Trilinear fuzzy seepage model of shale gas reservoirs with multiple fuzzy parameters

This paper focuses on establishing the trilinear fuzzy seepage model with multiple fuzzy parameters for shale gas reservoirs. Different from the conventional seepage models of shale gas reservoirs, the multiple fuzzy parameters seepage model uses fuzzy numbers to describe some parameters with uncertainty. Firstly, the multiple fuzzy parameters seepage model is constructed based on fuzzy concepts. The fuzzy structure element method and the centroid method are used to solve the fuzzy seepage model and defuzzify, respectively. Secondly, the advantages of the development fuzzy model over the conventional seepage model are discussed and illustrated through numerical examples and simulations. Finally, to further study the seepage laws inside shale gas reservoirs, this paper explores the sensitivity of relevant main control parameters to gas production based on the development model.

Challenges in the Preservation of Disaster Remains – Example of the Chelungpu Fault Preservation Park

Taiwan is located along the boundary of the Eurasian and the Philippine Sea plates and experiences tens of thousands of earthquakes each year. Based on historical records, Taiwan has had several earthquakes of magnitude greater than 7.0. Notable and deadly quakes occurred in 1906 (Meishan Earthquake), 1935 (Hsinchu-Taichung Earthquake), and 1999 (Chi-Chi Earthquake). Statistically, Taiwan has had a major earthquake every 30–60 years. Therefore, earthquake museums are needed for long-term earthquake education and geoheritage exhibitions. Earthquake museums highlight disaster risks and preparedness information. The purpose of preserving earthquake remains is to educate visitors about Taiwan’s natural disasters and provide a memorable experience that inspires earthquake preparedness. The Chushan trench across the Chelungpu fault is a good example of Chi-Chi Earthquake rupture. This trench has recorded the five most important earthquake events on the Chelungpu fault. Although the Chelungpu Fault Preservation Park (CFPP) has worked to preserve these earthquake remains, they have been threatened due to seepage over the years. The aim of this paper is to analyze trench seepage and explore the development of an anti-seepage model, to provide a reference for the preservation of earthquake remains and museum development worldwide.

Improving Dam Seepage Prediction Using Back-Propagation Neural Network and Genetic Algorithm

Statistical model is a traditional safety diagnostic model for dam seepage. It can hardly display the nonlinear relationship between dam seepage and the load sets and has the disadvantage of poor extension prediction. In this paper, the theories of Back Propagation Neural Network (BPNN) combined with Genetic Algorithm (GA) are applied to the seepage prediction model. Taking a typical dam in China as an example, the prediction results of BPNN-GA model and statistical model are compared with the monitoring values. The results show that the improved dam seepage model enhances the ability of nonlinear mapping and generalization and makes the seepage prediction more accurate and reasonable in the near future. According to the established criterion, the safety state of the dam in flood season is evaluated.