Coal particles cleanout which is regarded as the key technology in the operation of coal bed methane (CBM) wells, play an important part in making steady production. In oil wells, Sand cleanout is operated by circulating a liquid or a multiphase fluid into the wellbore to bring sand particles to the surface. Although the sand cleanout operations have been applied successfully in most wells with high efficiency and negligible leakage, it would leak working fluid into coal bed formation, destroy the structure of coal bed and jam the formed channel of gas production. In this paper, a new continuous vacuum cleanout technology has been developed to effectively remove coal particles in CBM wells by employing a jet pump. The Concentric Tubing String (CTS) which is assembled by 3.5 inch tubing and 1.5 inch tubing is also introduced in, because there is no CCT technology in China at the moment. Detailed structure and principle of the coal particles cleanout technology system are described, while a theoretical model is formulated to optimally design the system based on the coal particles settling experimental data and jet pumping theory. It has been shown from field applications that the coal particles cleanout technology makes significant improvements in achieving high efficiency and preventing leakage in CBM wells. Moreover, the new technology reduces the skin damage and increase the production compared to non-vacuum CBM wells.
The exploitation and utilization of coal resources have caused serious ecological and environmental problems that are closely related to the movement and destruction of the overlying strata, especially the activities of the overlying key strata (KS). The existing KS calculation methods are characterized by low efficiency and high costs. This study proposes an object-oriented improved recursive algorithm (OORA) model to achieve efficient calculations for KS. An application program was developed and tested with the KS of the Xiadian coal mine, Shanxi, China. The calculation results were basically consistent with field observations, and the calculation depth was increased by 146.05 m. In addition, five typical KS calculation cases were selected for in-depth testing. The calculation time ranged from 0.175–0.225 s, and the calculation time was shortened by approximately three times compared to that with traditional methods. Therefore, it is feasible to apply the model algorithm for KS calculations, and the model provides benefits such as high efficiency and low costs.
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