Condensate Reservoirs Research Articles

Liquid phase blockage in micro-nano capillary pores of tight condensate reservoirs

The development of tight condensate gas reservoirs faces complex formation damage mechanisms, seepage characteristics and hydrocarbon phase changes, which are common challenges for both tight gas reservoirs and condensate gas reservoirs. In the near-well area, the liquid phase blockage problem due to water phase retention formed by capillary spontaneous imbibition of invasive water and oil phase accumulation due to retrograde condensation precipitation has become a key obstacle to the efficient development of tight condensate gas reservoirs. Experiments were conducted to evaluate the damage of liquid phase blockage under different conditions near the wellbore area. The results show that when the liquid phase saturation in the near-wellbore area increased to 80.12%, the relative permeability of the gas phase decreased to 0. It is concluded that the mixed wettability of formation rocks, ultra-low water saturation, abundant hydrophilic clay minerals and high capillary resistance of micro-nano pores are the main causes for the easy adsorption and retention of liquid phase. Reduced pressure transmission capacity and irreversible formation damage induced by liquid-phase blockage are the two major controlling factors for the low liquid phase flowback rate. It is suggested that developing a flowback system based on the formation physical properties differentiation to control water phase invasion, and changing wettability or injecting thermochemical fluid to control condensate blocking are feasible methods to relieve liquid phase blockage damage in tight condensate reservoirs. Cited as: Wang, Y., Kang, Y., Wang, D., You, L., Chen, M., Yan, X. Liquid phase blockage in micro-nano capillary pores of tight condensate reservoirs. Capillarity, 2022, 5(1): 12-22. https://doi.org/10.46690/capi.2022.01.02

Modifying rock compressibility to analyze the production data of non-volumetric gas and gas condensate reservoirs

Production data analysis, particularly the flowing material balance method, has been used for many years as an efficient, practical, and significant method to obtain important reservoir parameters. Many studies have been done to develop the flowing material balance method in different types of reservoirs which in most of them, the main limitation is that the reservoir has been considered to be volumetric. Therefore, despite being widely used, this method has not been well developed for non-volumetric water drive reservoirs. In the present work, an extremely simple yet very accurate method was introduced to obtain an excellent estimation of average pressure and gas in place of non-volumetric dry gas and gas condensate reservoirs. In our proposed method, a modified rock compressibility parameter was presented to modify current flowing material balance equations which have been developed for volumetric dry gas and gas condensate reservoirs previously. Using the proposed compressibility, the modified flowing material balance equations can be used for non-volumetric dry gas and gas condensate reservoirs producing with constant bottomhole pressure during the boundary-dominated flow period. Moreover, the iterative procedures to estimate average pressure and gas in place of these kinds of reservoirs were presented in detailed steps. Also, the validity of the proposed flowing material balance equations was performed using a commercial numerical reservoir simulator. The obtained results prove the efficiency of the proposed method. Furthermore, due to the high amount of uncertainty in aquifer parameters, an uncertainty analysis has been performed on aquifer parameters using Monte-Carlo simulation. The results of the study indicated that the determination of appropriate aquifer parameters has a significant impact on the estimation of reservoir parameters which can be obtained using a combination of uncertainty analysis and the proposed flowing material balance technique.

Distribution of the Initial Fluid Composition in an Oil-Gas-Condensate Reservoir with Incomplete Gravity Segregation

It is known that initial composition of the hydrocarbon fluid in a petroleum reservoir changes significantly with depth due to the influence of gravity and geothermal gradient. Classical models of these phenomena are based on the assumption of equilibrium (quasiequilibrium) distribution of component concentrations in the gravity field with the presence of stationary thermodiffusional flux. However, there are typical situations in gas condensate reservoirs when the quasi-equilibrium conditions are not met. For example, this is true if immobile residual oil exists in the reservoir or for deep tight formations where gravity segregation is not completed. For such cases, modified models are required. They are proposed in this paper to take into account the non-equilibrium conditions of the initial fluid composition distribution in gas condensate (or oil-gas-condensate) reservoirs.

