Tight Reservoirs Research Articles

A novel deep learning method based on 2-D CNNs and GRUs for permeability prediction of tight sandstone

The accurate calculation of tight sandstone reservoir permeability is crucial for optimizing production and maximizing natural gas recovery. Traditional physical model-based permeability calculation methods heavily rely on core experimental parameters. However, petrophysical experiments are costly, prompting the development of fast and reliable reservoir permeability prediction methods. In this paper, a novel deep learning model that combines two-dimensional convolutional neural network (2-D CNN) model and gated recurrent neural network is proposed to predict tight sandstone reservoir permeability. The 1-D conventional well logs data is converted into the 2-D geological feature map to fit the model's input dimension. The TimeDistributed layer wrapping technology is used to couple the 2-D CNN and GRU to extract comprehensive features of geological feature maps. By training the model, a depth nonlinear mapping between the spatial and temporal features in the well logs data and permeability is established. The model is divided into two subnetworks, 2-D CNNs and GRUs, which are used to compare and analyze the functions of different modules in the proposed model. Additionally, two traditional machine learning algorithms, SVM and XGBoost, are also introduced as comparison models. Four regression evaluation metrics are used to quantify the predictive performance of different models. The test results in a blind well demonstrate that the proposed method outperforms the comparison models in predicting permeability, with a coefficient of determination (R2) of 0.9305, a root mean square error (RMSE) of 0.0895, a mean squared error (MSE) of 0.0080, and a mean absolute error (MAE) of 0.0725. This model can provide insight into the petrophysical characteristics of reaction reservoirs based on conventional well logs data and can accurately estimate reservoir permeability under limited core data, which has great application potential in improving the exploration accuracy of unconventional oil and gas resources.

Analysis of the Influence Mechanism of Nanomaterials on Spontaneous Imbibition of Chang 7 Tight Reservoir Core

This study investigates the impact of nanomaterials on different surfactant solutions. By measuring the parameters (including emulsification property, zeta potential, DLS, CA, IFT, etc.) of imbibition liquid system with nanoparticles and without nanoparticles, combining with imbibition experiments, the law and mechanism of improving the imbibition recovery of nanomaterials were obtained. The findings demonstrate that the nano-silica sol enhances the emulsification and dispersion of crude oil in the surfactant system, resulting in smaller and more uniform particle sizes for emulsified oil droplets. Non-ionic surfactant AEO-7 has the best effect under the synergistic action of nanomaterials. Zeta potential and DLS tests also showed that AEO-7 exhibits smaller particle sizes due to their insignificant electrostatic interaction with nanoparticles. Furthermore, the addition of nanomaterials enhances the hydrophilicity of core and reduces the interfacial tension. Under the synergistic action of nanoparticles, AEO-7 still showed the best enhanced core hydrophilicity (CA 0.61° after imbibition) and the lowest interfacial tension (0.1750 mN·m−1). In the imbibition experiment, the imbibition recovery of the system with nanomaterials is higher than that of the non-nanomaterials. The mixed system of AEO-7 and nano-silica sol ZZ-1 has the highest imbibition recovery (49.27%). Combined with the experiments above, it shows that nanomaterials have a good effect on enhancing the recovery rate of tight core, and the synergistic effect of non-ionic surfactant AEO-7 with nanomaterials is the best. Moreover, nanomaterials reduce adhesion work within the system while improving spontaneous imbibition recovery. These findings provide theoretical guidance for better understanding the mechanism behind nanomaterial-induced imbibition enhancement as well as improving tight oil’s imbibition recovery.

Post-mining related reactivation potential of faults hosted in tight reservoir rocks around flooded coal mines, eastern Ruhr Basin, Germany

