Real-Time Production Optimization of an Intelligent Well Offshore, Caspian Sea | Schlumberger
Tech Paper
Russia, Europe, Offshore
Sergey Shestov, Schlumberger; Mikhail Golenkin, and Aleksandr Senkov, Lukoil-Nizhnevolzhskneft; Vadim Blekhman, Varma Gottumukkala, and Igor Bulygin, Schlumberger
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Real-Time Production Optimization of an Intelligent Well Offshore, Caspian Sea


Recent advances in development of hardware for reservoir monitoring have caused rapid changes in production logging and testing techniques for instrumented wells. On-demand actuations of downhole valves and data acquisition from the downhole gauges remain available well into the useful well life due to improved reliability of the downhole equipment. A specific layout of the gauges could be tailored to support various types of production logging, and pressure transient and production tests. Instead of the often costly one-off surveys required for a the non-instrumented wells, both data gathering and interpretation become part of a continuous surveillance cycle for an instrumented, "intelligent" well. The resulting exhaustively sampled data sets from instrumented wells are typically very large and require substantial cleansing and cross-calibration with a range of physical models as well as empirical trends to extract valuable information encoded in the data. Most of these workflows also support decision making in real time.

The paper outlines practical ways of combining known well-testing principals with the modern downhole completion instrumentation to estimate production rate, productivity index, and reservoir pressure using surveillance workflows for a multi-zone intelligent completion in the Korchagina field, Russia. Data from permanent downhole pressure gauges supports a number of real-time workflows including those for zonal rate and productivity allocation. Sequential valve cycling can be interpreted as a multi rate inflow test and, when combined with initial well test data, can calibrate the rate allocation procedure. Meeting production goals for each of the zones requires a real-time optimization technique for setting the valve positions. The procedure was implemented in a form of automated surveillance software for pressure, rate, and productivity allocation and does not require shut-ins to obtain well test data.

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