Predicting microbially enhanced coalbed methane (MECBM) extraction accurately presents a significant challenge, largely because current models fail to adequately integrate microbial kinetics with the intricate and dynamic physical processes occurring within coal reservoirs. To bridge this critical gap, this study introduces a novel field-scale simulation framework specifically designed for evaluating MECBM performance. A key innovation of this work is the explicit integration of a biogenic methane (CH4) proxy model—derived from the Conus model, which was originally developed to characterize CH4 formation during organic substrate decomposition—with the commercial tNavigator simulator. This integration effectively couples microbial gas generation with the complex flow and adsorption processes within coal reservoirs. The implementation involved a concise three-stage workflow, incorporating static geological data, coal-specific Langmuir parameters, diffusion coefficients, and dual-porosity physics. This was complemented by simulating nutrient-tracer propagation using organic substrates, such as glucose from molasses and lignin, and the automated injection of microbially generated gases via dummy wells. The framework was applied to a 1.8 × 1.8 km fractured coal seam, featuring 25 hydraulically fractured wells, under three distinct scenarios: depletion, carbon dioxide (CO2) injection, and bio-stimulation. Numerical results indicate that primary depletion yields ∼616 million m3 of CH4 (∼60% recovery), whereas CO2 injection increases recovery to ∼74% by effectively maintaining reservoir pressure. In stark contrast, bio-stimulation contributes a negligible amount of CH4 (<1% gain), primarily because ∼66% of the microbially generated CO2 becomes adsorbed within the coal matrix, preventing it from reaching the production wells. Furthermore, a sensitivity analysis revealed that the CH4 Langmuir volume is the predominant factor controlling recovery, while operational parameters like nutrient injection rate and duration have only a minimal impact. This framework successfully links laboratory-scale microbial behavior with field-scale reservoir dynamics, offering a practical tool for optimizing MECBM strategies, facilitating concurrent CH4 production and CO2 sequestration, and valorizing organic substrates including glucose and lignin.
Large volumes of natural gas stored in hydrate form within marine and subpermafrost environments represent a significant resource for potential extraction and use. Various methods for developing hydrate deposits are currently under investigation. A promising strategy for efficient methane production involves the injection of carbon dioxide (CO2) or flue gas mixtures (CO2+N2). The introduction of these gases into hydrate-bearing sediments induces methane hydrate dissociation, followed by its partial replacement by CO2 hydrate without compromising wellbore integrity. In addition, the CO2-based approach facilitates carbon sequestration within hydrate structures, thereby reducing greenhouse gas emissions. For effective implementation, a detailed understanding of gas permeability behavior in response to CO2 or flue gas injection into hydrate-bearing formations is essential. This response was experimentally investigated by injecting CO2 and flue gas into sand-clay samples under pressure and temperature conditions representative of subpermafrost gas hydrate reservoirs. The experiments demonstrate that gas permeability decreases markedly during CO2/CH4 replacement in the model reservoir, due to the additional formation of CO2 hydrate from residual pore water. This reduction may reach several tens of percent, particularly in reservoirs with high residual water content. Consequently, sediments with higher total saturation and lower hydration coefficients exhibit substantially reduced gas permeability following CO2 or flue gas injection. Overall, the findings indicate that the extent of permeability reduction during CO2 or flue gas injection is strongly governed by the initial reservoir properties and secondary hydrate formation processes. This understanding enables improved prediction and optimization of the CO2/CH4 replacement process for the efficient and safe exploitation of gas hydrate resources.