The cessation of hard coal mining in the Ruhr Basin in 2018 marked the region's transition to the post-mining phase. Controlled mine water rebound induces changes in the subsurface stress conditions, as pore pressure increases locally. Presently, mine water rebound is observed in the eastern Ruhr Basin (water province “Haus Aden”) along with associated microseismicity. Furthermore, post-mining challenges might comprise the potential risk of fault reactivation, which is addressed in this study by conducting a fault slip assessment. Based on subsurface coal seam mapping data, a 3D structural model for the NE part of the “Haus Aden” water province has been constructed to serve as the basis for identifying the most vulnerable fault trends and types of the structural inventory. Slip tendency analysis, considering normal faulting conditions, revealed NW-SE to NNW-SSE trending normal faults to be most susceptible to reactivation. Probabilistic fault slip assessment, focused on NW-SE to NNW-SSE trending normal faults mapped within the “Heinrich-Robert” colliery, show no fault reactivation potential for a mine water rebound up to a level of 640 m below ground. Assuming hydrostatic conditions in the vicinity of the faults, friction coefficients are only partially exceeded for high differential stresses. In addition, a novel workflow is used to model the spatial variability of the frictional fault strength as input for a fault stability analysis, exemplified for a selected NNW-SSE trending normal fault. For considering hydrostatic pore pressure, results show that the fault consists mainly of stable, but also unstable, horizontally elongated patches. These findings question the conventional simplified approach of using a single constant friction coefficient for fault stability analysis.

Pore structure characterization and its influence on aqueous phase trapping damage in tight gas sandstone reservoirs.

Aqueous phase trapping (APT), which is one of the most prominent damages, seriously restricts the natural gas production in tight gas sandstone with low permeability. Pore size and microscopic pore structures are the most important factors to determine the water blocking damage. In this paper, 9 core samples from tight gas sandstone with various physical properties were employed, and the pore size distribution (PSD) of the core samples were investigated by high pressure mercury intrusion tests (HPMI). Results showed that the porosity of core samples ranges from 5.68% to 13.7%, and the permeability ranges from 0.00456 to 7.86 mD, which is a typical tight reservoir with strong heterogeneity. According to the HPMI capillary curve, the cores can be divided into two types: Type I and Type II, and the pore sizes of type I are larger than that of type II. Fractal distributions were obtained using HPMI data to further determine the pore structure characteristics of tight reservoirs. The pore structures of tight sandstones display the multifractal fractal feature: D1 corresponding to macro-pores, and D2 corresponding to fractal dimension of micro-pores. Furthermore, APT damage was determined by the permeability recovery ratios (Kr) after gas flooding tests. The correlation of Kr and PSD and fractal dimensions were jointly analyzed in tight gas sandstone. Although positive correlations between pore size parameters and the permeability recovery ratios were observed with relatively weak correlations, for those core samples with very close permeability, pore size parameters (both permeability and PSD) is inadequate in clarifying this damage. The fractal dimension can well describe the complexity and heterogeneity of flow channels in pores, which can become the determining factor to distinguish the flow capacity of tight sandstone. The D2 for samples of type I and type II exhibited a good negative relation with Kr with a correlation coefficient of 0.9878 and 0.7723, respectively. The significance of this finding is that for tight gas sandstone, fractal dimensions, especially the small pore fractal dimension (D2), can be used to predict the possible APT damage very well.

Preparation and performance evaluation of microencapsulated acid used for gel breaking of fracturing fluid in low-temperature reservoirs

In low-temperature reservoirs, the generation of free radicals by oxidizing breakers is challenging, and the alkaline fracturing fluid generally inhibits enzyme’s activity, making it difficult to break down the fracturing fluid. Previous studies have demonstrated that acids can consume borate ions and disrupt crosslinking nodes even at low temperatures, thereby efficiently breaking gels. Thus, microencapsulated oxalic acid (OA) was prepared via a coacervation method, using ethyl cellulose (EC) or acrylonitrile–butadiene–styrene (ABS) as shell materials with varying initiator viscosities and core–shell ratios. An optimal microcapsule MC[OA/ABS-2000-1:2] was determined based on the coating effect, productivity, encapsulation rate, and release performance. The test results of FT-IR and TGA together proved that the optimal microcapsule was composed of 24.4 and 74.8 % of OA and ABS, respectively. Scanning electron microscopy and laser particle size analysis were employed to characterize the optimal microcapsule with an average particle size of 402.8 μm, which exhibited a high degree of sphericity. Because of their porous shells, these microcapsules exhibited sustained slow-release characteristics. Evaluations conducted at temperatures of 30 and 50 ℃, simulating the tight sandstone reservoir conditions in the Ordos basin, revealed that delayed gel breaking could be achieved within approximately 2.5 h at low temperatures by adding only 0.25 % of the optimal microcapsule. Furthermore, increasing the temperature and dosage of microcapsules resulted in shorter breaking times. Additionally, a synergistic breaking effect was observed between the enzymes and the prepared microencapsulated acid. Thus, by optimizing the microcapsule dosage based on the reservoir temperature and fracturing construction pumping time, employing the two breakers together can achieve delayed and complete gel breaking at the desired time. In conclusion, the microencapsulated acid prepared in this study has significant potential as a gel breaker for fracturing fluids in low-temperature reservoirs.

