Numerical Reservoir Model Research Articles

Density of pure and mixed NaCl and CaCl2 aqueous solutions at 293 K to 353 K and 0.1 MPa: an integrated comparison of analytical and numerical data

This study reports on newly acquired density data of synthetically prepared pure and mixed NaCl and CaCl2 aqueous solutions that span a wide range of geothermally encountered concentrations and mixing ratios. The analytical data are provided for the temperature range of 293–353 K at ambient pressure. For the reproduction of that data, PHREESCALE was used. The predictive potential of this numerical tool regarding the density of geothermal fluids of known composition was the major target herein. As a result, the measured data are in good agreement with previous analytical studies found in the literature. Possible sources of errors are discussed in this paper. Density data of the mixed solutions at temperatures other than ambient are unique and close existing data gaps. The numerical model reproduces the newly measured and already existing density data within an error band of approximately 1%. For further use in geothermal applications, this can be considered an excellent agreement. Moreover, the model yields a direct calculation of density without the need to establish complex empirical equations of state and mixing rules. Finally, sensitivity calculations performed with a thermal–hydraulic (TH) numerical reservoir model demonstrate the required accuracy of fluid density for reliably predicting the long-term performance of deep geothermal energy systems. In terms of the productivity index and the timing of thermal breakthrough it shows that the present analytical and numerical uncertainty in density is small enough to reliably state both reservoir parameters.

Research and Practice on EOR Development Strategy of Water Drive Followed by Gas Drive in Fractured Carbonate Reservoir in Bohai Sea

Abstract Focusing on the issues of high comprehensive water cut and low recovery degree following water flooding in the CFD 2-2 carbonate buried hill reservoir in the Bohai Sea, the productivity variation law, water cut rising characteristics and development effect of horizontal wells were analyzed based on different types of reservoir classification systems. The reservoir numerical simulation model of dual media coupling of matrix and fracture is established, and the analysis is done on the matrix and fracture production state, the distribution pattern of the residual oil, and the primary governing parameters.. The physical simulation experiment of water flooding to gas flooding is carried out. In conjunction with the distribution characteristics of fractures and matrix residual oil in low, middle and upper tiers of the framework, the development strategy of nitrogen injection pressure water cone in low water-flooded area, nitrogen flooding in middle inter-well residual oil enrichment area and nitrogen huff and puff in high well point residual oil enrichment area is put forward. The recovery rate is increased by 5-8 %, which successfully enhances the high water cut stage development effect, and provides reference for similar oilfield development.

Feasibility Theory and Practice of CO2-EOR in High CO2-Content Near-saturated Edge-bottom Water Reservoir

Abstract CO2-EOR technology for low-permeability tight oil and gas reservoir is in the ascendant, and CO2-EOR technology for old oilfields has not been paid enough attention, but the implementation scale has great potential, and the expected effect and implementation conditions are good. The feasibility of CO2-EOR technology in the ultra-high water cut stage of high CO2 content, near saturation pressure and edge-bottom water reservoir was studied theoretically, and the field implementation effect was tracked and evaluated. Via petrophysics, reservoir engineering, and site case analysis, a relatively comprehensive reservoir numerical model was developed, clarifying the impact of periodic gas injection volume, gas injection rate, soak time and liquid production rate on the production effect of CO2 huff and puff were clarified. The key injection-production parameters of CO2 huff and puff test wells were designed, and the feasibility study progress of CO2-EOR in near-saturated edge-bottom water reservoirs with high CO2 content was summarized. The theoretical research shows that the change rules of gas-water dual-drive, CO2 water control and oil increase in the process of CO2 huff and puff in high CO2 near-saturated edge and bottom water reservoirs, and reveals the synergistic mechanism of CO2 huff and puff to suppress water and increase energy. The tracking evaluation shows that the sweep condition of CO2 after huff and puff in the test well is complex, the storage ratio is in the range of 40%-70%, the stage oil increase is in the range of 700t-3000t, and the optimized oil increase and oil change rate can reach 2.7t/t. Based on the comprehensive theory and practice, it is considered that CO2-EOR has good potential for high CO2 near-saturated edge and bottom water reservoirs under fine control. This study has guiding and reference significance for CO2-EOR technology and application in similar oilfields at home and abroad.

