The Impact of Petrophysical Uncertainty in Formation Evaluation and Reservoir Modelling - A Robust Methodology.
- Niccolò Ceresa (ENI SpA) | Michele Arcangeli (ENI SpA) | Maria Teresa Galli (ENI SpA) | Paola Cardola (ENI SpA) | Paolo Scaglioni (ENI SpA)
- Document ID
- Society of Petrophysicists and Well-Log Analysts
- SPWLA 60th Annual Logging Symposium, 15-19 June, The Woodlands, Texas, USA
- Publication Date
- Document Type
- Conference Paper
- 2019. held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors
- 4 in the last 30 days
- 135 since 2007
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The assessment of geological uncertainties in Reservoir Characterisation and Risk Analysis is nowadays a common and standard approach, but it is not yet available a unique, robust methodology for the evaluation of the uncertainty from well measurements down to the risk analysis process. Developing a sound methodology for the correct evaluation and propagation of petrophysical uncertainty is therefore mandatory.
This work wants to introduce a novel approach for the correct evaluation and propagation of petrophysical uncertainty. The workflow was applied to a deep-water, gas-bearing sandstone reservoir, with a complete and continuous set of log data available in all wells and several cores cut in the reservoir interval.
The scope of our work included three main steps:
- Analysis of the uncertainty in input data, including well logs and core analyses.
- Definition of a workflow aimed at achieving a ready-to-use approach for the evaluation of the uncertainty associated to the main petrophysical properties, like porosity, permeability and water saturation.
- Propagation of the petrophysical uncertainty to the reservoir static model and risk analysis through fit-for-purpose approaches, defined by a multidisciplinary team including sedimentologists, petrophysicists, geologists and reservoir engineers.
The improved knowledge of the uncertainty in the petrophysical properties allowed the definition of various scenarios, from conservative to optimistic, highlighting possible zones of further development; in particular, a sounder knowledge of the uncertainty associated to permeability contributed to a more robust evaluation of GIIP.
In critical, un-cored intervals characterized by facies analysis, the approach provided significant insight in the representativeness of core data and allowed to better understand the role played by log quality.
The analysis of the results, in the shape of statistical distributions of porosity, permeability and N/G, proved that the developed approach is robust and methodologically correct.
Overall, the availability of a quantitative and robust estimate of the petrophysical uncertainty proved beneficial to the construction of a final reservoir model honouring both static and dynamic measurements.
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