No abstract

No abstract

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 tests1,2. 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 data3. 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.

No abstract

First Intelligent multilateral TAML5 wells on Filanovskogo Field is the great example of how new technologies help to optimize CAPEX, and, thanks to higher productivity index, achieve higher production rate. Multilateral well geometry combined with ability to monitor and control each leg separately helps to optimize flow patterns, prolongs well life and contributes to higher cumulative production. The paper focuses on well design, project execution and production results. In order to achieve results, work was done in several phases: Choose well design which would optimize CAPEX and allow to reach production and recovery targets.Perform two trial jobs on existing mature field to learn technology and prove the concept.Use experience gained on trial jobs to optimize requirements, well design and procedures.Execute the job, control and manage execution to ensure compliance to the plan.Review first production results and estimate benefits obtained from project execution. This paper describes all the steps focusing mainly on installation procedure, execution and production results review. As a result of the work done, LUKOIL successfully installed two first intelligent TAML5 completions on Filanovskogo field and achieved ~20%-60% higher production than on nearby single bore wells (up to 38000 bpd). This first wells proven that contemporary intelligent and multilateral completion technologies are mature enough to deliver consistent results. Production results show that actual productivity index matches predicted one. This shows once again that intelligent multilateral well design gives a number of benefits, such as slot preservation, higher productivity indices, faster production buildup and can facilitate reaching higher cumulative production from the field. The paper describes introduction of complex intelligent multilateral well design on the field. This practical example can be used for future reference by drilling and production focused petroleum industry professionals to better understand benefits and limitations of existing technologies. Actual production result can also be used as a benchmark for field development planning.