Research on Production Prediction of Shale Gas Wells Based on Grey Relation Analysis and Typical Decline Models

Abstract

Against the backdrop of increasingly constrained global conventional oil and gas resources, the efficient development of shale gas, as a crucial unconventional alternative, is of paramount importance. Shale gas wells, particularly horizontal wells, exhibit a production decline behavior distinctly different from conventional gas wells, characterized by high initial rates followed by rapid decline, and ultimately transitioning to a long period of low-yield stabilization. This paper systematically investigates the production decline behavior of shale gas wells and the analytical methods of typical decline models. Firstly, it elaborates on the principles, formulas, and applicability of various models, ranging from the classical Arps decline model to modern models tailored for shale gas characteristics, such as the Duong, Power Law Exponential (PLE), Stretched Exponential Production Decline (SEPD), and Logistic Growth Model (LGM). Secondly, to address the insufficient analysis of factors influencing production decline, the Grey Relation Analysis (GRA) method is introduced. A complete analytical process—from determining analysis sequences and dimensionless processing to calculating the correlation degree—is established to quantify the impact of geological and engineering factors on the decline behavior. Finally, a comparative evaluation of the main analytical methods, including the Wattenbarger linear flow method, PLE, SEPD, Duong, and LGM, is conducted, highlighting their respective advantages, disadvantages, and application conditions. The comparison reveals differences among these models in terms of fitting accuracy, data sensitivity, flow regime identification, and early-time prediction capability. The research demonstrates that integrating grey relation analysis with appropriately selected decline models based on specific production stages and reservoir characteristics can more accurately elucidate the decline behavior of shale gas wells. This integrated approach provides a scientific basis for production forecasting, recoverable reserves estimation, and development plan optimization.