Commissioning and start-up (CSU) of an all-subsea development of offshore gas reserves feeding into an onshore liquefied natural gas (LNG) plant is complex and challenging – yet project success is driven by a timely and flawless LNG project start-up. To this end, development wells in the Jansz-Io gas field had to be flowed back to the onshore facility to prove up Gorgon LNG Train 1 capacity before the wells could be relied upon for uninterrupted gas supply to Train 1 start-up. Here, a carefully-considered well proving sequence can yield unique, once-in-a-lifetime and zero-cost subsurface data that improves reservoir characterisation and future decision quality. This paper describes:

  1. Design aspects of the well proving sequence that enabled opportunistic pulse and interference tests to be conducted at no expense to Train 1 start-up:

    • Optimality: balancing the well proving objectives of the various functional stakeholders (flow assurance, facilities, operations and subsurface) while honouring all CSU / operational constraints.

    • Flexibility: recognising and planning for CSU uncertainties (subsea gathering system versus onshore plant readiness; onshore gas demand; and pigging schedule for liquids management).

    • Contingencies: planning for sequence execution issues such as well unavailability and gauge failure(s).

  2. Execution – how the tests were executed and how the reservoir responded.

  3. Analysis and interpretation of pulse and interference test data, whereby:

    • A simple, conceptual analytical model based on the line source solution was constructed and used to guide analyses in more detailed numerical models.

    • A single-layer 2D numerical reservoir model with local grid refinement at the wells was constructed and used to infer inter-well average reservoir storativity (porosity-total compressibility-thickness product, ϕcth) and transmissivity (mobility-thickness product, kh/μ) and across-fault communication.

    • Existing 3D models were calibrated to the pulse and interference testing data for improved reservoir performance predictions in support of future reservoir management decisions.

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