Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.06.022
Lei Song , Xing-Yao Yin , Ying Shi , Kun Lang , Hao Zhou , Wei Xiang
Accurate characterization of the fault system is crucial for the exploration and development of fractured reservoirs. The fault characterization technique based on multi-azimuth and multi-attribute fusion is a hotspot. In this way, the fault structures of different scales can be identified and the characterization details of complex fault systems can be enriched by analyzing and fusing the fault-induced responses in multi-azimuth and multi-type seismic attributes. However, the current fusion methods are still in the stage of violent information stacking in utilizing fault information of multi-azimuth and multi-type seismic attributes, and the fault or fracture semantics in multi-type attributes are not fully considered and utilized. In this work, we propose a physic-guided multi-azimuth multi-type seismic attributes intelligent fusion method, which can mine fracture semantics from multi-azimuth seismic data and realize the effective fusion of fault-induced abnormal responses in multi-azimuth seismic coherence and curvature with the cooperation of the deep learning model and physical knowledge. The fused result can be used for multi-azimuth comprehensive characterization for multi-scale faults. The proposed method is successfully applied to an ultra-deep carbonate field survey. The results indicate the proposed method is superior to self-supervised-based, principal-component-analysis-based, and weighted-average-based fusion methods in fault characterization accuracy, and some medium-scale and microscale fault illusions in multi-azimuth seismic coherence and curvature can be removed in the fused result.
{"title":"Physic-guided multi-azimuth multi-type seismic attributes fusion for multiscale fault characterization","authors":"Lei Song , Xing-Yao Yin , Ying Shi , Kun Lang , Hao Zhou , Wei Xiang","doi":"10.1016/j.petsci.2025.06.022","DOIUrl":"10.1016/j.petsci.2025.06.022","url":null,"abstract":"<div><div>Accurate characterization of the fault system is crucial for the exploration and development of fractured reservoirs. The fault characterization technique based on multi-azimuth and multi-attribute fusion is a hotspot. In this way, the fault structures of different scales can be identified and the characterization details of complex fault systems can be enriched by analyzing and fusing the fault-induced responses in multi-azimuth and multi-type seismic attributes. However, the current fusion methods are still in the stage of violent information stacking in utilizing fault information of multi-azimuth and multi-type seismic attributes, and the fault or fracture semantics in multi-type attributes are not fully considered and utilized. In this work, we propose a physic-guided multi-azimuth multi-type seismic attributes intelligent fusion method, which can mine fracture semantics from multi-azimuth seismic data and realize the effective fusion of fault-induced abnormal responses in multi-azimuth seismic coherence and curvature with the cooperation of the deep learning model and physical knowledge. The fused result can be used for multi-azimuth comprehensive characterization for multi-scale faults. The proposed method is successfully applied to an ultra-deep carbonate field survey. The results indicate the proposed method is superior to self-supervised-based, principal-component-analysis-based, and weighted-average-based fusion methods in fault characterization accuracy, and some medium-scale and microscale fault illusions in multi-azimuth seismic coherence and curvature can be removed in the fused result.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4492-4503"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145698106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.07.020
Ji-Long Liu , Ran-Hong Xie , Jiang-Feng Guo , Chen-Yu Xu , Guo-Wen Jin , Xiang-Yu Wang , Bo-Chuan Jin , Xiao-Long Ju
It is of great significance to evaluate the petrophysical properties in shale oil reservoir, which can contribute to geological storage CO2. Two-dimensional nuclear magnetic resonance (2D NMR) technology has been applied to petrophysical characterization in shale oil reservoir. However, limitations of traditional 2D NMR (T1-T2 or T2-D) in detecting short-lived organic matter and the complexity of mineral compositions, pose NMR-based petrophysical challenges. The organic pores were assumed saturated oil and the inorganic pores were assumed saturated water, and the numerical algorithm and theory of T1-T2∗ in shale oil reservoir were proposed, whose accuracy was validated through T2,T1-T2 and T2∗ experiments. The effects of mineral types and contents on the T1-T2∗ responses were firstly simulated by the random walk algorithm, revealing the NMR response mechanisms in shale oil reservoir with complex mineral compositions at different magnetic field frequency (f). The results indicate that when the pyrite content is 5.43%, dwell time is 4 μs, the f is 200 MHz, and echo spacing is 0.4 ms, the T1-T2∗-based porosity is 2.39 times that of T1-T2-based porosity. The is 0.015 ms, which is 0.015 times that of T2LM. The T1LM is 8.84 ms, which is 0.63 times that of T1LM. The T1-T2∗-based petrophysical conversion models were firstly created, and the foundation of petrophysical conversion was laid at different f.