Tight carbonate reservoir evaluation case study based on neural network assisted fracture identification and analytic hierarchy process

Comprehensive evaluation of reservoirs is an important link in gas reservoir exploration and development. The evaluation of tight carbonate reservoirs often focuses on the characteristics of porosity and permeability, ignoring the important factor of fractures, also the quantitative evaluation of reservoirs is relatively few. It is difficult to identify fractures and evaluate the reservoir factors qualitatively and quantitatively. Herein, the sedimentary microfacies and microporosity of the tight carbonate reservoir of the Ma55 submember in the eastern Sulige area are comprehensively studied by casting thin section, rock physical property, and capillary pressure test data. The backpropagation (BP) neural network algorithm is used to identify and predict fractures. Finally, through the analytic hierarchy process, the above reservoir influencing factors are modeled and quantitatively analyzed for reservoir evaluation. The results show that the highest probability of fracture development in the central and northwest areas of the study area can reach 0.92. The accuracy of the BP neural network model in identifying cracks can reach 80%, which is reliable and effective compared with the conventional logging identification method. Reservoirs can be classified into four types according to their quality. The synthetic weights of porosity, permeability and fracture development probability are 0.2, 0.2 and 0.216 respectively, which are the three most important evaluation parameters. This study improves the accuracy of fracture identification and prediction of tight reservoirs in comprehensive reservoir evaluation, which provides guidance and scheme for more detailed exploration and development of tight carbonate reservoirs.

Pore‐throat structure and fractal characteristics of tight gas sandstone reservoirs: A case study of the second member of the Upper Triassic Xujiahe Formation in Zhongba area, western Sichuan depression, China

Pore‐throat structure is a key factor that influences the storage and fluid flow capacity of tight sandstone reservoirs. Taking the tight sandstone reservoir of Xu2 Fm in Zhongba area as an example, the reservoir quality, pore‐throat type and pore size distribution of tight sandstone in the study area were described by casting thin section, scanning electron microscope and high‐pressure mercury injection test. In order to quantitatively characterize the complexity and heterogeneity of pore‐throat structure, fractal analysis was performed using mercury saturation and pore size data. This study mainly reveals the relationship between the geometric shape characteristics and fractal dimension of the binary pore structure of ultra‐low permeability tight sandstone and clarifies the influence of different scale pore throats on reservoir physical properties. The results indicate that the physical properties of the reservoir in the study area are poor, the pores are mainly intergranular pores and dissolution pores, the throat is flake and necked and the pore size distribution range is large. The fractal curve obtained by the mercury saturation method shows a significant turning point, and the pore‐throat system is divided into two types: small‐scale and large‐scale. The fractal dimension of large‐scale pore throat is greater than the three‐dimensional Euclidean space dimension, which does not conform to the fractal theory. The fractal dimension of small‐scale pore throat is closely related to the pore‐throat structure and has obvious fractal characteristics. The geometric shape of binary pore‐throat structure in tight sandstone is the main factor affecting the difference of fractal dimension. The development of small pores in sandstone is positively correlated with the total porosity, but its contribution to permeability is relatively low. The physical properties of tight sandstone are mainly controlled by the development degree of large‐scale pore throat.

Pore Pressure Prediction for High-Pressure Tight Sandstone in the Huizhou Sag, Pearl River Mouth Basin, China: A Machine Learning-Based Approach