A new plotting technique for modeling critical flow through Multi-Orifice wellhead chokes

Well production rate is one of the most crucial parameters for reservoir modeling, management and surveillance. In most cases, this parameter is known by using empirical correlations to estimate the flow rate passing through fixed wellhead choke. However, in offshore and hostile environments, the multi orifice valve (MOV) choke is installed as a substitute to control the well production remotely. Due to complexity of flow in this type of restriction, theoretical choke modeling is impossible and the available empirical correlations for fixed chokes can’t be used for rate calculation. In this paper, a new, yet simple plotting technique is proposed for modeling the flow of gas condensate type fluid in MOV wellhead choke to estimate well gas rate. By using a set of test separator data including 164 well rate, choke opening and wellhead flowing pressure, gathered from an offshore gas condensate reservoir located in Middle East, the technique was developed and validated. The results revealed that proposed methodology can estimate well rate with an absolute average percent deviation of 5%. The critical need for rate data, make the findings of this paper attractive for petroleum industry.

Progress on Modeling of Dynamic Productivity of Fractured Gas Condensate Reservoir Based on a Fluid-Solid Coupling Method

Bozhong 19-6 gas field is the first discovered large-scale gas condensate field in eastern China, which is also one of the largest metamorphic rock gas condensate fields in the world. It is a buried hill type, low permeability reservoir, with ultra-high condensate content where the fluid is nearly at its dew point pressure. No similar experience with such reservoirs have previously been reported in the context of gas field development in China and step-by-step progresses is been made to characterize this reservoir. Overall, documentation concerning this type of reservoir is rarely seen worldwide. This paper includes key successful results from multiple perspectives including experiments correlations, numerical modeling and the significance of incorporating certain details. Based on a fluid-solid coupling method, the simulations consider several factors including the fracture distribution, low permeability, medium deformation, and condensate characteristics, as well as their effects on the gas productivity. In the laboratory experiments, the stress sensitivity of the rock was tested using representative core samples. Here, experiment-based correlations of the starting pressure gradient of the gas condensate reservoir are proposed. The starting pressure gradient of different fluid types, such as black oil and gas condensate are highlighted as accurately simulating the reservoir. As a result, the numerical model to predict the dynamic productivity of a single well was successfully established considering all those factors. This paper can serve as a reference for studying other studies of metamorphic, fractured gas condensate reservoirs.

Wells of gas and gas condensate reservoirs in the South-Eastern part of the Bukhara-Khiva region and methods for increasing their productivity

The article examines the methods of increasing the productivity of wells of gas and gas condensate reservoirs in the south-eastern part of the Bukhara-Khiva region (BHR). The role of gas calculation methods in determining the gas reserve of Mesopotamia in sveza with an increase in the share of gas reserves from 1 to 10 million tons of conventional fuel is shown. Certain difficulties have been identified in the issue of reliable determination of gas reserves in the limited fund of wells and large ranges of changes in calculated parameters. The determining significance of the value of gas reserves in calculating the forecast indicators of the development and technologies of their extraction is justified. It is established that increasing the degree of reliability of calculating gas reserves ensures the efficiency of its extraction, as well as the rational use of material and technical resources and financial capabilities of the enterprise. The advantages of such methods for determining gas reserves as the volume method, the material balance method, and static models are disclosed. A specific description of each of these methods and their application for calculating gas reserves at the Northern Guzar field is given.

Monitoring the composition of gas condensate well streams based on samples taken from multiphase flow meters

The article highlights the relevance of reliable estimation of the composition and properties of reservoir gas during the development of gas condensate fields and the complexity of the task for reservoirs containing zones of varying condensate content. The authors have developed a methodology that allows monitoring the composition of gas condensate well streams of similar reservoirs. There are successful examples of the approach applied in Achimov gas condensate reservoirs at the Urengoy oil and gas condensate field. The proposed approach is based on the use of the so-called fluid factors, which are calculated on the basis of the known component compositions of various flows of the studied hydrocarbon system. The correlation between certain "fluid factors" and the properties of reservoir gas (usually determined by more labor-consuming methods) allows one to quickly obtain important information necessary to solve various development control tasks.

