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Summary Gas-oil two-phase flow usually occurs during gas influx into the wellbore annulus of deepwater drilling with oil-based drilling fluid or gas-oil production from the wellbore annulus. A flow pattern transition often is used in well control or in production parameter design. Related studies primarily have focused on gas-water two-phase flow, which is significantly different from gas-viscosity oil two-phase flow. We conducted experiments on a facility that included a flow section that was 13 000 mm long, with a 60-mm inner pipe and a 100-mm outer pipe in the annulus. A range of oil viscosities from 16 to 39 mPa∙s has been studied. The superficial gas and oil velocities varied from 0.55 to 17.077 m/s and from 0 to 0.414 m/s, respectively. A flow pattern was identified based on visualized analysis using electrical capacitance volume tomography (ECVT) and void faction wave analysis. Flow pattern maps of different viscosities were plotted based on measured data. Transition criteria based on Froude number and Archimedes number were established. The new model was compared with gas-water two-phase flow transition models and validated with experimental data. The effect of viscosity on flow pattern transition was revealed. The transition boundary of the bubble to slug flow and slug to churn flow both moved in the direction of smaller superficial gas velocity with an increase in oil viscosity. There may exist a critical viscosity value when churn flow transited to annular flow. When the viscosity was lower than this critical point, the above result was the same for churn to annular flow when the superficial oil velocity was low. With an increase in the superficial oil velocity, however, the boundary gradually changed to high superficial gas velocity as the oil viscosity increased. When the viscosity was larger than the critical point, the oil viscosity had a slight influence on the transition.

Summary The exploration and development of offshore oil and gas have greatly alleviated the tension of global oil and gas resources. However, the abnormal pressure of offshore reservoirs is more common compared with terrestrial oil and gas reservoirs, and the marine geological structure is complex, with the development of faults, fractures, and high and steep structures, which leads to the strong anisotropy of formation pore pressure distribution and uncertainty of pressure system change. In this paper, considering the corresponding characteristics of the randomness of the formation pressure prediction results in the Eaton equation for their respective variables, a formation pressure inversion method based on multisource information, such as predrilling data, bottomhole while drilling data, seabed measured data, and surface measured data, is established. On this basis, combined with the data of a well in the South China Sea, the variation law of the uncertainty of formation pressure prediction results under the conditions of predrilling data, measurement while drilling (MWD) data, and their mutual coupling is analyzed. The simulation results show that the uncertainty distribution of formation pressure prediction based solely on predrilling data shows linear accumulation trend with well depth, and the formation pressure inversion method based on multisource information can significantly curb the increasing trend of uncertainty when MWD data are introduced. Therefore, through the analysis of typical change patterns of monitoring parameters under normal/abnormal conditions during drilling, combined with the method of multisource information, the abnormal pressure information can be accurately predicted and inversed, which provides important support for wellbore pressure regulation under complex formation conditions.

Summary Gas entrapment is a typical phenomenon in gas-yield stress fluid two-phase flow, and most of the related research focuses on the entrapped condition of the single bubble. However, the amount of entrapped gas, which is more meaningful for engineering, is rarely involved. In this paper, a theoretical model for calculating the maximum gas entrapment concentration (MGEC) is established for the first time. The critical distance between horizontal and vertical entrapped bubbles was determined by the yielded region caused by the buoyancy and the coupled stress field around the multiple bubbles. The MGEC is the ratio of a single bubble volume to its domain volume, which is calculated from the distance between the vertical and the horizontal bubbles. By comparing with the experimental results, the average error of MGEC calculated by this model is 4.42%, and the maximum error is 7.32%. According to the prediction results of the model, an empirical equation that can be conveniently used for predicting MGEC is proposed.

Summary The cost of offshore drilling operations can be significantly reduced by discharging drilling cuttings into the seabed. However, this leads to accumulation of cuttings piles on the seabed near the drilling site. A certain thickness of cuttings piles changes the original trend of the seabed terrain undulation condition, thus bringing potential safety hazards to the underwater installation of production manifolds. Moreover, the interaction between cuttings and ocean currents near the cuttings piles causes the geometric shape of cuttings piles to evolve over time, which makes it more difficult to accurately predict their characteristics. On the basis of the force analysis of cuttings, considering the effects of cuttings properties (cutting size, density) and ocean-current velocity on the geometric characteristic evolution of the formed cuttings piles, a continuous model for describing the evolution of the returned cuttings piles is established in this study. This model can quantitatively characterize the functional relationship between characteristics of cuttings piles and relevant parameters (current velocity, cutting size, evolution time), and predict the location and geometry characteristics of the cuttings piles evolving into a stable state in ocean currents. Comparing the measured data in laboratory experiments and at an offshore drilling field, the relative error of the model amounts to less than 10%, which demonstrates its rationality. Simulation results show that there will be significant changes in the geometry of cuttings piles before and after the evolution, in which the intensity is correlated with current velocity and cuttings size, and cuttings piles might even split into several parts under certain conditions. The simulation and analysis of the transport and deposition of cuttings returned from the wellhead on the seabed is highly significant for the guide and optimal design of underwater production manifolds.