Acid–rock reactions in carbonate reservoirs generate CO2, whose phase behavior significantly influences wormhole propagation and, consequently, matrix acidizing efficiency. In this study, backpressure-controlled core flooding experiments were conducted on >99% calcite plugs using 1 wt% HCl at ambient temperature. Injection rate (1–8 mL/min) and backpressure (0.1–8.2 MPa) were systematically varied, and wormhole development was quantified through pore volume to breakthrough (PVBT), CT imaging, and a Wormhole Propagation Index (WPI). The results show that (1) Despite non-monotonic behavior observed in individual cores, likely attributable to rock heterogeneity, averaged trends consistently demonstrated enhanced wormhole efficiency with reduced backpressure. (2) Reduced backpressure generally promoted wormhole propagation, resulting in thicker, less-branched channels and a reduced pore volume to breakthrough. (3) The most significant reduction in PVBT (∼15%) was observed at 8 mL/min when backpressure decreased from 8.2 MPa to 2.7 MPa. The operational significance of this reduction, however, is contingent upon specific economic and operational constraints. (4) Optimum injection rates of approximately 4.4–5.6 mL/min were identified, reflecting a balance between reaction kinetics and transport as characterized by the Damköhler number. (5) Mechanistically, non-aqueous CO2 generated at low backpressure may redistribute flow, shield reactive surfaces, and enhance local mass transfer, thereby promoting the formation of thicker and more efficient wormholes. These results suggest that strategies favoring non-aqueous CO2 formation (e.g., solubility-reducing additives, foam-acid systems, or chemical/thermal adjustments) could enhance wormholing efficiency in carbonate acidizing. However, extrapolation of these findings beyond the specific rocks and fluids tested necessitates further investigation.
The expansion of natural gas consumption and pipeline construction makes integrating artificial intelligence into pipeline network operations increasingly essential. This review summarizes progress in operation optimization, gas transmission capacity evaluation, and solution algorithms. The review systematically summarizes objective functions, hydraulic/thermal and compressor constraints, and decision variables, all framed by operator objectives such as transmission capacity, economic benefits, and supply reliability. It highlights gas transmission capacity optimization and extended models, including those for hydrogen-blended and renewable energy-coupled scenarios. The review also analyzes applications of deterministic and stochastic intelligent algorithms, alongside deep learning and hyper-heuristic methods. Key findings indicate that: (1) Traditional models often lack safety, reliability, and low-carbon indicators; (2) Deterministic algorithms struggle with high dimensionality, while heuristic algorithms are prone to premature convergence; (3) Hydrogen blending and new energy integration necessitate revised constraints; and (4) Existing online dynamic optimization methods are insufficient. Finally, current shortcomings are identified, and future directions, such as advanced online dynamic optimization and cross-domain intelligence, are proposed. In conclusion, while artificial intelligence is crucial for natural gas pipeline network operations, significant limitations persist. Future research must prioritize addressing these gaps to advance the industry's intelligent, low-carbon, and reliable development.
Within tight sandstones, diagenetic features exhibit strong heterogeneity and intra-subfacies similarities, meaning that different rock units often share comparable mineral compositions and pore structures. These similarities result in overlapping petrophysical signatures that obscure distinct logging responses, thereby significantly reducing the reliability of conventional well-logging interpretations for predicting diagenetic facies and favorable reservoirs. To address the limitations of manual interpretation under the conditions of limited data, this study developed an integrated framework that combines sandbody classification, diagenetic events, and machine learning. The main conclusions are as follows: (1) Sedimentological analyses of field outcrops and cores reveal that the tight sandstones in the braided delta-front subfacies of the Fourth Member of the Triassic Xujiahe Formation can be divided into four sandbody types: main subaqueous channels (MSC), branch subaqueous channels (BSC), terminal subaqueous channels (TSC), and distal bars and sheet sands (DB&SS). (2) Based on the quantitative characterization of diagenetic intensity, four representative diagenetic facies were identified: moderate compaction and moderate dissolution (Type I), strong compaction and weak dissolution (Type II), moderate compaction and moderate cementation (Type III), and strong compaction (Type IV). (3)Using the sedimentology-diagenesis coupling framework, a one-dimensional convolutional neural network algorithm achieved a prediction accuracy of an 81.17% for diagenetic facies through multi-parameter integration (e.g., CAL × GR, AC × DEN) and a class consolidation strategy that combines Types III and IV. (4) The internal architecture of sandbodies plays a key role in controlling the distribution of diagenetic facies and reservoir quality by regulating acidic fluid activity and cement precipitation. Favorable reservoirs (Types I and II) mainly occur in the middle-to-lower intervals of the MSC and BSC. This distribution is associated with coarse-grained, quartz-rich sandstones that promote the migration of acidic fluids and the dissolution of feldspar and rock fragments. In contrast, late-stage precipitation of authigenic carbonate and quartz results in ineffective reservoirs (Types III and IV) along the margins of the sandbodies.
