Reservoir Saturation Research Articles

Influence of reservoir water saturation on coalbed methane development: Based on multi-field coupling numerical simulation

Water in coal reservoirs serves as both the driving force of reservoir fluid and the resistance to coalbed methane (CBM) migration. However, the impact and control mechanism of water saturation on CBM development in the field have not been revealed yet. The evolution of reservoir dynamics and gas production rate under various initial water saturation conditions is simulated based on the COMSOL multiphysics numerical simulation software. The simulation results show that the reduction of initial water saturation can significantly enhance the effective permeability of the reservoir gas phase, which can be increased by up to 4764%. This increases the rate of gas production, which is the main mechanism for controlling production by water saturation in the reservoir. For high water saturation reservoirs, the positive effect of inter-well interference should be reasonably utilized, and high well network density should be used to rapidly increase gas-effective permeability. For low water saturation reservoirs, the negative effect of inter-well interference should be avoided, and low well network density should be used to increase the control of single well reserves.

A method for calculating saturation in tight sandstone reservoirs based on the dual porosity model

IntroductionWith the continuous development of exploration and development, tight sandstone reservoirs have become an essential field of oil and gas exploration. The tight sandstone reservoirs are characterized by complex lithology, poor pore structure, and strong heterogeneity, which bring great difficulties to formation evaluation by well logs. Especially, the accuracy of the Archie formula for calculating the water saturation of tight sandstone reservoirs containing fractures is not high, saturation evaluation faces greater challenges. Therefore, how to calculate the saturation of tight sandstone reservoirs more accurately is an urgent problem to be solved.MethodsIn this paper, the tight sandstone reservoirs of the Jurassic Ahe Formation in the Tarim Basin were taken as the research area. A saturation model that combines the effects of shale and fractures was proposed. Specifically, if the shale content is more than 20%, the Indonesian formula is used to calculate the saturation. If the shale content is less than 20%, the dual porosity model is adopted. Based on the rock resistivity and nuclear magnetic resonance (NMR) experiment results, the porosity and T2 logarithmic mean values are selected as influencing factors to calculate the key parameters of the dual porosity model.Results and DiscussionThe saturation of tight sandstone reservoirs in the Jurassic Ahe Formation of the Tarim Basin is calculated through the method proposed in this paper. The case study shows that the accuracy of the proposed method is higher than that of the Archie model. The method proposed in this paper demonstrates excellent adaptability in the quantitative evaluation of saturation for tight sandstone reservoirs.

The role of phase saturation in depressurization and CO2 storage in natural gas hydrate reservoirs: Insights from a pilot-scale study

The natural gas recovery and CO2 storage in natural gas hydrate (NGH) reservoirs is a promising integrated strategy for implementing clean energy production and CCUS. However, the fundamental characteristics (phase saturation) of NGH reservoirs on the feasibility and efficiency of the above-integrated processes remain unclear. In this study, we synthesized methane hydrate-bearing sediments (MHBS) with varying hydrate saturation (SH = 18–66 %) and aqueous saturation (SA = 7–92 %) at marine NGH conditions (T = 283.8 K, P = 11.0 MPa). The effect of phase saturation on depressurization-induced hydrate dissociation, and subsequent CO2 storage and hydrate restoration by CO2/N2 injection was investigated. The water-saturated MHBS with high SA can promote faster MH dissociation during the depressurization stage and prevent secondary hydrate formation, but a slower MH dissociation during the later stage due to slow heat transfer. A relatively high SH (> 63 %) results in sustained low temperatures due to insufficient heat supply slowing down MH dissociation. The CH4/CO2/N2 mixed hydrates (Mix-H) formation and CO2 storage in depleted MHBS after CO2/N2 injection initially increase and then decrease with post-mining SA (peak at SA = 54.5 %). The rate of Mix-H formation decreases as the post-mining SA increases. Higher pre-mining SH and CO2/N2 injection rate facilitates rapid gas phase mixing within the sediments, thereby improving the kinetics and homogeneity of Mix-H formation and hydrate-based CO2 storage efficiency. MHBS with relatively low SH and SA exhibit enhanced safety for the integrated process, offering reduced depressurization-induced sediment subsidence and increased hydrate restoration ratios (∼85 %) by Mix-H formation.

