Advanced Azimuthal Resistivity Analysis for Better Understanding of Subtle Carbonate Oil Reservoirs

Abstract

This paper presents a novel approach to processing azimuthal resistivity measurements, which significantly enhances the detection and characterization of thin porosity zones within dense limestone formations. The deterministic method utilizes Newton non-linear inversion techniques to convert electromagnetic data obtained during drilling operations into comprehensive multi-layer resistivity models.

In contrast to traditional distance-to-boundary methods that often encounter difficulties in low-resistivity contrast environments, the algorithm is specifically designed to excel in these challenging conditions. Under optimal circumstances, this technique can achieve investigation depths exceeding 40 feet from the wellbore while simultaneously resolving formation thickness and resistivity values across multiple layers.

The framework is highly adaptable, accommodating a range of layer configurations, from straightforward two-layer models to intricate ten-layer structures, allowing it to address various geological complexities effectively. A key feature of the approach is the integrated misfit analysis, which provides thorough quality control by automatically identifying solution confidence and potential ambiguities.

The algorithm maintains a consistently high number of degrees of freedom, with user-controlled constraints that ensure reliable and robust solutions, even in scenarios characterized by minimal resistivity contrast.

A field examples are presented that illustrate how this approach successfully tracked and determined adjacent layers in a carbonate reservoir. This capability is crucial for developing strategies to navigate between porous layers. In instances where reservoir contact was lost due to faulting, the method effectively assessed the structural position and guided the optimal path for re-establishing access to the target zone.

In summary, the multi-layer azimuthal resistivity inversion technique introduced in this paper represents an advancement in the characterization of carbonate reservoirs, offering a reliable and effective solution for complex geological challenges.