Research on the water flooding front based on dynamic and static data inversion – a case study

To clarify the movement of the water flooding front in fluvial reservoirs, this research takes the BZ oilfield as an example. By considering the equivalent flow resistance theory for oil–water two-phase flow, the horizontal micro-element equivalent method and the strong heterogeneity of fluvial facies reservoir comprehensively, a calculation model for a non-piston water flooding front in a horizontal well pattern was established. First, five horizontal injection–production well groups in the BZ oilfield were taken as examples to calculate the water breakthrough time for the oil wells. The calculation results are in good agreement with the actual production performance. In detail, the advancing speed of the water flooding front in the high-permeability strip was 0.8–1.6 m/day, and the speed in the low-permeability strip was 0.12–0.35 m/day. When water is seen in the oil well, the advancing speed in the low-permeability strip is reduced, resulting in uneven displacement and the formation of non-dominant potential areas. In addition, the water flooding front advancing distance was simulated to be 300–450 m by establishing a reservoir numerical simulation model, which is close to the result of the proposed model, indicating that the calculation method is reliable. This research is of great significance for predicting the water breakthrough time of horizontal production wells, judging the weak affected area on the mainstream line, and optimizing water injection and tapping reservoir potential in good time.

Numerical simulation study of natural gas hydrate extraction by depressurization combined with CO2 replacement

Utilizing depressurization combined with CO2 replacement for extracting natural gas hydrates (NGHs) is vital for sustainable energy and carbon sequestration. In this study, a NGH reservoir numerical model was developed to investigate the impacts of depressurization combined with CO2 replacement on hydrate extraction at a field scale. Findings reveal an increase in methane production with reduced bottom hole pressure. When the bottom hole pressure is 3.5 MPa, the methane production reaches its maximum at 1.71 × 106 m3. Methane hydrates near production and injection wells decompose first, with deeper hydrates decomposing more easily. Higher differential pressures between injection and production enhance methane extraction and CO2 hydrate formation. However, excessive pressure differential (1.5 MPa) can lead to CO2 breakthrough across reservoir barriers, adversely affecting the purity of methane. At 1800 d, the methane purity is only 36.2 %. Optimal methane extraction and CO2 sequestration occur at higher injection temperatures (9 °C) below the CO2 hydrate phase equilibrium temperature. Temperatures above this equilibrium adversely affect both processes. The study validates the feasibility of depressurization with CO2 replacement for extracting hydrates in the Shenhu area, offering theoretical guidance for synergistic offshore methane extraction and CO2 sequestration techniques.

Impact of Fluid Distribution and Petrophysics on Geophysical Signatures of CO2 Storage Sandstone Reservoirs

AbstractCarbon Capture and Storage (CCS) is a key element to achieving net‐zero energy challenge timely. CCS operations require the integration of geophysical data, such as seismic and electromagnetic surveys, numerical reservoir models and fluid flow simulations. However, the 10–100s m resolution of seismic imaging methods complicates the mapping of smaller scale rock heterogeneities, while borehole measurements commonly show large fluctuations at sub‐cm scales. In this study, we combine laboratory data, well‐logging, rock physics theories and a proof‐of‐concept time‐lapse seismic modeling to assess the effect of pore‐scale fluid distribution and petrophysical heterogeneities on the expected performance of whole‐reservoir CCS operations in deep saline aquifers, by analogy to the Aurora CCS site, North Sea. We monitored the elastic and electrical properties of three sandstone samples with slightly different physical and petrographic properties during carbon dioxide (CO2) flow‐through tests under equivalent in situ effective pressure. We inferred the CO2‐induced damage in the rocks from the variations of their hydromechanical properties. We found that the clay fraction, CO2‐clay chemical interactions, and porosity were the main factors affecting both the CO2 distribution in the samples and the hydromechanical response. We used seismic modeling of well‐log data and the laboratory results to estimate the reservoir‐scale time‐lapse seismic response to CO2 injection and to assess the effect of the rock heterogeneities in our interpretation. The results show that disregarding the effect of rock heterogeneities on the CO2‐brine fluids distribution can lead to significant misinterpretations of seismic monitoring surveys during CCS operations in terms of both CO2 quantification and distribution.