Fracturing and acoustic emission characteristics of saturated reservoir rocks under constant-amplitude-cyclic loading

Fracturing and acoustic emission characteristics of saturated reservoir rocks under constant-amplitude-cyclic loading

Evaluating the efficacy of water alternating gas injection technique in the upper jurassic hydrocarbon reservoirs, considering saturation pressure

A tertiary method of enhanced oil recovery (EOR) based on the watergas alternating injection process (WG) is examined in this article based on the ratio between saturation pressure and reservoir pressure. A hydrodynamic simulation of the WAG process was carried out using TEMPEST MORE software (version 7,1). Many hydrocarbon fields worldwide are currently experiencing declining production rates. However, by utilizing advanced technologies like alternate injection of water and associated petroleum gas, the final oil recovery factor (RF) can be significantly increased. To ensure successful water injection experiments in real fields, it is crucial to consider the ratio of saturation and reservoir pressures during injection. Any negligence in this regard can lead to failure of the experiments aimed at enhancing oil recovery through WAG application. The research examines two variations of reservoir system models with certainty. In the initial model, the saturation pressure is lower than the reservoir pressure, signifying an under-saturated state of the reservoir system containing dissolved gas. Consequently, when accompanying petroleum gas is introduced, it mixes with oil at precise thermobaric conditions. According to the second model, the reservoir is saturated with gas at a saturation pressure equivalent to the formation pressure. A thorough assessment indicates that the success of water alternating gas injection (WAG) is heavily influenced by the initial state of the reservoir. In situations where the reservoir is already saturated with gas, implementing water-gas stimulation may be ineffective as gas breakthroughs may occur rapidly. However, implementing WAG in saturated reservoirs can lead to a 1 – 8% rise in overall oil production, observable within 3 – 4 years, depending on the timing after waterflooding. Simultaneously, in the case of reservoirs with a low saturation pressure, which exhibits an undersaturated reservoir system, the implementation of water alternating gas injection can be seen as a viable approach for enhancing oil recovery. WAG is a proven method that confidently increases oil recovery up to 10% in undersaturated reservoirs compared to conventional waterflooding.

Experimental study on influencing factors of CO2 huff and puff effect in the tight water-bearing reservoir

The presence of a water phase in tight oil reservoirs is inevitable. To investigate the effect and influencing factors of the CO2 huff and puff technique on enhancing oil recovery in water-bearing tight oil reservoirs, CO2–water–crude oil phase experiments were conducted. The results reveal that the solubility of CO2 and the expansion coefficient of crude oil decrease with increasing water content in the system. Furthermore, CO2 huff and puff experiments were performed to analyze the effects of the number of huff and puff cycles, soaking time, soaking pressure, water saturation, and permeability on the performance of CO2 huff and puff under saturated/unsaturated water conditions. The experimental findings indicate that the oil recovery increases logarithmically with the number of huff and puff cycles. Increasing soaking time and soaking pressure gradually enhances recovery until reaching optimal soaking time and pressure. However, further increasing soaking time and pressure beyond the optimal values has minimal effect on recovery. Compared to the cases under unsaturated water conditions, the optimal number of huff and puff cycles, soaking time, and pressure are higher under saturated water conditions. Additionally, the CO2 huff and puff effect deteriorates with increasing water saturation in low permeability reservoirs.

