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Image courtesy of Halliburton

The real-time monitoring, model updating, simulation and optimal control of oil and gas fields is known in the industry by names such as Smart Fields, I-fields, E-fields, Closed-Loop Reservoir Management, etc. Optimization techniques can be deployed at any stage of the development of a field. Such techniques are of significant potential value in large and small fields. In addition to optimizing field operations, these techniques can be used to determine the location, number, type and scheduling of new wells. It is also possible to combine field development and operation in one continuous optimization loop. The implementation of such advanced technologies in large and complex oil and gas fields requires several key developments. Service companies and oil companies have already developed and continue to perform research on techniques for drilling and completing advanced wells, including long horizontal, deviated and multilateral wells, and wells with inflow control devices and/or downhole sensors. Simulation and monitoring techniques have also been advancing at a fast rate. Optimum development and operation of fields designed and equipped with advanced hardware will also require significant advances in software technologies to achieve optimum operations.

Some of the areas where developments are needed, and where the Smart Fields Consortium is active, are:

  • Optimization techniques for initial and continuous development over the life of the field. This includes determining where and when to drill, the design of the wells to be drilled, the operation of wells (e.g., determining optimal time varying rates or bottom-hole pressures), and the type of monitoring needed. Risk assessment and decision making techniques are also required for aiding reservoir management.
  • Efficient and reliable techniques for data filtering and assimilation, because huge quantities of data are produced in real-time monitoring.
  • Continuous model updating, since real-time model calibration could greatly improve future predictions. The model parameters to be determined could include geological variables (porosity and permeability in every grid block), relative permeability functions, or variables associated with models for multiphase flow in wells and facilities.
  • Very fast reservoir simulators and accurate proxies to enable efficient optimization, data assimilation and uncertainty quantification.
  • Effective integration of repeated geophysical remote-sensing data (e.g., seismic, gravity, electro-magnetic, etc.) into the reservoir updating and optimization process.

It is important to emphasize that a wide range of optimization algorithms (e.g., gradient-based methods that use adjoints, derivative-free direct search methods, global stochastic search procedures) are applicable for the applications noted above. These, and other, techniques are developed and applied within the Smart Fields Consortium.

The synthesis of all of the above in the closed-loop system is depicted below:


We have created a multidisciplinary, multi-department industrial affiliates research program in the areas identified above. The scope of the project is restricted to the development of methodologies.

The program includes research groups from within the School of Earth, Energy & Environmental Sciences (SES), as well as groups outside of SES, including Management Science & Engineering and Electrical Engineering. The program is housed and supervised in the Department of Energy Resources Engineering, and is closely integrated with some of the Department’s other research groups, such as SUPRI-B, SUPRI-D, and SCERF. Several major oil and gas producers and large service companies are currently affiliated with the Smart Fields Consortium (see “Our Affiliates” page). Please review the Research Policy Handbook for more information regarding visiting scholar requirements.