Coupled thermo-hydro-mechanical modeling on geothermal doublet subject to seasonal exploitation and storage

Combining the conventional high-temperature aquifer thermal energy storage system with the common geothermal reservoir development system is a potential alternative to increase energy access, but effects of natural parameters like fracture aperture and reservoir permeability and development parameters like flow rate and injection temperature on the efficiency of energy exploitation and storage have seldomly been investigated. In this study, three assessment parameters and three evaluation criteria were defined to evaluate the sustainability and efficiency of deep geothermal reservoirs with seasonal energy exploitation and storage, and a robust approach of optimizing the development parameters was proposed by combining numerical reservoir model, experimental design and surrogate model, and multiple response optimization method. Based on a case study of the geothermal doublet in Tsinghua University, China, the robustness and reasonability of the developed optimization method were demonstrated. The results show that the optimal development parameters can not only maximize the total recoverable energy and effective recovery efficiency, but also satisfy the requirements of sustainably developing deep geothermal reservoirs. The recoverable heat energy can increase about 20% by adding artificial thermal storage into geothermal reservoir development. Therefore, it is strongly recommended to add energy storage into the future geothermal reservoir development system.

Oil Production Optimization Using Q-Learning Approach

This paper presents an approach for optimizing the oil recovery factor by determining initial oil production rates. The proposed method utilizes the Q-learning method and the reservoir simulator (Eclipse 100) to achieve the desired objective. The system identifies the most efficient initial oil production rates by conducting a sufficient number of iterations for various initial oil production rates. To validate the effectiveness of the proposed approach, a case study is conducted using a numerical reservoir model (SPE9) with simplified configurations of two producer wells and one injection well. The simulation results highlight the capabilities of the Q-learning method in assisting reservoir engineers by enhancing the recommended initial rates.

Study on the Countermeasures and Mechanism of Balanced Utilization in Multilayer Reservoirs at Ultra-High Water Cut Period

After entering the ultra-high water cut stage of multilayer oil reservoirs, the remaining oil is highly dispersed. Due to the continuous development of general water injection, the generation of advantageous channels makes interlayer contradictions more prominent, and the differences in the utilization between different layers are even greater. After the water drive development of multilayer oil reservoirs enters the ultra-high water cut stage, the development effect deteriorates year by year. Layer restructuring is an effective method of improving the water injection development effect and increasing the degree of utilization. In essence, its goal is to achieve balanced utilization for multiple development layers to increase the degree of recovery. This article mainly employs physical simulation experiments combined with reservoir numerical simulation technology to jointly study the effects of different equilibrium production strategies in the ultra-high water cut period of multilayer oil reservoirs and their mechanism of action based on the remaining oil distribution field and streamline field. As a specific implementation, we use large-plate physical simulation to demonstrate the effectiveness of the rotational injection and production strategy, and to supplement the physical simulation experiment with a reservoir numerical simulation model, we analyze the mechanism of different balanced production strategies. The research results for the combination of physical simulation experiments and numerical simulation experiments show that the combined strategy of rotary injection and rotary production is the most effective method for use in multilayer and ultra-high water cut oil reservoirs. The displacement effect of the high-permeability layer is better, and the increase in the recovery degree is relatively large, while the displacement effect of the low-permeability layer is relatively weak. After conventional water drive oil recovery, the remaining oil mainly exists in the edge area of the research area. However, the use of three-dimensional well network injection wheel recovery changes the streamline field, produces the effect of fluid flow diversion, expands the water drive sweep coefficient, and improves the recovery rate. Chemical plugging can effectively replace water drive oil recovery and will become the main method for improving the recovery rate of such reservoirs in the lower part.

