The field in question is a super giant oil field located in Southern Iraq. Historically, the field had 27 wells, along with surface facilities capable of processing ca. 100kbbl/d of oil. An additional processing facility was installed and some 18 additional wells were drilled and completed in the period 2012–13 to increase production levels in the field to more than 200kbbl/d, referred to as First Commercial Production (FCP). The field was shut-in for approximately 14 months during the pre-FCP period.

Initially, only scarce historical pressure, well test and production allocation data existed and so an approach to prove up, manage and optimize field production performance was developed using Integrated Production System Modelling (IPSM). This involved both surface and subsurface disciplines collaborating to integrate stand-alone models and discipline data from operations, production technology, reservoir engineering, petrophysics and production geology into a single integrated model for proving up well capacity, field surveillance and optimization. Initially, the individual discipline model definitions were based on design case and oil field theoretical assumptions combined with single point(s) of actual data points. As more field data was collected the various models were updated and re-calibrated to ensure a maximum deviation of 10%.

Over the past 3 years, as the field has transitioned from the pre-startup phase to the stable production phase and with this has been the evolution of the uses and application of the IPSM. This paper will describe the data gathered, process of model calibration, uses of the model in the four key phases to date along with the future aspiration case:

  1. Pre-FCP start up (offline phase)

  2. FCP start up and production ramp up (Ramp up phase)

  3. Early production (FCP phase)

  4. Stable production (steady state phase) – current state

  5. Future state and aspiration

Generally speaking, the main objectives of building and maintaining an integrated production system model are:

  • To ensure all system components are operating within safe limits

  • To optimize the performance of the production system

  • Multiple scenarios are tested in a short period of time

  • Used to produce a production forecast with all the constraints accounted for

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