Effective proppant placement in multi-cluster hydraulic fractures is crucial for shale gas fracturing; however, existing numerical methods face challenges in accurately coupling dynamic fracture propagation with suspended-load transport, bed erosion, and accumulation at the field scale. To address this, a coupled solution integrating the DDM with an improved TLM was developed. This solution incorporates a logarithmic near-bed velocity profile to refine bed shear stress calculations, thereby capturing dynamic flow allocation, fracture-tip extension, and proppant bed evolution within a unified framework. The key findings are: (1) Increasing spacing from 6 m to 25 m minimizes stress interference, reducing flow allocation disparities among clusters by 96%, thereby promoting more uniform fracture propagation and bed-load transport; (2) Higher rates elevate net pressure and reduce pressure drop differences across perforations but increase shear within fractures, exacerbating proppant placement disparities; (3) As viscosity increases from 3 mPa·s to 5 mPa·s, bed-load transport differences intensify, causing a sevenfold rise in placement discrepancies; at 10 mPa·s most proppants remain suspended, transitioning to a suspended-load transport regime and nearly eliminating inter-cluster distribution differences; (4) Larger proppants tend to accumulate near fracture inlets, which can help ensure more uniform inter-cluster distribution. In contrast, smaller proppants are more susceptible to flow variations, often resulting in uneven placement across clusters. (5) Additionally, under high proppant concentrations, proppant dunes reach equilibrium sooner, and creeping motion dominates particle transport, significantly reducing inter-cluster placement non-uniformity. The proposed coupled DDM–TLM model can reasonably predict proppant behavior in multi-cluster fractures and underpins the optimization of shale gas fracturing treatments.
Deeply buried coarse clastic reservoirs of the Permian Upper Urho Formation in the Fukang Sag, Junggar Basin, exhibit pronounced reservoir-quality heterogeneity in pore systems and lithofacies architecture. However, how provenance-controlled sediment composition regulates mineral transformation and divergent diagenetic pathways, thereby controlling reservoir quality, remains unclear. This study integrates petrographic observations, XRD, SEM, MIP, EPMA, and bulk- and micro-XRF analyses to clarify the diagenetic evolution and the factors controlling reservoir quality in these deposits. The results indicate distinct provenance-controlled diagenetic pathways in two reservoir domains: (1) Reservoirs affected by the Xiquan Uplift Provenance, which contain intermediate-mafic volcanic materials, underwent stronger chemical weathering, enhanced mechanical compaction, and widespread illite-smectite mixed-layer mineral (I/S) cementation, leading to pore systems mainly composed of intercrystalline pores within clay minerals; (2) Reservoirs sourced from the Eastern Provenance, characterized by intermediate-acidic volcanic inputs, exhibit higher textural maturity and better fluid mobility, which favored the formation of early diagenetic authigenic chlorite coatings, the preservation of residual intergranular pores, and the dissolution of laumontite and feldspar; and (3) The alteration of the tuffaceous matrix differed according to diagenetic fluid chemistry. Micro-XRF elemental maps, EPMA oxide compositions, and mineral assemblage trends indicate that K-rich conditions promoted I/S enrichment, whereas Na-rich conditions favored laumontite formation followed by selective dissolution. These contrasting diagenetic pathways exert a first-order control on reservoir-quality heterogeneity. High-quality reservoirs are mainly developed in low-matrix, grain-supported thick sand bodies and sandstone interbeds within conglomerate successions, indicating that facies type, matrix content, and framework support are key screening criteria for reservoir prediction in deeply buried coarse clastic systems.
