This paper is reviewing 4D seismic data from the Valhall field located in the chalk province on the Norwegian continental shelf. The field is monitored with 4D seismic and is the first field in the world to be monitored with permanent installed cables at the seafloor. This concept, including 120 km cables trenched into the seafloor above the field, is providing seismic on demand for reservoir management purposes and is called Life of Field Seismic. This paper will focus on the seismic observations of production induced deformations outside the reservoir at Valhall and will review the theory behind the deformations, how they impact the seismic velocities and the use of 4D seismic for reservoir monitoring. The paper will present integration of relevant theories, numerical modelling and results from laboratory experiments.

The work presented should have applications to other fields where even limited reservoir compaction will take place. How significant the reservoir compaction will be is dependent on the structural geometry, rock properties of the surrounding rock, reservoir thickness, the compressibility of the reservoir, the pore pressure depletion and if any weakening of the rock takes place during secondary or tertiary recovery processes. The methods presented in the paper can also be used to improve the uniqueness of the static geologic model, the dynamic flow model and the geomechanical model and, hence, result in a more unique history match of the reservoir as well as improved future prediction.

The main technical contributions from this paper are a detailed review of theory, laboratory and field data of relevance from a well instrumented field under seismic surveillance. The paper will also outline how integration of geophysics, geology, geomechanics and reservoir engineering can produce better reservoir performance prediction based on new workflows. The paper will also show how a problem of production induced deformations outside a reservoir, with corresponding velocity changes, may be used as an advantage in reservoir performance prediction in the future.

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