Data driven approach using capacitance resistance model to determine polymer in-situ retention level

Polymer retention in reservoir rock can significantly impair polymer flood effectiveness and increases the required polymer bank slug size to maintain mobility control. Laboratory measurements such as static adsorption and coreflooding test are typically performed to assess polymer retention level in the reservoir, however such measurements are sensitive to rock sample used and its grain size, and the preparation method. Hence, to obtain the most representative data, polymer retention level measurement should be done at reservoir in-situ condition.This study presents an investigation to couple capacitance resistance model with polymer transport model. By utilizing produced polymer concentration data, polymer injection allocation can be determined. The coupled model also provides rapid polymer retention level estimate based on in-situ data. This model has been validated with numerical reservoir model and applied to evaluate a field polymer flood pilot.

Characterising and predicting low discharge pressure events in less permeable geothermal production wells

The heterogeneous nature of many geothermal resources can be observed in existing geothermal operations when an anomalously low permeability well is drilled amidst high permeability wells. This study looked at a low permeability, weak production well that shared a two-phase pipeline header and separator vessel with several stronger production wells on the same well pad. The utilisation history of the well under investigation had shown episodes wherein the well stopped producing due to its low discharge pressure, even at throttled conditions. Such episodes usually lead to additional costs for the power plant operator as the well has to be stimulated to reinitiate its discharge. Real-time wellhead pressure data was used in this work to develop classification models that would reliably predict the occurrence of such low discharge pressure events in the future. A good performing model would allow the operator to perform intervening measures to prevent the complete collapse of the well, thereby minimising well downtime and avoiding unnecessary costs.A workflow based on systematic time-series feature engineering was applied to characterise the dynamics of the wellhead pressure trend. Machine learning models built using the relevant time-series features were able to reliably predict the occurrence of the low discharge pressure events in the target well.A numerical reservoir model was developed and calibrated to match the transient pressure response and production history of the target well. The model results showed significant fluctuations in the fractional dimension parameter before and after the low discharge pressure events.

Offset Well Design Optimization Using a Surrogate Model and Metaheuristic Algorithms: A Bakken Case Study

Fracture-driven interaction FDI (colloquially called “Frac-hit”) is the interference of fractures between two or more wells. This interference can have a significant impact on well production, depending on the unconventional play of interest (which can be positive or negative). In this work, the surrogate model was used along with metaheuristic optimization algorithms to optimize the completion design for a case study in the Bakken. A numerical model was built in a physics-based simulator that combines hydraulic fracturing, geomechanics, and reservoir numerical modeling as a continuous simulation. The stress was estimated using the anisotropic extended Eaton method. The fractures were calibrated using Microseismic Depletion Delineation (MDD) and microseismic events. The reservoir model was calibrated to 10 years of production data and bottom hole pressure by adjusting relative permeability curves. The stress changes due to depletion were calibrated using recorded pressure data from MDD and FDI. Once the model was calibrated, sensitivity analysis was run on the injected volumes, the number of clusters, the spacing between clusters, and the spacing between wells using Sobol and Latin Hypercube sampling. The results were used to build a surrogate model using an artificial neural network. The coefficient of correlation was in the order of 0.96 for both training and testing. The surrogate model was used to construct a net present value model for the whole system, which was then optimized using the Grey Wolf algorithm and the Particle Swarm Optimization algorithm, and the optimum design was reported. The optimum design is a combination of wider well spacing (1320 ft), tighter cluster spacing (22 ft), high injection volume (1950 STB/cluster), and a low cluster number per stage (seven clusters). This study suggests an optimum design for a horizontal well in the Bakken drilled next to a well that has been producing for ten years. The design can be deployed in new wells that are drilled next to depleted wells to optimize the system’s oil production.