Pre-stack seismic inversion is an important tool for the quantitative interpretation of complex reservoirs. However, the increasing demands of deep tight sandstone exploration require a more integrated characterization of lithology, physical properties, and geofluid. Current inversion methodologies often treat these reservoir parameters separately, leading to fragmented understanding and redundant workflows. This study proposes a novel pre-stack seismic inversion method that simultaneously estimates lithology and physical properties of deep tight sandstone reservoirs. Its core innovation lies in establishing a direct, rock-physics-based link between seismic response and multiple reservoir attributes. The specific process involves: (1) Conducting a comprehensive rock-physics analysis to identify parameters sensitive to lithology, permeability, and geofluid types; (2) Deriving a novel reflection coefficient approximation through parameter combinations and mathematical simplification, followed by accuracy verification and feasibility assessment for seismic inversion; and (3) Implementing a model-constrained iterative reweighting Bayesian inversion scheme to reliably estimate model parameters. The effectiveness and reliability of the method have been validated through model tests and field data applications. This approach enables the identification of favorable zones within tight sandstone reservoirs, offering a feasible and efficient solution for their integrated seismic interpretation.
Cyclic-loading hydraulic fracturing generates alternating stresses and complex fracture networks in hot dry rock (HDR), but the predictive accuracy of existing models is limited by insufficient consideration of rock property degradation under cyclic loading. This study introduces an equivalent damage evolution equation to characterize the degradation of elastic modulus, permeability, specific heat capacity, and thermal conductivity, and establishes a thermal-hydro-mechanical (THM) coupled model for cyclic-loading hydraulic fracturing in HDR to simulate fracture initiation and propagation. The results show that under the cyclic hydraulic fracturing conditions examined, (1) When the natural fracture density reaches 0.006 fractures/m2, the total fracture length and damaged area increase by 6.63% and 9.44%, respectively. (2) Moderately reducing fracturing fluid viscosity effectively activates natural fractures. For example, a decrease in viscosity from 15 mPa·s to 5 mPa·s results in a 12.70% increase in fracture length and a 9.91% increase in damaged area. (3) A cycle period of 20–40 min/cycle is favorable for fracture network expansion, increasing the damaged area by 9.01%–19.59% and extending the fracture length by up to 21.65%. (4) Increasing the circulation flow rate from 10 m3/min to 16 m3/min accelerates wellbore pressurization, resulting in a 9.31% increase in fracture propagation distance and a 14.05% increase in damaged area. The proposed model effectively characterizes rock property degradation induced by cyclic loading and fracture evolution in HDR, providing theoretical support for optimizing cyclic hydraulic fracturing parameters and enhancing complex fracture network development.
In tight oil reservoir development, hydraulic fracture morphology critically controls post-fracturing flow behavior. However, conventional microseismic monitoring remains limited in real-time characterization of nonplanar fracture geometry. This study proposes a digital twin-driven approach for nonplanar fracture reconstruction and evaluation, enabling real-time fracture characterization in tight reservoirs. The results show that: (1) the reconstructed fracture morphology achieved a normalized relative geometric error of only 3.33% when experimentally validated against high-resolution laser scanning in a true triaxial hydraulic fracturing test, and demonstrated a computational speedup exceeding 700 times compared to the discrete element method under identical experimental conditions and specimen geometry; (2) the reconstructed fracture networks capture nonplanar propagation and fracture–natural fracture interactions, indicating that fracture complexity is jointly controlled by tortuosity and connectivity when the horizontal stress difference is below 5 MPa, but dominated by connectivity when it exceeds 5 MPa; (3) real-time fracture reconstruction enables the identification of potential inter-stage fracture communication, allowing engineers to adjust injection volume and stage spacing to mitigate interference and improve stimulation efficiency. These results demonstrate the proposed digital twin functions both as a monitoring tool and an integrated platform for real-time fracture reconstruction, evaluation, and operational optimization in tight reservoirs.
