الفهرس 
الفصل الاولOnly 14 pages are availabe for public view
 |  | from | 198 |  |  |
| | | from | 198 | | |
Abstract
Accurate prediction of production levels is crucial for the development of shale gas reservoirs. Empirical decline methods are widely used in the oil and gas industry due to their simplicity and effectiveness. However, these methods often fail to provide accurate predictions for wells with short production period experiencing transient flow followed by boundary-dominated flow. To address this pressing issue, sixteen empirical methods are compared based on their principles and characteristics. The findings demonstrate that the Duong method exhibits the highest reliability among all the methods. However, to overcome the impact of short production period and production fluctuations associated with wells exhibiting boundary-dominated flow, enhancements are proposed for Duong method. To illustrate, a new approach is suggested by combining the decline exponent of Duong’s method with Arps’ method. This new approach aims to achieve reasonable production forecasts for short period of production time for wells experiencing a rapid and unstable decline in transient flow production. To evaluate the accuracy and applicability of the new approach, seventeen field cases from the Haynesville Shale, Marcellus Shale, and Marcellus-Upper Shale in the United States of America are utilized. Comparing the new approach with the top performing methods among the sixteen considered, it consistently demonstrated superior performance across all cases, reducing mean absolute error percentages by a range of 4% to 48% and reaching R-square of 0.99. Notably, it outperformed even the most effective method previously identified in terms of mean absolute error percentage. Furthermore, Coding was employed to optimize and validate the new approach using machine learning (Python). By integrating data preprocessing, model fitting, evaluation, visualization, and economic analysis, the methodology provided deep insights into reservoir behavior and facilitated the optimization of production strategies. An easy-to use interface was established in order to implement the new approach in the real-world industry.