Separation of productivity index zones using fractal models to identify promising areas of fractured reservoir rocks

Abstract Identifying geological characteristics such as rock types and fractures is an important step in fractured reservoirs’ modeling developing oil gas fields. The productivity index (PI) essential parameter for this purpose. There are different methods separating identifying fractures, including simple statistical complex fractal based on the spatial structure of data. In study, areas were isolated after PI a reservoir southern Iran by ordinary kriging estimation. Then, concentration–area (C–A) concentration–number (C–N) used to classify zones. C–A analysis revealed six zones, C–N method indicated four anomalies data studied rock. Based models, parts with ≤ 44 63, respectively, correspond production wells from matrix field ≥ 223 include at fracture network Fractal indicates that highest values occurred southeast northwest field, suggesting better quality area. This problem attributed presence faults accumulation these areas, which increases rock’s permeability. present study showed multifractal very accurate all it separates things not visible other petrophysical methods. communities identified well confirmed evidence, especially impact diagenesis factors