CO2 solubility and mineral trapping behavior are critical to the stability and effectiveness of integrating CO2 geological storage synergistically with gas field produced water (GPW) reinjection, a promising strategy for achieving co-benefits in pollution mitigation and carbon emission reduction. To investigate CO2 solubility-mineral trapping during co-injection with GPW-characterized by high salinity and complex ion composition-a series of CO2-GPW-rock interaction experiments and geochemical simulations were conducted using sandstone and limestone samples, together with simulated GPW of salinities ranging from 47.6 to 225.5 g/L. The results indicate that: (1) CO2 solubility-mineral trapping behavior is governed primarily by CO2 pressure, injection method, and GPW salinity, and is further influenced by calcium concentration and rock mineralogy. Under the experimental conditions, the CO2 solubility-mineral trapping capacity ranged from 9.03 to 11.01 g/L, with corresponding trapping proportions between 74.56% and 87.38%; (2) within a closed CO2-GPW-rock reactive system, the time-dependent CO2 solubility-mineral trapping proportion can be described by the cumulative Weibull model. The CO2 solubility-mineral trapping capacity increases with increasing CO2 pressure but decreases with increasing GPW salinity. A slight elevation in calcium concentration enhances CO2 solubility-mineral trapping at low CO2 pressures, despite concurrent increases in ionic strength and brine salinity. When the GPW salinity remains constant, the variation in calcium concentration exerts only a limited influence on CO2 solubility-mineral trapping; (3) a higher reactive mineral content in the reservoir enhances CO2 solubility-mineral trapping, and intermittent injection significantly improves this process; (4) the cumulative solubility-mineral trapping capacity can reach 22.13-38.01 g/L, representing 2.28-3.04 times the capacity achieved under single-injection conditions. These findings underscore the importance of carefully selecting storage sites and designing injection schemes in CO2 geological storage operations. (c) 2026 Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The performance of oil-based drilling fluids (OBDFs) is critical for maintaining drilling efficiency under conditions in which water-based fluids fail to perform effectively. Mudcake or filtercake thickness (MCT) is a key property of OBDFs because it directly influences wellbore stability and the extent of formation damage. Conventional methods for determining MCT rely on manual laboratory measurements that are time-consuming and cannot represent real-time downhole conditions, thereby limiting their value for operational decision-making and motivating the development of reliable predictive methods. This study proposes a novel framework for the near-real-time classification of MCT in OBDF systems. A comprehensive field dataset was compiled from five routinely measured, rapidly acquired laboratory parameters: mud weight, temperature, alkalinity, emulsion stability, and Marsh funnel viscosity. Four machine-learning classifiers—extreme gradient boosting (XGB), support vector machine, extreme learning machine, and multi-layer perceptron—were developed to classify MCT into three operationally meaningful categories: Excellent (≤1.0 mm), Good (1.0–2.2 mm), and Poor (>2.2 mm). The developed models achieved high classification accuracy, with the XGB algorithm demonstrating the most stable and reproducible performance (test accuracy: 0.98, F1-score: 0.98). Comprehensive evaluation—including receiver operating characteristic analysis, model confidence assessment, learning curves, group K-fold cross-validation, and external validation—confirmed the strong generalization capability of the XGB model, which achieved 94.81% accuracy when applied to completely unseen wells. Interpretability analysis using SHapley Additive exPlanations (SHAP) identified emulsion stability as the dominant predictive feature and revealed that parameter interactions (e.g., alkalinity–emulsion stability) vary dynamically across different MCT classes. The primary innovation of this study lies in reframing MCT prediction as a multi-class classification problem rather than a traditional regression task, enabling rapid and actionable interpretation of drilling fluid performance. The proposed framework provides a semi-automated, data-driven tool for near-real-time monitoring of MCT in OBDF systems, reducing reliance on slow laboratory measurements and supporting timely operational decisions that improve drilling efficiency and preserve wellbore integrity in complex drilling environments.
