The Fars Platform is a geological region with significant untapped potential for petroleum resources. Its unique structural and stratigraphic features, combined with favorable reservoir conditions, make it a key area for hydrocarbon exploration and production. To better delineate the Paleozoic petroleum system and mitigate future charge-related risks in the region, one- and two-dimensional petroleum system modeling was carried out. The primary objective of this study is to analyze the burial, thermal, maturation, and generation histories of the source rock(s), as well as the migration pathways, hydrocarbon charging history, and accumulation within reservoirs in the central part of the Fars Platform based on a comprehensive integration of geological, geophysical, and geochemical data. Geochemical investigation on potential source rocks showed that the Silurian hot shale of the Sarchahan Formation is the only effective source rock charging the Permian reservoir rocks. By conducting 1-D models in 6 wells, the maturation and hydrocarbon generation histories and also the heat flow for each well were obtained after calibrating the models with the measured temperature and vitrinite reflectance data. The resulting heat flows were consequently used in 2-D petroleum system modeling based on the interpretation of seismic data. The simulation results show that the occurrence of overpressure in the Dashtak Formation has caused the pressure to be different in the upper and lower layers, making this formation a suitable cap rock in the area. The hydrocarbons generated from the Sarchahan source rock started to expel in the eastern parts of the study area since the late Cretaceous, and expulsion occurred almost along the entire area during the Eocene. Before the Zagros orogeny happened in the Neogene, the hydrocarbon migration was mostly vertical while, after the orogeny, the lateral migration also occurred, mainly towards the regional high, and charged most of the traps. The large amounts of hydrocarbon, mostly in gaseous form, was expelled after the formation of structural traps. The results from this study can become the guideline for future exploration endeavors in the region to reduce risks and operational costs.

The discovery of ultra-deep strike–slip fault–controlled hydrocarbon reservoirs in the central Tarim Basin has renewed interest in the structural evolution and reservoir-controlling mechanisms of intracratonic strike–slip systems. Based on integrated drilling data, high-resolution 3D seismic reflection interpretation, and structural analog modeling, this study investigates the FI12 and FI17 fault zones in the Fuman area as representative examples. The results show that ultra-deep strike–slip faults exhibit combined lateral segmented growth and vertical stratified propagation, with secondary shear faults overlapping and stepping in both horizontal and vertical directions. To characterize fault activity in a reproducible manner, a semi-quantitative slip intensity framework is established using fault-zone width, structural relief, and segmentation complexity. Comparative analysis demonstrates that slip intensity is the first-order control on the scale and effectiveness of fault-controlled carbonate reservoirs: fault zones with higher slip intensity develop wider damage zones, stronger fracture connectivity, and larger reservoir volumes. Within individual fault zones, slip intensity is preferentially concentrated at lateral step-overs and relay zones of secondary shear faults, where large-scale fracture corridors form and hydrocarbon productivity is significantly enhanced. In addition, for reservoirs characterized by a lower-source–upper-reservoir configuration, hydrocarbon productivity is positively correlated with the proximity of vertical fault step-overs to the target reservoir interval. Shallower vertical overlap facilitates more efficient upward hydrocarbon migration, resulting in higher hydrocarbon abundance. These results establish a three-dimensional structural control model linking slip intensity, fault architecture, and reservoir effectiveness in ultra-deep carbonate strike–slip systems, providing a robust geological basis for reservoir prediction and exploration risk reduction in complex ultra-deep settings.

CO₂ sequestration has a critical role in mitigating climate change impacts, thus we rely on numerical simulations to capture the processes of CO₂ injection, migration, and long-term storage. This paper presents a comprehensive benchmarking study of an in-house built multiphase compositional simulator for CO₂ storage modelling applications, emphasizing the accurate modeling of trapping mechanisms within geological formations. We perform rigorous tests to benchmark the simulator's performance against established analytical solutions, focusing on the evolution of CO₂ plumes, leakage rates through abandoned wells, and interactions of CO₂ with the formation water. Our results demonstrate the simulator's robustness in handling complex subsurface phenomena, including variable property simulations and the effects of hysteresis on plume behavior. These comparisons offer insights into the effects of parameter choices and boundary conditions on the simulation outcomes. Our work not only validates the simulator against known analytical solutions and numerical benchmarks, but also lays a foundation for future enhancements in our code, particularly in the area of geochemical interactions and the assessment of CO₂ leakage on the security of the storage media.