{"title":"Numerical investigations on T1-T2∗-based petrophysical evaluation in shale oil reservoir with complex minerals","authors":"Ji-Long Liu , Ran-Hong Xie , Jiang-Feng Guo , Chen-Yu Xu , Guo-Wen Jin , Xiang-Yu Wang , Bo-Chuan Jin , Xiao-Long Ju","doi":"10.1016/j.petsci.2025.07.020","DOIUrl":"10.1016/j.petsci.2025.07.020","url":null,"abstract":"<div><div>It is of great significance to evaluate the petrophysical properties in shale oil reservoir, which can contribute to geological storage CO<sub>2</sub>. Two-dimensional nuclear magnetic resonance (2D NMR) technology has been applied to petrophysical characterization in shale oil reservoir. However, limitations of traditional 2D NMR (<em>T</em><sub>1</sub>-<em>T</em><sub>2</sub> or <em>T</em><sub>2</sub>-<em>D</em>) in detecting short-lived organic matter and the complexity of mineral compositions, pose NMR-based petrophysical challenges. The organic pores were assumed saturated oil and the inorganic pores were assumed saturated water, and the numerical algorithm and theory of <em>T</em><sub>1</sub>-<em>T</em><sub>2</sub>∗ in shale oil reservoir were proposed, whose accuracy was validated through <em>T</em><sub>2,</sub> <em>T</em><sub>1</sub>-<em>T</em><sub>2</sub> and <em>T</em><sub>2</sub>∗ experiments. The effects of mineral types and contents on the <em>T</em><sub>1</sub>-<em>T</em><sub>2</sub>∗ responses were firstly simulated by the random walk algorithm, revealing the NMR response mechanisms in shale oil reservoir with complex mineral compositions at different magnetic field frequency (<em>f</em>). The results indicate that when the pyrite content is 5.43%, dwell time is 4 μs, the <em>f</em> is 200 MHz, and echo spacing is 0.4 ms, the <em>T</em><sub>1</sub>-<em>T</em><sub>2</sub>∗-based porosity is 2.39 times that of <em>T</em><sub>1</sub>-<em>T</em><sub>2</sub>-based porosity. The <span><math><mrow><msubsup><mi>T</mi><mrow><mn>2</mn><mtext>LM</mtext></mrow><mo>∗</mo></msubsup></mrow></math></span> is 0.015 ms, which is 0.015 times that of <em>T</em><sub>2LM</sub>. The <em>T</em><sub>1LM</sub> is 8.84 ms, which is 0.63 times that of <em>T</em><sub>1LM</sub>. The <em>T</em><sub>1</sub>-<em>T</em><sub>2</sub>∗-based petrophysical conversion models were firstly created, and the foundation of petrophysical conversion was laid at different <em>f</em>.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4538-4554"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hydrogels are widely used in reservoir flow control to enhanced oil recovery. However, challenges such as environmental contamination from conventional crosslinkers, poor solubility of crosslinking agents, and short gelation times under high-temperature conditions (e.g., 150 °C) have hindered their practical application. Herein, we present the synthesis of amine-functionalized carbon quantum dots (NH2-CQDs), which act as both a nano-crosslinker and a nano-reinforcing agent within hydrogel systems. The NH2-CQDs-incorporated hydrogel can remain stability for 300 days under the conditions of a mineralization degree of 2.11 × 104 mg/mL and 170 °C, and has high tensile strength (371 kPa), good toughness (49.6 kJ/m3), excellent viscoelasticity (G' = 960 Pa, G″ = 460 Pa) and shear resistance. In addition, NH2-CQDs adds many hydroxyl groups to the hydrogel, which can be attached to the surface of various substances. At the same time, micro-nano capsules containing NH2-CQDs were formed by self-assembly of hydrophobic SiO2 on water droplets, the NH2-CQDs solution is encapsulated in a capsule, and when stimulated by external conditions (temperature, pH, surfactant), the capsule releases the NH2-CQDs solution, this method greatly delays the crosslinking time between polymer and crosslinker at high temperature. Under the condition of 170 °C and pH = 7, the gelation time of 10% hydrophobic SiO2 coated hydrogel is 44 times that of uncoated hydrogel, which can be effectively used for deep formation flow control, and CQD give hydrogels fluorescence properties that can be used for underground signal tracking.
