Reservoir System Research Articles

Contribution of Various Shale Components to Pore System: Insights from Attributes Analysis

Shale pore systems are the result of the geological evolution of different matrix assemblages, and the composition of gas shale is considered to affect the pore systems in shale reservoirs. This study aimed to investigate the impact of both organic and inorganic constituents on the shale pore system, including specific surface area (SSA) and pore volume in Wufeng–Longmaxi Shale. Multiple linear regression (MLR) was employed to examine the contributions of different components to shale pore structure. The pore structure parameters, including pore SSA and pore volume, were obtained by gas adsorption experiments in 32 Wufeng–Longmaxi Shale (Late Ordovician–Early Silurian) samples. Both pore SSA and pore volume were calculated by the density functional theory (DFT) model on shale samples, and the pore types were determined by high-resolution field emission scanning electron microscopy (FE-SEM). The results of the X-ray diffractometer (XRD) analysis indicate that the Wufeng–Longmaxi Shale is dominated by quartz, clays, carbonates, feldspar, pyrite, and organic matter. Four models were made using SPSS software, all of which showed significant correlation between shale pore size and organic matter (OM) and clays. The content of organic matter played the biggest role in determining the size and structure of the pores. Although the content of quartz is the highest and serves as a rigid skeleton in shale reservoirs, it has complicated effects on the pore structure. In this study, most of the quartz is biogenetic and part of it is transformed from clays in deep shale. Therefore, these two parts of quartz are, respectively, related to organic matter and clays. In essence, the pores related to these two parts of quartz should be attributed to organic matter and clays, which also support the conclusion of the MLR models.

Fractal Features of Fracture Networks and Key Attributes of Their Models

This work is devoted to the modeling of fracture networks. The main attention is focused on the fractal features of the fracture systems in geological formations and reservoirs. Two new kinds of fracture network models are introduced. The first is based on the Bernoulli percolation of straight slots in regular lattices. The second explores the site percolation in scale-free networks embedded in the two- and three-dimensional lattices. The key attributes of the model fracture networks are sketched. Surprisingly, we found that the number of effective spatial degrees of freedom of the scale-free fracture network models is determined by the network embedding dimension and does not depend on the degree distribution. The effects of degree distribution on the other fractal features of the model fracture networks are scrutinized.

Microbial Communities Affected by Hydraulic Fracturing and Environmental Factors within an In Situ Coal Reservoir.

The rise of coalbed methane bioengineering enables the conversion and utilization of carbon dioxide through microbial action and the carbon cycle. The environment of underground coal reservoirs is the result of a comprehensive effort by microorganisms. Some studies on reservoir microorganisms have progressed in laboratory conditions. However, it does not replicate the interaction between microorganisms and the environment on site. Hydraulic fracturing is an engineering technology to improve the natural permeability of tight reservoirs and is also a prerequisite for increasing biomethane production. In addition to expanding the pore and fracture systems of coal reservoirs, hydraulic fracturing also improves the living conditions of microbial communities in underground space. The characteristics of microbial communities in the reservoir after hydraulic fracturing are unclear. To this end, we applied the 16S rRNA sequencing technique to coalbed methane production water after hydraulic fracturing south of the Qinshui Basin to analyze the microbial response of the hydraulic fracturing process in the coal reservoir. The diversity of microbial communities associated with organic degradation was improved after hydraulic fracturing in the coal reservoir. The proportion of Actinobacteria in the reservoir water of the study area increased significantly, and the abundance of Aminicenantes and Planctomycetes increased, which do not exist in non-fracturing coalbed methane wells or exist at very low abundance. There are different types of methanogens in the study area, especially in fracturing wells. Ecological factors also determine the metabolic pathway of methanogens in coal seams. After hydraulic fracturing, the impact on the reservoir's microbial communities remains within months. Hydraulic fracturing can strengthen the carbon circulation process, thereby enhancing the block's methane and carbon dioxide circulation. The study provides a unique theoretical basis for microbially enhanced coalbed methane.