Wellbore instability in chalk formations poses significant challenges during drilling and production due to low rock strength, fluid sensitivity, and creep. This study investigates the efficacy of diammonium phosphate (DAP) as a chemical consolidating agent to enhance chalk mechanical properties under simulated reservoir conditions. Austin Chalk core samples were treated with a 1 M DAP solution at 75 °C and 1000 psi confining pressure for 72 h to promote hydroxyapatite precipitation. Triaxial loading tests compared the treated and untreated specimens. Results demonstrated that the DAP treatment improved the confined compressive strength by 16%–8% across confining pressures (400–1600 psi). Mohr-Coulomb failure envelopes revealed a cohesion increase from 600 psi (untreated) to 1350 psi (treated), with unconfined compressive strength doubling to 3200 psi. These enhancements, attributed to hydroxyapatite cementation, indicate DAP’s potential to mitigate wellbore failure by strengthening the formation itself. The findings advance chemical stabilization strategies for chalk, offering a novel solution to reduce non-productive time and improve long-term well integrity in carbonate reservoirs.

During the drilling process in deep oil reservoirs with high temperature and high salinity, the drilling fluid faces the risk of performance failure. Experiments have shown that the high-temperature and high-salinity environment weakens the negative charges on the surface of bentonite, causing the particles to aggregate, destroying the network structure and losing its rheological properties, as well as its ability to carry rock and filtrate. To solve this problem, this study improved the Hummers method to prepare rigid graphene oxide particles (GO-Y). In the experiment, 0.05 wt% graphene oxide was added to the drilling fluid containing 4% bentonite. Under the conditions of 10 wt% NaCl and 160 °C, graphene oxide adsorbed onto the surface of bentonite, increasing the particle spacing, and its spatial steric hindrance effect inhibited the aggregation of bentonite in the high-temperature and high-salinity environment, maintaining a smaller particle size distribution, and thus preserving the network structure of bentonite in the drilling fluid. The results showed that the rock-carrying capacity of the drilling fluid increased by 75.3%, and the filtrate volume decreased by 19.7%. Moreover, after adding 4% graphene-based leak stopper to the water-based drilling fluid, the permeability decreased to 1.89 × 10 ⁻² mD, and the leak stop rate reached 91.7%. The synthesized graphene-based leak stopper is suitable for high-temperature and high-salinity environments and can provide technical support for the drilling development of deep oil reservoirs.

Although there are abundant shale gas resources in China, shale gas is generally buried much deeper than foreign countries. For large-scale development, there are still many core technologies that have not yet been solved. In this paper, we have analyzed microstructure of formation rock and its mineral composition, and the mechanism of wellbore instability is revealed by studying the petrophysical properties and characteristics of the wellbore instability strata in the Changning-Weiyuan area. The laboratory innovatively constructs the “solid phase intercalation-liquid phase expansion stripping method” and obtains high-quality graphene nanosheets. The results of the performance test and the HTHP filtration test on the graphene nanosheets show that it achieves the lowest HTHP filtration loss (8.0 mL) among tested additives, outperforming super-fine CaCO₃ (8.6 mL) and conventional agents (9.2 mL), while minimally affecting rheology. Other performance tests indicate that high-quality graphene nanosheets made by our laboratory can be well dispersed in solvent with almost no obvious aggregation and it has the median particle size ranges from 212 nm to 228 nm, which means it has perfect ability to plug micro-crack in the Changning-Weiyuan area. The oilfield application shows that adding 0.75% graphene nanosheets to the field mud significantly enhanced wellbore stability, achieving zero mud loss and a 94.6% drilling rate in the target zone, while reducing HTHP filtration to below 2.4 mL.

