4.4 Article

Comprehensive Well Test Interpretation Method, Process, and Multiple Solutions Analysis for Complicated Carbonate Reservoirs

Publisher

ASME
DOI: 10.1115/1.4044801

Keywords

well test interpretation; complicated carbonate reservoir; strong heterogeneity; concavity; multiple solution; dual-medium; multi-layers; oil/gas reservoirs; petroleum engineering

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Funding

  1. National Science and Technology [2017ZX05032-004]
  2. Innovation Fund of China National Offshore Oil Corporation (CNOOC) [CNOOC-KY-KJCX-CRI-2017-01]

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The main characteristic of the complicated carbonate reservoirs is notably strong heterogeneous, leading to a high uncertainty in formation parameter evaluation. The most reliable method for obtaining the dynamic parameters is well test interpretation. However, the well test curve shows similar characteristics for multi-layers reservoirs, dual-medium reservoirs, and carbonate reservoirs with lithology mixed sedimentation lithology. Sometimes the well test fitting result under the mentioned three kinds of models is satisfied, but the interpretation result is quite different. In order to reduce the parameter evaluation multiplicity, the synthetic identification and evaluation method for obtaining the physical parameters of the complicated carbonate reservoir was proposed, based on completion types, core analysis, lithology analysis, and well test results. The evaluation method distinguishes the different carbonate reservoir characteristics from similar well test responses by summarizing and classifying the completion method, reservoir fracture characteristics, and production logging test (PLT) results. The reliability of the proposed method is verified by an application of actual carbonate reservoir parameters evaluation. The proposed method can distinguish among multi-layers reservoirs, dual-medium, and complicated reservoirs with mixed sedimentation lithology whose main characteristic is that concavity existing in the pressure derivative curve. If the well test match results were satisfied enough which lead to the proposed method and process was ignored, the interpretation results and production performance prediction may deviate largely from the actual situation.

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