The paper established an optimization model to optimize 3D well trajectory of gas hydrate in deepwater considering wellbore stability and sand control. The sensitivity analysis of wellbore stability and critical production pressure related to inclination angle and azimuth angle is made for well trajectory optimization. The optimization model of well trajectory takes drilling depth as objective function and wellbore stability, critical production pressure, kick-off point and dogleg severity as constraints. Artificial bee colony algorithm is adapted for calculating the established model. A case study is presented and it indicates that the established model, in which the effects of wellbore stability and critical production pressure is assessed, is able to optimize the trajectory for gas hydrate well.


Gas hydrates are crystalline substances composed of gas and water, which are widely distributed in high latitudes permafrost zone and continental margin sediments. With more and more data from laboratory simulation experiment and numerical simulation, the pilot production of gas hydrates in deepwater, in which the well trajectory contains only one vertical section, is completed. There are two main issues in the producing test of gas hydrates in deepwater including wellbore stability and sand control. How to optimize the well trajectory by considering wellbore stability and sand control is significant in gas hydrates well design.

Until now, many researchers have built models to design well trajectory, and a systematic theoretical framework of well trajectory design is forming, namely, some trajectory parameters are given, others can be calculated (McMillian, 1981; Liu and Shi, 2001; Sawaryn and Thorogood, 2005; Han, 2007; Sawaryn and Tulceanu, 2007). As shown in Fig. 1 and Fig. 2, the typical trajectory for single well includes three sections, namely, one vertical section, one build section, and one hold section, or five sections which contains one vertical section, one build section, one drop section, and two hold sections. The determination of well trajectory parameters is a constrained optimization problem in which trajectory length is the objective function. To abtain the optimum trajectory parameters, namely, the optimum solution of the well trajectory optimization model, the heuristic algorithms are routinely applied to solve the model. Kasrvai (2017) optimized the well trajectory by genetic algorithm. Atashnezhad (2014) designed the wellbore trajectory by particle swarm algorithm.

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