Experimental Study on Enhanced Condensate Recovery by Gas Injection in Yaha Condensate Gas Reservoir

A condensate gas reservoir is an important special oil and gas reservoir between oil reservoir and natural gas reservoir. Gas injection production is the most commonly used development method for this type of gas reservoir, but serious retrograde condensation usually occurs in the later stages of development. To improve the recovery efficiency of condensate oil in the middle and late stages of production of a condensate gas reservoir, a gas injection parameter optimization test study was carried out, taking the Yaha gas condensate reservoir in China as an example. On the premise that the physical experimental model and key parameters met the actual conditions of the formation, the injection method, injection medium, injection-production ratio, and other parameters of the condensate gas reservoir were studied. Research on the injection method showed that the top injection method had a lower gas-oil ratio and higher condensate oil recovery. The study of injection medium showed that the production effect of carbon dioxide (CO2) injection was the best injection medium, and the maximum recovery rate of condensate oil was 95.11%. The injection-production ratio study showed that the injection-production ratio was approximately inversely proportional to the recovery factor of condensate gas and approximately proportional to the recovery factor of condensate oil. When the injection-production ratio was 1 : 1, the maximum recovery rate of condensate oil was 83.31%. In summary, in the later stage of gas injection development of the Yaha condensate gas reservoir, it was recommended to choose the development plan of CO2 injection at the top position with an injection-production ratio of 1 : 1. This research can not only provide guidance for the later formulation of gas injection plans for Yaha condensate gas reservoirs but also lay a foundation for the research of gas injection migration characteristics of other condensate gas reservoirs.

Difference in pore structure characteristics between condensate and dry shale gas reservoirs: Insights from the pore contribution of different matrix components

A breakthrough in shale gas exploration was made in the lacustrine shale of Qianfoya Formation located in the Sichuan Basin; a gas analysis has shown that the reservoir therein is a condensate gas reservoir. To enhance the production of shale gas in the Sichuan Basin, reduce the exploration risk, and facilitate development, the marine dry gas shale of the Longmaxi Formation was selected as a comparison to analyze the pore structure characteristics of condensate and dry gas reservoirs. The results showed that the dry gas shale reservoir is mainly developed as organic matter (OM) pores, followed by clay mineral (CM) pores. In condensate gas shale reservoirs, the OM pores, CM pores, intragranular dissolution (ID) pores, and microfractures are common. In the dry gas shale reservoir, the surface porosities of the organic matter, clay minerals, brittle minerals, and microfractures were 10%–65%, 0%–23%, 0%–22%, and 0%–13%, respectively. Micropores were mainly provided by OM pores; mesopores were mainly provided by OM and CM pores; macropores were mainly provided by OM, CM, and ID pores. In the condensate gas shale reservoir, the surface porosities of the organic matter, clay minerals, brittle minerals, and microfractures were 0%–52%, 6%–34%, 0%–18%, and 0%–21%, respectively. Micro-mesopores were mainly provided by OM and CM pores, while macropores were mainly provided by CM pores and microfractures. Because of the influences of material composition, diagenetic evolution, and hydrocarbon generation at the burial depth, there were significant differences in the surface porosities of the matrix components and the distribution and proportions of the different pores between the dry and condensate gas shale reservoirs. This essentially led to a difference in the reservoir space.

