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Analytical Fractured reservoir characterization by using geological and petrophysical log

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Abstract Background and Objectives: Due to structural complexities in some wells, higher than the expected thickness of Asmari formation is found. Fracture intensity and deep-rooted fractures broadly increase the risk of unpredictable water production. The well test analysis is not sufficient in describing fracture properties. Unfortunately, the core condition is poor in the fractured zones and cannot be used to provide reliable information. So, the objectives of this study are developing an accurate structural model for Asmari reservoir,fracture characterization in the borehole by interpreting image logs ,and comparing the log's image results with core data.Materials and Methods: Dip classification based on a geological log has the value of providing a direct demonstration of structural origin and detect Asmari fault and fracture systems and its impact on production and answer structural issue. So, in this study, the borehole imaging tools were interpreted to find solutions for fracture systems and fracture attributes.Result: Interpreting accurate structural dip determined structural problem, thus bringing the precise location of the well within the Asmari reservoir. Fracture properties (open or closed), occurrence, orientation, spacing, and porosity were interpreted using Image log . The high density of fractures seen on FMS image logs in the study well has been confirmed by inspection of the cores and the distinction between major and minor fracture types from the FMS image logs has been established following core review.Conclusion.As a result, this exercise has been confirmed to be very valuable, not only for indicating the value of the log data, but it has also emphasised some significant limitations of the core data. The amount of information extracted from the FMS image logs goes beyond that achieved from the core. This exercise has validated why image logs are the main source of fracture information in the oil fields of Iran.
Research Square Platform LLC
Title: Analytical Fractured reservoir characterization by using geological and petrophysical log
Description:
Abstract Background and Objectives: Due to structural complexities in some wells, higher than the expected thickness of Asmari formation is found.
Fracture intensity and deep-rooted fractures broadly increase the risk of unpredictable water production.
The well test analysis is not sufficient in describing fracture properties.
Unfortunately, the core condition is poor in the fractured zones and cannot be used to provide reliable information.
So, the objectives of this study are developing an accurate structural model for Asmari reservoir,fracture characterization in the borehole by interpreting image logs ,and comparing the log's image results with core data.
Materials and Methods: Dip classification based on a geological log has the value of providing a direct demonstration of structural origin and detect Asmari fault and fracture systems and its impact on production and answer structural issue.
So, in this study, the borehole imaging tools were interpreted to find solutions for fracture systems and fracture attributes.
Result: Interpreting accurate structural dip determined structural problem, thus bringing the precise location of the well within the Asmari reservoir.
Fracture properties (open or closed), occurrence, orientation, spacing, and porosity were interpreted using Image log .
The high density of fractures seen on FMS image logs in the study well has been confirmed by inspection of the cores and the distinction between major and minor fracture types from the FMS image logs has been established following core review.
Conclusion.
As a result, this exercise has been confirmed to be very valuable, not only for indicating the value of the log data, but it has also emphasised some significant limitations of the core data.
The amount of information extracted from the FMS image logs goes beyond that achieved from the core.
This exercise has validated why image logs are the main source of fracture information in the oil fields of Iran.

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