Schlumberger Technology Corporation

Trevor Graham Tonkin

Matthew Worthington

William John Bailey

Kashif Rashid

Michael David Prange

Shingo Watanabe

Frode Bratvedt

Rodney William Lessard

Mohamed Osman Mahgoub Ahmed

Hamza Keurti

Vijaya Halabe

Kim Fah Goh

Defining flow control device configurable positions include executing a reservoir simulator on a reservoir model to obtain a collection of flow control device settings defined in continuous space. For each number of multiple numbers of clusters, a cluster analysis is individually performed on the collection to obtain a set of flow control device configurable positions. The set includes the number of flow control device configurable positions and its corresponding inflow area or diameter. Performing the cluster analysis across the numbers generates multiple sets for the multiple numbers of clusters. The sets of flow control device configurable positions are compared to obtain a selected set of flow control device configurable positions, which is presented in a completion design.

Flow control device openings for completion design

Using a reservoir simulator, a reservoir model state is obtained. The reservoir model state is used to trace streamlines to obtain streamline trajectories and detect fluid fronts along the streamlines. Using the streamline trajectories, the streamlines are connected to wells. The streamlines are grouped for multiple granularity levels, into groups to obtain a grouping hierarchy. Through the granularity levels of the grouping hierarchy, fluid front time of flights are determined for the groups, and target flowrates assigned to completion devices based on the fluid front time of flights to obtain target flow rates. A completion design is presented that incorporates the target flowrates.

Streamline based creation of completion design

A physical pipeline network is decomposed into multiple subnetworks. The subnetworks include upstream subnetworks and at least one downstream subnetwork. A network solver is executed on the upstream subnetworks in parallel to obtain a set of boundary conditions and a set of control device settings. The set of boundary conditions and a set of control device settings are then used to execute the network solver on the downstream subnetwork and obtain a result having another set of control device settings. The network solver may repeat executions until convergence is achieved. When convergence is achieved, the result is presented.

Pipeline network solving using decomposition procedure

A method can include receiving realizations of a model of a reservoir that includes at least one well where the realizations represent uncertainty in a multidimensional space; selecting a portion of the realizations in a reduced dimensional space to preserve an amount of the uncertainty; optimizing an objective function based at least in part on the selected portion of the realizations; outputting parameter values for the optimized objective function; and generating at least a portion of a field operations plan based at least in part on at least a portion of the parameter values.

Optimization under uncertainty for integrated models

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Swindon, United Kingdom

Trevor Graham Tonkin