A growing number of large data sets have created challenges for the oil and gas industry in predicting reservoir parameters and assessing well productivity through efficient and cost-effective techniques. The design of drilling plans for a high-pressure tight-sand reservoir requires accurate estimations of pore pressure (Pp) and reservoir parameters. The objective of this study is to predict and compare the Pp of Huizhou Sag, Pearl River Mouth Basin, China, using conventional techniques and machine learning (ML) algorithms. We investigated the characteristics of low-permeability reservoirs by observing well-logging data sets and cores and examining thin sections under a microscope. In the reservoir zone, the average hydrocarbon saturation is 55%, and the average effective porosity is 11%. The tight sandstone reservoirs consist of fine- to extremely fine-grained argillaceous feldspathic sandstone. The mean absolute error for reservoir property prediction is 1.3%, 2.2%, and 4.8%, respectively, for effective porosity, shale volume, and water saturation. Moreover, the ML algorithm was employed to cross-check the validity of the prediction of Pp. Combining conventional and ML techniques with the core data demonstrates a correlation coefficient (R2) of 0.9587, indicating that ML techniques are the most effective in testing well data. This study shows that ML can effectively predict Pp at subsequent depths in adjacent geologically similar locations. Compared to conventional methods, a substantial data set and ML algorithms improve the precision of Pp predictions.

Gas–water percolation of tight sandstone reservoirs with different pore types in the Ordos Basin

To investigate the percolation mechanism of tight sandstone reservoirs, qualitative and quantitative methods are applied to analyze the pore structure of the Ordos Basin through scanning electron microscopy and high-pressure mercury injection. Based on gas–water relative permeability data and the visualization of real sandstone models, a gas–water displacement experiment was carried out to simulate the percolation mechanism and fluid distribution of different pore types. The results show that: ① The percolation of different pore types varies greatly, and the irreducible water saturation decreases when the reservoir properties improve. The relative permeability of gas at an irreducible water saturation increases, the width of the two-phase percolation area increases, and the percolation ability is enhanced as the reservoir properties improve. ② The gas–water displacement mode changes from fingering to uniform displacement with the improvement of pore type, which is beneficial to the formation of effective reservoirs filled with natural gas under the same hydrocarbon generation conditions. ③ The time required for the pressure relief of samples with good reservoir properties is short, and the recovery is higher with the improvement of pore type. ④ The residual water in samples with a poor pore type increases, which decreases the relative permeability of gas and recovery. A reasonable development pattern should be carried out, and the production pressure difference should be strictly controlled to maximize productivity. This study provides theoretical guidance for the development of tight sandstone reservoirs in the Ordos Basin.

Pore throat distributions and movable fluid occurrences in different diagenetic facies of tight sandstone reservoirs in the Triassic Chang 6 reservoirs, Wuqi Area, Ordos Basin, China

The 6th member of the Triassic Yanchang Formation, hereafter referred to as Chang 6 reservoir, in the Wuqi area of the Ordos Basin presents formidable obstacles for efficient tight oil development. This reservoir is known for its tight lithology, strong heterogeneity, inadequate oil saturation, and abnormally low reservoir pressure, which collectively contribute to the highly differentiated mobility of tight oil within the formation. To overcome these challenges, a comprehensive understanding of the factors influencing oil mobility is essential. This study investigates the occurrence characteristics of movable fluids in different diagenetic facies and the corresponding influential factors by employing various microscopic experiments, including high-pressure mercury intrusion, constant-rate mercury intrusion, nuclear magnetic resonance test, scanning electron microscopy, pore-casted thin section analysis, and X-ray diffraction measurement. There is a weaker correlation between the pore-throat radius ratio and the movable fluid saturation in reservoirs of various diagenetic facies (R2 = 0.6104), whereas there is a stronger correlation between movable fluid saturation and throat radius (R2 = 0.9415). Among the seven types of diagenetic facies, chlorite membrane cementation-intergranular pore facies (Facies I) and chlorite and illite membrane cementation-intergranular pore facies (Facies II) have the best-developed throats and the highest coordination number. Illite cementation-intergranular pore facies (Facies III) and illite and chlorite membrane cementation-dissolution facies (Facies IV) demonstrate smaller pore-throat radii and moderate to poor reservoir connectivity. The other three facies, namely illite cementation-dissolution facies (Facies V), illite cementation facies (Facies VI), and carbonate tight cementation facies (Facies VII) exhibit underdeveloped pore structures and lower recovery rates. Pore-throat radius emerges as the principal factor influencing reservoir permeability and storage capacity. The distribution of favorable diagenetic facies is influenced by depositional environments, diagenetic processes, and microscopic pore-throat characteristics. This study significantly enhances our understanding of the differential occurrence characteristics of fluids in different diagenetic facies in the Chang 6 reservoir, providing valuable insights for future exploration and production endeavors aimed at optimizing oil recovery in tight sandstone reservoirs.