Gas condensate reservoirs constitute important natural gas resources; however, their development is frequently hindered by condensate banking and complex multiphase flow behavior. Naturally fractured gas condensate reservoirs present additional challenges because their dual-porosity and dual-permeability structure induces strong phase redistribution and nonuniform flow between matrix and fracture systems, thereby complicating reservoir characterization and compositional simulation. In this study, integrated laboratory experiments and numerical simulations were performed for a deep, rich, naturally fractured gas condensate reservoir. Depletion, diffusion, and core flooding experiments involving CO2, N2, and dry gas injection were conducted using fractured core samples. A dual-porosity and dual-permeability compositional model incorporating a five-spot well pattern was established to evaluate condensate liquid recovery and to quantify mass transfer between matrix and fracture networks. The effect of matrix-fracture permeability contrast on production performance was systematically analyzed. The results indicate that matrix permeability is a primary parameter controlling recovery in gas condensate reservoirs. The ratio of matrix-fracture permeability contrasts exerts a stronger influence on condensate liquid recovery than on natural gas recovery. Pressure maintenance through gas injection is critical for improving recovery performance. When reservoir pressure declines below the dew-point pressure, early gas injection is recommended to mitigate condensate accumulation in the near-well region. Among the injected gases evaluated, CO2 demonstrated superior pressure maintenance performance compared with N2 and dry gas.
The complex viscoelastic and shear-thinning behavior of slickwater fracturing fluids imposes competing effects on proppant transport, complicating the prediction of sand-carrying capacity and increasing the sand plugging risk. This study quantifies slickwater elasticity over a range of shear rates using the Weissenberg number (Wi) and establishes a fracture-scale shear-rate calculation method to estimate elastic energy at different flow velocities. The results show that: (1) the Wi strongly correlates with sand-carrying capacity, demonstrating its effectiveness in characterizing elastic-dominated transport behavior; (2) fracture experiment identify distinct settling-rate thresholds for slickwater systems with different polymer concentrations; (3) at these thresholds, fluids transporting equivalent proppant volumes exhibit identical elastic energies, indicating a the existence of a critical elastic-energy requirement for stable proppant suspension; (4) elastic-energy thresholds are established for three sand concentrations, allowing rapid prediction of sand-carrying capacity across slickwater systems with different viscosities; and (5) a field construction strategy derived from the predicted operating window is validated through field trials conducted both within and outside this window, with close agreement observed between the predicted and actual proppant-transport performance. This study provides a quantitative and practical framework for optimizing slickwater fracturing operations.
Gas hydrate plugging is a common yet hazardous problem during oil and gas reservoir exploitation, compelling the petroleum industry to invest substantial resources annually in mitigation strategies. Two novel hydrate kinetic inhibitors (HKIs), a PVP derivative (PVP-DP) and a PVCap derivative (PVCap-DP), were synthesized and systematically evaluated. Structural characterization by FT-IR, NMR, and TG analyses confirmed increased molecular weights and the introduction of additional polar functional groups relative to the present polymers. In pure water at a subcooling temperature of 6.2 K and a concentration (Cp) of 1 wt%, the methane hydrate induction times (Ih) for PVP-DP and PVCap-DP were 358 min and 395 min, respectively. These values significantly exceed those observed in distilled water (23 min) and in systems containing commercial HKIs, such as PVP (138 min) and VC-713 (272 min). Increasing Cp to 3 wt% further prolonged Ih to 911 min and 964 min, respectively. Even at a higher subcooling of 8.4 K, Ih remained considerable at 126 min and 158 min, demonstrating sustained inhibition under more severe thermodynamic driving forces. Synergistic effects were observed when HKIs (3 wt%) were combined with glycol (1 wt%), resulting in Ih values of 230 min and 268 min. Increasing the glycol concentration to 3 wt% maintained a strong inhibition performance, with Ih values of 211 min and 238 min even at a subcooling of 9 K. In addition, both derivatives exhibited effective inhibition in water/diesel emulsion systems. At 6.2 K subcooling, the PVP-DP (3 wt%)–water/diesel emulsion system achieved an Ih of 404 min, which was markedly longer than that of the uninhibited water/diesel emulsion (51 min), although the emulsion phase moderately reduced the inhibitor efficiency. Overall, PVP-DP and PVCap-DP demonstrate strong kinetic inhibition performance against the formation of natural gas hydrate in both aqueous and emulsion systems, indicating promising application potential in complex production environments.
