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Experience shows that high-performance fractures (HPFs) may retain near-unit-flow efficiency (equivalent to zero skin in a vertical well) and rarely fail, even in highly deviated wells. This may be partly because overly simplistic models of the well flow behavior lead operators to maintain wells at lower production rates than could have been achieved for the same amount of injected proppant with a vertical-well-completion design. Rigorous models that account for widely accepted rock-mechanics fundamentals indicate that the fracture-to-well connection is compromised in deviated wells and lead to questions concerning whether the bulk of the flow to the well actually passes through the fracture. Distributed volumetric sources are used in this model to rigorously model a wide variety of possible fracture geometries such as an expanded wellbore because of halo effect, flow strictly through the fracture, and combined flow through a single fracture and to remaining flowing perforations not connected to the fracture. The model also includes turbulent-flow effects that may occur for radial-flow conditions in the fracture plane or in the reservoir opposite wellbore sections not connected to the fracture, along with high-velocity flow through the perforation tunnels. It also computes the effective flow area at the resulting face between the reservoir and the completion to check whether flow velocity exceeds conditions that would risk production of reservoir fines, and it estimates the screen-flow velocity on the basis of the number of flowing perforations. This comprehensive view of the HPF completion enables a thorough analysis of the risks of flowing the well at high rate. Field examples show that the new model depicts real field conditions in calculating the total skin, flow fractions, and the flux for HPF completions in high-rate gas and oil wells. Complete inflow-performance behavior for likely flow patterns for HPF wells in oil and gas reservoirs is provided. [ABSTRACT FROM AUTHOR]

In this work, we present an industrial automation framework for control and optimization of hydrocarbon-producing fields while satisfying business and physical constraints. The all-encompassing reservoir-management problem is decomposed into a hierarchy of decision-making problems at different time scales. We exemplify the proposed approach through a case study on a multiple-layer reservoir with a classical waterflood problem, in which a numerical reservoir model is used as a virtual field. A model-predictive control (MPC) strategy is used to regulate well and field instrumentation at economically optimal set points determined by an overlying supervisory control level. The study demonstrates significant reduction in water-handling costs and increased oil recovery. This work is a starting point for further development in automatic intelligent reservoir technologies, which capitalize on the abilities of permanent instrumented wells and remotely activated downhole completions. [ABSTRACT FROM AUTHOR]