Optimization of Continuous Gas Lift wells based on Well Modeling, Surveillance, Diagnostics and Lift Gas Re-allocation in a Mature Offshore Oil Field
Authors:   Research Scholar, Department of Petroleum Technology, Dibrugarh University, Dibrugarh, Assam, India., Dutta Ajoy Lal , Das Prof. Minati ,   Dean, Faculty of Earth Sciences and Energy, Dibrugarh University, Dibrugarh, Assam, India.
Published: November 2019

In an oil field, the optimization study of Continuous Gas Lift (CGL) wells require to encompass the single or multiphase inflow performance within the reservoir and the outflow performance from perforations up to the first separator; along with evaluation of the effect of lift gas injection through the operating Gas Lift Valve (GLV). Mature oil fields that inherit problems of increasing trend of water cut, decreasing trend of Formation Gas Oil Ratio, both leads to further increase in demand for lift gas. To optimize a group of CGL wells sharing common manifold and pipeline, it is required to first optimize every individual well. Well problem and Instability in one well can adversely affect the well performance of other wells of the same gathering system. Literature survey shows that the CGL optimization issues were studied either focused on part of the problem or based on secondary data, and not specific to the challenges of Mature Oil Field. Hence, a study has been carried out to address the well optimization problems with CGL, specifically based on field parameters monitored in a mature offshore oil field. In this present study, development of well models of 12 CGL wells of the study area Heera Field of western Indian offshore basin were carried out, in three different simulators with same set of input data. The best fit well models were selected based on comparative error analysis for approximation of operating points by plotting inflow and outflow performance curves using Nodal Analysis approach. Production History of each well, Flowing Gradient Survey data were correlated with the real-time monitored surface measured field parameters. Deviations were analyzed based on empirical data and screening criteria were used to preliminary diagnose well problems. Simulation experiments were performed on the best fit well models for the detail diagnostic analysis. Recommendations were drawn well wise for optimization, by applying engineering judgments, correlating the simulation results with the surface parameters. Gas Lift Performance Curves (GLPC) were generated for each well by simulation experiment on well models. Non-linear functions of Production rate as a function of Gas Lift Injection Rates (GLIR) were approximated by curve fitting of GLPCs using non-linear regression. GLPC based Lift gas re-allocation problem was formulated and solved with limited lift gas quantity as constraints by Equal Slope Graphical Method and by FMINCON solver of MATLAB. Comparative results of envisaged production gain from both approach is being discussed. The integrated approach for real time monitoring of surface parameters, well model based diagnostic analysis and then further allocation of optimum GLIR to each well shows better results than addressing part of the problem for optimization of CGL wells. Lessons learnt from this ‘integrated optimization approach’ were presented, which will be useful in optimization of CGL wells as standalone well or as a part of a group of wells, especially with similar constraints of mature oil field.