In this study, a numerical model of a partial wellbore is developed by coupling computational fluid dynamics (CFD) with the discrete element method (DEM) in order to simulate the operation of a double-circulation system (DCS) in coalbed methane (CBM) well drilling, which is a novel technique used for cuttings transport. The values of the flow field are computed by a fluid solver and the motions of the particle phase are calculated by the DEM, for which an additional multi-sphere particle model is integrated. After verification of the model, the analysis centers on the working mechanism, the DCS parameters, and optimization of the angle θ of the injection nozzles, which is the most critical parameter affecting the efficiency of the DCS. Simulations reveal the working details of the DCS and prove its applicability to cuttings transport, especially in the curved and horizontal parts of the well. The effects of viscosity and particle size are investigated, and a low-viscosity drilling fluid is recommended. The optimal range for θ is obtained as 30° to 50°. This work provides a reference for the engineering application of DCSs, and by feedback from drilling sites the reliability of the results can be verified.

A novel optimised back analysis method is proposed in this paper. The in situ stress field of an underground gas storage (UGS) reservoir in a Turkey salt cavern is analysed by the basic theory of elastic mechanics. A finite element method is implemented to optimise and approximate the objective function by systematically adjusting boundary loads. Optimising calculation is performed based on a novel method to reduce the error between measurement and calculation as much as possible. Compared with common back analysis methods such as regression method, the method proposed can further improve the calculation precision. By constructing a large circular geometric model, the effect of stress concentration is eliminated and a minimum difference between computed and measured stress can be guaranteed in the rectangular objective region. The efficiency of the proposed method is investigated and confirmed by its capability on restoring in situ stress field, which agrees well with experimental results. The characteristics of stress distribution of chosen UGS wells are obtained based on the back analysis results and by applying the corresponding fracture criterion, the shaft walls are proven safe.

Coalbed methane (CBM) is produced through desorption, diffusion and seepage processes. However, pressure during CBM production, especially the seepage process, is a very complicated problem. Methods for solving the pressure models for CBM reservoir are multidisciplinary and rather sophisticated. In this paper, an elementary and simple method for solving the CBM seepage model was proposed. First, a classical seepage model was built to study CBM seepage at variable flow rate. After the transformation of pressure into pseudo-pressure and dimensionless treatments, a definite problem for the CBM seepage model can be obtained. By Laplace transformation, the definite problem can be solved as a boundary value problem in Laplace space. Then, this boundary value problem was solved by the proposed method which is elementary and simple and its solutions have a similar structure to continued fraction. This explains why this method is called similar constructive method. With this method, solutions for the model of pressure response of CBM reservoir can be obtained. A corresponding program for the method was written, which can help engineers working on CBM reservoir solve similar problems even without pre-training. In addition to the typical analysis curves for well testing such as the conventional log-log graph for pressure and pressure differential and semi-log graph, another type of analysis curve, i.e., the log-log graph for first-order pressure derivative, was plotted. On such basis, the diagnosis of the pressure response of CBM well would be more accurate. Our results might be of great significance to the theoretical study on pressure responses of CBM reservoir. And results of this research could provide great simplicity for software developers to make well testing analysis software and well testing interpreters to interpret CBM well test data.

In the traditional safety assessment of casing string, some influencing factors are ignored for modelling convenience, which makes the casing string safety assessment effect of oil and gas well not very ideal. For complexity and randomness of casing load and its properties parameters in complex well conditions, BP artificial neural network is created in MATLAB based on the analysis of the influencing factors of casing string security. Casing string section whose safety assessment is more mature is taken as a sample to train the BP neural network. The trained network is applied to make case assessment. At the same time, GUI interface is applied to implement the visualization. The results show that safety evaluation of the casing string can be achieved by using BP neural network. The accuracy of the casing string network safety evaluation is high. It will realize the visualization of safety evaluation and provide more accurate and effective reference for the design of casing string.