A Workflow to Integrate Core and Image Logs in Order to Enhance the Characterization of Subsurface Facies on Carbonate Reservoirs, Offshore Abu Dhabi

BinAbadat, Ebtesam (ADNOC Offshore) | Bu-Hindi, Hani (ADNOC Offshore) | Lehmann, Christoph (ADNOC Offshore) | Kumar, Atul (ADNOC Offshore) | AL-Harbi, Haifa (ADNOC Offshore) | AL-Ali, Ahmed (ADNOC Offshore) | Al Katheeri, Adel (ADNOC Offshore)



In this study, core and log data were integrated to identify intervals which are rich in stromatoporoids in an Upper Jurassic carbonate reservoir of an offshore green field Abu Dhabi. The main objective of this study was to recognize and stromatoporoids floatstones/rudstones in core, and develop criteria and workflow to identify them in uncored wells using borehole images.

The following workflow was used during this study: i) Identification of the stromatoporoid feature in pilot wells with core and borehole images, ii) Investigate the properties and architecture of stromatoporoid bodies, iii) Integrate the same scale of core observations with borehole images and conventional log data (gamma ray, neutron porosity and bulk density logs) to identify stromatoporoid-rich layers, iv) Performing a blind test on a well by using the criteria developed from previous steps to identify "stromatoporoid accumulations" on a borehole image, and validate it with core observations.

In the reservoir under investgation, stromatoporoid floatstones/rudstones intervals were identified and recognized both on core and borehole image in the pilot wells. These distinct reservoir bodies of stromatoporoids commonly occur in upper part of the reservoir and can reach to a thickness of around 20ft. The distribution and thickness of stromatoporoid bodies as well as growth forms (massive versus branching) were recognized on core and borehole images. The accumulations varied between massive beds of containing large pieces of stromatoporoids and grainstone beds rich in stromatoporoid debris. The massive beds of stromatoporoid accumulations are well developed in the northern part of the field. These layers can enhance the reservoir quality because of their distinct vuggy porosity and permeability that can reach up to several hundred of milidarcies (mD). Therefore, it is important to capture stromatoporoid layers both vertically and laterally in the static and dynamic model. Integrating borehole image data with core data and developing a workflow to identify stromatoporoid intervals in uncored wells is crucial to our subsurface understanding and will help to understand reservoir performance.

Integration of image log data which is calibrated to core and log data proved to be critical in generating reservoir facies maps and correlations, which were integrated into a sequence stratigraphic framework as well. The results were used in the static model in distribution of high permeability layers related to the distribution of stromatoporoids.