Upscaling simulation method of fluid flow for fracturing-shut in-flowback-production process in tight oil reservoirs: Hysteresis effects of capillary pressure and relative permeability

The hysteresis effect is a key factor to accurately predict the fluid distribution and production performance of fracturing-shut in-flowback-production (FSFP) process in tight oil reservoirs. In this paper, the upscaling simulation method of fluid flow for FSFP process has been proposed. This method, which establishes the connections between the pore network model (PNM) and the reservoir numerical model, not only effectively characterizes the hysteresis effects of capillary pressure and relative permeability in tight oil reservoirs, but also realizes the upscaling process from the pore-throat scale to the reservoir scale. First, the quasi-static pore network model for tight oil reservoirs considering the boundary layer has been established. And then, the capillary pressure curves and relative permeability curves of the drainage process (non-wetting phase displacing wetting phase process) and imbibition process (wetting phase displacing non-wetting phase process) have been obtained. Moreover, the hysteresis model has been added to numerical simulation of FSFP process and the hysteresis scanning curves have been calculated. Finally, a numerical model considering different hysteresis effects for multistage-fractured horizontal well of a tight oil reservoir located at Ordos Basin, China, has been established to investigate the oil saturation change and oil recovery during the whole process of FSFP. The results show that the hysteresis effects of capillary pressure and relative permeability will increase the predicted exchange volume of oil-water between matrixes and fractures in fracturing-shut in process, and decrease the predicted oil recovery in flowback-production process. Which is proved by the actual production performance of the tight oil reservoir developed by elastic energy.

A Novel Methodology for Predicting the Production of Horizontal CSS Wells in Offshore Heavy Oil Reservoirs Using Particle Swarm Optimized Neural Network

Cyclic steam stimulation (CSS) is one of the main offshore heavy oil recovery methods used. Predicting the production of horizontal CSS wells is significant for developing offshore heavy oil reservoirs. Currently, the existing reservoir numerical simulation and analytical models are the two major methods to predict the production of horizontal CSS wells. The reservoir numerical simulation method is tedious and time-consuming, while the analytical models need many assumptions, decreasing models’ accuracy. Therefore, in this study, a novel methodology combining the particle swarm optimization algorithm (PA) and long short-term memory (LM) model was developed to predict the production of horizontal CSS wells. First, a simulation model was established to calculate the cumulative oil production (COP) of horizontal CSS wells under different well, geological, and operational parameters, and then the correlations between the calculated COP and parameters were analyzed by Pearson correlation coefficient to select the input variables and to generate the initial data set. Then, a PA-LM model for the COP of horizontal CSS wells was developed by utilizing the PA to determine the optimal hyperparameters of the LM model. Finally, the accuracy of the PA-LM model was validated by the initial data set and actual production data. The results showed that, compared with the LM model, the mean absolute percentage error (MAPE) of the testing set for the PA-LM model decreased by 4.27%, and the percentage of the paired points in zone A increased by 2.8% in the Clarke error grids. In addition, the MAPEs of the training set for the PA-LM and LM models stabilized at 267 and 304 epochs, respectively. Therefore, the proposed PA-LM model had a higher accuracy, a stronger generalization ability, and a faster convergence rate. The MAPEs of the actual and predicted COP of the wells B1H and B5H by the optimized PA-LM model were 8.66% and 5.93%, respectively, satisfying the requirements in field applications.

