be beneficial to the recovery of condensate oil and natural gas. In order to clarify the retrograde condensation control mechanism during the non-equilibrium depletion development of condensate gas reservoirs, the phase characteristics of a condensate oil and gas system were studied by constant composition expansion and constant volume depletion experiments. Then, on the basis of a long core depletion experiment and chromatographic analysis experiment, the influence of different pressure drop speeds, fluid properties, and reservoir physical properties on the control effect of non-equilibrium retrograde condensation after the coupling of the fluid retrograde condensation and reservoir core is analyzed. The results show that during the pressure decline process, the condensate oil and gas system will produce a strong foggy retrograde condensation phenomenon, with the saturation of the retrograde condensate increasing and then decreasing. The cumulative recovery of the condensate oil and natural gas, as well as the mass fraction of the heavy components in the condensate oil, increase with the increase in the depletion rate. Different fluid properties and reservoir physical properties have a great influence on the cumulative recovery degree of the condensate oil, and have little influence on the recovery degree of the natural gas. This work has a certain guiding role for the stable production and enhanced recovery of fractured condensate gas reservoirs in subsurface structures of metamorphic rocks.

Consistency Checks for Pressure-Volume-Temperature Experiment of Formation Oil and Gas at High Temperature

The oil and gas phase behavior of high temperature is complex and changeable, which is usually obtained by PVT experiments. The accuracy of the experiment data plays a crucial role in the reserve evaluation and development plan of oil and gas reservoirs. However, the current PVT experiment consistency checks are not suitable for high-temperature reservoir conditions. This paper proposes a systematic check method for the PVT experiment data consistency at high temperature. These checks revise the material balance method, Hoffman method, and equilibrium constant method by using the equilibrium constant calculation method at high temperature. The consistency check of component data and constant volume depletion experiment data is carried out by combining the three improved methods with the component check method, so as to judge the experiment data accurately. In this paper, two high-temperature reservoir fluids—gas condensate sample fluid X and volatile oil sample fluid Y—are selected to carry out consistency checks with component data and constant volume depletion data. This check method is of great significance to study the phase behavior of formation oil and gas at high temperature, especially for volatile oil and gas condensate fluid.

Machine learning model for constant volume depletion prediction of the Niger Delta condensate systems

Accurate assessment and evaluation of condensate reservoir performance is dependent on the depth of study of the condensate systems. Due to the anomalous behavior of these reservoirs, a great deal of knowledge is required to accurately forecast performances associated with these systems. Three machine learning (ML) models with proven capabilities and accuracy were developed based on Extratrees (ET), Adaptive Boosting (Adaboost) and Gradient Boosting algorithm (GBM). These models were used to exploits various parameters such as, gas composition, C7+ fraction properties, depletion pressure steps, and reservoir temperature. The data points stretching through different samples from the Niger Delta that passed the quality control tests were used in the validation of the proposed model for this study. Using various metrics to evaluate the accuracy of the models, analyzing the result of two samples A and B show that algorithm with R2 of 0.9868 and 0.9951, MAPE of 0.21224 and 0.10984, RMSE of 0.01746 and 0.01697, MAE of 0.0128 and 0.01457 for sample A and B respectively. Algorithm presents a more accurate prediction when compared with Adaboost and GBM models for two samples. The results from this study can be uniquely serialized and deployed into PVT simulation packages

Insights on equation of state modeling PVT experiments for deep volatile oil reservoir

Accurate prediction of the PVT properties and phase behavior plays an important role in developing volatile oil reservoirs. The objective of this study is to characterize volatile oil sample using our improved Perturbation from n-Alkane (PnA) method and validate the results by use of high-quality PVT experimental data from GT1 well through detailed PVT simulation. We implemented PnA method for reservoir fluid characterization and simulated all PVT experiments through an in-house programming package. We compared the modeling results to the experimental data and found that the equation of state (EOS) parameters characterized by the PnA method is able to describe the PVT properties and phase behavior of volatile oil very well. According to the PVT modeling results, we suggested that (1) constant volume depletion test for GT1 volatile oil can be replaced by differential liberation experiment, combined with the data obtained from reliable EOS calculations; (2) the amount of surface-produced condensate for a volatile oil reservoir is up to 4.5% OOIP depending on reservoir abandonment pressure. Therefore, for GT1 volatile oil, condensate production should be carefully evaluated throughout the entire development life-cycle in order to make an optimum design of surface processing facilities for condensate recovery.