Carbon-Negative Scenarios in High CO2 Gas Condensate Reservoirs

A gas condensate reservoir in Northern Croatia was used as an example of a CO2 injection site during natural gas production to test whether the entire process is carbon-negative. To confirm this hypothesis, all three elements of the CO2 life cycle were included: (1) CO2 emitted by combustion of the produced gas from the start of production from the respective field, (2) CO2 that is separated at natural gas processing plant, i.e., the CO2 that was present in the original reservoir gas composition, and (3) the injected CO2 volumes. The selected reservoir is typical of gas-condensate reservoirs in Northern Croatia (and more generally in Drava Basin), as it contains about 50% CO2 (mole). Reservoir simulations of history-matched model showed base case (production without injection) and several cases of CO2 enhanced gas recovery, but with a focus on CO2 storage rather than maximizing hydrocarbon gas production achieved by converting a production well to a CO2 injection well. General findings are that even in gas reservoirs with such extreme initial CO2 content, gas production with CO2 injection can be carbon-negative. In almost all simulated CO2 injection scenarios, the process is carbon-negative from the time of CO2 injection, and in scenarios where CO2 injection begins earlier, it is carbon-negative from the start of gas production, which opens up the possibility of cost-effective storage of CO2 while producing natural gas with net negative CO2 emissions.

Robust hybrid machine learning algorithms for gas flow rates prediction through wellhead chokes in gas condensate fields

Condensate reservoirs are the most challenging hydrocarbon reservoirs in the world. The behavior of condensate gas reservoirs regarding pressure and temperature variation is unique. Adjusting fluid flow rate through wellhead chokes of condensate gas wells is critical and challenging for reservoir management. Predicting this vital parameter is a big step for the development of condensate gas fields. In this study, a novel machine learning approach is developed to predict gas flow rate (Qg) from six input variables: temperature (T); upstream pressure (Pu); downstream pressure (Pd); gas gravity (γg); choke diameter (D64) and gas–liquid ratio (GLR). Due to the absence of accurate recombination methods for determining Qg, machine learning methods offer a functional alternative approach. Four hybrid machine learning (HML) algorithms are developed by integrating multiple extreme learning machine (MELM) and least squares support vector machine (LSSVM) with two optimization algorithms, the genetic algorithm (GA) and the particle swarm optimizer (PSO). The evaluation conducted on prediction performance and accuracy of the four HML models developed indicates that the MELM-PSO model has the highest Qg prediction accuracy achieving a root mean squared error (RMSE) of 2.8639 Mscf/d and a coefficient of determination (R2) of 0.9778 for a dataset of 1009 data records compiled from gas-condensate fields around Iran. Comparison of the prediction performance of the HML models developed with those of the previous empirical equations and artificial intelligence models reveals that the novel MELM-PSO model presents superior prediction efficiency and higher computational accuracy. Moreover, the Spearman correlation coefficient analysis performed demonstrates that D64 and GLR are the most influential variables in the gas flow rate for the large dataset evaluated in this study.

Technology Focus: Field Development (September 2021)

The digital transformation that began several years ago continues to grow and evolve. With new advancements in data analytics and machine-learning algorithms, field developers today see more benefits to upgrading their traditional development work flows to automated artificial-intelligence work flows. The transformation has helped develop more-efficient and truly integrated development approaches. Many development scenarios can be automatically generated, examined, and updated very quickly. These approaches become more valuable when coupled with physics-based integrated asset models that are kept close to actual field performance to reduce uncertainty for reactive decision making. In unconventional basins with enormous completion and production databases, data-driven decisions powered by machine-learning techniques are increasing in popularity to solve field development challenges and optimize cube development. Finding a trend within massive amounts of data requires an augmented artificial intelligence where machine learning and human expertise are coupled. With slowed activity and uncertainty in the oil and gas industry from the COVID-19 pandemic and growing pressure for cleaner energy and environmental regulations, operators had to shift economic modeling for environmental considerations, predicting operational hazards and planning mitigations. This has enlightened the value of field development optimization, shifting from traditional workflow iterations on data assimilation and sequential decision making to deep reinforcement learning algorithms to find the best well placement and well type for the next producer or injector. Operators are trying to adapt with the new environment and enhance their capabilities to efficiently plan, execute, and operate field development plans. Collaboration between different disciplines and integrated analyses are key to the success of optimized development strategies. These selected papers and the suggested additional reading provide a good view of what is evolving with field development work flows using data analytics and machine learning in the era of digital transformation. Recommended additional reading at OnePetro: www.onepetro.org. SPE 203073 - Data-Driven and AI Methods To Enhance Collaborative Well Planning and Drilling-Risk Prediction by Richard Mohan, ADNOC, et al. SPE 200895 - Novel Approach To Enhance the Field Development Planning Process and Reservoir Management To Maximize the Recovery Factor of Gas Condensate Reservoirs Through Integrated Asset Modeling by Oswaldo Espinola Gonzalez, Schlumberger, et al. SPE 202373 - Efficient Optimization and Uncertainty Analysis of Field Development Strategies by Incorporating Economic Decisions in Reservoir Simulation Models by James Browning, Texas Tech University, et al.

