Advancing Carbonate Complex Reservoir Characterizations Using Integrated Logging Technologies

Abstract

A heterogeneous and complex carbonate reservoir consists of many sub-layers. Each layer has unique characteristics. To enable comprehensive reservoir characterization, logging while-drilling technologies comprising high-resolution electrical imager, magnetic resonance and formation pressure tester were deployed. The integration of logging data had delivered detailed interpretation and proposes of a new workflow for best practice to advance reservoir performance and to optimize completion design. Magnetic resonance was acquired with dual-wait time enabled T2 polarization to differentiate between moveable water and hydrocarbon. After acquisition, standard deliverables were porosity and permeability index. Porosity was divided into clay-bound water (CBW), bulk-volume irreducible (BVI) and bulk-volume moveable (BVM). Following good test results from the formation pressure tester, the permeability index from magnetic resonance was calibrated to mobility. Then rock quality was interpreted based on Lorenz Plot and permeability-calibrated to effective porosity ratio. The ratio was classified to high, low and no flow unit zones. The classification based on gradient of the ratio. Steeper gradient inferred high flow, lower gradient inferred low flow and flat gradient inferred no flow. To advance reservoir characterizations, flow unit zones were integrated to sedimentary facies interpretation. The interpretation was conducted based on high-resolution electrical imager. The analyzed reservoir was divided in 23 flow units. The flow units were useful to identify reservoir compartments. Similar flow units were combined into one compartment. There are 3 intervals of high flow, 3 to 4 intervals of low flow and 4 intervals of no flow. The interval definition was used to design the completion. For best point of the completion within the intervals, high resolution electrical imager interpretation had added valuable input. Categories for best point in this particular study were homogeneous and less-cemented facies. The interval for best point would be varies based in completion strategy. The expectation result of the integrated logging data was to deliver maximum and stable flow rate with efficient completion design and advance the understanding of reservoir characterization. In addition, sedimentary facies interpretation was being correlated with the fluid flow behavior. In high-density cement intervals, permeability is low. In porous high-resistive sedimentary facies, the permeability is high. This inferred, the matrix and cement in the formation were affecting the fluid flow behavior. The integration of logging data had resulted comprehensive reservoir characterization. The integration lead to completion optimization to advance reservoir performance and develop a comprehensive workflow. The workflow had combined petrophysical analysis, reservoir information and geological interpretation. This workflow would be best practice to be implement to advance complex carbonate reservoir and optimize completion strategy.