Comprehensive methodology for detecting fracture aperture in naturally fractured formations using mud loss data

Abstract

Abstract When encountered with naturally fractured formations, the knowledge of the location and the aperture of the fractures intersecting the wellbore has a strong technical and economical impacts on drilling engineering, oil production and reservoir management strategies. So far no method has been well-developed for predicting fracture aperture to optimize particle size of lost circulation materials (LCMs) based on mud loss data, which is the primary source of information retrieved from the drilling process. The typical curve in traditional analytical model, which has been the predominant tool in the assessment of fracture aperture in the past several decades, has two major deficiencies: (1) no consideration of the mechanical properties of fracture and (2) incapable of providing accurate fracture aperture in the case of fracture networks. Based on the mathematic model previously published in JPSE (Xia et al., 2015. J. Pet. Sci. Eng. 129, 254–267), this paper develops a methodology that optimizes the fracture characteristics based on recording mud loss data. The methodology poses the prediction problem as history matching, where the outer optimization shell involves the length and the aperture of the fractures intersecting the wellbore. The proposed methodology systematically integrates a Fracture Generation Module, a Mud Loss Simulator, and a Global Optimization Module. The suggested methodology is automated and accurate for field development. We end this paper with some case studies to illustrate the applicability of this methodology.