Shale gas is a key transitional low-carbon energy source, offering a cleaner-burning alternative to coal, reducing greenhouse gas emissions, and supporting energy security during the transition to renewable energy systems. However, its efficient production is challenged by issues such as fracturing fluid retention, which adversely affects gas flow. During well shut-in and flowback following hydraulic fracturing, fracturing fluid imbibes into the formation, redistributing within its complex pore structure and altering gas-water flow dynamics. This study develops a comprehensive gas-water relative permeability model for shale reservoirs, using fractal theory and porous media mechanics. The model incorporates key factors, including pore size distribution, fractal geometry, tortuosity, pore connectivity, and fluid-phase interactions within distinct fractal regions of the shale. The analysis shows that increases in fractal tortuosity, critical water saturation, fractal dimension in the large-pore fractal region, displacement probability in the small-pore fractal region, and imbibition time reduce water relative permeability. In contrast, increasing displacement probabilities in both fractal regions, pore coordination number, and imbibition time enhance gas relative permeability. These findings highlight the importance of mitigating aqueous phase trapping and optimizing fracturing fluid flowback to minimize formation damage and improve production rates. By advancing our understanding of fluid behavior under complex reservoir conditions, this study provides a theoretical framework for designing operational strategies that enhance shale gas recovery, supporting its role in meeting energy demands while reducing greenhouse gas emissions.

Fracability evaluation is a crucial basis for fracturing and production enhancement in tight reservoirs. Due to the complexity of the geological environment, factors influencing reservoir fracability exhibit significant uncertainty. Ignoring the uncertainty of relevant parameters and conducting fracability evaluation based on deterministic parameters may lead to deviations from actual fracability results. To address this issue, this paper proposes a comprehensive evaluation method for the fracability of unconventional oil and gas reservoirs, considering reservoir description uncertainty. Based on fundamental evaluation methods, a reservoir fracability evaluation model is constructed, incorporating the Monte Carlo stochastic simulation method to determine the comprehensive probability distribution of the reservoir fracability evaluation index. This approach enables a more scientific and reliable evaluation of reservoir fracability. The research results indicate that the assumed distribution of input parameters has a certain impact on fracability evaluation results, with normal distribution demonstrating significant disturbance resistance. Additionally, brittleness index is found to be the most sensitive factor affecting fracability evaluation. The proposed evaluation method and insights can provide theoretical references for the fracability assessment of highly heterogeneous tight reservoirs.

This study investigates the performance of various huff and puff (HnP) strategies for enhanced oil recovery (EOR) in the Sanish field of the Bakken formation, using a numerical model developed with CMG software. The model integrates PVT validation, CO₂ miscibility, swelling tests, heterogeneity, and history matching with field data. Several HnP strategies, including Supported (S HnP), Alternative Supported (AS HnP), and Alternative Zigzag Supported (AZS HnP), were evaluated. Key findings show that dual porosity and permeability are essential for accurate modeling, while CO₂ diffusion has minimal impact in field-scale simulations with high fracture spacing. The S HnP strategy improves oil recovery with 50% less CO₂ than the Normal HnP, and the AS HnP further enhances production. The AZS HnP outperforms both, offering higher oil recovery and better CO₂ utilization. Fracture length was found to influence recovery significantly, and the sensitivity of oil production to CO₂ injection rates was notably higher in the AZS HnP compared to the N HnP scenario. These results highlight the potential for optimized CO₂-EOR strategies in unconventional reservoirs.

