Estimation of static and dynamic petrophysical properties of multi-layer hydrocarbon reservoirs is crucial for the assessment of storage and flow capacities, compartmentalization, and for best primary or enhanced recovery practices. Previously, we introduced the concept of Common Stratigraphic Framework (CSF) to construct and cross validate multi-layer static/dynamic petrophysical models by invoking the interactive, numerical simulation of well logs both before and after invasion. This paper documents the successful implementation of the CSF concept to examine and quantify the effects of mud-filtrate invasion on apparent resistivity, nuclear, and magnetic resonance logs acquired in San Martin, Cashiriari and Pagoreni gas fields in Camisea, Peru. Conventional petrophysical interpretation methods yield abnormally high estimates of water saturation in some of the reservoir units that produce gas with null water influx. This anomalous behavior is due to relatively low values of deep apparent electrical resistivity, and has otherwise been attributed to the presence of clay-coating grains and/or electrically conductive grain minerals. On the other hand, electrical resistivity logs exhibit substantial invasion effects as evidenced by the separation of apparent resistivity logs (both LWD and wireline) with multiple radial lengths of investigation. In extreme cases, apparent resistivity logs "stack" because of very deep invasion. We diagnose and quantify invasion effects on resistivity and nuclear logs with interactive numerical modeling before and after invasion. The assimilation of such effects in the interpretation consistently decreases previous estimates of water saturation to those of irreducible water saturation inferred from core data. It is shown that capillary pressure effects are responsible for the difference in separation of resistivity curves in some of the reservoir units. The final multi-layer CSF is in agreement with gas production measurements and permits reliable flow predictions to assist in reservoir engineering and production studies.

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