Diffusion Effect on Shale Oil Recovery by CO2 Huff-n-Puff

The CO2 diffusion effect is an important mechanism of injected CO2 penetrating the reservoir matrix and diffusing into the oil phase during the huff-n-puff (HNP) process. However, the CO2 diffusion coefficient of shale is still uncertain under the reservoir conditions, and the contribution of diffusion to enhanced oil recovery (EOR) needs to be further explored. In this study, the CO2 diffusion coefficient of shale is determined under the simulated reservoir conditions (9–10 MPa, 90 °C) in the laboratory, and the determined CO2 diffusion coefficient is applied in the reservoir numerical model to evaluate the contribution of the CO2 diffusion effect to EOR in the HNP process. First, a radial constant volume diffusion (RCVD) device was built to measure the CO2 diffusion coefficient by the pressure decay method. After that, both the analytical solution and the numerical solution are used to ensure that the result is correct. Finally, a field-scale model consisting of one stage of hydraulic fracture in a shale oil reservoir is established. The effects of reservoir properties such as fracture spacing, fracture half-length, and operational properties of HNP like injection rate, injection time, and soaking time on oil recovery were discussed when the diffusion was included and excluded. The CO2 diffusion coefficient of a shale core is ranging from 1.44 × 10–7 to 5.50 × 10–7 cm2/s, and it is reasonable to be applied in the field reservoir numerical simulation model. According to simulation results, the lower fracture spacing and longer fracture half-length make more CO2 diffuse into the shale matrix, which are critical parameters, to promote the CO2 diffusion effect. When the injection rate is slow and the injection time is short, the CO2 diffusion effect in the reservoir may contribute more to EOR. A high injection rate means sufficient pressure supplement, and the CO2 diffusion effect may become relatively negligible. The soaking time may not be necessary for the EOR of HNP, but the longer soaking time will promote the contribution of CO2 diffusion to EOR, and the incremental recovery is about 0.15–0.26%.

Analysis of water invasion effect and development scheme design for deep water HHT gas reservoir: A case study of LS25 gas field

Based on the South China Sea deepwater high temperature and high pressure gas reservoir LS25 gas field, 3D geological model and a numerical reservoir model of LS25 gas field are established. Through numerical simulation of gas reservoir production, quantitative analysis of water invasion characteristics of 11 wells has been completed. The whole process of water invasion in space is as follows: bottom water conies in the early stage, forming water cone shape, the scale of the water body to the ridge increases, and the horizontal section completely emerges. Through comparative study, it is concluded that the combined water control technology of variable density screen pipe has the best water control effect. According to the prediction and analysis of the final production plan of variable density technology, it can prolong the water-free gas production period of the gas reservoir by 0.7 years, prolong the total production time by 1.9 years, increase the gas production by 1.9×108m3, and increase the recovery factor by 10.5% compared with that without water control measures. The research results are aimed to establish an optimal water control development model for buried hill gas reservoirs, and provide a good technical support for reasonable and scientific water control research of horizontal wells in offshore buried hill fractured gas reservoirs.

Study on Enhancing Shale Oil Recovery by CO2 Pre-Pad Energized Fracturing in A83 Block, Ordos Basin

The Ordos Basin is rich in shale oil resources. The main targeted layers of blocks A83 and X233 are the Chang 7 member of the Yanchang Formation. Due to extremely low permeability, a fracturing technique was required to enhance oil recovery. However, after adopting the stimulated reservoir volume-fracturing technology, the post-fracturing production of the A83 block is significantly lower than that of the X233 block. For this problem, the dominating factors of productivity of the two blocks were analyzed using the Pearson correlation coefficient (PCC) and the Spearman rank correlation coefficient (SRCC), showing that the main reason for the lower production of the A83 block is its insufficient formation energy. To solve this problem, the CO2 pre-pad energized fracturing method was proposed. To study the feasibility of CO2 pre-pad energized fracturing in the A83 block, an integrated reservoir numerical simulation model of well A83-1 was established based on the idea of integration of geology and engineering. Additionally, the productions within five years after conventional volume fracturing and CO2 pre-pad energized fracturing were compared. The results show that compared with conventional volume fracturing, the cumulative oil production of CO2 pre-pad energized fracturing increases by 11.8%, and the water cut decreases by 16.5%. The research results can guide the subsequent reservoir reconstruction operation in the A83 block and provide new ideas for fracturing in the future.

