A general dynamic model for any flow-related operation during well construction and interventions has been developed. The model is a basis for a new generation support tools and technologies needed in today's environment with advanced well designs, challenging drilling conditions and need for fast and reliable real-time decision support.
The solution method uses a "divide and conquer" scheme, which computes the flow in each well segment separately, and then solves for the appropriate flow in the junctions.
This simplifies greatly simulating complex flow networks, such as multilateral wells and jet subs. The flexibility allows incorporating additional pumps in the flow loop, as in Dual Gradient Systems.
The model includes dynamic 2-D temperature calculations, covering the radial area affecting the well and assuming radial symmetry in the vicinity of the well.
Flexible boundary conditions (which includes drilling, tripping)
Non-Newtonian frictional pressure loss
Transient well-reservoir interaction
Slip between phases
Advanced PVT relationship
The reason for this new approach was to respond constructively to today's challenges (complex and difficult drilling conditions, need for reliable real time decision support). Our approach has been more flexibility, improved accuracy, reduced numerical diffusion and increased computational speed.
The paper will present the basic model assumptions; the model architecture, and solution methods.
Integration of the model into a real time system with links to real time databases and advanced visualization tools is currently ongoing. Thus the model may follow the whole work process through planning, training, execution, and post analysis. Examples of applications of the model so far will be presented, as well as visions for future applications.
Alongside the advances in instrumentation and the more intelligent tools being developed today, there is a need for advanced numerical simulators that can bring all the technologies together to do intelligent drilling that will increase safety, reduce the costs, and make previously "impossible" fields "possible".
The challenge in making the simulators lies in making the simulator kernel able to include all the important physical parameters; the important events; compute correct results; and fast enough to meet real time requirements. Examples of some of the recent improvements of the "events" that simulators are able to dynamically simulate are: control during underground blowout1; and hydrate formation2. In order to do this, the kernel needs to be able to change boundary conditions and connectivity during a single simulation.
The simulator kernel presented here fulfills the needs of the present and many of the future challenges, as shown in the examples. The next chapters briefly explain the models used in the simulator, and the numerical methods used. The flexibility of the simulator is illustrated through a few examples, and the results of its use in real situation are presented.