Performance Evaluation of Experimental and Simulated Constant Volume Depletion Tests on Gas Condensate Reservoir Fluid

Performance Evaluation of Experimental and Simulated Constant Volume Depletion Tests on Gas Condensate Reservoir Fluid

Predicting the performance of constant volume depletion tests for gas condensate reservoirs using artificial intelligence techniques

Predicting the performance of constant volume depletion tests for gas condensate reservoirs using artificial intelligence techniques

GAS-CONDENSATE FLUID PVT MODEL QUALITY CHECK BASED ON THE CONCEPT OF A SINGLE-CELL SIMULATION MODEL

The problems of gas-condensate PVT-models (Pressure Volume Temperature, PVT) creation under limited input information were analyzed. Traditional fluid phase behavior characterization approach relies on creation of the equation of state (EOS) based on initial composition of reservoir fluid and its future regression for critical parameters (pressure and temperature), binary interaction coefficients, acentric factors of residual “plus” fraction or pseudo-components. The adjustment is done until the moment when EOS is reproducing the results of laboratory experiments. Classic PVT experiments performed on gas-condensates and volatile oils are constant composition expansion (CCE), constant volume depletion (CVD) and separator tests. However, in the case of most Ukrainian fields, discovered and explored in the last century, not only the reliable detailed initial fluid composition is not available, but phase behavior was studied with non-equilibrium method of so-called differential condensation, that does not allow their direct application for PVT models creation. Previously, the authors [1, 2] presented an alternative method for fluid characterization based on the fractional distillation test. At the same time, due to significant uncertainty in input data, particularly a) condensate production allocation; b) commingled production from multiple reservoirs with different C5+ yield; c) non-recorded change of separator conditions that affects liquid extraction and its density; d) technological production losses, issues of reproducing the condensate production during history matching of several models of Dniper-Donetsk Basin were faced. There was proposed and explained in detail an example of single-cell reservoir simulation model application concept for quality check of created PVT model for one of the fields with potential yield of 86 g/m3. The idea of the concept is based on the reproduction of material balance of gas-condensate reservoir through one conditional well controlled on a primary (gas) phase, that allows quick identification of changes into calculated gas-condensate yield curve, necessary for matching of condensate production. Implementation of these changes allows quick and precise full-field model calibration.

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.

Experimental Investigation of Phase Behavior of Condensate Gas and Crude Oil System in Underground Gas Storage

Abstract The phase behavior of reservoir fluids is crucial for the smooth operation of an underground gas storage (UGS). In this work, three experiments were conducted to investigate the phase behavior of condensate and crude oil systems within different development stages of gas storage in Bohai Bay Basin of eastern China. In stage 1, constant volume depletion (CVD) test was conducted to simulate the interaction of the original condensate gas-live oil system. In stage 2, the phase behavior of a series of mixtures of live oil with 47.5, 58.3, 69.9, and 77.4 mol% of condensate gas was studied by constant composition expansion (CCE) test. In stage 3, a new experiment was designed to study the mass transfer and phase behavior during cyclic injection-production process of the underground gas storage. The results from the CVD test describe the effect of each pressure stage on produced gas composition and equilibrium oil properties in the condensate crude oil system. The results of the CCE test indicate that condensate gas can expand the oil and improve the properties. The results of cyclic injection-production experiment demonstrate that the mass transfer in condensate gas and oil system is a dual mechanism of condensation and vaporization. With the increase of the cycle, the intermediate components of oil phase are enriched and the heavy components decreases. After four cycles, the oil and gas interphase mass transfer reaches dynamic equilibrium. In addition, test results show that multicycle operation is beneficial to improve the oil properties. This work is of great significance to understand the phase transition mechanism of underground gas storage, which provides a basis for other researchers to further update and improve the EOS model.