{"title":"An intelligent micro-nano capsule green hydrogel decorated with carbon quantum dots with delayed crosslinking characteristics for enhanced oil recovery in harsh reservoir","authors":"Chuan-Hong Kang, Ji-Xiang Guo, Zheng-Hao Zhang, Wyclif Kiyingi, Peng-Cheng Xue","doi":"10.1016/j.petsci.2025.09.032","DOIUrl":"10.1016/j.petsci.2025.09.032","url":null,"abstract":"<div><div>Hydrogels are widely used in reservoir flow control to enhanced oil recovery. However, challenges such as environmental contamination from conventional crosslinkers, poor solubility of crosslinking agents, and short gelation times under high-temperature conditions (e.g., 150 °C) have hindered their practical application. Herein, we present the synthesis of amine-functionalized carbon quantum dots (NH<sub>2</sub>-CQDs), which act as both a nano-crosslinker and a nano-reinforcing agent within hydrogel systems. The NH<sub>2</sub>-CQDs-incorporated hydrogel can remain stability for 300 days under the conditions of a mineralization degree of 2.11 × 10<sup>4</sup> mg/mL and 170 °C, and has high tensile strength (371 kPa), good toughness (49.6 kJ/m<sup>3</sup>), excellent viscoelasticity (<em>G</em><em>'</em> = 960 Pa, <em>G</em>″ = 460 Pa) and shear resistance. In addition, NH<sub>2</sub>-CQDs adds many hydroxyl groups to the hydrogel, which can be attached to the surface of various substances. At the same time, micro-nano capsules containing NH<sub>2</sub>-CQDs were formed by self-assembly of hydrophobic SiO<sub>2</sub> on water droplets, the NH<sub>2</sub>-CQDs solution is encapsulated in a capsule, and when stimulated by external conditions (temperature, pH, surfactant), the capsule releases the NH<sub>2</sub>-CQDs solution, this method greatly delays the crosslinking time between polymer and crosslinker at high temperature. Under the condition of 170 °C and pH = 7, the gelation time of 10% hydrophobic SiO<sub>2</sub> coated hydrogel is 44 times that of uncoated hydrogel, which can be effectively used for deep formation flow control, and CQD give hydrogels fluorescence properties that can be used for underground signal tracking.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4809-4822"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145698109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.08.003
Xin Fu , Feng Zhang , Dan-Ping Cao
Seismic AVO/AVA (amplitude-versus-offset or amplitude-versus-angle) analysis, based on prestack seismic angle gathers and the Zoeppritz equation, has been widely used in seismic exploration. However, conducting the multi-parameter AVO/AVA inversion using only PP-wave angle gathers is often highly ill-posed, leading to instability and inaccuracy in the inverted elastic parameters (e.g., P- and S-wave velocities and bulk density). Seismic AVO/AVA analysis simultaneously using both PP-wave (pressure wave down, pressure wave up) and PS-wave (pressure wave down, converted shear wave up) angle gathers has proven to be an effective method for reducing reservoir interpretation ambiguity associated with using the single wave mode of PP-waves. To avoid the complex PS-wave processing, and the risks associated with PP and PS waveform alignment, we developed a method that predicts PS-wave angle gathers from PP-wave angle gathers using a deep learning algorithm—specifically, the cGAN deep learning algorithm. Our deep learning model is trained with synthetic data, demonstrating a strong fit between the predicted PS-waves and real PS-waves in a test datasets. Subsequently, the trained deep learning model is applied to actual field PP-waves, maintaining robust performance. In the field data test, the predicted PS-wave angle gather at the well location closely aligns with the synthetic PS-wave angle gather generated using reference well logs. Finally, the P- and S-wave velocities estimated from the joint PP and PS AVA inversion, based on field PP-waves and the predicted PS-waves, display a superior model fit compared to those obtained solely from the PP-wave AVA inversion using field PP-waves. Our contribution lies in firstly carrying out the joint PP and PS inversion using predicted PS waves rather than the field PS waves, which break the limit of acquiring PS-wave angle gathers.
