Abstract
Petrophysical analysis plays a strategic role in the evaluation of well productivity and, ultimately, hydrocarbons in place, but its importance in formation damage assessment and evaluation has often been overlooked or inappropriately applied. Over-reliance on often ambiguous well test data, and a lack of real understanding of the formation's static and dynamic petrophysical properties have combined to produce misleading conclusions on formation damage.
Two field examples are presented to illustrate the benefits of a forensic re-evaluation of log, core and test data in both the recognition and rejection of formation damage in low permeability oil and gas condensate reservoirs where data constraints precluded direct laboratory or field testing to quantify damage potential.
In the first, the results of the initial welltest interpretation proved decisive in the original operator's decision to relinquish the field license. Forensic re-evaluation of core, log and welltest data indicated that the low oil rates on test were more likely to be the consequence of formation damage rather than poor formation permeability, and challenged the negative skin factor in the original interpretation. Recognition of formation damage and the opportunity to drill a new well specifically to mitigate formation damage have persuaded the new operator of hidden potential in a reservoir that had been condemned to be non-viable. Conversely, in the second example, the poor gas productivity on test was initially attributed to formation damage. However, forensic petrophysical analysis, which integrated log, test and SCAL relative permeability data, demonstrated that the true formation permeability was significantly lower than estimated from logs and conventional core tests.
Both examples incorporate dynamic SCAL measurements which are often overlooked in classical static petrophysical interpretations. In these lower permeability reservoirs, relative permeability and stress effects significantly suppress the effective hydrocarbon permeability compared to ambient condition estimates.
The workflows and best practices described in this paper have clearly beneficial applications in reservoirs where poor productivity on test does not necessarily represent formation damage or, conversely, the true formation potential. Integrating permeability modelling results with mineralogical information and dynamic SCAL relative permeability data provides a powerful tool for verifying well and production tests; and ultimately, the assessment of formation damage. This integrated and systematic methodology has demonstrably realised the true potential of what were regarded as uneconomic prospects, or has verified that poor productivity is solely a result of poor permeability – not formation damage.