Gro Field Assessment: A Lean Gas Condensate, Low Permeability Simulation Study

Abstract

New technologies increase the development of deep water fields and a significant portion of these undeveloped deep discoveries are gas condensates in low permeability reservoirs. This study is aimed at investigating the production of a lean gas condensate from a heterogeneous, fairly tight rock.

The PVT model is based on the PVT report from the Gro field, a Shell/Statoil/GDF SUEZ/PGNiG lean gas condensate field in the Norwegian Sea offshore Norway. The measured data have been validated and what was not already given was calculate from correlations and assumed as standard value tables. A single well radial model has been used with gas properties determined by the composition of the sampled fluid. Rock properties are found from digitized petrophysical logs.

The data file was initialized on a no-simulation basis. A single well radial model was then built to study the productivity of the field and the effect of condensate blockage on reservoir performance.

This thesis presents an analysis of the characteristics and a review of performance of this tight gas condensate reservoir. An EOS based PVT model, which fits fairly well to the experimental data, is made for the Gro lean gas condensate fluid. It should be noted that the PVT model is based on mathematically decontaminated data.

In the case of the Gro field it is strongly recommended not to use cutoffs in the simulation model as the flow dynamics are altered and the recovery mechanism is changed.

The recovery from 5 wells is found to be 35% of the condensate and 46% of the gas with a production life of 20 years. The impact of stimulation on well performance and recovery on Gro is significant. Compared with no stimulation of 5 wells and increased in recovery of 9% and 31% for condensate and gas was found. According to the economical analysis 5 stimulated wells showed the best economics, with a NPV of USD 1.044 billion. 10 wells with cutoffs implemented was the only case with a negative NPV. The field will need to be optimized on number of wells and type of wells to get the best well performance. This final solution needs to contain the no-cutoff simulation grid.