Gas-bearing prediction in tight sandstone reservoirs based on multinetwork integration

Tight sandstone reservoir gas is an important component of unconventional natural gas exploration and production in China. However, tight sandstone reservoirs have the characteristics of poor lateral continuity, strong vertical heterogeneity, complex lithology, and large changes in physical properties, which means traditional oil and gas evaluation sometimes suffers from low accuracy. Therefore, a method for predicting the gas content of tight sandstone reservoirs is developed. This method selects seismic attributes through Pearson coefficients, combines multiple attribute information, and inputs it into a deep neural network. This study constructed MultipleNet by combining a convolutional neural network, a bidirectional gated neural unit network, and a self-attention mechanism. This network takes advantage of the complementary advantages of the preceding network modules and can more effectively mine information on various seismic attributes and improve gas-bearing prediction accuracy. This method is applied to actual data from a tight sandstone gas exploration area in the Sichuan Basin. Experimental results indicate that the results of well-side predictions using this method are consistent with well data, providing a new approach and perspective for predicting gas bearing in tight sandstone reservoirs.

A Novel Oriented Perforation Approach for Fracturing Deep and Tight Reservoirs

A Novel Oriented Perforation Approach for Fracturing Deep and Tight Reservoirs

A novel algorithm for asphaltene precipitation modeling in shale reservoirs with the consideration of capillary pressure during the CCUS processes

Tight and shale reservoirs have markedly expanded their role in global oil and gas production. However, the overall recovery from these reservoirs is suboptimal, leaving much of the shale oil unrecovered. CO2 flooding is a promising enhanced oil recovery (EOR) technique that can improve oil extraction and simultaneously facilitate carbon capture, utilization, and storage (CCUS). However, this method presents challenges, notably the precipitation and deposition of asphaltene, which risks plugging the nanoporous structure characteristic of shale reservoirs. Given that the nanopore sizes in these reservoirs align closely with asphaltene particle dimensions, the risk of pore and throat blockages during gas injection is pronounced. Although various asphaltene precipitation models have been proposed, there is still a lack of robust algorithms accounting for the substantial influence of capillary pressure on asphaltene precipitation in these nanopores. In this study, a novel three-phase vapor–liquid-asphaltene equilibrium calculation algorithm coupled with capillary effect is developed. The algorithm is first validated by comparing with the experimental data of the Px phase diagram and asphaltene precipitation amount. The validated algorithm is then used to conduct example calculations to demonstrate the robustness of the new algorithm and to examine the impact of capillarity on the three-phase vapor–liquid-solid (VLS) equilibria. Computation results show that capillary pressures in nanopores substantially modify the three-phase VLS equilibria, causing shifts in saturation pressure and influencing asphaltene precipitation. Generally, asphaltene precipitation in nanopores occurs at a lower pressure and gas injection concentration. The smaller pore sizes intensify these effects, but the impact diminishes as pressure increases. Additionally, the gas composition also greatly affects asphaltene precipitation. The results reveal that this new algorithm is robust across different conditions, offering an innovative approach that reliably predicts asphaltene precipitation considering the effect of capillary pressures, paving the way for improved EOR and CCUS in shale reservoirs.

Mathematical modeling of mass transfer in CO2 injection for confined fluids at near-miscible condition

Complex interaction between fluid and solid in tight formations leads to capillary confinement and interface slip. Mass transfer between oil and CO2 in CO2 flooding is essential to understand the flow complexity. Therefore, the objective of this work is to propose a comprehensive model to analyze the mass transfer during CO2 injection in the confined fluids. The modified Peng-Robinson equation of state considering the fluid-wall interaction and adsorption was established to calculate the properties of hydrocarbons and CO2. Relative permeability for the near-miscible state was then estimated using the new relative permeability model with corner flow effect. Predicted results agree well with the experimental observations. Afterwards, it was integrated with a one-dimension mathematical model to analyze the physical mechanisms of CO2 flooding in tight reservoirs. Results indicate that nanoconfinement increases the relative permeability at near-miscible condition, and confined fluid is more likely to be miscible than the bulk fluid. Additionally, nanoconfinement can reduce the velocity of CO2 front and increase the breakthrough time of CO2, which is favorable to improve the efficiency of CO2 flooding. This model provides a deep understanding of mass transfer between CO2 and hydrocarbons, and it can be integrated with compositional simulators to solve the field-scale cases including the microscale mechanism of tight reservoirs.

