摘要：The hydraulic fracturing pumping in the process of reservoir stimulation is characterized by complex and diverse technologies, irreversible process and high risk, so it needs timely and accurate decision-making and control to enhance the effectiveness of the fracturing stimulation. The current decision-making approach mainly takes the hydraulic fracturing design and pumping program as the base to manually control pumping parameters. The advancement of artificial intelligence technology enables the construction of intelligent decision-making systems for hydraulic fracturing pumping and the implementation of autonomous decision-making. Based on a review of researches on hydraulic fracturing pumping decision-making around the world, this paper proposes an intelligent decision-making design concept for hydraulic fracturing pumping based on reinforcement learning theory, and discusses its realization paths. The following results are obtained. First, the core of the intelligent decision-making system for hydraulic fracturing pumping is the pumping decision-making agent, which autonomously determines the pumping program and optimizes the parameters, while transmitting the decision-making actions to surface equipment to form a closed-loop control system, thereby achieving "auto driving" throughout the entire pumping process. Second, the design concept of the intelligent decision-making system for hydraulic fracturing pumping based on reinforcement learning theory is to construct a fracturing simulation environment with the reinforcement learning as the core, the hydraulic fracturing big data as the base, and the mechanism model insights and expert prior knowledge as the constraints, to train the pumping decision-making agent, so as to achieve the real-time optimization of decision and closed-loop feedback control of ground equipment according to pumping parameters. Third, the intelligent decision-making system for hydraulic fracturing pumping achieves its functionality primarily through the technologies such as autonomous identification of fracturing conditions, dynamic sensing and risk warning of fracture propagation, optimization and decision making of fracturing pumping parameters, autonomous control of ground equipment, and digital twin of hydraulic fracturing pumping. In conclusion, the design concept of the intelligent decision-making system for hydraulic fracturing pumping based on reinforcement learning theory provides valuable reference for accelerating the process of intelligent fracturing pumping, and is conducive to the efficient development of oil and gas. 漏 2024 Natural Gas Industry Journal Agency. All rights reserved.

ISSN号：1000-0976

卷、期、页：v 44,n 9,p108-113

发表日期：2024-09-01

收录情况：EI（工程索引）

发表期刊名称：Natural Gas Industry

第一作者：盛茂,田守嶒,朱丹丹,王天宇,廖勤拙,李根生

论文类型：期刊论文

论文概要：盛茂,田守嶒,朱丹丹,王天宇,廖勤拙,李根生，Design concept of intelligent decision-making system for hydraulic fracturaing pumping and its implementation path，Natural Gas Industry，2024，v 44,n 9,p108-113

论文题目：Design concept of intelligent decision-making system for hydraulic fracturaing pumping and its implementation path