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.

Retrograde Gas Condensate Reservoirs: Reliable Estimation of Dew Point Pressure by the Hybrid Neuro-Fuzzy Connectionist Paradigm

AbstractThe dew point pressure (DPP) is a crucial thermodynamic property for gas reservoir performance evaluation, gas/condensate characterization, reservoir development and management, and downstream facility design. However, dew point pressure measurement is an expensive and time-consuming task; its estimation using the thermodynamic approaches has convergency problems, and available empirical correlations often provide high uncertainty levels. In this paper, the hybrid neuro-fuzzy connectionist paradigm is developed using 390 literature measurements. The adaptive neuro-fuzzy inference system (ANFIS) topology, including the training algorithm and cluster radius (radii), was determined by combining trial-and-error and statistical analyses. The hybrid optimization algorithm and radii = 0.675 are distinguished as the best characteristics for the ANFIS model. A high value of observed R2 = 0.97948 confirms the excellent performance of the designed approach for calculating the DPP of retrograde gas condensate reservoirs. Furthermore, visual inspections and statistical indices are employed to compare the ANFIS reliability and available empirical correlations. The results showed that the ANFIS model is more accurate than the well-known empirical correlations and previous intelligent paradigms in the literature. The designed ANFIS model, the best empirical correlation, and the most accurate intelligent paradigm in the literature present the absolute average relative deviation (AARD) of 1.60%, 11.25%, and 2.10%, respectively.

A workflow for flow simulation in shale oil reservoirs: A case study in woodford shale

In recent years, with new technologies of long horizontal wells and staged hydraulic fracturing, the development of unconventional oil and gas reservoirs (i.e., shale gas and shale oil) has gained significant momentum. Due to extremely low permeability, these unconventional formations cannot be produced economically without significant stimulation. In the current research, the workflow for shale reservoir history matching that can be used for other shale resources producing from either condensate or oil reservoirs is developed. Production data and well geometry data for nineteen wells were available in Woodford shale. During this work, using the available data, single well simulation models for all the individual wells were constructed and then models were tuned to match the historical data. It has been shown that the fracture half length, shear fracture distribution and the interaction between matrix and fractures should be captured. Also, the results showed that fracture half-length can be longer than 2,000 ft, but the permeability of the fracture is dependent on how far the fracture is from the well. It was found that for multiple well history matching, fracture half-length and the interaction between the wells are the most important factors. Using multiple history matched models, it was shown that multiple models with different fracture distributions could capture the historical data, but they exhibit different future predictions. Cited as: Sharifi, M., Kelkar, M., Karkevandi-Talkhooncheh, A. A workflow for flow simulation in shale oil reservoirs: A case study in woodford shale. Advances in Geo-Energy Research, 2021, 5(4): 365-375, doi: 10.46690/ager.2021.04.03

Hybrid machine learning algorithms to predict condensate viscosity in the near wellbore regions of gas condensate reservoirs

