Conceptual approach to DFN modeling

Introduction. Natural fracturing is typical for carbonate rocks and plays a decisive role in the development of carbonate fractured and fractured-porous types of reservoirs. A necessary condition for successful natural fractures modeling with obtaining discrete fracture systems is the availability and interpretation in a single uniform way of the results of formation microimager logging, seismic exploration data of suitable quality and, if possible, paleoreconstruction of the geological evolution of the rock mass. In case of a lack of these data or their insufficient quality, an effective alternative may be a conceptual approach, the development and approbation of which is devoted to the article.
Aim. The purpose of this work was to analyze possible approaches to discrete fracture modeling, as well as to develop and test such an approach in the case when the use of standard methods turned out to be ineffective.
Materials and methods. Analysis of formation microimager logging and seismic exploration data allows building direct correlations of fractures parameters both for wells and making a forecast in the interwell space. In the case where the quality of available data does not allow correctly determining such dependencies and correlating fractures parameters between wells, structures and seismic attributes, a conceptual approach based on understanding the mechanism of fracture forming and propagation in ever changing geological conditions can serve as an effective alternative.
Results. The proposed approach involves developing a concept of fractures formation in a specific regional or deformation environment with its subsequent digitization and use with well information. Within the framework of this approach, an analysis of the initial data of formation microimager logging was carried out with the allocation of low-reliability intervals of interpretation and their exclusion from subsequent consideration, as well as an analysis of mud loss incidents while drilling, considering the results of 1D geomechanical modeling, to identify fractured zones bypassed by well studies. The calculated fractures parameters were stochastically distributed in the modeled area according to the distributions of fracture intensity, dip angle and strike azimuth for the previously identified petrotypes.
Conclusion. Even though the conceptual approach requires signifi cantly more efforts and competencies both in the development of the concept itself and its digitization, and in subsequent modeling, it ultimately allowed us to build a DFN model, the reliability and predictive power of which were confirmed during multiple “blind” tests for various parameters.

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