Accurately forecasting the sealing failure behavior of the casing-cement sheath-formation assembly under various steam injection operational parameters and cyclic steam stimulation conditions remains challenging. Such unpredictability heightens the risk of seal integrity compromise in the wellbores of thermal heavy oil production. This paper develops a numerical simulation and analytical approach based on heat-fluid-solid interactions within the casing-cement sheath-formation system. It assesses the impact of potential cement sheath and interfacial failures in response to differing steam injection pressures, temperatures, injection rates, and cyclic steam volumes. This assessment leverages the established relationships between the temperature-dependent elastic modulus and Poisson’s ratio of cementitious materials, as well as the dynamics of wellbore pressure, temperature, and steam quality during steam injection. Experimental findings suggest that maintaining steam injection temperatures between 340 ℃ and 380 ℃ can effectively mitigate the risk of shear-induced damage and enhance the safety of the cementing interface. The injection rate appears to have a minimal impact on interface integrity. The extent of plastic strain in the cement sheath is proportionate to the size of the micro-annular gap at the interface. When the initial formation has an elastic modulus of 15 GPa, variations in the cement sheath’s elastic modulus do not influence the micro-annular gap size. However, in formations with an initial elastic modulus of 5 GPa, a lower elastic modulus of the cement sheath corresponds to a smaller micro-annular gap. The study concludes that a higher initial geostress and temperature, coupled with a high elastic modulus of the surrounding strata, are conducive to maintaining the integrity of the cement sheath interface.

Discharge of oily wastewater, generated from oil and gas production can lead to severe marine and soil contamination, posing long-term threats to ecosystems and water security. Therefore, developing environmentally sustainable, high-flux, and chemically robust separation membranes is crucial for green petroleum production and water reuse. In this work, pre-oxidized polyacrylonitrile/polyvinylpyrrolidone (p-PAN/PVP) nanofibrous membrane has been fabricated to address this challenge aforementioned. The PVP, during pre-oxidation, formed cross-linked junctions, reinforcing the mechanical stability and the resistance to harsh chemical conditions. Additionally, our membrane also exhibited superhydrophilicity in air, underwater super-oleophobicity, low oil adhesion, ultrahigh flux (>8500 L·m⁻²·h⁻¹·bar⁻¹), and >99.8% separation efficiency for both crude-oil-in-water and surfactant-stabilized emulsions. More importantly, the p-PAN/PVP membrane could maintain integrity and wettability under acidic, alkaline, and high-salinity environments (1 M HCl, 1 M NaOH, 10 wt% NaCl) as well as in organic solvents (N, N-dimethylformamide, N, N-dimethylacetamide, dimethyl sulfoxide, etc). Our study provides a sustainable strategy to protect vulnerable ecosystems and promote cleaner energy development.

This study developed a data-driven surrogate-box correlation to predict wax deposition rates in crude-oil pipelines and help address the limited generalizability of empirical and mechanistic models under variable flow and thermal conditions. Literature-derived dataset of 215 experimental and field observations was compiled with inputs as oil temperature T_o, wall temperature T_w, dynamic viscosityμ, wall shear stressσ, flow velocity v_f, wall temperature gradient ΔT, and wall concentration gradient ΔC, and target as wax deposition rateδ _W (g·m^-2.h^-1). After outlier control, standardization, and ANOVA-based feature engineering, Five supervised black-box models; SVR, Random Forest, MLP, Gradient Boosting, and KNN, models were trained with an 80/20 train–test split, 5-fold cross-validated, hyperparameter-tuned and evaluated using MSE, RMSE, MAE,R², and AAPRE. The top performing model, KNN, was modeled into an interpretable surrogate via elastic net (benchmarked against polynomial Ridge degree-2/3) to yield a closed-form correlation. KNN achieved excellent test performance (R² = 0.985, RMSE ~ 0.101, AAPRE ~ 5.09%), outperforming alternative models. The Elastic Net surrogate preserved predictive ability with balanced generalization (R² ≈ 0.61–0.65 for train/validation/test) while exposing parameter level effects and nonlinear interactions among temperature, viscosity, shear stress, velocity, and wall-scale gradients. When compared to a physics-based correlation, the surrogate exhibited tighter clustering to measurements, which indicates improved field relevance. The principal contribution of this study is a hybrid workflow that couples high-accuracy black-box learning with transparent surrogate modeling to help enable real-time monitoring and control, proactive pigging scheduling, and optimized chemical/thermal treatments of oil flow in pipelines. The resulting correlation offers a deployable, interpretable alternative to nontransparent machine learning models or assumption-heavy empirical relations, with clear value for flow-assurance planning and operational reliability.