An improved oil recovery prediction method for volatile oil reservoirs

To describe the complex phase transformation in the process of depletion exploitation of volatile oil reservoir, four fluid phases are defined, and production and remaining volume of these phases are calculated based on the principle of surface volume balance, then the recovery prediction method of volatile oil reservoir considering the influence of condensate content in released solution gas and the correction method of multiple degassing experiments data are established. Taking three typical kinds of crude oil (black oil, medium–weak volatile oil, strong volatile oil) as examples, the new improved method is used to simulate constant volume depletion experiments based on the corrected data of multiple degassing experiment to verify the reliability of the modified method. By using “experimental data and traditional method”, “corrected data and traditional method” and “corrected data and modified method”, recovery factors of these three typical kinds of oil are calculated respectively. The source of parameters and the calculation methods have little effect on the recovery of typical black oil. However, with the increase of crude oil volatility, the oil recovery will be seriously underestimated by using experimental data or traditional method. The combination of “corrected data and modified method” considers the influence of condensate in gas phase in both experimental parameters and calculation method, and has good applicability to typical black oil and volatile oil. The strong shrinkage of volatile oil makes more “liquid oil” convert to “gaseous oil”, so volatile oil reservoir can reach very high oil recovery by depletion drive.

Two deterministic methodologies for estimation of OGIP by production dynamics diagnostic of gas-condensate reservoir

This study presents two independent methodologies for estimation of original gas in place (OGIP) by production dynamics diagnostic of gas-condensate reservoir with no-flow outer boundary based on black-oil concept. Classic Blasingame decline-type curves are also extended to apply in gas-condensate reservoir to calculate kh . Both numerically simulated case and field data are used to demonstrate the applicability and validity of proposed methodologies. One method develops a novel analytical model to obtain average reservoir pressure, OGIP and Diatz shape factor at the same time by coupling flow equation of gas-condensate reservoir for boundary dominated flow (BDF) and general material balance equation (GMBE). The two-phase variable-rate flow equation at late time for BDF is clearly and concisely derived in this study in terms of defined two-phase pseodopressure and two-phase material balance pseudotime. In addition, another innovative, simple and effective method for estimation of OGIP is proposed in this study requiring input data of only cumulative production of well and reservoir fluid PVT characteristics of Constant Volume Depletion (CVD) experiment. The fundamental concept of this method suggests that transient cumulative production GOR is determined by only current gas recovery degree and fluid PVT characteristics of the reservoir. Due to the accurate, simple and relaxed data-requiring nature of this method, widespread use in field to estimate OGIP of gas-condensate reservoir is potentially encouraging. On the contrary, if OGIP is already known, an intermediate equation of the method can also be applied to check accuracy of CVD experiment results from laboratory. The first methodology extends OGIP estimation to gas-condensate reservoir from Blasingame and Lee (1988)’s method for dry-gas reservoir. Often used two-phase z factor, which is inconvenient to evaluate and easy to yield error, for gas-condensate reservoir in material balance equation is avoided in this methodology by applying more analytical and accurate Walsh et al. (1994)’s GMBE instead. The second methodology, to the authors’ knowledge, is the first proposed allowing OGIP estimation of gas condensate reservoir without requiring bottom hole flowing pressure (BHFP), pressure tests and complex calculation.

Hydrocarbon mixture and CO2 adsorptions in A nanopore-bulk multiscale system in relation to CO2 enhanced shale gas recovery

Thanks to the continuous depletion of conventional gas reservoirs, shale gas plays an important role to meet the global natural gas demand. The CO2 'huff-n-puff' process has been proven to be an effective method to enhance shale gas recovery and sequestrate CO2. Unlike conventional reservoirs, shale media can contain a significant number of nano-scaled pores and their pore volume can be comparable to that of macropores and fractures in which fluids behave as bulk. While previous works studied the mechanisms of CO2 ‘huff-n-puff’ process in shale gas exploitation, the volume partitioning between nanopores and macropores/fractures is not fully taken into account. In this work, we built a nanopore-bulk multiscale model with varying pore size distributions (PSDs) to study the CO2 'huff-n-puff' process in a constant volume depletion (CVD) setting by using density functional theory (DFT). We found that the volume partitioning effect on adsorption, fluid compositions, hydrocarbon mixture (C1, C2, and C3) recovery is significant in the CO2 'huff-n-puff' process. The majority of hydrocarbon mixtures can be released from micropores and smaller mesopores during the CO2 ‘huff’ and ‘soak’ process, while the average hydrocarbon densities in larger mesopores might increase. During the CO2 ‘huff’ and ‘soak’ process, due to a stronger confinement effect in smaller pores, the PSD case with a higher volume ratio of smaller pores releases fewer hydrocarbons, while stores more CO2 per unit pore volume. Overall, the volume partitioning has a significant effect on hydrocarbon adsorption, compositions, and recovery as well as CO2 storage during the CO2 ‘huff-n-puff’ process in shale gas exploitation and geological CO2 sequestration.

