New Approach to Fluid Typing Concepts in Tight Carbonate Source Rocks | Schlumberger
Tech Paper
Location
Middle East, Asia
Byline
Stefan Steiner, ADNOC Upstream; Laurent Mosse and Ishan Raina, Schlumberger
Society
SPE
Paper Number
193249
Presentation Date
12–15 November 2018
Products Used
Premium

New Approach to Fluid Typing Concepts in Tight Carbonate Source Rocks

Abstract

Assessment of the porosity - fluid system, while challenging, is important in source rock oil plays. This is due to the wide range of hydrocarbon weight fractions, from bitumen to light hydrocarbon encountered in the source rock, along with the presence of both, the organic and the inorganic porosity systems, simultaneously. In such a play, while comparing zones of similar total porosity and water saturation, intervals with a better fluid type and porosity system will contribute more to the flow than other zones. In this paper an approach to poro-fluid typing a source rock is presented through examples from a carbonate source rock case study from the Middle East.

The following core measurements were acquired on two wells: 1. NMR T1-T2 measurements on as received, oil saturated and water saturated samples, 2. Retort measurements for effective and total porosity and saturation analysis 3. Solvent extraction saturations for quantifying total hydrocarbon saturation, and 4. Mercury Injection Capillary Pressure Analysis for estimating pore throat size distribution. TOC measurements were also acquired on all the samples. A classification technique called the Blind Source Separation analysis (BSS) is carried out on the combined dataset of NMR 2D maps and various classes are identified based on the typical signatures observed on the maps in different saturation states.

The classes identified using BSS were correlated to other core measurements to assign a physical meaning to each class. Based on the results, three key poro-fluid groups are identified. These groups are bitumen hosted porosity, porosity in the organics, and inorganic hosted porosity. By integrating results from MICP and SEM, we identify the typical pore sizes observed in the above groups and recommend zones that will bet better contributors to flow. Finally, we tie the results back to the limited measurements available in the log domain to predict zones with better flow potential.

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