The dynamic characterization and the description of fluid flow behavior at well location are critical steps for production optimization and reservoir modeling purposes. The conventional approach makes use of well test data interpreted by adopting appropriate analytical models aimed, in particular, at permeability evaluation and flow regime identification. In complex reservoir scenarios, the standard well test interpretation lacks a direct link with the actual flowing thickness of the reservoir rock and this represents the major cause of inaccurate permeability estimations. Moreover, an a-priori knowledge of fluid flow path through the porous medium and around the wellbore is one of the most desired targets but, at the same time, one of the most challenging issues to be addressed.
This paper deals with a novel dynamic characterization approach that mainly integrates well test data and spectral noise logging. The latter, with its high-resolution noise pattern recognition in a wide frequency range, can provide valuable information of the fluid flow behavior in the near wellbore region in order to locate the active units and to describe the origin and the character of the flow (through mesopores, macropores, fractures, behind-casing channels and completion elements).
The added value of the methodology is demonstrated by means of a study performed on three wells drilled in a Cretaceous carbonate reservoir. The accurate estimation of the net-pay flowing thickness, after a fit-for-purpose modeling of noise data, revealed the subsequent robust estimation of effective permeability and different scenarios with respect to those based on standard approaches. Then, the integration of quantitative spectral noise analysis, pressure transient tests, production logging data, and advanced nuclear magnetic resonance log interpretation completed the picture of the flow regime through the pore-space. In turn, the results represent a critical input for the dynamic reservoir model, and a fruitful driver to optimize commingled completions or required workovers.
The deep understanding of fluid movement from sandface to surface is a critical aspect in production optimization and reservoir modeling studies. According to conventional approaches, the actual dynamic characterization of a well usually comes after production logging tool (PLT) data interpretations and/or well test (WT) analyses.
