TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractResistivity logs, as directly used for the determination of Water Saturation profiles, have always been of focal interest for the oil industry; it's clear that the quality of these measurements, currently used in the net pay and hydrocarbonin-place determination, must be very high. As a consequence, more accurate and flexible resistivity tools have been developed in recent years. We are addressing here the family of array tools, and especially the HRLA 1 , which makes available a set of 5 galvanic resistivity measurements at different depths of investigation.Unfortunately, the most common types of environmental noise (borehole effects, shoulder bed resistivity contrasts, invasion, the presence of dips, anisotropy), still alter the measured resistivity, thus affecting the estimation of the true resistivity in hydrocarbon bearing levels.In order to remove these alterations, Schlumberger, in cooperation with ENI-AGIP, has developed a 2D resistivity modeling & inversion technique that can simultaneously correct a number of environmental effects. This paper presents the results obtained in two wells of a reservoir in the offshore Norway area where the sandstone bodies are interbedded with deltaic shales. The values of porosity and permeability are generally very high and a complete set of data (conventional & special core analysis, conventional wireline logs, microresistivity imaging logs, NMR, sedimentological analysis from core and images) is available. Mark of SchlumbergerThe 2D modeling provided a better definition of the water saturation in the thinner sandstone bodies of the sequence and in the presence of anomalous invasion profiles.When comparing the resistivity modeling results with those obtained by standard interpretation techniques, we can see the effectiveness of the developed methodologies (both hardware and software) in improving the reservoir characterization and in maximizing the return of the investments in logging and well data measurements.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.