{"title":"Joint PP and PS seismic inversion using predicted PS waves from deep learning","authors":"Xin Fu , Feng Zhang , Dan-Ping Cao","doi":"10.1016/j.petsci.2025.08.003","DOIUrl":"10.1016/j.petsci.2025.08.003","url":null,"abstract":"<div><div>Seismic AVO/AVA (amplitude-versus-offset or amplitude-versus-angle) analysis, based on prestack seismic angle gathers and the Zoeppritz equation, has been widely used in seismic exploration. However, conducting the multi-parameter AVO/AVA inversion using only PP-wave angle gathers is often highly ill-posed, leading to instability and inaccuracy in the inverted elastic parameters (e.g., P- and S-wave velocities and bulk density). Seismic AVO/AVA analysis simultaneously using both PP-wave (pressure wave down, pressure wave up) and PS-wave (pressure wave down, converted shear wave up) angle gathers has proven to be an effective method for reducing reservoir interpretation ambiguity associated with using the single wave mode of PP-waves. To avoid the complex PS-wave processing, and the risks associated with PP and PS waveform alignment, we developed a method that predicts PS-wave angle gathers from PP-wave angle gathers using a deep learning algorithm—specifically, the cGAN deep learning algorithm. Our deep learning model is trained with synthetic data, demonstrating a strong fit between the predicted PS-waves and real PS-waves in a test datasets. Subsequently, the trained deep learning model is applied to actual field PP-waves, maintaining robust performance. In the field data test, the predicted PS-wave angle gather at the well location closely aligns with the synthetic PS-wave angle gather generated using reference well logs. Finally, the P- and S-wave velocities estimated from the joint PP and PS AVA inversion, based on field PP-waves and the predicted PS-waves, display a superior model fit compared to those obtained solely from the PP-wave AVA inversion using field PP-waves. Our contribution lies in firstly carrying out the joint PP and PS inversion using predicted PS waves rather than the field PS waves, which break the limit of acquiring PS-wave angle gathers.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4573-4583"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145697932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.07.008
Jing-Qi Lin , Xia Yan , Er-Zhen Wang , Qi Zhang , Kai Zhang , Pi-Yang Liu , Li-Ming Zhang
In this study, we propose a constraint learning strategy based on interpretability analysis to improve the convergence and accuracy of the enriched physics-informed neural network (EPINN), which is applied to simulate two-phase flow in heterogeneous porous media. Specifically, we first analyze the layerwise outputs of EPINN, and identify the distinct functions across layers, including dimensionality adjustment, pointwise construction of non-equilibrium potential, extraction of high-level features, and the establishment of long-range dependencies. Then, inspired by these distinct modules, we propose a novel constraint learning strategy based on regularization approaches, which improves neural network (NN) learning through layer-specific differentiated updates to enhance cross-timestep generalization. Since different neural network layers exhibit varying sensitivities to global generalization and local regression, we decrease the update frequency of layers more sensitive to local learning under this constraint learning strategy. In other words, the entire neural network is encouraged to extract more generalized features. The superior performance of the proposed learning strategy is validated through evaluations on numerical examples with varying computational complexities. Post hoc analysis reveals that gradient propagation exhibits more pronounced staged characteristics, and the partial differential equation (PDE) residuals are more uniformly distributed under the constraint guidance. Interpretability analysis of the adaptive constraint process suggests that maintaining a stable information compression mode facilitates progressive convergence acceleration.
{"title":"A layer-specific constraint-based enriched physics-informed neural network for solving two-phase flow problems in heterogeneous porous media","authors":"Jing-Qi Lin , Xia Yan , Er-Zhen Wang , Qi Zhang , Kai Zhang , Pi-Yang Liu , Li-Ming Zhang","doi":"10.1016/j.petsci.2025.07.008","DOIUrl":"10.1016/j.petsci.2025.07.008","url":null,"abstract":"<div><div>In this study, we propose a constraint learning strategy based on interpretability analysis to improve the convergence and accuracy of the enriched physics-informed neural network (EPINN), which is applied to simulate two-phase flow in heterogeneous porous media. Specifically, we first analyze the layerwise outputs of EPINN, and identify the distinct functions across layers, including dimensionality adjustment, pointwise construction of non-equilibrium potential, extraction of high-level features, and the establishment of long-range dependencies. Then, inspired by these distinct modules, we propose a novel constraint learning strategy based on regularization approaches, which improves neural network (NN) learning through layer-specific differentiated updates to enhance cross-timestep generalization. Since different neural network layers exhibit varying sensitivities to global generalization and local regression, we decrease the update frequency of layers more sensitive to local learning under this constraint learning strategy. In other words, the entire neural network is encouraged to extract more generalized features. The superior performance of the proposed learning strategy is validated through evaluations on numerical examples with varying computational complexities. Post hoc analysis reveals that gradient propagation exhibits more pronounced staged characteristics, and the partial differential equation (PDE) residuals are more uniformly distributed under the constraint guidance. Interpretability analysis of the adaptive constraint process suggests that maintaining a stable information compression mode facilitates progressive convergence acceleration.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4714-4735"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145698017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.10.003