Gas condensate reservoirs display unique phase behavior and are highly sensitive to reservoir pressure changes. This makes it difficult to determine their PVT characteristics, including their condensate viscosity, which is a key variable in determining their flow behavior. In this study, a novel machine learning approach is developed to predict condensate viscosity in the near wellbore regions (μc) from five input variables: pressure (P), temperature (T), initial gas to condensate ratio (RS), gas specific gravity (γg), and condensate gravity (API). Due to the absence of accurate recombination methods for determining μc machine learning methods offer a useful alternative approach. Nine machine learning and hybrid machine learning algorithms are evaluated including novel multiple extreme learning machine (MELM), least squares support vector machine (LSSVM) and multi-layer perceptron (MLP) and each hybridized with a particle swarm optimizer (PSO) and genetic algorithm (GA). The new MELM algorithm has some advantages including 1) rapid execution, 2) high accuracy, 3) simple training, 4) avoidance of overfitting, 5) non-linear conversion during training, 6) no trapping at local optima, 6) fewer optimization steps than SVM and LSSVM. Combining MELM with PSO, to find the best control parameters, further improves its performance. Analysis indicates that the MELM-PSO model provides the highest μc prediction accuracy achieving a root mean squared error (RMSE) of 0.0035 cP and a coefficient of determination (R2) of 0.9931 for a dataset of 2269 data records compiled from gas-condensate fields around the world. The MELM-PSO algorithm generates no outlying data predictions. Spearman correlation coefficient analysis identifies that P, γg and Rs are the most influential variables in terms of condensate viscosity based on the large dataset studied.

Influence of geological reservoir heterogeneity on exploitation conditions of Garadagh field / underground gas storage (Azerbaijan)

Underground oil and gas reservoirs (formations) are characterized by spatial variability of their structure, material composition and petrophysical properties of its constituent rocks: particle size distribution, porosity, permeability, structure and texture of the pore space, carbonate content, electrical resistivity, oil and water saturation and other properties. When assessing development and exploitation conditions for underground gas storages, created in depleted underground oil and gas reservoirs, the inherited nature of the reservoir development should be taken into account. Therefore, identifying the features of variations in well productivity is a crucial task, solution of which can contribute to the creation of more efficient system for underground gas storage exploitation. The paper presents the findings of comparative analysis of spatial variations in well productivity during the exploitation of the Garadagh underground gas storage (Azerbaijan), created in the depleted gas condensate reservoir. An uneven nature of the variations in well productivity was established, which was connected with the reservoir heterogeneity (variations in the reservoir lithological composition and poroperm properties). The research was based on the analysis of spatial variations of a number of reservoir parameters: the reservoir net thickness, lithological composition and poroperm properties. The analysis of variations in the net thickness and poroperm properties of the VII horizon of the Garadagh gas condensate field was carried out based on the data of geophysical logging of about 40 wells and studying more than 90 core samples. The data on of more than 90 wells formed the basis for the spacial productivity variation analysis. The analysis of productivity variation in the space of well technological characteristics (based on data from 18 wells) in the Garadagh underground gas storage (UGS) was carried out through the example of the volume of cyclic gas injection and withdrawal in 2020–2021 season. The studies allowed revealing non-uniform spacial variations in the volumes of injected and withdrawn gas at the Garadagh UGS, created in the corresponding depleted gas condensate reservoir. The features of the UGS exploitation conditions are in good agreement with the features of the reservoir development conditions (variations in the well productivity). The inherited nature of the reservoir development and the underground gas storage exploitation is substantiated by the reservoir heterogeneity caused by the spatial variability of the reservoir lithological composition and poroperm properties. Assessing and taking into account the reservoir heterogeneity when designing underground gas storage exploitation conditions should be an important prerequisite for increasing UGS exploitation efficiency.

Procedure for Predicting the Indices of Development of Deep-Seated Gas–Condensate Reservoirs in a Depletion Regime from Wellhead Data

Procedure for Predicting the Indices of Development of Deep-Seated Gas–Condensate Reservoirs in a Depletion Regime from Wellhead Data

Technique Proves Effective in Remediation of Phase-Trapping Damage in Tight Reservoirs

