The Influence of Natural Joints on the Evolution of Fracturing Curves: From a Numerical Perspective

• Published in: Arabian journal for science and engineering (2011) Vol. 48; no. 7; pp. 9113 - 9126
• Main Authors: Liu, Zhiyuan, Zhang, Meizhu, Sun, Lei, Ye, Shen, Chen, Zitao, Tang, Xuhai
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2023; Springer Nature B.V
• Subjects: Algorithms; Engineering; Evolution; Humanities and Social Sciences; Hydraulic fracturing; multidisciplinary; Pressure curve; Pressure drop; Pressure recovery; Research Article-Petroleum Engineering; Science; Simulation; Fracturing curves; Numerical simulation; Natural joints; Hydraulic fracturing; Inversion algorithm
• ISSN: 2193-567X; 1319-8025; 2191-4281
• DOI: 10.1007/s13369-022-07097-6

With the development of fracture-cavity reservoirs, a better understanding of the natural joints is critical to optimizing the hydraulic fracturing operation. However, traditional methodologies, such as well-logging interpretation, are difficult to obtain the properties of natural joints which are deeply buried. This work proposes a potentially useful method by combining the TOUGH-AiFrac simulator with an inversion algorithm to predict the natural joint properties according to the characteristics of fracturing curves, which are easily obtained in fieldwork. The simulation results show that the fracturing curves experience a significant change when hydraulic fractures connect to natural joints. Three main stages can be observed: (I) pressure increase stage, (II) pressure drop stage, and (III) pressure recovery stage, which are consistent with the field observation. The natural joint plays an important role in the pressure curve evolution, where a larger joint permeability or a longer joint length will induce a larger pressure drop, and a more rapid pressure change rate. Based on the simulation results, an inversion algorithm based on the gradient descent method was then developed to predict the properties of natural joints using fracturing curves characterized by four critical parameters. The present work proposes a promising tool for understanding and predicting the natural joint effect on fracturing curves.