Ling-Ban Wang , Xiao-Hui Wang , Yu-Hao Bu , Zhen-Bin Xu , Xian Sun , Yi-Fei Sun , Peng Xiao , Qing-Ping Li , Shou-Wei Zhou , Praveen Linga , Chang-Yu Sun , Guang-Jin Chen
Large-scale physical simulation is essential for advancing our understanding of natural gas hydrates exploitation mechanism. However, cylinder-shaped simulators often face challenges in balancing large volume, controllability, and comprehensive monitoring. In this study, we developed a fan column-shaped hydrate simulator (FCHS) with an internal angle of 6°, a radius of 3 m, and an inner height of 0.3 m, resulting in an effective volume of ∼142 L. Moreover, the FCHS is equipped with an integrated "thermal-pressure-acoustic" sensing system, enabling in-situ monitoring of temperature, pressure, and P-wave velocity evolution during hydrate formation and dissociation process. The experimental results indicate that a pressure gradient successfully established from the reservoir center toward its boundaries during depressurization stage, and pressure propagation is relatively slow, resulting in a radial pressure difference of 3–4 MPa within a 3 m range. Once the system reaches pressure equilibrium, the pressure difference decreases to 0.3–0.4 MPa. The depressurization at the wellbore promotes hydrate dissociation in the near-well region, resulting in the radial temperature difference reaches ∼1.5 °C along the radial direction. The acoustic data reveals that a radial gradient in hydrate saturation gradually forms from the center to the boundary during depressurization-induced gas production. The evolutions of spatio-temporal multi-fields obtained in the FCHS are consist with that of field production. The FCHS proves to be a cutting-edge platform for experimental simulation of NGH exploitation and carbon sequestration processes.
{"title":"Development and feasibility test of a fan-shaped hydrate simulator with a radius of 3 m","authors":"Ling-Ban Wang , Xiao-Hui Wang , Yu-Hao Bu , Zhen-Bin Xu , Xian Sun , Yi-Fei Sun , Peng Xiao , Qing-Ping Li , Shou-Wei Zhou , Praveen Linga , Chang-Yu Sun , Guang-Jin Chen","doi":"10.1016/j.petsci.2025.10.003","DOIUrl":"10.1016/j.petsci.2025.10.003","url":null,"abstract":"<div><div>Large-scale physical simulation is essential for advancing our understanding of natural gas hydrates exploitation mechanism. However, cylinder-shaped simulators often face challenges in balancing large volume, controllability, and comprehensive monitoring. In this study, we developed a fan column-shaped hydrate simulator (FCHS) with an internal angle of 6°, a radius of 3 m, and an inner height of 0.3 m, resulting in an effective volume of ∼142 L. Moreover, the FCHS is equipped with an integrated \"thermal-pressure-acoustic\" sensing system, enabling in-situ monitoring of temperature, pressure, and P-wave velocity evolution during hydrate formation and dissociation process. The experimental results indicate that a pressure gradient successfully established from the reservoir center toward its boundaries during depressurization stage, and pressure propagation is relatively slow, resulting in a radial pressure difference of 3–4 MPa within a 3 m range. Once the system reaches pressure equilibrium, the pressure difference decreases to 0.3–0.4 MPa. The depressurization at the wellbore promotes hydrate dissociation in the near-well region, resulting in the radial temperature difference reaches ∼1.5 °C along the radial direction. The acoustic data reveals that a radial gradient in hydrate saturation gradually forms from the center to the boundary during depressurization-induced gas production. The evolutions of spatio-temporal multi-fields obtained in the FCHS are consist with that of field production. The FCHS proves to be a cutting-edge platform for experimental simulation of NGH exploitation and carbon sequestration processes.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4794-4808"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145698105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.08.033
Kai Wei , Zhe Xu , Ao Cai , Yan-Xian Wu , Yan Yan
Underground gas storage facilities play a crucial strategic role in ensuring the balance of natural gas supply and demand, addressing seasonal fluctuations, and responding to emergencies. The design of the wellbore structure is key to both construction and operation, directly influencing long-term efficiency and economic benefits. However, since gas storage is typically located in complex geological environments, parameters such as formation pressure, porosity, and fracture pressure exhibit significant spatial variation and uncertainty. Traditional design methods based on deterministic geological data struggle to accurately predict the drilling fluid density window, reducing design precision and reliability. To address this, this paper proposes an optimized design method based on grey geological information and a three-parameter drilling fluid density window. By constructing a model of the three-parameter density window, including upper and lower limits and the centroid, and developing drilling risk evaluation models for overflow, collapse, wellbore loss, and stuck pipe, the method combines procedural approaches with geometric plotting to determine casing levels and depth. Case studies show that this method significantly improves the safety and economy of gas storage wellbore structure design, providing scientific guidance for similar complex gas storage well designs. The drilling risk evaluation model based on three-parameter grey intervals aligns closely with actual risks, validating its reliability and applicability. In practical engineering, a balanced wellbore structure design effectively ensures safety while controlling construction costs. This method offers flexible and reliable references for gas storage well design at different risk levels, holding significant practical value.