Effects of Geo-Stress and Natural Fracture Strength on Hydraulic Fracture Propagation in a Deep Fractured Tight Sandstone Reservoir.

Hydraulic fracturing technology has been widely used in the tight reservoir reconstruction. Unfortunately, with the deepening of mining depth and the increase of geo-stress, the propagation mechanism of medium-pressure fractures in the reservoir is significantly different from that of conventional shallow reservoirs. Based on the combined finite discrete element method, this paper conducts numerical simulation research on deep tight sandstone reservoirs in the west. The discrete fracture network modeling method is used to establish a tight sandstone reservoir model with natural bedding, and the influence of geo-stress difference and natural fracture strength on hydraulic fracture propagation law in a high geo-stress environment is discussed in detail. The results show that the difference between geo-stress and the strength of natural fractures has a significant effect on the shape and expansion of hydraulic fractures under the high geo-stress conditions. The greater the difference in ground stress, the more obvious the tendency of the main fractures of the reservoir, and the shorter the branch fractures. With the increase of natural fracture strength, the changes in propagation pressure, fracture length, area, and width, which can be fitted with a linear function with a goodness of fit as high as 0.99. In addition, the morphological results of hydraulic fractures in the simulation are not only affected by the constitutive parameters of the model but also may be affected by the randomness of the natural fracture network, thus, showing a certain degree of dispersion. Therefore, it is extremely necessary to build a reservoir fracturing model in a specific area based on more detailed geological monitoring data to guide actual construction. The above achievements have certain reference significance for the field operation of deep tight sandstone reservoirs.

Analyzing the Microscopic Production Characteristics of CO2 Flooding after Water Flooding in Tight Oil Sandstone Reservoirs Utilizing NMR and Microscopic Visualization Apparatus

The microscopic pore structure of tight sandstone reservoirs significantly influences the characteristics of CO2 flooding after water flooding. This research was conducted using various techniques such as casting thin sections, high-pressure mercury injection, scanning electron microscopy, nuclear magnetic resonance (NMR) testing, and a self-designed high-temperature and high-pressure microscopic visualization displacement system. Three types of cores with different pore structures were selected for the flooding experiments and the microscopic visualization displacement experiments, including CO2 immiscible flooding, near-miscible flooding, and miscible flooding after conventional water flooding. The characteristics of CO2 flooding and the residual oil distribution after water flooding were quantitatively analyzed and evaluated. The results show the following: (1) During the water flooding process, the oil produced from type I and type III samples mainly comes from large and some medium pores. Oil utilization of all pores is significant for type II samples. The physical properties and pore types have a greater impact on water flooding. Type I and II samples are more suitable for near-miscible flooding after water flooding. Type III samples are more suitable for miscible flooding after water flooding. (2) In CO2 flooding, oil recovery increases gradually with increasing pressure for all three types of samples. Type II core samples have the highest recovery. Before miscibility, the oil recovered from type I and type II samples is primarily from large pores; however, oil recovery mainly comes from medium pores when reaching miscibility. As for the type III samples, the oil produced in the immiscible state mainly comes from large and medium pores, and the enhanced oil recovery mainly comes from medium and small pores after reaching the near-miscible phase. (3) It can be seen from the microscopic residual oil distribution that oil recovery will increase as the petrophysical properties of the rock model improve. The oil recovery rate of near-miscible flooding after water flooding using the type II model is up to 68.11%. The oil recovery of miscible flooding after water flooding with the type III model is the highest at 74.57%. With increasing pressure, the proportion of flake residual oil gradually decreases, while the proportion of droplet-like and film-like residual oil gradually increases. Type II samples have a relatively large percentage of reticulated residual oil in the near-miscible stage.

