Shale oil represents a relatively new form of unconventional oil and gas resource, and the extensive exploration and development of shale oil resources carry significant implications for China’s oil and gas supply and demand dynamics. At present, within the realm of low-maturity shale oil extraction technologies, the reservoir must be subjected to elevated temperatures ranging between 400 to 60 °C. Prolonged exposure of wellbores to such high temperatures can result in a substantial decrease in cement strength, the formation of microcracks due to cement cracking, and damage stemming from thermal stresses on the casing. Casing damage stands out as a prominent factor contributing to wellbore integrity failures and well shutdowns within the context of shale oil development. Given the limited natural energy reservoirs of shale oil formations, it becomes necessary to supplement the reservoir’s energy during the development process. Furthermore, shale oil exhibits high viscosity and poor flowability, and conventional water injection methods yield limited efficacy. This situation can induce significant shifts in the stress field and rock mechanical parameters, potentially activating specific formations and complicating the load dynamics on the casing. Consequently, the risk of failure increases. In light of these considerations, this study uses numerical simulations to study the integrity of high-temperature injection and production wellbores in shale oil and aims to encompass a comprehensive evaluation and analysis of the principal factors that influence casing damage, the fluctuations in thermal stress, and the yield strength of various steel grades of casings exposed to alternating stress conditions. Subsequently, this paper developed a model for simulating the temperature and pressure within shale oil and steam injection wellbores to support engineering design analysis. The research results indicate that the application of pre-stress results in a significant increase in stress at the casing pipe head while causing a noticeable decrease in stress within the pipe wall. When N80 casing is used, the entire casing experiences thermal stresses surpassing the casing’s yield limit. Stress concentration may arise at both ends of the external seal, potentially leading to casing contraction, shear failure, and, under non-uniform stress conditions, casing bending deformation. The temperature of steam injection significantly influences the temperature field of the casing wall, with stress values experiencing a marked reduction when the steam injection temperature decreases from 350 °C to 200 °C, underscoring the substantial impact of temperature on casing thermal stress. As the steam injection process advances along with injection-production cycles, shear stresses at the interface can exceed the bond strength, resulting in relative slippage between the cement and the casing. The bonding force between the wellbore and the cement primarily depends on the interface’s friction, particularly in the context of friction during wellhead lifting. This study endeavors to determine rational injection and production parameters under varying conditions, optimize completion methods, reduce casing damage, and extend the casing’s operational life; it aims to offer critical technical support for the safe and efficient development of shale oil resources.

In offshore drilling, accidents such as gas invasion, overflow, and kicks are unavoidable, and they can escalate into blowouts and other catastrophic events, resulting in casualties and significant economic losses. Therefore, ensuring drilling safety requires precise monitoring of gas invasion and overflow. Currently, most overflow monitoring methods used at drilling sites are based on threshold criteria. However, the monitoring parameters obtained during actual drilling operations often contain noise signals, which makes it challenging for threshold-based methods to achieve a balance between improving accuracy and minimizing false positives. This paper proposes a novel method called Pattern-Recognition-based Kick Detection (PRKD) for diagnosing overflow in offshore drilling. The PRKD method utilizes the overflow evolution process by integrating multiphase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. By analyzing the shape and wave characteristics of the curves, PRKD effectively detects and monitors gas intrusion and overflow based on single parameters. Through case analysis, it is demonstrated that the proposed method achieves high precision in monitoring drilling overflow while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations. The case analysis shows that by integrating the probabilistic information of pre-drilling kicks and various characteristic parameters, when the noise amplitude is less than 8 L/s, the PRKD model exhibits superior detection performance. Moreover, when the noise amplitude is 16 L/s, the PRKD model detects the continuous overflow approximately 200 s after the actual overflow occurs and predicts a 95.8% probability of overflow occurrence at the specified location, meeting the on-site requirements. The gas invasion monitoring method proposed in this paper provides accurate diagnostic results and a low false positive rate, offering valuable guidance for gas invasion monitoring in drilling operations.

CO₂ sequestration is a kind of technology that can effectively mitigate the greenhouse effect, and the wellbore integrity of the storage system is the key issue to ensure successful CCUS. Failure to timely diagnose tubing leakage in offshore gas wells with high CO₂ will lead to annular pressure risk and wellbore corrosion problems. The annular pressure caused by tubing leakage is characterized by high pressure and rapid rise rate, resulting in wellhead jacking, gas leakage, and wellbore structure corrosion, which has become the main cause of wellbore integrity failure in offshore gas wells. Therefore, a model of heat and mass transfer and distribution in offshore gas wells was established firstly, and the physical process of gas leakage and accumulation was described based on the pinhole model and the principle of gas PVT characteristics and volume compatibility. The results show that the depth and equivalent size of the leakage point are two important factors affecting the pressure rise process and leakage rate. Taking case well parameters as an example, after inversion calculation, the annulus pressure in case well was 23.0MPa, the leakage point equivalent diameter was 2.3mm, the maximum leakage rate was 0.30m³/min, and the wellbore safety risk is relatively high. Mechanical repair and chemical plugging agent are recommended to seal the tubing leakage. These risk assessment technologies provide reference for wellbore integrity design and management to reduce CO₂ leakage risk caused by wellbore integrity failure.

In offshore drilling, accidents such as gas invasion, overflow, and kicks are inevitable, and they can escalate into blowouts and other catastrophic events that result in casualties and substantial economic losses. Therefore, maintaining drilling safety requires accurate monitoring of gas invasion and overflow. The majority of overflow monitoring methods currently utilized at drilling sites are threshold-based. However, monitoring parameters acquired during actual drilling operations frequently contain noise signals, making it difficult for threshold-based methods to strike a balance between improving accuracy and minimizing false positives. In this paper, Pattern Recognition-based Kick Detection (PRKD) is proposed as a novel method for diagnosing overflow in offshore drilling. This method utilizes the overflow evolution process by integrating multi-phase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. The PRKD effectively detects and monitors gas intrusion and overflow based on single parameters by analyzing the shape and wave characteristics of the curves. The case analysis demonstrates that the proposed method for monitoring drilling overflow achieves high precision while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, the PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations.