A comparative study is carried out between a deterministic and a stochastic approach via Bayesian McMC to obtain estimates of changes in pressure and saturation. The aim is to provide insights into well performance and pressure distribution within a geo-mechanically active chalk reservoir (Ekofisk). Uncertainty of such predictions is usually high; henceforth the solution of such an inverse problem is not limited to a single set of predicted parameters but represented by a probability density function on the model space. Both inversion approaches are similarly constrained by reservoir engineering concepts and predictions. We show that the Bayesian framework provides a suitable platform to incorporate data uncertainties and prior information. Quantitative interpretation on this field using the inversion results shows good agreement with well production data and helps to explain strong localized anomalies in both the Ekofisk and Tor formations.
|Number of pages||5|
|Journal||SEG Technical Program Expanded Abstracts|
|Publication status||Published - 19 Aug 2015|
|Event||SEG New Orleans Annual Meeting 2015 - New Orleans, United States|
Duration: 18 Oct 2011 → 23 Oct 2011
ASJC Scopus subject areas
- Geotechnical Engineering and Engineering Geology