Abstract

The Najmah-Sargelu (NJSR) are calcareous and kerogen-bearing reservoirs that are deep, tight and highly pressured with matrix permeability in the range of 0.0001 to 0.1 mD. Production from these unconventional reservoirs is mainly dependent on the presence of natural fractures (NF). Production from wells depend on the extent and intensity of natural fracturing coupled with matrix acidization. Where NF do not exist, stimulation is needed for wells to produce. At this early stage of field exploitation, an emphasis has been put on understanding naturally fractured intervals and their impact on production. In this work we present an integrated approach to characterize and build a 3D fracture network model for one of the NJSR naturally fractured reservoirs (NFR) in west Kuwait.

We developed a 3D discrete fracture network (DFN) using an integrated approach by coupling static and dynamic data. Families of NF and fracture intensity were characterized across the field by borehole images and core. Relationships were established between 3D seismic attributes such as dip, discontinuity and curvature, and the NF intensity. NF drivers were built using seismic attributes, the structural fault / lineament model and the NF interpretation from borehole images and core data. Additional observations from drilling (e.g. losses) were used. Integration of NF data with borehole breakouts helped understand the relationship between NF orientation and productivity. An iterative procedure was used to ensure consistency between the DFN and observations from the dynamic model.

We found that the dip attribute had the best correlation with the NF intensity from images and core. The resultant DFN using this attribute showed consistency between areas of excellent natural fracturing and wells with prolific production results. Productive zones were also observed to have NF that were parallel to maximum horizontal stress. However, limitations were identified with this seismic-driven DFN due to the vertical resolution, which was not able to discern thinner productive beds as identified in the PLT. History matching of producing well data was key in calibrating the DFN because the production response was impacted by natural fracture density and permeability. Additionally, non-producers provided a baseline across the field for negligible to zero natural fracturing.

Unconventional naturally fractured reservoirs such as the Najmah-Sargelu are of prime focus globally by operating companies. However, success in these reservoirs requires a good understanding of natural fractures, their characterization, and close integration with dynamic production data. This paper provides a good reference demonstrating field-wide characterization of natural fractures and their coupling with dynamic data. Ultimately, state of the art natural fracture characterization and the resultant fit-for-purpose 3D DFN model will supplement in designing fit-for-purpose completions which will improve success rates in these complex reservoirs.

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