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A reservoir development plan was developed from a detailed geological model of the SE Gobe Iagifu reservoir. This model incorporated sequence stratigraphy and extensive core and log analysis to provide the detailed layering framework for reservoir simulation. Cross-sectional balancing techniques were applied to field derived dip and strike, dipmeter log, and RFT data to obtain a structural model for the reservoir. Cross-sectional, sector and, finally, full field reservoir simulation models were constructed and used by the team to generate a reservoir development and management plan.

The simulation models were used to examine the relative merits of vertical, deviated and horizontal wells, well placement, offtake rates, gas compression requirements and pressure maintenance strategies. Due to the uncertainty in the size and shape of the field, development options were considered at each of three reserve levels: proven, probable and possible.

The simulation results showed that well rates should be held to less than 8000 stb/d and that horizontal wells, with a length of at least 700 m, generally out-performed vertical wells. Oil recovery ranged between 34 and 45% of OOIP. The cases offering the best recoveries included both water injection and horizontal wells.


The SE Gobe oilfield was discovered in April 1991 by the drilling of the SE Gobe 1 well in the northern part of the Gulf Province of Papua New Guinea. The well flowed 4250 stb/d of 45 API crude during a production test. The well was drilled by a helicopter transportable drilling rig (heli-rig) in rugged, heavily karstified, jungle terrain. Since the discovery well, four appraisal wells have been drilled in the PPL 56 permit and the neighbouring PPL 161 permit by their respective operators, to attempt to define the structure in an environment where seismic technology is not applicable and structuring is complex.

A team of Petroleum/Reservoir Engineers and a Development Geologist was formed from the operators of the PPL 56 and PPL 161 permits in order to model the reservoir and determine optimum development scenarios for the field, and to address the uncertainty in the reserves estimate due to the structural complexity and sparse reservoir data.

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