Fractured zones detection using conventional petrophysical logs by differentiation method and its correlation with image logs

摘要

Evaluation of reservoir structure and fracture zones is necessary in oil production optimization and field development. The purpose of this study is to find a quick method for identification of fractured zones using petrophysical logs, which are available in all wells, and then use the Velocity Deviation Log (VDL) to identify fracture aperture opening and their effects on porosity and permeability. The result shows that some parameters, such as lithology and reservoir fluids, affected on petrophysical logs, but fracture zones can be determined using conventional logs with logs corrections by mathematical methods, such as differentiation, which has great correlation with image logs. Results show that zones with high fracture density can be easily recognized by first stage of differentiation on petrophysical logs. Also among fracture parameters, fracture aperture has the most effect on logs. To check the results, other data, such as mud loss data, thin section and VDL log, were used to support our interpretation. Based on VDL log, the production in the Asmari reservoir in this field is a combination of fractures and rock matrix. In addition, fractures and porous zones have had a great impact on the reservoir rock properties. RHOB, NPHI, GR, DT, PEF, and CAL logs used in this study, and they are the best types of logs that can be used in the identification of fracture zones and will be used for old wells without image log and core data. Based on their responds in fractured zones and correction on responds, they can be used to detect fractures. In this method, understanding of structure and stratigraphy of the studied field is important as well as mathematical and software knowledge in fractured zones identification. Finally, the knowledge of geology of the field is necessary for all petrophysical analyses as well as interpreting the fracture zones. (C) 2016 Elsevier B.V. All rights reserved.