{"title":"Risk-based design method for gas storage wellbore structure using grey geological information","authors":"Kai Wei , Zhe Xu , Ao Cai , Yan-Xian Wu , Yan Yan","doi":"10.1016/j.petsci.2025.08.033","DOIUrl":"10.1016/j.petsci.2025.08.033","url":null,"abstract":"<div><div>Underground gas storage facilities play a crucial strategic role in ensuring the balance of natural gas supply and demand, addressing seasonal fluctuations, and responding to emergencies. The design of the wellbore structure is key to both construction and operation, directly influencing long-term efficiency and economic benefits. However, since gas storage is typically located in complex geological environments, parameters such as formation pressure, porosity, and fracture pressure exhibit significant spatial variation and uncertainty. Traditional design methods based on deterministic geological data struggle to accurately predict the drilling fluid density window, reducing design precision and reliability. To address this, this paper proposes an optimized design method based on grey geological information and a three-parameter drilling fluid density window. By constructing a model of the three-parameter density window, including upper and lower limits and the centroid, and developing drilling risk evaluation models for overflow, collapse, wellbore loss, and stuck pipe, the method combines procedural approaches with geometric plotting to determine casing levels and depth. Case studies show that this method significantly improves the safety and economy of gas storage wellbore structure design, providing scientific guidance for similar complex gas storage well designs. The drilling risk evaluation model based on three-parameter grey intervals aligns closely with actual risks, validating its reliability and applicability. In practical engineering, a balanced wellbore structure design effectively ensures safety while controlling construction costs. This method offers flexible and reliable references for gas storage well design at different risk levels, holding significant practical value.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4624-4644"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145698013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.07.021
Hao Chen , Pei-Fu Xu , Yong-Xian Zhu , Jia-Yi Yu , Mei Zhang , Xian-Min Zhou , Ming-Cheng Ni , Yi Wu , Xi-Liang Liu
The tight-tuff heavy oil reservoir exhibits severe heterogeneity and is characterized by high density, high viscosity, and a high wax content, posing significant challenges for its development. While CO2 huff-and-puff (H-n-P) enhances oil recovery, these reservoirs struggle with low displacement efficiency. This study proposes a method that combines CO2 with an oil-soluble viscosity reducer to improve displacement efficiency in the H-n-P process for tight-tuff heavy oil reservoirs. It also focuses on evaluating pore utilization limits and optimizing the injection strategy. Core samples and crude oil from the TH oilfield (a tight-tuff heavy oil reservoir) were used to conduct online NMR core flooding experiments, including depletion development, water, CO2, and HDC (CO2 combined with an oil-soluble viscosity reducer) H-n-P injection processes. A single-porosity model accurately reflecting its geological characteristics was developed using the GEM component simulator within the CMG numerical simulation software to investigate the optimized schemes and the enhanced oil recovery potential for a tight-tuff heavy oil reservoir in the TH oilfield. This model was utilized to evaluate the impact of various injection strategies on oilfield recovery efficiency. The study was designed and implemented with five distinct injection schemes.
Results showed that oil was produced primarily from large and medium pores during the depletion stage, while water H-n-P, with CO2 H-n-P, first targeted macropores, then mesopores, and micropores. The lower pore utilization limit was 0.0267 μm. In the HDC H-n-P process, most oil was recovered from water-flooded pores. Still, HDC's lower injection capacity increased the pore utilization limit to 0.03 μm, making micropore recovery difficult. Experimental and modeling results suggest that the optimal development plan for the TH oilfield is one cycle of HDC H-n-P followed by two cycles of CO2 H-n-P. This strategy leverages HDC's ability to promote water and oil recovery in the early stage and mass transfer and extraction capacity of CO2 in later cycles.