Hydrocarbon mixture phase behavior in multi-scale systems in relation to shale oil recovery: The effect of pore size distributions

Shale media contains a large amount of nano-scale pores, with their total pore volume comparable to that of the connected macropores and natural/hydraulic fractures (bulk). Previous work largely neglected the interplay between nanopores and bulk region as well as the effect of pore size distribution (PSD), where fluids can freely exchange between nanopores and bulk region. To accurately predict production and ultimate oil recovery, PSD effect should be taken into consideration. In this work, engineering density functional theory (DFT) is used to study phase behaviors of hydrocarbon mixtures in multi-scale nanoporous media with PSD effect during constant composition expansion (CCE) and constant volume depletion (CVD) processes. We found that under the PSD effect, due to the chemical equilibrium between various nanopores and connected bulk as well as competitive adsorption in nanopores, the interplay between nanopores and bulk region influences phase behaviors and properties of fluids in the multi-scale system. Phase transitions first occur in the bulk region, then the larger pores followed by the smaller pores. The bulk bubble point pressure increases as the volume ratio of the smaller pores in the system increases, while the bulk dew point decreases. When fluids in one specific pore begin to vaporize, in other pores, the heavier component would be adsorbed, while the lighter component would be released, which suppresses the phase transitions in the smaller pores because of the heavier component accumulation. The higher volume ratio of the smaller pores suppresses the heavier component production, when pressure is below the bulk dew point.

GAS-CONDENSATE FLUID PVT MODEL QUALITY CHECK BASED ON THE CONCEPT OF A SINGLE-CELL SIMULATION MODEL

The problems of gas-condensate PVT-models (Pressure Volume Temperature, PVT) creation under limited input information were analyzed. Traditional fluid phase behavior characterization approach relies on creation of the equation of state (EOS) based on initial composition of reservoir fluid and its future regression for critical parameters (pressure and temperature), binary interaction coefficients, acentric factors of residual “plus” fraction or pseudo-components. The adjustment is done until the moment when EOS is reproducing the results of laboratory experiments. Classic PVT experiments performed on gas-condensates and volatile oils are constant composition expansion (CCE), constant volume depletion (CVD) and separator tests. However, in the case of most Ukrainian fields, discovered and explored in the last century, not only the reliable detailed initial fluid composition is not available, but phase behavior was studied with non-equilibrium method of so-called differential condensation, that does not allow their direct application for PVT models creation. Previously, the authors [1, 2] presented an alternative method for fluid characterization based on the fractional distillation test. At the same time, due to significant uncertainty in input data, particularly a) condensate production allocation; b) commingled production from multiple reservoirs with different C5+ yield; c) non-recorded change of separator conditions that affects liquid extraction and its density; d) technological production losses, issues of reproducing the condensate production during history matching of several models of Dniper-Donetsk Basin were faced. There was proposed and explained in detail an example of single-cell reservoir simulation model application concept for quality check of created PVT model for one of the fields with potential yield of 86 g/m3. The idea of the concept is based on the reproduction of material balance of gas-condensate reservoir through one conditional well controlled on a primary (gas) phase, that allows quick identification of changes into calculated gas-condensate yield curve, necessary for matching of condensate production. Implementation of these changes allows quick and precise full-field model calibration.

Study on the phase behaviour of condensate gas in nanostructure media

Condensate dropout near the wellbore region in gas condensate reservoirs is the main reason for low well deliverability. Here, the gas and condensate phase behaviour in this region was investigated to find the conditions for better deliverability. Firstly, micro-computerised tomography (CT) experiments were carried out on a condensate gas system in four sandstone rock core samples. However, due to limitations of the experimental technique, the phase characteristics of the condensate gas could not be fully described in nanostructure pore scale. Therefore, an improved Peng–Robinson equation of state incorporating capillary force was used to simulate the flash phase behaviour of condensate gas and the constant volume depletion experiment in a single pore. Then, based on a pore network model generated using a random fractal method, a modified model was developed to investigate fluid distribution in a gas condensate system at the nanostructure pore scale. A new method was developed that applies a flash calculation in all throats in the network to estimate the amount of accumulated condensate in the corners of the throats. Finally, the phase behaviour of condensate gas in different types of porous media was studied in parallel capillary bundle and three-dimensional network models. The experimental phenomena observed in the CT experiments were explained by the characteristic simulation study. The results of this study provide theoretical support for phase behaviour predictions in condensate gas reservoirs.