During winter natural gas transportation, hydrate formation under low-temperature and high-pressure conditions frequently results in pipeline blockage and severe low assurance challenges. Although conventional thermodynamic hydrate inhibitors (THIs) are effective in shifting hydrate phase equilibrium, the application is constrained by high volumetric injection requirements and the associated operational costs, thereby driving research interest toward low-dosage hydrate inhibitors (LDHIs). This study integrates high-pressure pipeline flow simulations with molecular dynamics simulations to systematically evaluate the inhibition performance and elucidate the molecular-scale mechanisms of representative inhibitor classes in methane hydrates. Pipeline simulation results indicate that, at low additive concentrations: (1) the inhibition effectiveness of cations follows the order Al3+ > Fe2+ > Ca2+ > Na+, suggesting a strong dependence on ionic charge density; (2) at identical mass fraction, methanol exhibits greater thermodynamic inhibition performance than ethylene glycol. Notably, 5.0 wt% ethylene glycol accelerates hydrate formation kinetics, exhibiting an anomalous promotion effect. For kinetic inhibitors and their blends, the following observations were obtained: (3) PVP K30 exhibited optimal inhibition performance at 1.0 wt%, significantly extending the hydrate induction time; moreover, the combination of 1.0 wt% PVP K30 with 5.0 wt% methanol completely suppressed hydrate formation under the tested conditions while substantially reducing the required alcohol dosage; (4) molecular-scale analysis indicates that methanol and ethylene glycol primarily act by shifting the hydrate phase equilibrium and perturbing the hydrogen-bond network of water. In contrast, PVP K30 inhibits hydrate formation by disrupting hydrogen-bond structures and decreasing methane–water association through steric hindrance and interfacial adsorption. The blended system exhibits a clear synergistic effect between thermodynamic and kinetic inhibition, combining a phase equilibrium shift with delayed hydrate formation kinetics. This THI-focused investigation systematically clarifies the inhibition of mechanisms of representative additives and provides a scientific basis for selecting cost-effective LDHIs strategies for hydrate control in oil and gas pipelines, with direct relevance to mitigating hydrate blockage in field operations.
The vertical transfer of overpressure significantly influences the subsurface fluid dynamics, fault zone stability, and geomechanical drilling safety. However, the mechanisms governing vertical overpressure transfer through faults remain poorly understood, and few quantitative assessments have clarified how key geological parameters control the magnitude and evolution of vertically transferred overpressure. In this study, a conceptual model for overpressure vertical transfer was developed, and a sensitivity analysis of geological factors controlling this process was conducted using the DMflow simulator. The results indicate that fault-zone permeability, fault activity duration, sand body permeability, the number of sand bodies connected by a fault, and the initial overpressure difference exert a strong control on both the transfer process and the magnitude of the vertically transferred overpressure. In contrast, the fault dip and sand body spacing have a relatively minor influence on the vertical transfer overpressure. In permeable formations, vertically transferred overpressure dissipates rapidly; therefore, overpressure generated by multiple fault activation events cannot be effectively accumulated. The overpressure is uniform within permeable formations connected by a fault; however, the pressure coefficient is highest in the shallow formation. Overpressure transfer alters local fluid migration pathways. During overpressure re-equilibration, the development of a strong fluid potential gradient promotes the rapid upward migration of deep fluids into shallower layers along the fault. This understanding not only provides new insights into the mechanisms of overpressure generation in sedimentary basins but also has significant implications for predicting pre-drilling formation pressure and improving the understanding of fluid flow behavior within fault zones.