Additionally, the characteristics of CO2 and HDC H-n-P processes, pore utilization, and recoverable oil (at the pore scale) were evaluated. The results of this study are crucial for refining the reservoir development plan.
{"title":"An experimental study of huff-and-puff oil recovery for tight-tuff heavy oil reservoirs by synergistic with viscosity reducer and CO2 utilizing online NMR technology","authors":"Hao Chen , Pei-Fu Xu , Yong-Xian Zhu , Jia-Yi Yu , Mei Zhang , Xian-Min Zhou , Ming-Cheng Ni , Yi Wu , Xi-Liang Liu","doi":"10.1016/j.petsci.2025.07.021","DOIUrl":"10.1016/j.petsci.2025.07.021","url":null,"abstract":"<div><div>The tight-tuff heavy oil reservoir exhibits severe heterogeneity and is characterized by high density, high viscosity, and a high wax content, posing significant challenges for its development. While CO<sub>2</sub> huff-and-puff (H-n-P) enhances oil recovery, these reservoirs struggle with low displacement efficiency. This study proposes a method that combines CO<sub>2</sub> with an oil-soluble viscosity reducer to improve displacement efficiency in the H-n-P process for tight-tuff heavy oil reservoirs. It also focuses on evaluating pore utilization limits and optimizing the injection strategy. Core samples and crude oil from the TH oilfield (a tight-tuff heavy oil reservoir) were used to conduct online NMR core flooding experiments, including depletion development, water, CO<sub>2</sub>, and HDC (CO<sub>2</sub> combined with an oil-soluble viscosity reducer) H-n-P injection processes. A single-porosity model accurately reflecting its geological characteristics was developed using the GEM component simulator within the CMG numerical simulation software to investigate the optimized schemes and the enhanced oil recovery potential for a tight-tuff heavy oil reservoir in the TH oilfield. This model was utilized to evaluate the impact of various injection strategies on oilfield recovery efficiency. The study was designed and implemented with five distinct injection schemes.</div><div>Results showed that oil was produced primarily from large and medium pores during the depletion stage, while water H-n-P, with CO<sub>2</sub> H-n-P, first targeted macropores, then mesopores, and micropores. The lower pore utilization limit was 0.0267 μm. In the HDC H-n-P process, most oil was recovered from water-flooded pores. Still, HDC's lower injection capacity increased the pore utilization limit to 0.03 μm, making micropore recovery difficult. Experimental and modeling results suggest that the optimal development plan for the TH oilfield is one cycle of HDC H-n-P followed by two cycles of CO<sub>2</sub> H-n-P. This strategy leverages HDC's ability to promote water and oil recovery in the early stage and mass transfer and extraction capacity of CO<sub>2</sub> in later cycles.</div><div>Additionally, the characteristics of CO<sub>2</sub> and HDC H-n-P processes, pore utilization, and recoverable oil (at the pore scale) were evaluated. The results of this study are crucial for refining the reservoir development plan.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4736-4752"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145698018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.petsci.2025.07.009
Xiao Deng , Mohammad Otaibi , Mohanad Fahmi , Mobeen Murtaza , Muhammad Shahzad Kamal , Shirish Patil , Syed Muhammad Shakil Hussain
Surfactants play a critical role in enhanced oil recovery (EOR) applications; however, their performance is often compromised in harsh reservoir conditions, such as high temperature and high salinity, due to precipitation caused by interactions with multivalent metal ions. Chelating agents were introduced into oilfields for various purposes due to their ability to sequester metal ions. In this work, we conducted a comprehensive investigation about chelating agent-surfactant (CS) flooding for carbonate reservoirs, as an alternative to the well-established alkaline surfactant (AS) flooding used in sandstone. The tested surfactants include sodium dodecyl sulfate (anionic) (SDS), dodecyltrimethylammonium bromide (cationic) (DTAB), Triton X100 (nonionic), and a locally synthesized zwitterionic surfactant. The tested chelating agents include diethylenetriaminepentaacetic acid (DTPA), ethylenediaminetetraacetic acid, and glutamic acid N,N-diacetic acid. pH and temperature, as dominant factors in chelating agent solubility and brine stability, were modified to test chelating agent solutions of different concentrations and their mixtures with surfactants. Interfacial tension reduction by chelating agents alone, surfactants alone, and their mixtures were measured. Wettability alteration brought by chelating agents and surfactants on carbonate rock surfaces was evaluated using the static contact angle