Experimental study on the effect of hydrate saturation in reservoir on microwave heating hydrate decomposition gas production

Microwave heating technology is an effective method to promote the decomposition of hydrates, with hydrate saturation being an important parameter influencing this process. This study has synthesized natural gas hydrates with different saturations within a high-pressure reaction vessel to conduct experiments on the decomposition of natural gas hydrates by microwave heating. The reservoir temperature, gas production dynamics, and energy utilization rate are investigated for hydrate saturations of 30.26 %, 35.63 %, and 39.61 %, respectively. The results indicate that increasing hydrate saturation enhances the microwave penetration depth, which in turn elevates the reservoir temperature and accelerates hydrate decomposition. When the hydrate saturation increases from 30.26 % to 39.61 %, the gas production time decreases. Simultaneously, both the volume and rate of gas production increase, accompanied by enhanced energy utilization rate. When the hydrate saturation is 39.61 %, the experiment achieves an average gas production rate of 1.17 L/min, a total volume of 19.73 L, and an energy utilization rate of 2.716. The research results can promote the application of microwave heating technology in the development of hydrates.

Learning CO[formula omitted] plume migration in faulted reservoirs with Graph Neural Networks

Deep-learning-based surrogate models provide an efficient complement to numerical simulations for subsurface flow problems such as CO2 geological storage. Accurately capturing the impact of faults on CO2 plume migration remains a challenge for many existing deep learning surrogate models based on Convolutional Neural Networks (CNNs) or Neural Operators. We address this challenge with a graph-based neural model leveraging recent developments in the field of Graph Neural Networks (GNNs). Our model combines graph-based convolution Long-Short-Term-Memory (GConvLSTM) with a one-step GNN model, MeshGraphNet (MGN), to operate on complex unstructured meshes and limit temporal error accumulation. We demonstrate that our approach can accurately predict the temporal evolution of gas saturation and pore pressure in a synthetic reservoir with impermeable faults. Our results exhibit a better accuracy and a reduced temporal error accumulation compared to the standard MGN model. We also show the excellent generalizability of our algorithm to mesh configurations, boundary conditions, and heterogeneous permeability fields not included in the training set. This work highlights the potential of GNN-based methods to accurately and rapidly model subsurface flow with complex faults and fractures.

Method for Predicting Bound Water Saturation in Tight Sandstone Reservoirs Using Morphology and Fractal Models

The nuclear magnetic resonance T2 spectrum was used to identify the T2 cut-off value, which is the key to determining the irreducible water saturation of a reservoir. In this paper, the saturation and centrifugal T2 spectra of sandstone and coal samples were used to explore the correlation between each parameter and the T2 cut-off value, using a single fractal dimension, a multifractal dimension and a spectral morphology discrimination method. The conclusions are as follows: (1) The T2 spectra of nine sandstone samples in this paper can be divided into four types. Type A is represented by sample 2, wherein the T2 spectrum shows a bimodal state and the area of the right T2 spectrum (2.5~100 ms) is larger than that of the left T2 spectrum (T2 < 2.5 ms), indicating that the sample has good pore connectivity and belongs to the macroporous development sample. The B-type T2 spectrum is unimodal, and the pore connectivity is poor, indicating that it is a large-pore development sample. The T2 spectrum of the C-type sample is unimodal, and the pore connectivity is very poor, indicating that it is a mesoporous development sample. The T2 spectrum of the D-type sample shows a single peak state, and the main T2 is distributed within 0.1~2.5 ms. The pore connectivity is very poor, which indicates that it belongs to the small pore development type sample. (2) The single fractal model shows that, compared with other single fractal parameters, D2 increases with the increase in the T2 cut-off value, but the correlation is weak. Therefore, it is not feasible to predict the T2 cut-off value using the single fractal dimension parameter. (3) The multifractal model shows that D−10–D10 increases linearly with the increase in D−10–D0, but there is no obvious linear correlation between D0–D10 and D−10–D10, indicating that the low pore volume area in this kind of sample controls the overall heterogeneity of pore distribution. (4) The related parameters affecting the T2 cut-off value include D−10–D10, D−10/D10, D−10–D0, TM and D2. Therefore, based on the above five parameters, a T2 cut-off value prediction model is constructed. The T2 cut-off value calculated by the model is highly consistent with the experimental value, which proves the reliability of the model.

