Abstract

AbstractMud loss is the most serious formation damage in oil and gas well drilling engineering and is an unsolved technical problem. To prevent mud loss, it is necessary to accurately understand and identify three key factors of mud loss, including the location of the loss, the time of occurrence, and the severity of the loss. The diagnosis of mud loss is a prerequisite for the proper formulation of mud loss control techniques. It emphasizes the integration of predrilling, drilling, and postanalysis information to describe and characterize loss zones and predict potential loss zones. On the basis of the theory of engineering fuzzy mathematics, we develop a mathematical model for loss probability evaluation that combines logging anomaly features and engineering data to predict the location of losses from drilling mud and develop a loss formation identification method. The study of hydraulic fracture deformation through stress‐sensitive experiments and numerical simulations can predict the deformation and severity of loss channels, which can help optimize the loss of circulating material by adding drilling fluid. Loss pressure models have been developed based on mud loss mechanisms, and loss pressure for hydraulic fracture creation, connection, and extension has been studied to help identify loss mechanisms and types. Mud losses can be identified by unusual engineering characteristics, including sudden changes in drilling times, cuttings, and mud logging. Real‐time logging parameters can be used to monitor the loss process and hence predict the loss trend. The framework of loss diagnosis techniques is established, which helps in successful mud loss controlling.

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