Jeonghwan Lee

A comprehensive approach to select completion and fracturing fluid in shale gas reservoirs using the artificial neural network

For the development of shale gas reservoirs, hydraulic fracturing is essential to create fractures and keep the fracture network open to help gas escape from rock matrix with low permeability. However, the extremely low permeability of shale gas reservoirs requires complex and time-consuming analysis to select optimum completion and fracturing fluids. This paper presents a comprehensive approach based on the artificial neural network (ANN) to determine completion methods and fracturing fluids for shale gas reservoirs. To develop the ANN system, the relationship between reservoir parameters and hydraulic fracturing was investigated, and the results were used to obtain ranges of key reservoir properties. Based on the learning data set generated from the categorized ranges, the optimum ANN architecture was designed by adjusting the ANN design parameters, such as training algorithms, and the number of hidden layers and hidden layer neurons. The developed system was also converted to a graphical user interface, to make it more practical for users to access the system. The system was validated by comparing the result values of the system with the desired values, and this revealed that the system showed a high accuracy of correlation factor of over 0.9. Field application for the system was also conducted by using field data and showed that the result values significantly matched with the targeted values. Therefore, the selection system can be an effective tool to determine the optimum completion methods and fracturing fluids in accordance with the reservoir characteristics.

Adsorption characteristics of the shale matrix in Mancos and Eagle Ford basins, USA

ABSTRACT This study presents an experimental apparatus to investigate the adsorption characteristics in shale samples of two major US basins. The adsorption measurement is based on volumetric method, and the results are analyzed by Langmuir isotherm at various pressures. To analyze the impact of temperature on the adsorption characteristics, the experiments were conducted on the samples. The experimental results revealed that the change of adsorption capacity became constant with the increase of pressure and the decrease of adsorption capacity was dependent on the increase of temperature. This study allows us to evaluate shale gas in place and production forecast through adsorption characteristics.