A case study on the integration of 4D seismic with various multi-scale and multidimensional field data to understand dynamic behaviour of the reservoirs is presented.

4D seismic is a key dataset amongst others e.g.geochemical fingerprinting, well inflow tracers, injection logging tools/production logging tools, and multi-well pressure deconvolution) together withconventional field data, which is acquired since starting up the field in late-2016. 4D data proved to be an essential piece that complemented field observations and is integral for constraining the subsurface models in support of a rapid second pahse of development and WRFM decisions. The paper describes the approaches taken to integrate these distinct datasets in the dynamic model as well as the various challenges faced in assimilating them in a coherent manner.

One key subsurface challenge is to understand the degree of compartmentalisation risk to make sound WRFM decisions and to plan for a robust phase 2 development. As a starting point, conventional field performance analysis (production & injection performance) indicated connectivity across the reservoirs, though more limited in certain areas. This was supplemented with other subsurface data to further validate and improve the dynamic models. The 4D signals provided an indication of pressure and fluid connectivity as well as an indication of water sweep direction. Updates to the dynamic fault seal were performed in line with observations from 4D seismic and various field data.

Understanding the dynamic behavior of the M field is key in view of the various challenges faced in reservoir management, e.g. increasing GOR trends and lower WI performance, in parallel with developing plans for the Phase 2 development. The incorporation of data of different scales and dimensions (4D seismic, fluid chemistry, PLT, multi-well pressure deconvolution) added value to the process of updating the dynamic models.

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