Deriving operating rules for inter-basin water transfer projects incorporating a scenario reduction strategy

Streamflow uncertainty is one of the main challenges in managing reservoir systems. To accurately characterize the streamflow uncertainty in a reservoir operation model, numerous streamflow scenarios should be considered, but this results in a huge computational burden for multi-objective optimization. Here, we propose a methodology for deriving the operating rules for an inter-basin water transfer project (IBWT). The methodology adopts a scenario-reduction strategy to balance accuracy against the computational burden. The proposed method first reduces a large number of streamflow scenarios to several typical scenarios and the corresponding occurrence probabilities using a simultaneous backward reduction method. A multi-objective optimal operation model is then formulated to optimize the expected values of performance indices of the IBWT system under the typical scenarios. Finally, a simulation-based optimization framework is adopted to derive the multi-objective operating rules. To test the method, the Han to Wei IBWT project in northwest China is considered as a case study. The results show that the proposed methodology produces effective reservoir operating rules with a relatively low computational burden. After the initial 1,000 streamflow scenarios have been reduced to 20, the model solution time decreases significantly, from 49.17 h to 1.05 h, while the changes in mean value (0.47%) and standard deviation (0.93%) of these scenarios are less than 1%. Compared with an operation scheme that uses only historical streamflow data, the operation performance is further improved in terms of energy production, energy consumption, and water shortage index when the streamflow uncertainty is considered.

Occurrence, Bioavailability, and Environmental Risk of Heavy Metals and Metalloids in the Sediment and Drawdown Area of Fengshuba Drinking Water Reservoir

ABSTRACT Heavy metal and metalloid pollution in reservoir systems has attracted widespread attention due to their toxic, persistent, and nonbiodegradable characteristics. This study investigated the distribution and risks of heavy metals and metalloids in the sediment and drawdown area of the Fengshuba reservoir system. Sediment phase exhibited substantial heavy metal and metalloid pollution and higher ecological risk that the drawdown phase. There were significant differences in the structure and composition of the total metal content and the bioavailable fraction between the sediment and the drawdown area, which indicates that the total metal content and the bioavailable fraction might dominantly regulate by a complex combination of sediment characteristics. Positive Matrix Factorization model was used to identify sources of heavy metals and metalloids pollution and revealed that heavy metals and metalloids contamination in Fengshuba reservoir might originate from anthropogenic activities. Evaluations from risk assessment show that As and Cd in the reservoir system may pose health risks. Knowledge of distribution, potential risk assessment, and source apportionment of heavy metals and metalloids in the Fengshuba drinking water is critical in promoting the sustainable development of the reservoir, developing water management and conservation strategies in the Fengshuba reservoir.

Insights into Toxic Prymnesium parvum Blooms as a Cause of the Ecological Disaster on the Odra River

In 2022, Poland and Germany experienced a prolonged and extensive mass fish kill in the Odra River. During the period from the end of July to the beginning of September 2022, a high level of incidental disease and mortality was observed in various fish species (dozens of different species were found dead). The fish mortality affected five Polish provinces (Silesia, Opole, Lower Silesia, Lubuskie, and Western Pomerania) and involved reservoir systems covering most of the river (the Odra River is 854 km long, of which 742 km are in Poland). Fatal cases were investigated using toxicological, anatomopathological, and histopathological tests. Water samples were collected to determine nutrient status in the water column, phytoplankton biomass, and community composition. High nutrient concentrations indicated high phytoplankton productivity, with favorable conditions for golden algal blooms. The harmful toxins (prymnesins secreted by Prymnesium parvum habitats) had not been found in Poland before, but it was only a matter of time, especially in the Odra River, whose waters are permanently saline and still used for navigation. The observed fish mortality resulted in a 50% decrease in the fish population in the river and affected mainly cold-blooded species. Histopathological examinations of fish showed acute damage to the most perfused organs (gills, spleen, kidneys). The disruption to hematopoietic processes and damage to the gills were due to the action of hemolytic toxins (prymnesins). An evaluation of the collected hydrological, meteorological, biological, and physico-chemical data on the observed spatio-temporal course of the catastrophe, as well as the detection of three compounds from the group of B-type prymnesins in the analyzed material (the presence of prymnesins was confirmed using an analysis of the fragmentation spectrum and the accurate tandem mass spectrometry (MS/MS) measurement, in combination with high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS), allowed the formulation and subsequent testing of the hypothesis for a direct link between the observed fish mortality and the presence of prymnesins in the Odra River. This article systematizes what is known about the causes of the fish kill in the Odra River in 2022, based on official government reports (one Polish and one German) and the EU technical report by the Joint Research Centre. A review and critical analysis of government findings (Polish and German) on this disaster were conducted in the context of what is known to date about similar cases of mass fish kills.

