Abstract

In today's competitive cost environment, core acquisition and analysis is too often dismissed as unaffordable. This forces petrophysicists to make every dollar count in core evaluation. Tough choices have to be made—many people chase the lowest bid, least expensive methodologies, reduced oversight, and less sampling. In this paper, insights will be shared from a comprehensive round-robin study directly comparing the results of the most common techniques (GRI/Retort/RCA) used by major vendors. Understanding differences in techniques early in an evaluation process can help efficiently direct technical spending.

As with many comparison studies, this project started with the reconciliation of analysis sourced from different laboratories using different methodologies.

There was a significant business driver to this work as we noticed differences in measured porosity and fluid saturations that contribute to significant differences, approximately 25%, in hydrocarbon pore volume among vendors using alternative techniques. These differences directly impact log calibration objectives as well as estimations of hydrocarbons in place.

We began to ask a series of simple questions: Should we use crushed samples or routine core plugs What is the impact of analytical technique on the results What role does lithology and organic content play in the results from different analytical techniques What is the role of sample size What is the variability between vendors for identical procedures If there is variability, what is the apparent cause

A set of 10 twin samples of Permian Bone Spring formation from the Delaware Basin in Texas and New Mexico was evaluated using a variety of laboratory-derived measurements, including X-ray diffraction (XRD), total organic carbon (TOC)/RockEval, retort, and Dean- Stark/Gas Research Institute (GRI) protocol analyses from two labs and RCA from one lab. These 10 samples were selected to represent varying lithofacies with a range of organic, mineralogical, and water/oil content. The level of oversight at each data source was also tracked.

Through detailed analysis of the raw data from these measurements, we address the questions above. With these results, we hope to (1) maximize every dollar spent in core analysis, (2) focus oversight where it is truly required, and (3) accurately and consistently evaluate the core analysis in the Permian play for fast and value-driven business decisions.

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