The vertical heterogeneity of the pore structure in deep coal seams with varying ash yields is a key control for coalbed methane storage and producibility; however, its specific impact on gas adsorption is not clearly defined. The focus of this study is the No.8 coal seam of the Carboniferous Benxi Formation in the Central-Eastern Ordos Basin. By integrating microscopic identification, proximate analysis, gas adsorption (CO2, N2, and CH4), and the multifractal theory, we quantitatively characterized the nanopore structure (micropores <2 nm and mesopores 2 nm–100 nm) of coal reservoirs with varying ash yields. The results indicate that (1) ash yield is the primary factor that controls the vertical evolution of pore structures in coal seams. In low-ash yield coal seams, the extent of thermal evolution and ash yield jointly constrain the heterogeneity of pore size distribution. In medium- to high-ash yield coal seams, the heterogeneity of pore structure and pore size distribution are predominantly constrained by ash yield. (2) As the ash yield vertically increases, the mesoporous pore volume and specific surface area initially decrease and subsequently increase, while the contribution of micropores to both pore volume and specific surface area continuously diminishes. Consequently, the total pore volume and specific surface area of the coal samples exhibit a two-stage reduction close to an ash yield threshold of approximately 20 %. (3) Further, the Langmuir volume for CH4 adsorption sharply declines below the 20 % threshold, followed by a gradual decrease; in contrast, the Langmuir pressure initially decreases and subsequently increases. Hence, the vertical increase in ash yield constrains the development of pore systems and diminishes pore connectivity, thereby reducing methane adsorption capacity and adversely affecting coalbed methane productivity. (4) Low-ash yield coal reservoirs are characterized by a rapid gas breakthrough and high productivity, whereas medium-ash yield coal reservoirs generally require prolonged depressurization to achieve peak gas production. These findings reveal that in medium-high rank coal, ash yield—and not thermal evolution—is the main factor that controls vertical pore evolution and methane adsorption efficiency. The quantitative ash yield threshold (20 %) established in this study provides a practical criterion for evaluating reservoir quality and predicting vertical variations in gas storage potential in the Ordos Basin.
The coupled chemo-mechanical impact of supercritical CO2–H2O (ScCO2–H2O) reactions on fracture geometry and nonlinear flow regimes in deep shale under confining pressures remains inadequately quantified. This study systematically investigates the effects of ScCO2–H2O–shale interactions on fracture morphology and flow properties under confining pressures from 15 MPa to 40 MPa by integrating XRD (X-ray diffraction), micro-CT, 3D surface profilometry, and multistage steady-state flow experiments. The results demonstrate that ScCO2–H2O exposure drives pyrite/feldspar dissolution and localized clay precipitation, resulting in fracture branching and macroscopic aperture regularization. Critically, confining pressure dictates the net hydraulic response: under low confining pressure (15–25 MPa), dissolution dominates, enhancing permeability, flow efficiency (Q/∇P), and pre-linear flow behavior (n < 1). At high confining pressures (30–40 MPa) mechanical compaction and mineral precipitation amplify flow resistance, shifting the flow regime toward quasi-linear behavior, as inertial effects become negligible compared to dominant viscous forces and increased flow resistance. Confining pressure thus critically mediates the dissolution–precipitation balance during ScCO2–H2O treatment, with an optimal window of 15–25 MPa identified for enhancing conductivity while minimizing clogging risk. These findings provide a quantitative framework for predicting stress-dependent flow evolution in chemically altered shale fractures.
This paper examines how natural gas disperses vertically when high-pressure pipelines with large openings fail in unconfined environments, providing insight into hazardous gas cloud development and behavior. A comprehensive study was conducted using a full-scale field experiment (1,219 mm diameter, 12 MPa pressure, 100 mm aperture) combined with a validated computational fluid dynamics (CFD) numerical simulation model to systematically analyze the coupling effects of pipeline pressure and ambient wind speed. The results indicate that: (1) Pipeline pressure determines the vertical jet scale, where jet height is positively correlated with pressure; at 12 MPa, the maximum jet height reaches 69.4 m (approximately 2.65 times that at 4 MPa), and the lower explosive limit (LEL) cloud area follows a quadratic polynomial trend.(2) Ambient wind speed significantly alters the diffusion trajectory; at a wind speed of 10 m/s, the LEL gas cloud area expands by 1.69 times compared to calm conditions, while the jet height is suppressed to 29.9 % of the calm wind value.(3) Our developed dynamic prediction model for the hazardous gas-cloud region achieves a determination coefficient of 0.975 and maintaining prediction errors maintained within approximately 12 %. The proposed empirical correlations and dynamic prediction model provide essential quantitative data support for safety-distance design and emergency-response decision-making for high-pressure natural gas pipelines.