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 202996, “An Efficient Treatment Technique for Remediation of Phase-Trapping Damage in Tight Carbonate Gas Reservoirs,” by Rasoul Nazari Moghaddam, SPE, Marcel Van Doorn, and Auribel Dos Santos, SPE, Nouryon, prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually 9–12 November. The paper has not been peer reviewed. Aqueous- and hydrocarbon-phase trapping are among the few formation-damage mechanisms capable of significant reduction in effective permeability (sometimes near 100%). In this study, a new chemical treatment is proposed for efficient remediation of water- or hydrocarbon-phase-trapping damage in low-permeability porous media. The method proposed here is cost-effective and experimentally proved to be efficient and long-lasting. Such a chemical treatment is recommended to alleviate gas flow in tight gas with aqueous-trapping-damaged zones or in gas condensate reservoirs with condensate-banking challenges. Introduction Remediation techniques for existing aqueous- or hydrocarbon-phase-trapping damage can be categorized into two approaches: bypassing the damaged region by direct penetration techniques and trapping-phase removal. In the former category, the damaged zone is bypassed by creation of high-conductance flow paths through hydraulic fracturing or acidizing. However, for tight and ultratight formations, conventional acidizing may not be feasible (mostly because of injectivity difficulties). In the second category, direct removal and indirect removal have been used, but usually are seen as short-term solutions. The fluid used in the proposed treatment is comprised of a nonacidic chelating agent. The treatment fluid can be injected safely into the damaged region, while a slow reaction rate allows it to penetrate deep into the formation. In the proposed treatment, the mechanism is the permanent enlargement of pore throats where the nonwetting phase has the most restriction (to overcome the capillary forces) to pass through. In fact, phase trapping or capillary trapping occurs inside the pore structure when viscous forces are not strong enough to overcome the capillary pressure. The experimental setup and method are detailed in the complete paper. Results and Discussion Treatment of Outcrop Samples: Lueder Carbonate. The performance of the proposed treatment fluid initially was investigated on two outcrop core samples from the Lueder carbonate formation. The first treatment was conducted on the Le1 core sample with an absolute permeability of 1.46 md. To establish trapped water in the core, 10 pore volumes (PV) of 5 wt% potassium chloride brine were injected followed by nitrogen (N2) gas displacement. Then, to achieve irreducible water saturation, N2 was injected at a rate of 2 cm3/min for at least 100 PVs until no further water was produced. Next, the effective gas permeability was measured while N2 was injected at approximately 0.2 cm3/min. The effective gas permeability was obtained as 0.042 md. The trapped water saturation was also calculated (from the core weight) as 77.7%. After all pretreatment measurements, the core was loaded into the core holder for the treatment. The treatment injections with preflush and post-flush were performed at 130°C. In this test, 0.5 PV of treatment fluid was injected.

Study of the efficiency of nitrogen application for regulating the front of formation water movement in conditions of the manifestation of a water drive

Using modern tools of hydrodynamic modeling, a study of the process of nitrogen injection into gas-condensate reservoirs near the initial gas-bearing contour was carried out in order to regulate the front of formation of water movement in conditions of the manifestation of a water drive. Calculations of the main technological indicators of the development of a productive reservoir were carried out for the duration of the nitrogen injection period at the level of 5, 6, 8, 10, 12, 14 months. The simulation results show that the injection of non-hydrocarbon gas ensures that the reservoir pressure in the reservoir is maintained at a higher level compared to depletion development. At the same time, it is possible to create additional hydrodynamic and filtration barriers at the initial gas-water contact, due to which there is an effective blocking of the flow of formation water into gas-saturated horizons. According to the results of the studies, it was found that in the case of the introduction of the nitrogen injection technology, significantly smaller volumes of produced water are produced in comparison with the development for depletion. The use of nitrogen as a pumping agent makes it possible to slow down the process of movement of the gas-water contact and prevent trapping of the residual reserves of natural gas. On the basis of the calculation results, the optimal value of the duration of the nitrogen injection period, beyond which the gas recovery coefficient changes insignificantly, was established. The optimum value for the duration of the injection period is 8.04 months. The predicted gas recovery factor for the optimum period of nitrogen injection is 58.11 %. When developing a gas condensate reservoir for depletion, the final gas recovery factor is 34.6 %. The results of the studies carried out indicate a high technological efficiency of nitrogen injection at the initial gas-water contact in order to regulate the process of formation water inflow into gas condensate reservoirs and increase the final gas recovery.