The integration of data and discipline specific knowledge is a common challenge when attempting to optimize or accelerate an asset's recovery through hydraulic fracture stimulations. Any potential omission of data or understanding will increase uncertainty and a project's chance of failure. Therefore, when looking to optimize the production of a given asset, it is key to take a holistic approach that breaks down any technical and organisational barriers.

This project couples the output of the different subsurface and stimulation disciplines to reduce the uncertainty associated with the production forecast of planned stimulation designs. The following paper presents the integrated approach for the Graben sector of UK's North Sea Clair oil field, largest oil field currently in Europe.

Geophysicists, petrophysicists, and geologists generate a static model which is calibrated and validated by reservoir engineers through dynamic reservoir simulation. This model is used to identify the optimum exploitation scenario for a hydrocarbon reservoir and is assessed by the geomechanics engineer to deduce the subsurface stresses and strains to create a 3D mechanical earth model. The multidisciplinary validated representation is handed over to the stimulation engineer to implement various treatments, either performed or to be performed. Once these treatments are designed, the reservoir engineer produces a production forecast which is then fed back to all team members involved in the process, enabling an optimization loop. Considering that this is a multi-well (producers and injector) study, any inference is reflected by the analysis and the optimum hydraulic fracture design is chosen for implementation by an offshore stimulation vessel.

Traditionally, for forecasting purposes, hydraulic fractures can be implemented using conventional reservoir simulation; however, these are very much approximated models of what the stimulation engineers are designing and implementing. Often, the reservoir, production, stimulation engineers can come up with individual forecasts that are obtained independently and omit basic information. A typical example is the way stresses might change due to stimulation and production and the possibility to account for them in an integrated way. The proposed workflow eliminates these shortcomings, and the asset team delivers a single forecast of the exact fracture design considering a fully consistent model of the subsurface, which is to be implemented by the stimulation vessel for the different wells.

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