Multi-Dimensional Approach to Inter-Well Connectivity Analysis

Carbonates are known to be heterogeneous. In this paper, we will focus on characterising inter-wellconnectivity by applying a multi-dimensional approach to production data analysis along with integration ofinter-disciplinary data for a Brazillian carbonate reservoir. Results of the analysis are used for interpretationof a noisy 4D seismic data to locate sweet spots. This unique integrated approach characterizes inter-well connectivity from four perspectives: (1)determine reservoir quality (2) identify source of water production (3) tracking of injected fluid's flow path(4) verify impact on 4D seismic response. We will show how the quality of a carbonate reservoir and itsaquifer strength can be verified with well logs, pressure depletion rates and production behaviour. The useof sensitivity analysis in mechanistic models will also be shared to analyse the impact of heterogeneity onproduction behaviour. Using Chan's (1995) water-oil-ratio diagnostic plots, the source of water productionwill be identified as well. Explanation of analysis of well chronology, bubble maps of water cut will alsobe provided for tracking of injected fluid flow paths. Finally, interaction of production parameters betweenwell-pairs and resistance modelling will be used to evaluate inter-well connectivity, and verified with 4Dseismic data. Findings from all the analysis in the integrated approach are summarized into an inter-well connectivitymetric, which is used as a reference for production and seismic history matching and interpretation of thenoisy 4D seismic data. The integrated data analysis shows that the sweet spot corresponds with softening onthe 4D seismic map, un-swept by injectors as it is located on a structural high southeast of the reservoir. Thispaper offers a comprehensive analysis to characterize important reservoir characteristics (such as thief zonesand tight streaks). It will also emphasize ways to integrate inter-disciplinary data, and showcase variousvisualization perspectives to fortify and enhance the importance of data integration.