Raageshwari Deep Gas Field, India is a low permeability (0.01-1md), medium CGR gas condensate reservoir. The pay-zone consists of a poorly sorted sandstone interval on top of stacked succession of thick lava flow cycles of volcanic origin. The field is developed with vertical wells and multi-stage hydraulic fractures. Developing a tight heterogeneous system comes with its own set of challenges – reservoir characterization and pay identification, fluid distribution, well placement, frac placement with optimum parameters, interconnected volumes, per well recovery, etc. This paper highlights our approach to mitigate various uncertainties to accurately predict field performance.
An extensive data acquisition plan coupled with 4 years of production history played a crucial role in identifying the correct solution set. Extended well testing was carried out for different wells during the appraisal phase. Pressure transient (PTA) data acquired during this period helped in estimating the "KH" of the various layers which was correlated with the log derived permeability and hence validating the petrophysical and geo-mechanical model. Similarly, other core and drilling data were incorporated into the model for proper reservoir characterization and pay identification. As more wells were drilled and brought on production, sufficiently long PTA was impossible. However, massive hydraulic fracturing campaign provided ample opportunity to conduct DFIT (diagnostic fracture injection test) for estimating the reservoir parameters as well as validate the model. Variation in fluid distribution across the section was expected as production data confirmed areal and vertical variation in CGR. Multiple samples were captured from different wells and a PVT model was created which justified the fluid produced. Application of Digital Oilfield ensured the continuous production data which was analyzed via RTA for guidance on "Per Well Recovery". This was integrated with traditional PTA, time-lapsed production log, core analysis and DFITs.
Such a complex system is best resolved using individual well analysis. A comprehensive workflow was created which ensured data acquired from all the individual wells were integrated and accordingly the petrophysical and geo-mechanical models were updated. The workflow permitted us to reduce our uncertainty on the key parameters of pay identification, frac optimization and Well Spacing. This improved our perspective of the field, and permitted us to optimize our field development, which is robust despite market uncertainties.
Few innovative ideas were used in our design for data acquisition to minimize the time constraint – such as extended DFITs, use of well-head pressure for PTA using an accurate well-bore model, time-lapsed flowing pressure and PLT data to study the effects of changing productivity etc. These innovations helped us move down the uncertainty ladder quickly with a high degree of confidence.