To address the modeling fragmentation and predictive deviation caused by the conventional “single-mechanism, weakly coupled, additive response” approach in formation damage research, this study proposes an integrated modeling framework for multi-mechanism coupling throughout the entire drilling and completion process. Five dominant damage mechanisms are unified into a multi-physics formulation featuring a dual solid–liquid module architecture and a shared-state coupling mechanism. A structural-state integrated damage function (SSIDF) is introduced to establish a continuous mapping from microscopic mechanism evolution to macroscopic permeability degradation. A feedback network encompassing scaling, clay swelling, and water blocking is further developed, achieving bidirectional dynamic coupling among reaction kinetics, interfacial transport, and saturation fields, and representing one of the most systematic coupling schemes currently known. The model is solved via a space-time multi-scale optimization strategy, ensuring strong numerical stability and scalability. Field validation demonstrates a prediction accuracy of 98.6%, representing an improvement of over 8% compared to traditional additive models. The model is particularly applicable to unconventional reservoirs such as deepwater formations, where multi-mechanism damage evolves rapidly and conventional additive models fail to capture dynamic coupling behavior.

A new drilling fluid additive-biomimetic strengthen wellbore stabilizer(JBWDJ) was prepared to solve the issue of wellbore collapse and instability in weakly cemented argillaceous unconsolidated sandstone natural gas hydrate reservoirs in the South China Sea. JBWDJ was developed by imitating the adhesion mechanism of mussel catechol groups underwater environment in this study. Polyvinyl alcohol(PVA) with the property of film-forming and tannic acid(TA) rich in catechol and pyrogallol groups were used based on hydrogen bond. It enhanced hydrate reservoir stability from three aspects: actively improving the bonding strength between clay mineral particles, inhibiting clay hydration dispersion and expansion, and stabilizing hydrate configuration. The experiment results showed that the core soil blocks soaked in JBWDJ for 16 hours remain complete in shape and have a certain compressive strength, while treated with solutions including water, polyacrylamide, and polyamine inhibitors are all in a loose sand shape. The compressive strength of the artificial core treated by 3%JBWDJ increased by 2.01 times compared with untreated core samples. Additionally, the adhesion force between atomic force microscope(AFM) probe modified by SiO2 microsphere and 5% JBWDJ reached 2314 nN. Shale cuttings treated with 3% JBWDJ had a rolling recovery rate of 80.85%, which can significantly improve the recovery rate of rock cuttings compared with rock cuttings treated by clean water(48.4%), polymer wellbore stabilizer(52.35%), and potassium chloride(26.3%). The core expansion height of the drilling fluid containing 3% JBWDJ is only 0.9 mm, compared with the core soil block expansion height treated by the drilling fluid system without JBWDJ, the expansion height can be reduced by 50%. Rheological testing and reservoir protection experimental evaluation show that the JBWDJ has good rheological properties and certain reservoir protection capabilities. Microscopic analyses including transmission electron microscopy(TEM), infrared spectroscopy, scanning electron microscopy (SEM), and energy dispersive spectroscopy(EDS) revealed the mechanism of JBWDJ. It is mainly to build a network structure through hydrogen bonding, adsorb on the surface of the rock, enhance the bonding between clay mineral particles, and form a dense biomimetic film on the surface. Meanwhile, it has a good effect on inhibiting the hydration expansion and dispersion of clay, thereby achieving the goal of improving the compressive strength of rock cores and strengthening reservoir stability. Furthermore, in-situ Raman spectroscopy comparative analysis showed that JBWDJ has no impact on the structure of type I methane hydrates. Hopefully, through the above mechanical performance testing and microscopic mechanism characterization, it can provide new materials for ensuring the stability of hydrate reservoir wellbore.

In this paper, to deal with the problem of insufficient temperature resistance of existing filter loss reduction agents for natural materials, we have searched for a green material, grape extract (GE), that is resistant to high temperatures, and evaluated the filter loss reduction performance and filter loss reduction mechanism of GE for the first time. The structure of GE was firstly characterized by Fourier transform infrared spectroscopy (FT-IR), and thermogravimetric experiments (TGA) showed that it had a good thermal stability. Subsequently, the effects of GE on the filter loss reduction of base slurry under high temperature conditions were evaluated by medium-pressure filtration loss and high-temperature and high-pressure filtration loss experiments, and the filter loss reduction mechanism of GE was analyzed by using zeta potential, particle size distribution, and scanning electron microscopy (SEM) experiments. The experimental results showed that after aging at 170 ℃ for 16 h, the medium pressure (API) filtration loss of the base slurry containing 3% GE was the smallest, 12.8 mL (less than 15 mL), and the high-temperature and high-pressure (HTHP) filtration loss at 120 ℃ was 24.0 mL, which was superior to those of the commonly used fluid loss controlling agent, carboxymethyl starch (CMS), polyanionic cellulose (PAC), and foreign polymer fluid loss controlling agent Driscal, and the filtration loss reduction effect of sulfonate copolymer (DSP-2) was comparable. GE has excellent performance in reducing the loss of filtration is mainly attributed to the strong adsorption on the surface of bentonite through hydrogen bonding and strong electrostatic effect, increasing the absolute value of the zeta potential of the surface of the bentonite, improving the electrical stability of bentonite at high temperatures, so that the bentonite at high temperatures is not easy to occur under the conditions of agglomeration, reducing the size of the bentonite, and better promote the dispersion of the bentonite, and the surface of the filter cake is smooth. In addition, the molecular structure of GE contains a benzene six-membered heterocyclic ring, this structure can enhance the rigidity of the molecular chain, it is not easy to curl and deform at high temperatures conditions, so that it maintains an excellent filtration loss reduction performance at high temperatures of 170 ℃. At the same time, the biotoxicity EC50 of GE is 133690 mg/L, which is greater than 30000 mg/L, and the biodegradability BOD5/CODcr of GE is 32.75%, which is greater than 5%, which indicates that it is non-toxic and easily biodegradable.