method. Based on the obtained results, chelating agents can be applied as low-cost additives for surfactant stabilization in high salinity conditions. The addition of chelating agents significantly improved the stability of SDS and DTAB in salt solutions and seawater. At a relatively low concentration (0.25 wt%), DTPA was able to stabilize DTAB of 1.00 wt% in seawater at high temperature (90 °C). DTPA, among the tested three chelating agents, exhibited a stronger stabilization effect on surfactants of different ion types. When chelating agents are to be applied in brine, an optimal applicable pH range of 5–9 is recommended so not to induce solubility issue of chelating agents or stability issues of metal ions. In this range, IFT reduction is more significant at high pH, while wettability alteration is more significant at low pH. The combination of a cationic surfactant with a chelating agent forms a low adsorption wettability modifier which can change strongly oil-wet rock to water-wet conditions, thus significantly increasing the residual oil recovery from oil-wet carbonate formations. Zwitterionic and nonionic surfactants are also applicable to combine with a chelating agent for EOR purposes. Anionic surfactant SDS, however, showed a growing inhibition on the wettability alteration effect induced by EDTA as the concentration of SDS increased.
{"title":"Synergistic effects of chelating agents and surfactants for chemical EOR in carbonates","authors":"Xiao Deng , Mohammad Otaibi , Mohanad Fahmi , Mobeen Murtaza , Muhammad Shahzad Kamal , Shirish Patil , Syed Muhammad Shakil Hussain","doi":"10.1016/j.petsci.2025.07.009","DOIUrl":"10.1016/j.petsci.2025.07.009","url":null,"abstract":"<div><div>Surfactants play a critical role in enhanced oil recovery (EOR) applications; however, their performance is often compromised in harsh reservoir conditions, such as high temperature and high salinity, due to precipitation caused by interactions with multivalent metal ions. Chelating agents were introduced into oilfields for various purposes due to their ability to sequester metal ions. In this work, we conducted a comprehensive investigation about chelating agent-surfactant (CS) flooding for carbonate reservoirs, as an alternative to the well-established alkaline surfactant (AS) flooding used in sandstone. The tested surfactants include sodium dodecyl sulfate (anionic) (SDS), dodecyltrimethylammonium bromide (cationic) (DTAB), Triton X100 (nonionic), and a locally synthesized zwitterionic surfactant. The tested chelating agents include diethylenetriaminepentaacetic acid (DTPA), ethylenediaminetetraacetic acid, and glutamic acid <em>N</em>,<em>N</em>-diacetic acid. pH and temperature, as dominant factors in chelating agent solubility and brine stability, were modified to test chelating agent solutions of different concentrations and their mixtures with surfactants. Interfacial tension reduction by chelating agents alone, surfactants alone, and their mixtures were measured. Wettability alteration brought by chelating agents and surfactants on carbonate rock surfaces was evaluated using the static contact angle method. Based on the obtained results, chelating agents can be applied as low-cost additives for surfactant stabilization in high salinity conditions. The addition of chelating agents significantly improved the stability of SDS and DTAB in salt solutions and seawater. At a relatively low concentration (0.25 wt%), DTPA was able to stabilize DTAB of 1.00 wt% in seawater at high temperature (90 °C). DTPA, among the tested three chelating agents, exhibited a stronger stabilization effect on surfactants of different ion types. When chelating agents are to be applied in brine, an optimal applicable pH range of 5–9 is recommended so not to induce solubility issue of chelating agents or stability issues of metal ions. In this range, IFT reduction is more significant at high pH, while wettability alteration is more significant at low pH. The combination of a cationic surfactant with a chelating agent forms a low adsorption wettability modifier which can change strongly oil-wet rock to water-wet conditions, thus significantly increasing the residual oil recovery from oil-wet carbonate formations. Zwitterionic and nonionic surfactants are also applicable to combine with a chelating agent for EOR purposes. Anionic surfactant SDS, however, showed a growing inhibition on the wettability alteration effect induced by EDTA as the concentration of SDS increased.</div></div>","PeriodicalId":19938,"journal":{"name":"Petroleum Science","volume":"22 11","pages":"Pages 4753-4765"},"PeriodicalIF":6.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145698019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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