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Water injection using horizontal wells has started since 2012 in North Kuwait carbonate reservoirs. The objective of this work is to integrate a detailed steady-state single well model with a dynamic reservoir model along to improve the permeability distribution inside the dynamic model along the horizontal section of the well. The workflow starts first by building a well model and quantifying the injectivity profile along the horizontal section from the actual wellhead injection pressure and dynamic reservoir parameters. Then the ILT (Injection Logging Tool) data is used by the well modeling simulator to calculate permeability distribution along the horizontal section of the well resulting in the measured outflow profile. The final step is to export the permeability multipliers along the open hole horizontal section of the well into the dynamic model to improve the dynamic model results at the well level. This workflow was examined on one injection well from the North Kuwait Carbonate formation and shows improvement in well bottom hole injection pressure, reservoir pressure, well injectivity index and water injection rates distribution along the horizontal Openhole section from the dynamic model and better history match. The coupling of a single-well advanced ILT interpretation with the field-scale dynamic model is considered as a novel approach that improves the dynamic modeling construction on a well-scale level. Instead of a classical approach where reservoir properties are used only to calculate outflow into the well an inverse problem is solved: calculate reservoir properties from a measured outflow profile.

This paper presents a method for the fast evaluation of fracture-stimulated condensate reservoir economics. For the calculation of production decline in such reservoirs, an efficient numerical model with a three-phase transient analysis of pressure distribution was built and validated using the predictions from reservoir solvers and field data. This model solves for gas-, oil-, and water-flow parameters, accounting for the gas-oil phase transition, and has been realized in a numerical code and compared with predictions from commercial software and available field data, such as production-decline curves. The developed numerical model has been implemented in commercial software and used for the sensitivity analysis of reservoir productivity regarding changes of fracture size and spacing, as well as reservoir permeability in the fractured condensate reservoirs, with an account for multiphase reservoir flows and reservoir properties. A side-by-side comparison of predictions from two commercial reservoir simulators has shown that that this model accurately calculates transientpressure fields near the fractures and the productiondecline curve. The objective of the economic analysis and fracture optimization stage is reduced to finding the target function minimum in an N-dimensional parametric space using various constrained minimization techniques, including a Quasi-Monte Carlo analysis and the Active Set Method.

Horizontal wells are a widely applied architecture in modern field developments. However, because of the frictional pressure drop and reservoir permeability variations along the well, there is usually a non-uniform influx from the reservoir along the length and higher injection or production flow rates at the heel. Inflow control devices (ICDs) have been used for more than a decade to balance or equalize flow rates by creating additional pressure drop. To improve performance and longevity of the ICDs, their design must account for axial non-uniformity of pressure distribution and fluid flow details in the vicinity of the wellbore. This paper discusses an effective approach to the problem and analytical solution of the pressure and flow field near the ICD section of the wellbore and prediction of the leveling of the non-uniform axial pressure distribution as a function of distance from the wellbore. The obtained analytical equations are validated through comparison with results of detailed numerical simulation using the finite difference method.