An Experimental Investigation into the Role of an In Situ Microemulsion for Enhancing Oil Recovery in Tight Formations

Surfactant huff-n-puff (HnP) has been shown to be an effective protocol to improve oil recovery in tight and ultratight reservoirs. The success of surfactant HnP for enhanced oil recovery (EOR) process depends on the efficiency of the designed chemical formula, as the formation of an in situ microemulsion by surfactant injection is considered to be the most desirable condition for achieving an ultra-low interfacial tension during the HnP process. In this work, we conducted experimental studies on the mechanism of in situ microemulsion EOR in the Mahu tight oil reservoir. Salinity scan experiments were carried out to compare different surfactants with crude oil from the Mahu reservoir, starting with the assessment of surfactant micellar solutions for their ability to form microemulsions with Mahu crude oil and examining the interfacial characteristics. Subsequently, detailed micromodels representing millimeter-scale fractures, micron-scale pores, and nano-scale channels were utilized to study the imbibition and flowback of various surfactant micellar solutions. Observations of the in situ microemulsion system revealed the mechanisms behind the enhanced oil recovery, which was the emulsification’s near-miscibility effect leading to microemulsion formation and its performance under low-interfacial-tension conditions. During the injection process, notable improvements in the micro-scale pore throat heterogeneity were observed, which improved the pore fluid mobility. The flowback phase improved the channeling between the different media, promoting a uniform movement of the oil–water interface and aiding in the recovery of a significant amount of the oil phase permeability.

Characterization of the Gas-Bearing Tight Paleozoic Sandstone Reservoirs of the Risha Field, Jordan: Inferences on Reservoir Quality and Productivity

Characterization of the Gas-Bearing Tight Paleozoic Sandstone Reservoirs of the Risha Field, Jordan: Inferences on Reservoir Quality and Productivity

Pore-to-field scale modeling of residual gas trapping in tight carbonate underground gas reservoirs

The deep saline aquifer and depleted gas reservoirs are suitable candidates for CO2 storage. The estimation of residual gas and corresponding flowing behavior are major parameters for successful CO2 trapping in geological formations. In this article the residual gas trapping phenomenon in pore scale has been studied using Micro-CT images. In macro scale, the results of imbibition experiments on core plug samples have been considered to determine residual gas saturation (RGS) and the corresponding water relative permeability. In the field scale, pressure transient data in water leg has been used to determine the water relative permeability at RGS in a tight carbonate reservoir in Middle East. In the proposed workflow, an artificial intelligence approach is applied to determine absolute permeability profile. Then, a numerical dynamic single well model is built to calculate the water relative permeability. The comparison of core and pressure transient data shows that the absolute permeability and water relative permeability from core imbibition test are significantly overestimated while the results of gas-water simulation in pore scale confirmed the real field transient data. The proposed method can be used by industrial reservoir simulator to define rock/fluid interaction parameters in simulation of CO2 storage in depleted underground gas reservoirs.

Effective reservoir identification and sweet spot prediction in Chang 8 Member tight oil reservoirs in Huanjiang area, Ordos Basin

Abstract The Chang 8 reservoir of the Huanjiang Oilfield in the Ordos Basin is a tight sandstone reservoir with poor reservoir physical properties and uneven oil distribution. In this study, the effective reservoirs developed on a large scale under the condition of horizontal well volume fracturing technology of the Chang 8 Member was identified based on the data of core observation, experimental analysis, logging, oil test, and production dynamics, and the identification standard of effective reservoirs in terms of reservoir physical properties, oil content, and comprehensive logging characteristics of gas logging was established. This scheme allows for a thorough identification of the effective reservoirs for horizontal well development in tight sandstone reservoirs. The findings indicate that the study area’s tight oil resources can be successfully produced. The well logging results show that the oil-bearing property of sand bodies with oil stains is better than that of oil spots. The bottom limit of the acoustic wave time difference is 210 μs/m, the permeability is 0.03 mD, the porosity is 6.0%, the rock resistivity is 30 Ω m, and the total hydrocarbon gas measurement value exceeds five times the baseline. At the same time, the total oil thickness is greater than 6 m, and the thickness of a single sand body is above 4 m. We have defined the lower limit standard of high-efficiency reservoir of Chang 8 tight oil in L289 block of Huanjiang oilfield. According to the analysis of oil-bearing property, comprehensive logging display, and reservoir thickness, the geological “sweet spots” is optimized to provide reference for subsequent mining. Through comparative analysis, the rules and trends are found to provide a basis for selecting mining strategies. With the help of technical means such as numerical simulation and geological modeling, the prediction accuracy and decision-making effect are improved. By clarifying the lower limit standard of reservoir, optimizing geological “sweet spots” and avoiding risk areas, the mining efficiency is improved and the cost is reduced, which provides reference for similar oilfield development.