This paper describes the work flow adopted by Eni Australia to support Blacktip daily production operations. The Blacktip gas field is located offshore in the southern Bonaparte Basin, Australia. Eni Australia is the operator for the Blacktip gas field and holds 100 per cent (%) working interest. Production from the Blacktip gas field started in September 2009 and has been the primary source of gas for Darwin, Northern Territory. The Blacktip gas project consists of a normally unmanned Wellhead Platform (WHP) at a water depth of 50 meters (m), a 110 kilometer (km) offshore Gas Export Pipeline (GEP) and the onshore Yelcherr Gas Plant (YGP). Two deviated production wells were drilled and completed on the WHP in September 2009. Well intervention was carried out on the WHP to shut off a lower production zone and perforate the main production zone in June 2013. Untreated gas from the wells is directly sent to the YGP via the GEP, without offshore processing. The gas is treated at the YGP to meet the customer's specifications and it is sent to Darwin via an onshore gas transmission pipeline operated by a third party. Condensate is processed and stored at the YGP, and offloaded via a 10 km offshore offloading line. Multiphase flow numerical transient simulation (dynamic simulation) techniques have been used to establish the work flow to support daily production operations. Three fit for purpose models have been constructed in order to fulfill this task in a timely manner. They are the well(s) model, the GEP model and the offloading line model. History matching of the GEP model has been routinely conducted to monitor pipeline performance and to provide the operations team with relevant information such as liquid volume in the GEP, slug prediction, etc. The condensate offloading line model was used to develop operational guidelines for the first offloading operations conducted in July 2010. In due course, dynamic simulations were applied to support well operations using well models. Regular history matching has been conducted to validate the models and monitor well performance. The well model was also used to establish a sound and safe operations plan for the well intervention campaign, to change the production zone. The application of dynamic simulation is now an integral part of daily production operations for the Blacktip gas field.

Gas compression has been widely adopted by the petroleum industry and is validated as a reliable method for improving reserves base. As depletion drive gas fields mature, their reservoir pressure declines with an associated reduction in gas production rates. This phenomenon is even more pronounced in fields where aquifer water breaks through and results in rapidly falling well head pressures which naturally result in reduced reserves recovery over the producing life of the field. Compression at wellhead or at the facility elongates well and field life resulting in tapping additional reserves, which may be left behind in case surface compression facilities are not put in place in a timely and phased manner. Compression was initiated at Bhit Gas Field from 2009 and implemented in a phased manner over several years. In first phase, well head compression was deployed to ensure a continuous plateau rate and provide additional gas recovery at 100 psig suction pressure which was selected through matching compressor curves against well deliverability. In second phase, booster compressors at selected wellheads were installed to further drop pressures d upto 50 psig. This was followed by optimization where existing compressors were not only swapped, relocated and reconfigured but also spare compression capacity was utilized by merging wellhead to nodal compression to further drop pressures upto 20 psig leading to increased recovery. Surface optimization actions were justified by set of forecasted results from simulation model utilizing compressor curves. This paper will demonstrate the continuous surface optimization performed as a function of reservoir and well response with the ultimate aim of enhancing reserves recovery by comparing actual field performance with Forecasts from a numerical simulation model. Highlights on the benefits of timely identification and implementation of compression needs achieved through significant cost savings and reduced project time to market will also be presented