Reservoir protection plays a significant strategic role throughout the entire process of oil and gas exploration and development. The development of deep oil and gas resources faces complex environmental conditions and high technical demands. Effective reservoir protection technologies can help achieve the goal of “low input, high output, and significantly improved economic efficiency.” As such, the role of reservoir protection in various stages such as drilling, completion, and production is critical. In recent years, the widespread application of machine learning and other Artificial Intelligence (AI) technologies has provided intelligent solutions for reservoir protection, making smart reservoir protection technologies a major trend in the industry. A systematic review of recent literature on the integration of artificial intelligence and reservoir protection has been carried out to analyze the various model methods, the characteristics of sensitivity damage prediction data sets, and the development and application of intelligent decision systems used in reservoir protection. Through this review, the study identifies several key issues and limitations when applying “AI + reservoir protection” technologies. Firstly, the data quality is inconsistent, leading to unreliable inputs for model training. Secondly, the application scenarios are complex; the engineering environments of different oil and gas fields vary widely, and models may not perform effectively in these complex, heterogeneous conditions. Thirdly, models have low generalizability, and their adaptability in various scenarios is often limited, making it difficult to apply them universally across different field conditions. Finally, the supporting software and development systems for these models are not fully matured, restricting the practical implementation of these intelligent solutions. To address these challenges, several directions for future development are proposed. Firstly, improving data governance to enhance the quality of data is essential. This can be achieved by constructing a high-quality reservoir protection database, which would provide reliable data for training and optimizing intelligent models. Secondly, it is crucial to integrate domain-specific knowledge from the reservoir protection field into intelligent models. Incorporating expert knowledge into the models can improve their accuracy and predictive performance, making them more suitable for real-world applications in reservoir management. Thirdly, model interpretability should be enhanced. Increasing the transparency of decision-making processes within AI models will help build trust among technical personnel in the predicted results, thereby encouraging their acceptance and adoption of these systems. Finally, there is a need for the development of intelligent decision support systems that can handle large models, ultimately facilitating more advanced, high-level smart solutions for reservoir protection.

To address the challenges of the oil-based drilling fluid system’s deteriorating rheological properties and insufficient plugging pressure resistance under high-low temperature cycling conditions in the Yaha gas storage reservoir drilling, a temperature-sensitive high-temperature thickener, RHT, was developed. Optimized plugging materials and supporting agents were selected to construct a high-temperature resistant oil-based drilling fluid system. Characterization methods, including infrared spectroscopy, nuclear magnetic resonance hydrogen spectra, thermogravimetric analysis, and differential scanning calorimetry (DSC), were used to analyze RHT’s molecular structure, thermal stability, and temperature-sensitive characteristics in depth. The systematic evaluation of its rheological control in emulsions and oil-based drilling fluids was conducted. Experimental results showed that RHT significantly improved the shear-thinning and thixotropic properties of the emulsion, demonstrating excellent rheological control capabilities under high-low temperature cycling conditions. At 80 ℃, the dynamic yield stress increased by 87% without any increase in plastic viscosity; at 220 ℃, the dynamic yield stress increased by 220%, with a dynamic plastic ratio of 0.49 Pa/(m Pa·s). The drilling fluid system maintained strong rock-carrying capacity after aging at 220 ℃ and effectively sealed 20~40 mesh sand beds and 1~3 mm cracks, achieving a maximum pressure resistance of 8 MPa. In the field application of the Yaha gas storage reservoir well X, this system significantly enhanced the rock-carrying and plugging performance of the drilling fluid, reducing complexities such as fluid loss and stuck pipe incidents, thereby providing strong technical support for the efficient development of the Yaha gas storage reservoir.

Addressing the inherent challenges of low recovery rates and difficulties in shale gas extraction, this study investigates the application potential of CO₂-enhanced shale gas recovery (CO₂-ESGR) coupled with carbon sequestration (CS). Utilizing low-field nuclear magnetic resonance (NMR) technology, we conducted real-time monitoring of methane adsorption and desorption processes within collected shale samples. Through the analysis of T₂ spectra and corresponding peak areas, we achieved quantitative differentiation among adsorbed CH₄, free CH₄ within pore spaces, and free CH₄ within fractures. The results demonstrate that within a pressure range of 0.01–10 MPa, the total methane volume increased progressively from 79.4 to 177.83 cm³/g. Following CO₂ injection, a significant weakening of the short-T₂ signal (representing adsorbed CH₄) was observed, accompanied by a concomitant enhancement of the long-T₂ signal (representing free-phase CH₄). Furthermore, depressurization desorption experiments revealed that CO₂ injection increased the methane desorption rate by approximately 10%, while simultaneously facilitating the long-term, stable sequestration of CO₂ within the shale matrix. These findings not only validate the mechanism of competitive adsorption, whereby CO₂ enhances shale gas recovery, but also highlight the significant carbon sequestration potential of shale reservoirs. Consequently, this research provides a crucial theoretical basis and technical support for advancing both shale gas development and carbon emission reduction strategies.