Affiliation:
1. Reservoir Dynamics Ltd.
2. The University of Edinburgh
3. Schlumberger
Abstract
Abstract
A major key to rejuvenating mature oil and gas fields for improved recovery is the ability to characterize the reservoir between existing wells: currently practised methods for surveying inter-well properties are generally costly. A recent project has combined three technologies which utilize readily available fluid production histories to produce a process for identifying inter-well reservoir communications in producing oil or gas fields. Fluctuations in the well production and injection rate histories are analyzed in the context of coupled geomechanical-flow processes involving activated faults and fractures through (i) the Statistical Reservoir Model (SRM), (ii) conventional correlation analysis and a new technique for extracting rate diffusivity tensors, and (iii) coupled geomechechanical-flow modelling. These technologies have been applied to five oilfields located in the North Sea from the North Viking graben to the Central graben with the key results that (i) the general long-range nature of rate correlations is consistent with some dependence on hydro-mechanical changes near a critical point, and (ii) the patterns of orientational distributions of rate correlations from all five fields are consistent with induced shearing on faults or fractures as an inherent mechanism of reservoir communication. Identification of major reservoir pathways is of substantial advantage to efficiency in reservoir management, leading to benefit for practical issues of well placements and configurations, injectivities, productivities, sweep efficiencies, short-term and longer-term forecasting. In particular the techniques can be used in a time-lapse fashion in order to monitor changes in reservoir behaviour and provide real-time updating of reservoir models. Together, these techniques can directly assist rejuvenation of mature fields; additionally, albeit tentatively, the improved understanding of fundamental reservoir mechanisms can lead to better planning of ‘green’ fields.
Cited by
3 articles.
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