Logging Evaluation of Irreducible Water Saturation: Fractal Theory and Data-Driven Approach—Case Study of Complex Porous Carbonate Reservoirs in Mishrif Formation

Evaluating irreducible water saturation is crucial for estimating reservoir capacity and developing effective extraction strategies. Traditional methods for predicting irreducible water saturation are limited by their reliance on specific logging data, which affects accuracy and applicability. This study introduces a predictive method based on fractal theory and deep learning for assessing irreducible water saturation in complex carbonate reservoirs. Utilizing the Mishrif Formation of the Halfaya oilfield as a case study, a new evaluation model was developed using the nuclear magnetic resonance (NMR) fractal permeability model and validated with surface NMR and mercury injection capillary pressure (MICP) data. The relationship between the logarithm mean of the transverse relaxation time (T2lm) and physical properties was explored through fractal theory and the Thomeer Function. This relationship was integrated with conventional logging curves and an advanced deep learning algorithm to construct a T2lm prediction model, offering a robust data foundation for irreducible water saturation evaluation. The results show that the new method is applicable to wells with and without specialized NMR logging data. For the Mishrif Formation, the predicted irreducible water saturation achieved a coefficient of determination of 0.943 compared to core results, with a mean absolute error of 2.37% and a mean relative error of 8.46%. Despite introducing additional errors with inverted T2lm curves, it remains within acceptable limits. Compared to traditional methods, this approach provides enhanced predictive accuracy and broader applicability.

Flow unit classification and characterization with emphasis on the clustering methods: a case study in a highly heterogeneous carbonate reservoir, eastern margin of Dezful Embayment, SW Iran

Previous attempts to classify flow units in Iranian carbonate reservoirs, based on porosity and permeability, have faced challenges in correlating the rock's pore size distribution with the capillary pressure profile. The innovation of this study highlights the role of clustering techniques, such as Discrete Rock Type, Probability, Global Hydraulic Element, and Winland's Standard Chart in enhancing the reservoir's rock categorization. These techniques are integrated with established flow unit classification methods. They include Lucia, FZI, FZI*, Winland R35, and the improved stratigraphic modified Lorenz plot. The research accurately links diverse pore geometries to characteristic capillary pressure profiles, addressing heterogeneity in intricate reservoirs. The findings indicate that clustering methods can identify specific flow units, but do not significantly improve their classification. The effectiveness of these techniques varies depending on the flow unit classification method employed. For instance, probability-based methods yield surpassing results for low-porosity rocks when utilizing the FZI* approach. The discrete technique generates the highest number of flow unit classes but provides the worst result. Not all clustering techniques reveal discernible advantages when integrated with the FZI method. In the second part, the study creatively suggests that rock classification can be achieved by concurrently clustering irreducible water saturation (SWIR) and porosity in unsuccessful flow unit delineation cases. The SWIR log was estimated by establishing a smart correlation between porosity and SWIR in the pay zone, where water saturation and SWIR match. Then, the estimated saturation was dispersed throughout the reservoir. Subsequently, the neural network technique was employed to cluster and propagate the three finalized flow units. This methodology is an effective recommendation when conventional flow unit methods fail. The study also investigates influential factors causing the failure of flow unit classification methods, including pore geometry, oil wettability, and saturation in heterogeneous reservoirs.

Dynamics of oil–CO2–water three-phase under the nanopore confinement effect: Implications for CO2 enhanced shale oil recovery and carbon storage

