A dynamic flux model of a hydrocarbon reservoir relies on various geological and petrophysical parameters. Some inputs are related to the flow properties of the formation, such as matrix permeability and understanding the fracture environment. The sooner we acquire this knowledge, the better we can comprehend the field and mitigate production risks. However, the low seismic resolution poses challenges in identifying open fractures through geophysical analysis. The primary information about open fractures is obtained from image logging tools at the well scale, but its limited depth of investigation may not guarantee accurate assessment of fluid flow potential fractures.
The objective of this study is to develop a methodology for identifying fluid flow potential fractures at both well and seismic scales. At the well scale, a combined interpretation of image and sonic logging tools, utilizing anisotropy and Stoneley information, enabled the construction of a "Potential Flow Fracture Indicator" (PFFI). This up-scaled curve was then used to guide the seismic analysis, employing a Self-Organizing Map (SOM) approach with specific combinations of seismic attributes to identify fractured regions.
The methodology was applied to a group of wells in the same field. The results indicate a promising capability of the PFFI in distinguishing open fractures identified by image logging tools, which are deeper within the formation and exhibit good fluid mobility. This information can be valuable for future reservoir modeling related to fracturing. By utilizing the PFFI, it was possible to identify the contribution of open fractures in a formation flow test.
Seismic results demonstrate a positive correlation between a constructed blocked "log" from K-means (cluster number, representing identified regions on a 2D Kohonen map) and the PFFI. High and low values correspond to supposed fractured and non-fractured regions, respectively. These regions align with wells exhibiting varying levels of fractures. Integrated analysis with rock data suggests a potential lithological control.
It is important to emphasize that all the results serve as good indications, but their certainty levels can be further enhanced through additional tests, new analyses, and the availability of more data in different fields.