Simulation-optimization with machine learning for geothermal reservoir recovery: Current status and future prospects

In geothermal reservoir management, combined simulation-optimization is a practical approach to achieve the optimal well placement and operation that maximizes energy recovery and reservoir longevity. The use of machine learning models is often essential to make simulation-optimization computational feasible. Tools from machine learning can be used to construct data-driven and often physics-free approximations of the numerical model response, with computational times often several orders of magnitude smaller than those required by reservoir numerical models. In this short perspective, we explain the background and current status of machine learning based combined simulation-optimization in geothermal reservoir management, and discuss several key issues that will likely form future directions. Cited as: Rajabi, M. M., Chen, M. Simulation-optimization with machine learning for geothermal reservoir recovery: Current status and future prospects. Advances in Geo-Energy Research, 2022, 6(6): 451-453. https://doi.org/10.46690/ager.2022.06.01

Probabilistic Resource Assessment of The Ulumbu Geothermal Field, East Nusa Tenggara, Indonesia

DOI:10.17014/ijog.9.2.183-193A resource assessment of the Ulumbu Geothermal Field, East Nusa Tenggara, Indonesia, is proposed here. The fundamental issue of reserve estimation is determining the optimum capacity to be installed (field size) that affects the decision-making in geothermal projects. The reservoir numerical model and heat stored method are the most appropriate tools for geothermal resource assessment. Therefore, the hybrid numerical simulation and heat stored methods, coupled with the probabilistic approach, are applied to Ulumbu. Based on the calibrated numerical model, the estimation of the reservoir is divided into the steam zone and liquid reservoir. The energy reserve of the Ulumbu is estimated by Monte Carlo simulation with the results P10-P50-P90 are 71 MWe, 95 MWe, and 127 MWe, respectively

Increasing hydrocarbon recovery of Hadiach field by means of CO2 injection as a part of the decarbonization process of the energy sector in Ukraine

Purpose is studying the efficiency of a carbon dioxide injection technology to control a water flooding process of the reservoir of the horizon V-16 of Hadiach oil and gas condensate field and displace the residual gas reserves trapped by the formation water involving numerical modelling. Methods. A technology of carbon dioxide injection into the reservoir of the horizon V-16 of Hadiach oil and gas condensate field was tested in terms of numerical reservoir model with the use of basic modelling instruments. Findings. The modelling results makes it possible to calculate the main technological indices of the development of the reservoir of the horizon V-16 of Hadiach oil and gas condensate field in terms of carbon dioxide injection and while developing for depletion. According to the results of the performed calculations, it is identified that there is considerable influence of the number of injection wells on the efficiency of the analyzed technology as for control of a water flooding process in the productive formation. It should be noted that while increasing the number of injection wells, more complete coverage of the gas-bearing area with carbon dioxide is provided; owing to that, the efficiency of blocking the formation water inflow into the production wells turns to be much higher. The implementation of the technology under study makes it possible to increase the final hydrocarbon recovery factors. In case of using wells ## 52, 101, 201, 202 for carbon dioxide injection, the highest final hydrocarbon recovery factors are provided. The predictive gas recovery factor grows by 2.95% and the condensate recovery factor increases by 1.24% comparing to the field development for depletion. Originality. Basing on the research results, technological efficiency of the implementation of a carbon dioxide injection technology in terms of the reservoir of the horizon V-16of Hadiach oil and gas condensate field is determined; that is aimed at increasing the hydrocarbon recovery within the field by controlling a water flooding process in the productive formations and production wells. Practical implications. Application of the research results helps improve the current system of the development of productive formations of Hadiach oil and gas condensate field in terms of water drive. Implementation of such technologies stipulates the increase in final hydrocarbon recovery of the depleted fields and allows developing optimal ways of utilization of technogenic carbon dioxide in terms of the whole decarbonization process of the energy sector in Ukraine.