Abstract

Abstract A new processing workflow has been engineered to combine reservoir deliverability, defined by production logging (PL) measurements, with nodal analysis evaluation. This allows the effects of various completion modifications to be quantitatively modeled, predicting the resulting changes in well production prior to intervention. A graphical computer interface is used to implement the workflow and facilitate comparisons of the effect on production of multiple completion/recompletion scenarios, using "drag and drop" icons for placing simulated plugs, patches, perforations, etc. on the base profile. Beginning with the flow profile and formation pressure, the process defines zonal reservoir parameters in terms of the productivity index, water cut, and gas/oil ratio. These data are passed transparently to a nodal analysis package that automatically creates a model to match the measured rates and pressures as closely as possible to allow production computations. The process is designed to significantly decrease workover decision time and risk. This technique provides opportunities to compare and recommend formation evaluations, profile modifications, various artificial lift options, and stimulation activities to maximize production. The modified completion is then passed to the nodal analysis engine and a new predicted production profile is computed and displayed. Outputs include graphic and ASCII format log data, ASCII format tables, and data files, which can be used for further studies. In this paper, the use of the workflow is demonstrated by one example and two case studies, including a selective inflow performance analysis of a gas well and a successful water shutoff operation in an oil well. PL answers provide an opportunity to evaluate the downhole flow performance of multizone completions. Nodal analysis techniques provide a method to model the effects of the fluid properties and completion configuration as the fluids are produced to the surface. Combining PL answers seamlessly with nodal analysis provides unique insight into the reservoir completion performance and production improvement potential.

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