Compositional numerical analysis of multiphase flow of crude oil in porous media under non-isothermal conditions

Abstract The present work details the development of a compositional model to replicate the heavy hydrocarbon flow in porous reservoir systems under non-isothermal conditions. The mathematical model considers mass and energy conservation equations describing the reactive of natural variables distributed in a multiphase hydrocarbon system. Such natural variable based compositional models better suit fully implicit numerical schemes with inexpensive Jacobian matrix computations. Further, the model accommodates a switch of primary variables for the disappearance and reappearance of a phase. The resulting nonlinear conservation equations are numerically discretized using a block-centered finite-difference scheme and solved with a quasi-Newton based implicit iterative solver. The present model is validated with the thermal profiles presented in the literature for the multiphase flow during the combustion of heavy crude oil in petroleum reservoir system with performance coefficient (R 2), mean absolute error (MBE), and maximum absolute percentage error (MAPE) of about 0.954, 0.37, and 0.01 respectively. The developed compositional model projected 26 and 72 % of light and heavy oil recoveries respectively in about 160 days with a maximum or peak temperature of about 798 K. Further, the thermal and production profiles projected by the sensitivity analysis on various operating parameters are presented. It is noteworthy that the present works aid in providing an economical numerical based tool in evaluating the flow and transport during underground or in-situ combustion process for efficient energy exploration.

Neural network surrogate for flow prediction and robust optimization in fractured reservoir systems

Embedded discrete fracture models are widely used to model flow in naturally fractured systems. These models are, however, time-consuming to simulate, and this limits their use for computationally demanding applications such as optimization. In this work we present a deep-learning-based surrogate model for fast prediction of time-varying well flow rates over multiple fracture realizations, for given well bottom-hole pressure schedules. Our surrogate model applies convolutional and recurrent neural networks. The convolutional neural network is used to capture the spatial variability of fractures in different realizations, though the direct input of the fracture geometry is not feasible because structured data are required. We show, however, that the use of the single-phase steady-state pressure solution defined on the structured rock-matrix grid, for each realization, provides the requisite input to the convolutional neural network. The resulting proxy is shown to give accurate flow rate predictions for different discrete fracture realizations. The proxy is then applied for robust optimization (expected net present value computed over an ensemble of realizations is optimized) subject to nonlinear output constraints. Proxy-based optimization provides an 18% improvement in net present value, with an overall speedup of ∼500 relative to simulation-based optimization. The optimized solutions are validated through comparison to simulation results, and agreement is within 1%.

Characterization of a complex sand-rich gas hydrate reservoir system in the Indian marine continental margin with downhole log and seismic data

Logging-while-drilling (LWD) and coring data were acquired in Areas A, B, C and E during the National Gas Hydrate Program Expedition 02 (NGHP-02). At Sites NGHP-02-16, −17, −20, −23 and −24 of Area B in the Indian Krishna-Godavari Basin, the gas hydrate-bearing sand-rich reservoirs directly in contact with an underlying water-saturated sediment were revealed near the seismic-inferred bottom simulating reflector (BSR) along a large anticlinal structure. Lithofacies analysis of cores show that the lower gas hydrate-bearing reservoir section at these sites is an interbedded unit with thin fine-sand layers alternating with clay-rich layers. We reanalyzed the LWD data including resistivity, compressional-wave and shear-wave acoustic velocities to assess and compare the spatial variation of sand-hosted gas hydrate and possible related free-gas accumulations. The presence of free gas-bearing sediments in direct contact with gas hydrate-bearing sediments was confirmed at Sites NGHP-02-20 and −24 along the northeastern flank of the anticline. The sand-rich reservoirs associated with the Area B anticlinal feature reveal different pore-filling constituents and variable boundary conditions, including gas hydrate/water contacts and gas hydrate/free gas contacts. We infer that the sedimentary depositional history at Sites NGHP-02-20 and −24, may have resulted in an upward shift of the base of gas hydrate stability zone, that could have led to in situ gas hydrate dissociation and the accumulation of free gas and coexistence interval below the log-inferred gas hydrate-bearing reservoir sections. This study demonstrates that reservoir heterogeneity and fluid migration were major factors affecting the distribution of gas hydrate and free gas in the identified sand-rich reservoirs.