Hydrates cause serious flow assurance problems during deepwater operations (e.g. well testing). In order to efficiently prevent wellbore/pipeline blockage, it is of great importance to have a good understanding of hydrate formation, deposition and blockage behavior in the flowline. In this work, a model is developed to describe the development of hydrate blockage in the wellbore. The results indicate a non-uniform hydrate layer is formed on the inner wall along the testing tubing during deepwater gas well testing. With the proposed model, the position where hydrate blockage is most likely to occur can be identified. The blockage severity in terms of dimensionless hydrate layer thickness can also be assessed. Based on the model, a method is developed to prevent hydrate blockage with lower inhibitor consumption. We recommend that testing operations should be run within the Hydrate Blockage Free Window (HBFW). The HBFW refers to the period from the beginning of testing operations to the moment when a significant pressure drop increase is encountered. Implementation procedure of the proposed method is developed and further illustrated through case studies. The inhibitor consumption is much lower compared with the current over-inhibition THI-based method. This work provides possible ways to overcome the shortcomings of the current over-inhibition THI-based method.

To overcome the deficiencies of current porosity prediction methods, the XGBoost algorithm is introduced to construct a model for porosity prediction, and the obtained model is optimized by the grid search method and genetic algorithm. First, the optimal values of the three integer hyperparameters and the ranges of optimal values for the five floating-point hyperparameters of the XGBoost algorithm are determined by the grid search method. Then, the optimal values of the five floating-point hyperparameters of the XGBoost algorithm are determined with the genetic algorithm based on the determined value ranges. In this way, the model for porosity prediction based on the XGBoost algorithm and optimized by the grid search method and genetic algorithm (GS-GA-XGBoost) is constructed, and it has eight hyperparameters with determined optimal values. Compared with other porosity prediction methods, our method solves the problems such as the strong subjectivity and poor generalizability of conventional logging interpretation methods and the insufficient generalization performance of machine learning methods in previous porosity prediction studies, and the accuracy of the constructed model for porosity prediction is also greatly improved. Specifically, the RMSE, MAE and MAPE generated by GS-GA-XGBoost on the test set are 0.527946, 0.155880 and 0.020500 respectively, while those generated by linear regression (LR), support vector regression (SVR), random forest (RF), the XGBoost algorithm with default parameters (XGBoost) and the XGBoost algorithm optimized only by the grid search method (GS-XGBoost) on the test set are 3.535521, 2.801047, 0.375713, and 2.695310, 2.002280, 0.283582, and 1.015801, 0.638878, 0.085942, and 2.781069, 1.860557, 0.293334, and 1.380065, 0.979419, 0.128486, respectively. Finally, the multithread technology is introduced to improve the computational speed of GS-GA-XGBoost. GS-GA-XGBoost provides some technical references for the construction of porosity prediction models for oil fields in Northern Shaanxi, China, and other regions.

Natural gas hydrates may be the world's future resources, but extracting from the reservoirs involves accurately understanding the transport mechanism of the fluids caused by hydrate dissociation. In this paper, based on Darcy's unsaturated soil mechanics theory, we establish a coupling model of two-phase flow and heat transfer caused by hydrate dissociation, which considering methane gas compressibility and capillary force naturally. The new model is validated through Masuda's test dataset, and notably, the experimental phenomenon of the small peak in the gas pressure of the far-end boundary (Run 4) is reproduced for the first time. Additionally, an implicit function of pore pressure and time in the initial stage of hydrate dissociation is deduced to interpret the in-situ pore accumulation of the gas generated in dissociation, which leads to a more comprehensive description of the migration mechanism of hydrate reservoir fluids. Furthermore, the initial hydrate saturation of the Run 4 sample in Masuda's test is proved to be closer to 0.501 instead of 0.443 that the author reported, which can help Masuda's test dataset being a benchmark for the hydrate dissociation researching in future. Thus, this work provides further insight into the migration mechanism of the gases caused by hydrate dissociation and services practical support for efficiently and safely extracting methane gas from the hydrate reservoirs.