The widespread nanopores, diverse minerals, and varying water saturation in shale reservoirs complicate the mechanism analysis and performance prediction of CO2 enhanced oil recovery (CO2-EOR) and CO2 storage (CS) in hydrated nanopores. Therefore, molecular dynamics methods were used to simulate the process of CO2 replacing shale oil in hydrated nanopores of inorganic, organic and composite minerals. Importantly, the effects of mineral type, temperature, pressure and water content on CO2-EOR and CS performances in hydrated nanopores were analyzed, and the CO2-EOR mechanisms of dissolution, extraction, viscosity reduction, miscibility and competitive adsorption were revealed. The results show that water in illite, kerogen, and composite nanopores are distributed in the forms of water films, water clusters (films), and water columns, respectively. The replacement efficiency of shale oil in three types of nanopores is improved with increased water content but reduced in kerogen nanopores under high water content. Water is not conducive to the diffusion and viscosity reduction of oil in nanopores, but the miscibility and competitive adsorption of CO2 and oil are improved. The replacement efficiency is positively correlated with temperature and pressure. The increasing temperature promotes diffusion and viscosity reduction of oil and competitive adsorption between CO2 and oil in hydrated nanopores, and increasing pressure promotes miscibility and competitive adsorption. Water columns in kerogen and composite nanopores reduce the CS performance, while thin water films in illite nanopores improve it. Moreover, an excellent CS rate can be achieved at high temperatures and pressures, but the high temperature is not conducive to CS stability. This study provides a theoretical basis for CO2 injection to improve oil production and carbon storage performance in hydrated shale reservoirs and contributes to the optimization of CO2 injection schemes.

Production optimization in a fractured carbonate reservoir with high producing GOR

The Gas-Oil Ratio (GOR) is a crucial production parameter in oil reservoirs. An increase in GOR results in higher gas production and lower oil production, potentially leading to well shut-ins due to economic infeasibility. This study focuses on a real fractured oil field that requires urgent production operations to reduce the producing GOR. In this study, the static model for the field was developed using commercial software, involving steps such as data collection, fault modeling, meshing, and statistical analysis to prepare for dynamic simulation. The dynamic model incorporates geometry, gridding, and rock properties from the static model, utilizing a dual-porosity approach for the naturally fractured reservoir and the Peng-Robinson equation for fluid phase behavior. Initial reservoir conditions, production history, and rock-fluid interactions were defined, with relative permeability curves indicating a water-wet reservoir and low critical gas saturation affecting the GOR. To better understand the relationship between reservoir and production parameters, a detailed sensitivity analysis was performed using the Response Surface Methodology (RSM). Following the sensitivity analysis, a history matching process was conducted using the Designed Exploration and Controlled Evolution (DECE) optimizer to validate the model for future forecasts. Six operational scenarios were defined to decrease the production GOR and enhance final recovery from the field. The results indicate that the water injection scenario is effective in preventing the GOR increase by maintaining reservoir pressure, thereby sustaining production over a longer period. This scenario also improves oil recovery by approximately 6% compared to the base case. Finally, optimization was carried out using the DECE optimizer for each scenario to fine-tune the operational parameters. The goal was to maximize oil revenue for each scenario during the optimization process. This study stands out as one of the few that provides a comprehensive analysis of production behavior and development planning for a real fractured reservoir with high producing GOR.

DEVELOPMENT OF AN ALGORITHM FOR CALCULATING COMPONENT COMPOSITION TO IMPROVE THE DEVELOPMENT OF OFFSHORE OIL FIELDS IN THE NORTH CASPIAN BASIN

The paper presents an algorithm to reconstruct the component composition of the mixture based on the results of production modeling in the black oil format and a fixed set of tables with the results of phase equilibrium calculations in a given pressure range. The approach is based on analyzing the ratio of flow rates for each phase and the ratio between average reservoir pressure and saturation pressure. The algorithm takes into account the possibility of oil degassing when saturation pressure decreases, as well as gas breakthrough of gas caps to the bottoms of producing wells.Implementation of the method is based on a unified thermodynamic model of multilayer reservoir, built on the principles of a single set of HC mixture components and uniform parameters of the equation of state on a set of fluid samples for all modeling stages: reservoir model, model of the gathering system and site facilities. In addition to steady-state flow calculations performed together with reservoir modeling, the unified model is planned to be used for dynamic flow calculations in the corresponding simulator (well start/stop), which will allow solving production problems in the process of operation of wells with complex completions.The conversion algorithm is automated using modern high-level tools: Python and data automation components from MS Excel, which eliminates the need for manual data input at all stages and makes it possible to obtain the estimated component composition of produced fluid for any set of wells and for any time step within the forecasting horizon.The obtained compositions are used to verify the reproduction of the main controlled parameters (oil density and gas oil ratio) and can be used for subsequent calculations of fluid transportation and treatment systems.The implemented algorithm has been tested for stability at different ratios of gas and oil flow rates by wells and meets the practical requirements of engineering calculations — the error of oil density is not higher than 2 % and gas factor is not higher than 10 %.