A framework for the forensic-engineering assessment of reservoir operation during floods based on a new standard operation policy

Floods inflict financial and human losses worldwide. The importance of assessing the effectiveness of flood management policies rises as the frequency and severity of floods increase. This study presents a novel forensic engineering framework for assessing the role of reservoir operation in achieving objectives under flood conditions. Specifically, this work develops two approaches, called the standard operation policy (SOP) and the ideal approach (IA) for the forensic assessment of reservoir-operation performance, which are compared with the historic management (HM) of reservoirs under flood conditions. This work introduces an innovative SOP for operation of reservoirs with the functions of flood control, meeting water demands, and hydropower generation. The genetic algorithm (GA) with the objective function of minimizing the maximum release from the most downstream reservoir in a multi-reservoir system is applied with the IA. The proposed framework is applied to evaluate the performance of the Seimare and Karkheh reservoirs system during floods in 2019 and 2020 in the Karkheh basin, Iran. The results show that in 2018–2019 and 2019–2020, on average, and under HM, the Seimare reservoir’s and Karkheh reservoir’s performance were respectively 28 and 68% worse than the SOP, and they were respectively 46 and 83% worse than the IA. This work’s forensic methods contribute to the practice of flood mitigation by means of reservoir operation.

Joint probability analysis of storage reservoir system characteristics

A comprehensive evaluation of the frequency distribution analysis of reservoir storage capacity plays an important role in reducing the uncertainty in the design and operation of reservoir systems. In most studies, a simplified reservoir system (such as over-year system and using annual data, without incorporating evaporation losses and performance measures, i.e. reliability, vulnerability, and constant monthly demand) was investigated. On the other hand, the required reservoir capacity variable is not independent of other characteristics of the reservoir system such as performance measures, critical period, and evaporation losses, and has a high correlation with these variables. Therefore, in this study, the joint probabilities of different characteristics of the reservoir system were comprehensively developed using copulas. Hence, an extensive Monte Carlo reservoir simulation procedure incorporating monthly streamflow data, performance measures, evaporation losses, and demand was applied to extract the population of dependent variables of an actual reservoir. The results showed that a) the required storage capacity in the reservoir system is highly dependent on other reservoir characteristics such as performance measures, critical period, and evaporation losses; b) the joint probability of the reservoir system characteristics are well modeled by a Gaussian copula and c) the joint probability of the reservoir characteristics has a systematic behavior for given reliability and vulnerability values.

A new method to evaluate integrated production system capacity in oil fields

To improve the design and management of an integrated production system (IPS), a set of mathematical models and workflows are developed for evaluating the capacity of an IPS at steady-state conditions. Combining the conservation laws with applicable multiphase fluid and choke models, these mathematical models are solved to characterize the hydraulics of an integrated system of reservoir, wells, chokes, flowlines, and separator at steady state. The controllable variables such as well count, choke size and separator pressure are adjusted to optimize the performance of the IPS at a specific time. It is found that increasing the well count can increase the bulk flow rate of the production network, but too many wells may increase the manifold pressure, leading to decline of single-well production. Increasing the choke size can improve the capacity of the IPS. The production of the IPS is negatively correlated with the separator pressure. With increasing separator pressure and decreasing choke size, the increment of total fluid production (the capacity of IPS) induced by increasing well count decreases. Validation tests with field examples show a maximum absolute deviation is 1.5%, demonstrating the robustness and validity of the proposed mathematical models and workflows.

Study of the Dissolved Organic Matter Fluorescence Spectrum and Indicator Effect of Environmental Factors in Sediments of a Reservoir System: a Case Study of the Three Gorges Reservoir Area

Study of the Dissolved Organic Matter Fluorescence Spectrum and Indicator Effect of Environmental Factors in Sediments of a Reservoir System: a Case Study of the Three Gorges Reservoir Area

Exploiting image logs to reduce drilling hazards: an innovative Artificial Intelligence methodology applied in East Africa

