Supercritical-dense phase CO₂ pipeline transportation has been proven to have excellent economic and safety benefits for long-distance CO₂ transportation in large-scale. Hydrates are easily generated in the high-pressure and low-temperature sections, resulting in blockage, so it is necessary to build the prediction model for hydrate formation in the long-distance CO₂ pipeline transportation. In the prediction model of hydrate formation of our work, the phase equilibrium was determined by the Chen-Guo model, and the lateral growth of hydrate was calculated by the comprehensive growth model, and the hydrate growth was estimated by analogy with the condensation process. Subsequently, the prediction model for hydrate volume in the CO₂ pipeline was established considering the process of hydrate growth and water droplet distribution. The effects of thermodynamic conditions, impurities, and operating conditions on the hydrate formation were analyzed. The impurities can expand the temperature and pressure ranges for hydrate generation. The increase in the moisture content, the increase in the pressure, the decrease in the temperature, or the increase in the fluid velocity could increase the volume of hydrates in the pipeline. After running for 10 h, the hydrates volume in the pipeline with the moisture molar fraction of 0.05% is over 10 times that with the moisture molar fraction of 0.005%. In addition, by using the proposed hydrate formation prediction model, the hydrate formation in a supercritical-dense phase CO₂ long-distance pipeline was predicted, and a suggested cleaning cycle was achieved. This study can guide the operation of CO₂ long-distance transportation pipelines.

Supercritical CO₂ pipeline transportation is a critical component of the carbon capture, utilization and storage (CCUS) industry chain, where long distance operation introduces inherent risks of accidental leakage. During the leakage process of supercritical CO₂ pipelines, throttling pressure reduction and the Joule–Thomson effect generate distinct negative pressure wave characteristics. The magnitude of the leakage directly impacts localization effectiveness, particularly under small leakage conditions where negative pressure wave signals are less pronounced, so the leakage is difficult to effectively detect. To solve this problem, the mutual correlation function model for pipeline leakage was developed by using the mutual correlation analysis method, and it was verified by the dense-phase CO₂ leakage data from Trondheim University of Technology. Based on the TGNET software, the actual pipeline model of the Yanchang oilfield is established, and the captured leakage signal is imported into MATLAB for differential pressure conversion, using the verified cross-correlation function model of the differential pressure signal to calculate the time difference between the arrival of the negative pressure wave at the two ends of the pipeline. Finally, the actual leakage location was determined. The simulation results indicate that the leakage detection method based on mutual correlation analysis of negative pressure wave signals exhibits varying localization performance under different leakage rates. By enhancing negative pressure wave characteristics and utilizing mutual correlation analysis, this method effectively addresses the challenges of indistinct negative pressure wave features and difficult localization during small leakage conditions. When leakage exceeds 5%, the relative error is controlled within ±5.40%, meeting the preliminary localization requirements for rapid identification and regional determination in engineering applications. Through the application of actual engineering cases, it is shown that this method has high accuracy in pipeline leakage detection. These findings provide theoretical and methodological support for supercritical CO₂ pipeline leakage detection in the CCUS projects currently under construction.

CO2 transport pipelines, as a critical link in CCUS technology, are more prone to fracture propagation under the effects of environment and high pressure due to the special characteristics of CO2, resulting in ductile fracture incidents. However, the commonly used original Batelle two curves method (BTCM) has large errors applied to CO2 pipelines containing impurities. In this paper, a corrected BTCM based on a hoop stress calibration factor was proposed to evaluate the crack arrest ability of CO2 pipelines. The reliability of the modified model was verified based on the experiments data. The results show that the GERG-2008 equation of state is more suitable in predication of decompression wave velocity, and fracture propagation velocity model with a correction factor of c cf =2.0 was verified in quite good agreement with experiment results. This corrected BTCM that can be directly applied to engineering, provided theoretical basis and suggestions in the design and safe operation of CO2 pipelines containing impurities.