Research on the influence of mineral heterogeneity under different CO2 injection schemes in low permeability reservoirs

In the pursuit of sustainable oil and gas resource extraction, the innovative integration of carbon capture, utilization, and storage (CCUS) technology has emerged as the most promising approach. During the CCUS process, intricate physicochemical interactions between the injected CO2, facilitated through various injection strategies (Water Alternative Gas: WAG/Continue Gas Injection: CGI) and the formation fluids and heterogeneous mineral assemblages within the reservoir trigger alterations in mineral structures, consequently impacting permeability and recovery factors, constituting a pivotal aspect. Precisely delineating and quantifying these interactions is paramount for optimizing process design and evaluating reservoir dynamics in the successful implementation of CCUS operations. This study has carried out qualitative and quantitative characterization of mineral heterogeneity, different pore types, and mineral combination characteristics from a low-permeability sandstone reservoir. Additionally, the effect on the physical properties of minerals from different development methods (WAG/CGI) was investigated using numerical simulation for CCUS applications. The results indicate that the saturated CO2 fluid selectively dissolves the potassium feldspar (orthoclase) in intergranular pores, while the intergranular pores are filled with illite and secondary precipitated clay minerals. It initially dissolves the sensitive mineral (ankerite) in the intergranular pores. The decrease of ankerite and increase of illite result from the prolonged contact period between saturated CO2 and minerals, which changes the mineral cementation to argillaceous type, thus affecting permeability in the context of CCUS. The spatial impact on reservoir physical properties depends on the spatial heterogeneity of the original sensitive minerals (ankerite, anorthite, illite, etc.) distributed in the study area. In the WAG scheme, the physicochemical interaction between saturated CO2 and reservoir minerals is more intense than in the CGI scheme for CCUS operations, significantly impacting cumulative production.

Deep learning algorithm-enabled sediment characterization techniques to determination of water saturation for tight gas carbonate reservoirs in Bohai Bay Basin, China

Understanding water saturation levels in tight gas carbonate reservoirs is vital for optimizing hydrocarbon production and mitigating challenges such as reduced permeability due to water saturation (Sw) and pore throat blockages, given its critical role in managing capillary pressure in water drive mechanisms reservoirs. Traditional sediment characterization methods such as core analysis, are often costly, invasive, and lack comprehensive spatial information. In recent years, several classical machine learning models have been developed to address these shortcomings. Traditional machine learning methods utilized in reservoir characterization encounter various challenges, including the ability to capture intricate relationships, potential overfitting, and handling extensive, multi-dimensional datasets. Moreover, these methods often face difficulties in dealing with temporal dependencies and subtle patterns within geological formations, particularly evident in heterogeneous carbonate reservoirs. Consequently, despite technological advancements, enhancing the reliability, interpretability, and applicability of predictive models remains imperative for effectively characterizing tight gas carbonate reservoirs. This study employs a novel data-driven strategy to prediction of water saturation in tight gas reservoir powered by three recurrent neural network type deep/shallow learning algorithms—Gated Recurrent Unit (GRU), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Support Vector Machine (SVM), K-nearest neighbor (KNN) and Decision tree (DT)—customized to accurately forecast sequential sedimentary structure data. These models, optimized using Adam's optimizer algorithm, demonstrated impressive performance in predicting water saturation levels using conventional petrophysical data. Particularly, the GRU model stood out, achieving remarkable accuracy (an R-squared value of 0.9973) with minimal errors (RMSE of 0.0198) compared to LSTM, RNN, SVM, KNN and, DT algorithms, thus showcasing its proficiency in processing extensive datasets and effectively identifying patterns. By achieving unprecedented accuracy levels, this study not only enhances the understanding of sediment properties and fluid saturation dynamics but also offers practical implications for reservoir management and hydrocarbon exploration in complex geological settings. These insights pave the way for more reliable and efficient decision-making processes, thereby advancing the forefront of reservoir engineering and petroleum geoscience.

Evaluation method of tight sandstone reservoir saturation based on frequency domain electrical dispersion measurement data

The traditional Archie model, which is primarily applicable to medium-high porosity and permeability sandstones, often fails to accurately characterize the resistivity-saturation relationship in tight sandstones, and it makes the saturation evaluation face great challenges. In this paper, complex resistivity spectrum measurements across 1 kHz to 10 MHz frequencies are performed on tight sandstone reservoir cores. Then, the percentage frequency effect (PFE) values are calculated from complex resistivity modulus at 1 kHz and interfacial polarization frequency under varied saturation states. Furthermore, a new quantitative saturation evaluation model based on the normalized PFE is developed by referring to the normalization method of the resistivity index in the classic Archie formula. The results demonstrate that a good linear correlation between the PFE of the tight sandstone reservoirs and water saturation, and the new saturation evaluation model effectively eliminates electrical differences between samples due to pore structures. Experimental data from tight sandstones shows that higher accuracy of the predicted water saturation by the new saturation evaluation model against measured values compared to the predicted water saturation by the Archie model, and the normalized PFE used in this model can quantitatively evaluate water saturation of tight sandstone reservoirs instead of the traditional Archie formula. The results provide a theoretical model and experimental reference for saturation evaluation in tight sandstone reservoirs.

An integrated approach to the substantiation of the boundary values and the assessment of the character of saturation in the deposits of the Tyumen formation

Background. The Tyumen formation is characterized by the complexity of the structure of deposits and consists of the sediments of different facies groups. To build hydrodynamic models, improve the development system and identify prospective zones, the conditions of sedimentation must be taken into account. Objective. Increasing the reliability of reservoir permeability assessment and clarifying critical resistivities when assessing the nature of saturation, which requires new approaches to petrophysical modeling. Materials and methods. The work uses the results of core studies and interpretation of well-logging data for the JV2 formation considering the facies. Results. The wettability of extracted and nonextracted samples is studied, the dependence of the saturation parameter on the water saturation coefficient is corrected taking into account the wettability of reservoirs, and the relative phase permeabilities are calculated for drainage conditions in the “oil–water” system. Conclusions. An integrated approach makes it possible to clarify the values of permeability, critical resistivities and oil and gas saturation of reservoirs, which can be used to identify prospecting zones when drilling new wells.

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.

Charging dynamic, resistance and accumulation process of tight sandstone oil of the paleogene Es3 member in linnan sag, jiyang depression

The study of the coupling relationship between the dynamic and resistance of oil charging is the key to revealing the process of tight oil accumulation. The Paleogene Es3 member of Linnan sag, Jiyang Depression was taken as an example, basin simulation, fluid inclusion analysis, and porosity inversion were comprehensively utilized to recovery the residual fluid pressure and charging resistance during the critical oil accumulation periods. Combined with the physical modeling of tight oil charging, the charging process and characteristics of tight oil under dynamic and resistance coupling were reproduced and the effects of dynamic and resistance on the oiliness of tight reservoirs were analyzed. The comprehensive analysis indicates that there were early and late periods of oil accumulation in early Dongying period and late Guantao-Quaternary period. The reservoirs had not been densified during the early oil accumulation period. The residual pressure of the formation was between 1.0–4.4 MPa and the reservoir charging resistance was generally small, so that the dynamic was generally greater than the resistance. But the oil saturation of the reservoirs was low due to the small amount of hydrocarbon generation. During the late oil accumulation period, the source rocks entered the peak period of hydrocarbon generation and expulsion and the residual pressure of the formation was between 4.2–12.1 MPa. The reservoirs had been close to or completely densified. The dynamic, resistance and dynamic and resistance difference all increased significantly. Under the stronger dynamic, the oil saturation of reservoirs rapidly increased, ultimately achieving tight oil enrichment. The results of this study provide insights into the dynamic process of tight oil accumulation and the distribution of oil in tight reservoirs.