SUMMARY Image logs are crucial for petrophysical and structural characterization of drilled formations. Logging while drilling (LWD) image logs allow near real-time characterization of formations during drilling. Interpretation time required by humans can become critical, as structural interpretation provides the most crucial information for decision-making steps with respect to drilling operations. An example of this occurred in a deepwater system of reservoirs in East Africa. During the drilling of some wells, drilling was interrupted by unexpected borehole stability issues observed in a mass transport deposit. Those problems can detrimentally affect operations by impacting the efficiency of drilling. Therefore, a procedure for the automation of LWD data analysis was developed aimed at reducing drilling risk associated with borehole stability. A workflow is proposed based on an innovative assortment of AI methodologies for automatic real-time interpretation of LWD image log, applied to density image logs. The goal is to mimic manual human dip picking, combining computer vision, numerical series analysis and machine learning. Computer vision techniques are applied to detect the main density contrasts, representing the most likely surfaces. Sharp contrasts in the image are then investigated by dynamic time warping for similarity analysis. Finally, the geological plane is defined as a regression plane passing through the most similar contrasts, and a surface confidence criterion is defined based on the homogeneity of contrast along the curve suggested by the regression. Feature identification by a geologist was used as benchmark for comparison and metrics. Accuracy is referred to the difference between apparent dip and azimuth of geological surfaces coming from human and automated workflows, following the idea that two similar geometric results would eventually lead to equally similar geological considerations, and thus to similar operational measures. In general, a prediction accuracy of 60 per cent for the tested wells is observed, considering the total set of surfaces coming from the model. Nevertheless, the results suggest a positive correlation between the apparent dip of the discontinuities and the model error and a general less confidence for the surfaces with greater dip. By isolating the subset of low dipping features generated by the model, that is up to 35°, the accuracy appears to increase up to more than 70 per cent, suggesting that correlation is more difficult for high dipping geological planes. This class of curves also shows a general lower confidence and much of this latter class of surfaces are more likely to be found in the depth interval in which borehole stability issues occurred.

Water Quality and Flow Management Scenarios in the Qu’Appelle River–Reservoir System Using Loosely Coupled WASP and CE-QUAL-W2 Models

The water bodies of the Saskatchewan Prairies suffer multiple stressors, and demand for water is expected to increase. Water quality models can help evaluate water management strategies and risks such as climate change. This study assesses the impact of interbasin water transfers on the water quality of a strategic, eutrophic prairie reservoir that receives poor-quality watershed run-off. A one-dimensional WASP model was used to estimate nutrient transformations in the transfers along a 97 km river channel. The WASP model was then loosely coupled to a two-dimensional CE-QUAL-W2 model of the downstream receiving reservoir. Output from the WASP model was manually transformed into boundary conditions for the CE-QUAL-W2 reservoir model. This method improves on an earlier attempt to estimate nutrient transformations in the transfers using linear regression. Results from the loosely coupled models suggest Buffalo Pound Lake would respond well to the interbasin transfers. The number of threshold exceedances decreased for all modeled water quality variables. Nutrient concentrations were most influenced in the open water season following spring freshet. Any additional reduction of threshold exceedances during winter was minimal in comparison. These results are interesting from a management perspective as increased transfers under winter operations risk ice damage to the river channel.

Dox-loaded TPU-PLGA nanoparticles embedded chitosan hydrogel formulation as an effective anti-cancer therapy

Recently, Polylactic-co-glycolic acid (PLGA)-based polymeric nanosystems are gaining a lot of attention as drug carriers for cancer treatment. However, the degradation of PLGA-based systems through bulk erosion induces systemic toxicity and is quite unfavorable, thus signifying the need for a controlled drug release system. In this perspective, the present study involves the synthesis of a novel thermoplastic polyurethane-polylactic-co-glycolic acid (TPU-PLGA) copolymer. Proton nuclear magnetic resonance and Fourier transform infrared spectroscopy were used to characterize the synthesized copolymer. The novel copolymer was further evaluated for encapsulation of the anticancer drug doxorubicin (Dox). To facilitate more sustained drug delivery, Dox-loaded TPU-PLGA nanoparticles (TPU-PLGA-Dox NPs) were embedded in a chitosan (CTP-Dox NPs) hydrogel which protected the embedded NPs and aided in additional engineering flexibility. Also, the drug release profiles showed stable and pH-responsive drug release from the CTP-Dox NPs based-hydrogel reservoir system. Furthermore, the cell viability assay and internalization studies were performed for the CTP-Dox NPs hydrogel along with native Dox and TPU-PLGA-Dox NPs. The novel CTP-Dox NPs hydrogel system has a lot of potential for improving the overall therapeutic performance of anti-cancer treatments by prolonging the sustained release of the drug.

