(626a) Characterization of Factors Affecting the Gas Well Deliverability of  the Jiaoshiba Shale Gas Field by Multivariate Statistical Analysis | AIChE

(626a) Characterization of Factors Affecting the Gas Well Deliverability of  the Jiaoshiba Shale Gas Field by Multivariate Statistical Analysis

Authors 

Zhang, Y. - Presenter, University of Regina
Zeng, F. - Presenter, University of Regina
Mei, H. - Presenter, Southwest Petroleum University
Guo, P. - Presenter, Southwest Petroleum University
Zhang, M. - Presenter, Yangtze University
Ju, B. - Presenter, Southwest Petroleum University
The Longmaxi shale gas in the Jiaoshiba Shale Gas Field is the first and the largest successfully developed shale gas in China. The analysis of controlling factors of deliverability of gas wells plays a significant role in efficiently developing shale gas reservoirs. However, there are few methods analyzing the key factors of deliverability of shale gas wells by considering both geological characters and engineering parameters. In this study, the reservoir characteristics, the drilling and completion data, fracturing data (including the well logging interpretation of horizontal section, the track and layer section that the well bore passed through, and fracturing parameters) and production data of 86 gas wells in the Wufeng-Longmaxi shale, Jiaoshiba Shale Gas Field in Eastern Sichuan Basin, China are statistically analyzed and ordered by multivariate statistical analysis. The gas well deliverability is described by absolute open flow potential and 9 factors (physical parameters of reservoir, including density of rock, porosity, total organic carbon, brittle mineral content of rock and drilling and fracturing engineering quality, including horizontal length of gas well, horizontal length ratio through different stages in the formation, number of fracturing stages, liquid volume, and sand amount) that may affect the deliverability of shale gas wells are considered. The results reveal that the absolute open flow potential has a close relationship with porosity, total organic carbon, brittle mineral content and total fluid volume. The multivariable nonlinear regression models of absolute open flow potential with different key factors considered are built, and the prediction results are reliable by goodness-of-fit test acceptable with real gas well deliverability testing data. The research methods and results in this study can provide a reference basis for reasonable production rate allocation, design, and adjustment of development plan for the shale gas reservoirs.

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