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New equation for predicting Critical desorption pressure of coal seam gas based on BP neural network

The exploration and development of coalbed and coalbed methane is the key scientific and technological research direction of China's "Thirteenth Five-Year Plan". Eastern Yunnan and western Guizhou is an important coal and CBM resources area in southern China, with the CBM geological resources of the Upper Permian accounting for about 10% of the whole country (oil and gas resources strategic research center, ministry of land and resources, 2006) having the geological characteristics of multiple and thin coal seams, high stress, weak water rich, and complex coal structure (Lin, 2014; Xu, et al., 2016; Jia et al., 2016). Commingling production is the best choice for the development method in this area. Some single wells have higher production, but generally there are scientific problems in single-well or well-combined layer production and production instability, unsatisfactory development results, and difficult to effectively identify the contribution of production layers. The critical desorption pressure (Pcd) is the basic measure of whether the multi-gas system can be combined and drained and it is also the basic index of effectively determining the contribution of multiple layers (Zhang et al., 2014; Zhou et al., 2016). If the difference between the critical desorption pressures of the multi-productive layers is too large, it means that it is not suitable for the combined production and drainage and it is easy to cause reservoir damage. In the initial stage of exploration and development, predicting the critical desorption pressure is not only the need of the optimal combination of production layers, but also the need of identify the gas production sequence and analyze the contribution of the production layers. For this reason, the Yuwang block in Laochang of eastern Yunnan was chosen as an example. Based on the large amount of basic data, test data and related research accumulated in this block (Ju et al., 2019; Yang et al., 2019). Based on the formula of critical desorption pressure, this paper discusses the main controlling geological factors of critical desorption pressure, adopts the neural network analysis method, and finally establishes the prediction model for application.