Quantum correlations and thermal coherence in a two-superconducting charge qubit system

Superconducting charge qubits represent a cutting-edge technology in the field of quantum computing, offering a promising platform for quantum processing. This study delves into the behaviors of thermal coherence and quantum correlations within a two-superconducting charge qubit system coupled by a fixed capacitance. Specifically, we investigate the effects of thermal noise on entanglement (measured by concurrence), nonclassical correlations (quantified by local quantum uncertainty), and quantum coherence (measured by correlated coherence) within the two-superconducting charge qubit capacitively coupled. Our analysis takes into account the interplay between the equilibrium temperature of the reservoir and various system parameters. Our findings demonstrate that an increase in temperature leads to a decrease in coherence and quantum correlations within the considered system. However, the behavior of these quantum resources is heavily dependent on the system parameters, and a careful selection of these parameters can help mitigate the negative effects of absolute temperature. Additionally, we observe that local quantum uncertainty and correlated coherence are more resilient than thermal entanglement to rising temperatures. These results provide insight into how a two-superconducting charge qubit system can be optimized for achieving quantum advantages.

How Important for Society Is Recreation Provided by Multi-Purpose Water Reservoirs? Welfare Analysis of the Vltava River Reservoir System

Contrary to the other functions of multi-purpose reservoirs, recreational use is not associated with a tangible social value, which hinders the search for new balances among optimal uses of water that will likely be needed under climate change. The objective of this study is to analyze visitation behavior and its patterns at a large-scale reservoir system on the Vltava River to quantify the total social benefits associated with recreation in monetary terms and to suggest how the magnitude of estimated recreation welfare relates to hydro-energy benefits, which are in usual practice taken much more into account than recreation in the strategic management of water dams. The elicited average consumer surplus per person and trip is EUR 55.7, which yields a total yearly recreation value of EUR 34 billion (ranging between 22 and 57). When compared to, e.g., the social value of hydro-energy generation, the actual yearly recreation welfare represents 1/3 of this nowadays more prioritized use. The results of the study bring new information for water management bodies that has been missing up to now, and they bring new arguments for reaching socially optimal water use in the strategic and operational management of the cascade of dams. From this perspective, the actual strategic relative prioritization of these two reservoir functions at the pilot site may be viewed as rational.

GIS-based potential assessment of floating photovoltaic systems in reservoirs of Tamil Nadu in India

Abstract Floating photovoltaic systems (FPVs) are one of the emerging renewable-energy technologies suitable for implementation in land-scarce areas around the world. The installation of FPVs in water bodies in highly populated countries such as India will improve renewable-energy production with added advantages in terms of efficiency, water savings and reduced carbon emissions. In this context, the present study aims to identify suitable reservoirs for solar energy production using FPV technology in Tamil Nadu, India using geographic information system techniques. A total of 118 reservoirs located in the study area were considered. The results have shown that the implementation of FPV systems will significantly improve the production of renewable energy. The most suitable reservoirs with hydroelectric power plants for hybrid FPV implementation and their potential to reduce water evaporation and carbon emissions are presented. The results reveal that hybrid systems will generate 1542.53 GWh of power annually and also save 36.32 × 106 m3 of water every year. The results of this investigation will aid in fulfilling sustainable energy production in India, and the methodology presented may be useful for the analysis and prioritization of reservoirs for the implementation of FPV all over the world.

Study of the influence of non-carbon gases on the condensate recovery coefficient of gas condensate fields using a hydrodynamic model

There is enough research work on the effective use of non-hydrocarbon gases in order to increase the component recovery of hydrocarbon deposits. Over a long period, we have also carried out a number of research works on the effect of nitrogen and carbon dioxide on the final condensate recovery factor of fields, as well as on the productivity of gas condensate wells. However, it is known that the formation systems of gas condensate fields, along with other non-hydrocarbon gases, contain nitrogen and carbon dioxide. Sometimes their number has a rather large share in the total volume. But, the effect of the amount of nitrogen and carbon dioxide naturally present in reservoir systems on the final condensate recovery coefficient of gas condensate fields has not been studied enough. The influence of the amount of nitrogen and carbon dioxide in the composition of reservoir systems on the condensate recovery coefficient of gas condensate fields has been studied. To this end, a multicomponent hydrodynamic model of the Bulla-Sea field was used as a base case, the factors influencing the process were studied by comparing the final condensate recovery coefficient of the field with other systems containing nitrogen and carbon dioxide.